Podcasts about kyruus

Dr. Graham Gardner is a visionary in healthcare innovation. He is the co-founder and CEO of Kyruus Health – Kairus Health, leading the development of a platform that revolutionizes patient access and provider data management, now serving over 425 thousand providers and 1,000 hospitals. Dr. Gardner's unique perspective is shaped by his background in cardiology and his entrepreneurial journey, which includes co-founding Generation Health, a genetic benefit management company that was acquired by CVS Caremark. His work with Kyruus has set new standards for patient-provider matching, significantly enhancing healthcare access and efficiency. In this episode, we discuss Dr. Gardner's transition from medicine to entrepreneurship, and how Kyruus is transforming healthcare access and efficiency. We also explore his thoughts on the future of healthcare technology and the importance of data-driven decision-making. Do you have any thoughts or guest suggestions? Please email us at hello@rosenmaninstitute.org.

In this episode Paul Merrild, President, HealthSparq & Kyruus and Jeff Stewart, System Director, Strategic Marketing at CHRISTUS Health out of Texas join us for an important discussion on member experience. Tune in as they dive into how putting a strong focus on accurate data shapes the consumer's perspective.This episode is sponsored by HealthSparq.

In this episode Paul Merrild, President, HealthSparq & Kyruus and Jeff Stewart, System Director, Strategic Marketing at CHRISTUS Health out of Texas join us for an important discussion on member experience. Tune in as they dive into how putting a strong focus on accurate data shapes the consumer's perspective.This episode is sponsored by HealthSparq.

In this episode, we are joined by Paul Merrild, President of HealthSparq & Kyruus, to discuss creating a consistent healthcare experience for members and patients regardless of where they begin their search. Tune in to learn what health plans can do to ensure members have access to the information needed to select a trusted provider and how health plans & health systems can maximize their partnerships to deliver a better experience.This episode is sponsored by HealthSparq.

Doctors Want In On Their Digital Presence Scott Andrews drops knowledge from Kyruus' Provider Perspectives on Digital Access report and what it tells us about consumers' access needs. Spoiler alert: Doctors want a bigger role in their online presence and scheduling! All that, plus the Flava of the Week about the Consumer-First Health Manifesto. Why is this document significant, and how can it accelerate the industry towards consumer transformation?  Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen/

Dr. Graham Gardner, Co-Founder and CEO of Kyruus is passionate about patient care, and ensuring they get the care they need.    With the idea of a “Moneyball” approach to matching patients and providers, Graham transitioned from cardiology to co-founding and leading Kyruus, a digital health company that offers provider search and scheduling solutions.     He says he knew that there was a better way to match patients with the appropriate provider, and Kyruus' system allows patients to enter medical symptoms and book appointments.   By helping declutter the scheduling process, allowing patients to self-schedule, and get to the provider they need, doctors can spend more time with patients, and patients get the help they need more efficiently.   Graham also shares several amazing stories that show his true drive to serve patients, increase #accesstocare and #healthequity.  Learn more about Kyruus:  https://www.kyruus.com/  Connect with Graham: https://www.linkedin.com/in/grahamsgardner/ You can also listen to the interview with the following podcast providers:  Apple podcast link:  https://podcasts.apple.com/us/podcast/speaking-of/id1549592446   I Heart podcast link: https://www.iheart.com/podcast/269-speaking-of-76708275/#   Spotify podcast link: https://open.spotify.com/show/1g2LUGr0SzxbBmSHB3FHyL?si=PNO79sBOReGXQJu_CrsJEg Topical time codes:  00:39 - Transition from Cardiology to Kyruus 3:12 - How the process works  8:33 - Connecting with patients, story from medical school at Brown 11:00 - Increasing access for homeless patients  13:39 - Helping providers focus on the patient 17:40 - Forming partnerships to fully serve patients  19:59 - Patient advisory council __________________________ Thanks to the following organizations for supporting the Making Healthcare Work for You mission. Informed Consulting works with insurance carriers, digital health companies, insurtech organizations, and venture capital firms to drive distribution solutions in the employee benefits ecosystem. They help companies reach revenue potential, confidently navigate a complex ecosystem, and position benefit ecosystem innovations for more efficient growth. Visit https://www.informed.llc to learn more. _____ UpStream is the fastest-growing primary healthcare solution provider in the US.  UpStream underwrites and supports the delivery of value-based care for older patients and people living with chronic conditions. By working in partnership with healthcare practices and clinics UpStream offers a comprehensive risk-free solution for physicians that finances, delivers and sustains better outcomes for everyone. Visit https://www.upstream.care  to learn more.

Scott Andrews drops knowledge from Kyruus' Provider Perspectives on Digital Access report and what it tells us about consumers' access needs. Spoiler alert: Doctors want a bigger role in their online presence and scheduling!  All that, plus the Flava of the Week about the Consumer-First Health Manifesto. Why is this document significant, and how can it accelerate the industry towards consumer transformation?  This show is produced by Shift Forward Health, the channel for change makers. Subscribe to Shift Forward Health on your favorite podcast app, and you'll be subscribed to our entire library of shows. See our full lineup at ShiftForwardHealth.com. One subscription, all the podcasts you need, all for free. (#235)See omnystudio.com/listener for privacy information.

It's that time of the year! Summer is over and it's conference season! The Rock Health Summit was a fun session, the highlight of which was diversity, equity, inclusion, and representation. Tune in for Jess's and my thoughts on the summits, the end of the world, and new deals: Redesign Health raises $65 million, Theranica raises $45 million, Soda Health raises $25 million, and Kyruus buys Epion Health.

Host Matt Fisher's guest is Karen Conley, Senior Vice President of Clinical, Kyruus. They discuss addressing access by enabling care to be found and to schedule; making access determination process more frictionless; integration of virtual care to support access and promoting proactive care; systemic transitions needed to support value based care. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play Healthcare NOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen

The pandemic has cast a harsh light on the unequal distribution of care. Instead of hiding from the reality, leading healthcare organizations like Adventist Health are addressing the problem head-on by adopting technologies and practices that prioritize access to care. Adventist has partnered with GetWell, Kyruus, VisitPay, and Tonic Health for example, to provide consumer-like experiences for patients to help make it easier to engage with them. Healthcare IT Today recently sat down with Jason Wells, Chief Strategy, Consumer & Innovation Officer at Adventist Health and Michael O'Neil, Founder and CEO at GetWell to discuss consumerism, patient experience and the digital transformation of healthcare. Learn more about Adventist: https://www.adventisthealth.org/ Learn more about GetWell: https://www.getwellnetwork.com/ Find more great health IT content: https://www.healthcareittoday.com/

Our guest today is Scott Andrews, general manager of Health Systems at Kyruus. Scott is here today to talk about key steps to take in optimizing the patient digital experience. Resources for this episode: • Scott Andrews(https://www.linkedin.com/in/gsandrews/) • Kyruus (https://www.kyruus.com/about) • MGMA's ACMPE Program (www.mgma.com/certification/amer…ge-of-medical-prac) • MGMA Education Opportunities (www.mgma.com/events) This episode is sponsored by: MPE: DX Conference — Join MGMA's Pathways Conference DX June 7-8 online. Our digital experience is built on three content areas vital to medical practice excellence: finance, operations and data. Go to mgma.com/events to register today. Onsite Women's Health — Onsite Women's Health provides healthcare practices and providers with the ability to bring screening mammography in-house. Partnering with Onsite allows more women to keep up with their annual screening and gives anyone impacted by breast cancer a fighting chance. Learn more at www.onsitewomenshealth.com. We'd love to hear from you. Tell us what you think. Let us know if there's a topic you want us to cover or an expert you'd like us to interview. Email us at podcasts@mgma.com. The MGMA Insights podcasts are produced by Daniel Williams, Rob Ketcham and Decklan McGee.

As the new digital health consumer continues to familiarize and trust digital health solutions, health systems need to focus on those fundamental digital solutions to improve their overall experience. In this episode, hosts Reed Smith and Chris Boyer discuss the elements of a good digital health experience, and are joined by Chris Gervais of Kyruus who shares how patient access solutions are evolving as we move to the post-pandemic normal.  Mentions from the Show: A Great Digital Healthcare Customer Experience Is Critical for Health Organizations to Meet and Exceed User Expectations Reverse SEO? Hospitals caught hiding price details from Google Search 'Open Notes' Rule Delayed Until April Chris Gervais on LinkedIn Chris Gervais on Twitter Kyruus.com Learn more about your ad choices. Visit megaphone.fm/adchoices

This episode's Community Champion Sponsor is Catalyst. To virtually tour Catalyst and claim your space on campus, or host an upcoming event: https://www.catalysthealthtech.com/ (CLICK HERE) --- With over twenty-five years of founding startups and leading global product and innovation initiatives, our next guest is leveraging his passions and skillset to help our healthcare industry rapidly and sustainably create, adopt, and implement healthcare innovation at scale.  Aaron Martin, Executive Vice President and Chief Digital and Innovation Officer at Providence, joins us to discuss how he and his team are building a world-class digital innovation hub to identify unmet needs and drive solutions designed to improve health at the community level. Additionally, Aaron shares how his previous professional pursuits set the stage for him to help lead a national movement of industry professionals prioritizing healthcare innovation that improves convenience, lowers costs, and improves quality.  Join us for this timely conversation to learn why and how Aaron and his team invest in its communities and health innovation leaders to create lasting change across the healthcare industry and our nation. Let's go! Episode Highlights: Aaron's professional career leading up to Providence and the value he brings to the organization as someone from outside of healthcare. Providence Venture's process of focusing on innovation and commercial partnership within the greater healthcare ecosystem. The three big opportunities health systems can take in solving some of the industry's biggest problems. About Our Guest:  Aaron Martin is the Executive Vice President and Chief Digital and Innovation Officer for Providence where he leads Digital, Marketing, and Ventures for Providence. Aaron is also Managing General Partner for Providence Ventures where he is responsible for early stage/venture technology and device investments for the $300M Providence Venture fund. Aaron has more than 25 years of experience in product, ventures, and technology, including leadership of the Amazon teams that transitioned traditional publishing from physical books to Kindle. He has experience as an executive/founder at two venture-backed startups and has held strategy positions at McKinsey & Company. He currently serves on the board of Wildflower Health, Avia, Xealth, and Kyruus. He is also a board member of Presbyterian Healthcare Services in New Mexico. Aaron holds a BS in Economics and Music from Austin College and an MBA in finance and healthcare management from The Wharton School. Links Supporting This Episode: Providence website: https://www.providence.org/ (CLICK HERE) Aaron Martin LinkedIn page: https://www.linkedin.com/in/aaronmartinfc/ (CLICK HERE) Aaron Martin Twitter page: https://twitter.com/aaronmartinfc (CLICK HERE) Clubhouse handle: @mikebiselli Mike Biselli LinkedIn page: https://www.linkedin.com/in/mikebiselli (CLICK HERE) Mike Biselli Twitter page: https://twitter.com/mikebiselli (CLICK HERE) Visit our website: https://www.passionatepioneers.com/ (CLICK HERE) Subscribe to newsletter: https://forms.gle/PLdcj7ujAGEtunsj6 (CLICK HERE) Guest nomination form: https://docs.google.com/forms/d/e/1FAIpQLScqk_H_a79gCRsBLynkGp7JbdtFRWynTvPVV9ntOdEpExjQIQ/viewform (CLICK HERE)

Host Matt Fisher's guest is Matt Parker, Senior Vice President of Product, Kyruus and HealthSparq. Their discussion topics include, history of price transparency in healthcare; explanation of new mandates and phased approach for implementation; necessity of making data easy to access and understand for all; benefit of increasing awareness around data availability and using as differentiator; anticipation of transparency mandates breaking down silos. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play HealthcareNOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen

Julie Yoo is a General Partner at Andreessen Horowitz where she leads investments in healthcare technology. Prior to joining a16z, Julie was the co-founder, Chief Product Officer, and Board Director at Kyruus, a venture-backed health tech company recognized as a market leader in patient access.If you like what you hear, let a friend know, subscribe wherever you get your podcasts, and connect with us on Twitter @AIHealthPodcast.

Patient Access was never a straightforward challenge. It is a complex, nuanced, and layered issue that requires solutions as diverse as the people affected. The pandemic brought the varied nature of the challenge into focus. Thankfully forward-thinking organizations like Kyruus took notice and expanded their approach to the problem. We sat down with Erin Jospe MD - CMO and Chris Gervais - CTO & CSO at Kyruus to discuss the patient access challenge. Learn more about Kyruus: https://www.kyruus.com/ Find more great health IT content: https://www.healthcareittoday.com/

Chris Gervais is in the house to share some provocative thinking about how consumers are feeling based on Kyruus' Fifth Annual Patient Access Journey Report. Chris dives deep into whether we should be surprised that consumers value digitally enabled access to their healthcare. All that, plus the Flava of the Week about why leaders should be overinvesting in their consumer strategy heading into 2022. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen/

In This Episode:The days are shorter and colder, but this second COVID-19 thanksgiving is much more hopeful than last year's. At Think Medium we are thankful for many things. We are thankful for the healthcare workers who provided stellar care during such a stressful time. We are thankful that the percentage of our fellow Americans having been vaccinated continues to increase. And we are thankful to you, our audience, for being a part of our amazing journey. For this holiday episode, we asked leaders what they are thankful for and happiest about this Thanksgiving. Key Insights:Thank You Vaccines. Julie Yoo, General Partner at Andreessen Horowitz and co-founder of Kyruus, shared that she is thankful for the advancement in mRNA vaccine technology and vaccine delivery. (1:50)Thank You (Almost) Normalcy. Matthew Dicks is a storytelling coach, bestselling author, and elementary school teacher. He is thankful that some aspects of life, such as teaching in person, have returned close to normal. (2:32)Thank You Science. Ruth Williams-Brinkley, President of Mid-Atlantic States at Kaiser Foundation Health Plan, shared her thankfulness for her family, friends, frontline workers, and researchers that developed the vaccines. (4:05)Thank You Life. Lieutenant General Scott Dingle is the Surgeon General of the United States Army and the Commanding General for the Army Medical Command. He is thankful for his health, family, and opportunity to serve Army Medicine. (8:09)

Chris Gervais is in the house to share some provocative thinking about how consumers are feeling based on Kyruus' Fifth Annual Patient Access Journey Report. Chris dives deep into whether we should be surprised that consumers value digitally enabled access to their healthcare. All that, plus the Flava of the Week about why leaders should be overinvesting in their consumer strategy heading into 2022. Shout-out to the Shift.Health Content Network for spreading the awesome, yo! Check out some of our favorite related podcasts: Better Experiences with Amy Heymans, The Health Innovators Show with Dr. Roxie Mooney, DGTL Voices with Ed Marx, Healthcare IT Today with John Lynn and Colin Hung, and Hello Healthcare with Chris Hemphill See acast.com/privacy for privacy and opt-out information.

Health system digital presences can be amplified with the adoption of a content federation strategy. In this episode, hosts Chris Boyer and Reed Smith share the basics of content federation, the three critical approaches to consider, and then are joined by Scott Andrews of Kyruus and Mark Menton of HealthSparq, who share the importance of including 3rd party sites as your content distribution strategy.  Mentions from the Show: Controlling Information Silos With Content Federation Overcoming Your Content Silos: 3 Approaches to Content Federations Kyruss.com ATLAS 2021: The Future is Flexible 2021 Patient Access Journey Report Scott Andrews on LinkedIn Mark Menton of HealthSparq Kyruus.com HealthSparq.com Find Us Online:  Touchpoint podcast Twitter Reed Smith Twitter Chris Boyer Twitter Chris Boyer website

Relicans host Ali Diamond talks to Senior Developer at Kyruus, Autumn Crossan, about encouraging and helping developers to get started and achieve their full potential by enabling them to do cool stuff they want to do, making business's workforce work better, and doing code reviews + giving helpful feedback.Should you find a burning need to share your thoughts or rants about the show, please spray them at devrel@newrelic.com. While you're going to all the trouble of shipping us some bytes, please consider taking a moment to let us know what you'd like to hear on the show in the future. Despite the all-caps flaming you will receive in response, please know that we are sincerely interested in your feedback; we aim to appease. Follow us on the Twitters: @PolyglotShow.

Our guest: Dr. Erin Jospe, Chief Medical Officer at Kyruus. "Kyruus delivers leading enterprise provider search and scheduling solutions that help health systems match patients with the right providers across points of access." On this episode, we discussed: - Her background - How she got to where she is today - Her role as the Chief Medical Officer at Kyruus - Essential pillars health systems need to focus on to address patient access issues exposed by the pandemic - ...and much more! Our sponsors for this episode are BlocHealth and Curation Health. BlocHealth is building the ecosystem of services and solutions to power the future of healthcare. Through their platform, healthcare professionals and organizations can enter, upload and share core credentialing documents and information. Professionals and organizations then have the opportunity to use that information to order multiple services and solutions like credentialing, state license registration, certifications, payer enrollment, renewals, and more! On average, the BlocHealth platform saves users 40-60% on credentialing and licensing-related costs. Organizations can use BlocHealth as an extension of their team, or as their whole licensing and credentialing team. For more information, please go to www.blochealth.com and be sure to follow BlocHealth on social media - @blochealth "Curation Health’s advanced clinical decision support platform seamlessly integrates into the electronic health record and leverages more than 750 proven clinical and quality rules. With this intelligent point-of-care platform, you can power a scalable risk adjustment process and amplify quality program performance." For more information, please go to www.curationhealthcare.com and be sure to follow Curation Health on social media - @curationhealth To learn more about Kyruus please use the links below: - Website - LinkedIn - Twitter - Facebook Also, be sure to follow Slice of Healthcare on our social channels: - Website - Facebook - LinkedIn - Twitter - YouTube - Newsletter

The United States is now 5 months into its national vaccine rollout. Although hundreds of millions of doses have been successfully administered, the process has hit several snags along the way, including, but not limited to, disparities in administration and a failure to collect racial data on nearly half of those vaccinated at the national level. But to achieve this feat, health systems have had to adjust to shifting vaccine eligibility requirements, ensure outreach efforts are successful, and combat misinformation within their communities, all the while scheduling appointments and making sure shots get into arms. In an effort to meet some of the logistical challenges of the rollout, Kyruus works alongside health care organizations and provides search, scheduling, and data management solutions to help connect patients with the right care. On this episode of Managed Care Cast, we speak with Chris Gervais, the chief technology and security officer at Kyruus, and Erin Jospe, MD, chief medical officer at Kyruus.

As the new digital health consumer continues to familiarize and trust digital health solutions, health systems need to focus on those fundamental digital solutions to improve their overall experience. In this episode, hosts Reed Smith and Chris Boyer discuss the elements of a good digital health experience, and are joined by Chris Gervais of Kyruus who shares how patient access solutions are evolving as we move to the post-pandermic normal.  Mentions from the Show: A Great Digital Healthcare Customer Experience Is Critical for Health Organizations to Meet and Exceed User Expectations Reverse SEO? Hospitals caught hiding price details from Google Search 'Open Notes' Rule Delayed Until April Chris Gervais on LinkedIn Chris Gervais on Twitter Kyruus.com Find Us Online:  Touchpoint podcast Twitter Reed Smith Twitter Chris Boyer Twitter Chris Boyer website

Karen Conley, VP of Clinical Services at Kyruus shares innovative ways Kyruus is increasing patients' access to care. She and the team at Kyruus are making a difference in healthcare nationwide by doing things like taking a "moneyball" data approach to match providers and patients, to balancing virtual care with in-person visits, to how an easier search could allow patients to get an appointment with the right doctor faster, while also reducing physician burnout.

In the Fourteenth episode of our Funding the Future of Healthcare podcast series, we were joined by Graham Gardner, who is the CEO of Kyruus, and Aaron Martin, who is the Managing Director at Providence Ventures, and Chief Digital Officer of Providence’s Digital Innovation Group. In this episode, our host Pat McKay spoke with Graham to learn more about his background and career path in healthcare. We also took a chance to elaborate on Kyruus, and how it’s helping expand access for health systems to connect with patients. We also discussed how Graham and his team at Kyruus had to make pivots during the onset of the COVID-19 pandemic.

In the Fourteenth episode of our Funding the Future of Healthcare podcast series, we were joined by Graham Gardner, who is the CEO of Kyruus, and Aaron Martin, who is the Managing Director at Providence Ventures, and Chief Digital Officer of Providence's Digital Innovation Group.

Building a software company in healthcare is hard—and comes along with unique challenges no other entrepreneurs face. In this conversation, a16z bio general partner (and previous founder of genomics company Knome) Jorge Conde; and a16z bio partner and former founder Julie Yoo (of patient provider matching system, Kyruus) share their mistakes and hard earned lessons learned with Bio Eats World host Hanne Winarsky in this now classic episode, first aired on the a16z Podcast. Why is this so damn hard? How should founders think about this space differently? What are the specific things that healthcare founders can do—when, where, and why? You wish you only knew all this when you started your own company.

In this episode, Dan Kennedy, who leads Strategy and Corporate Development at Kyruus, shares his perspective on how technology can improve patient access in healthcare. Kyruus, an industry leader in the patient access space, provides search, scheduling and data management solutions to over 300,000 providers across 65+ health systems.

Chris Gervais, CTO/CSO at Kyruus, is in the house to help us reimagine the process of building a better digital experience for healthcare consumers. In this episode, you’ll hear insights from the recent 2020 ATLAS Conference and Kyruus’ annual patient access journey report, including how digital access is a key to designing a consumer-first experience. All that, plus the Flava of the Week about the need for standardized skills in our industry. Thanks to gSight, Geonetric, and the Shift.Health Content Network for spreading the awesome, yo! See acast.com/privacy for privacy and opt-out information.

On Episode 128 of Health in 2 Point 00, Jess and Matthew talk about Proteus filing for bankruptcy, Walmart buying the tech from CareZone for prescription drug management for an unconfirmed $200 million, Kyruus raising another $30 million for referrals and scheduling for large health systems, Headspace raising another $47.7 million, and CareAcademy raising $9.5 million in a Series A to provide online training for professional caregivers for seniors.

Chris McMahon is the Senior Vice President of People at Kyruus where he is responsible for all aspects of the employee experience and spearheads talent acquisition, development, and retention. Near and dear to Chris are the mission and vision of Kyruus and he is also the ambassador of the company's CORE values - Caring, Ownership, Respect, and Empowerment.  When Chris isn't wearing his Kyruus hat, he is a proud husband and father of two teenagers. In this episode we talk about topics ranging from the importance of mission in attracting the right people at Kyruus to how they've pivoted quickly to help their primarily office-based team thrive in a WFH environment.

While data is probably one of the least interesting aspects of digital transformation, it is one of the four foundational pillars. In this episode, hosts Chris Boyer and Reed Smith “dive into data” by discussing how organizations can start adopting a data thinking mindset. They are joined by Chris Gervais of Kyruus, who shares how interoperability and data liquidity can help health systems find new ways to innovate their offerings.  Mentions from the Show: Why a Data Strategy is Crucial for Digital Transformation Success Digital Transformation: It All Starts With Data Thinking What is the Difference Between Interoperability and Data Liquidity The great conundrum of data liquidity in healthcare Chris Gervais on LinkedIn Chris Gervais on Twitter Kyruus.com Find Us Online:  Touchpoint podcast Twitter Reed Smith Twitter Chris Boyer Twitter Chris Boyer website Social Health Institute

Graham Gardner discusses how his company, Kyruus, targets patient access issues in health systems.

Graham Gardner discusses how his company, Kyruus, targets patient access issues in health systems.

Julie Yoo has joined Andreessen Horowitz as its newest general partner. She will make investments out of the venture capital firm's bio fund, which closed on $450 million in 2017. Yoo spent the last eight years as a co-founder and chief product officer of Kyruus, a venture-backed healthcare provider matching tool.

Broadcasting live from the 2019 Healthcare Marketing and Physician Strategies Summit in Chicago, IL, this week's episode brings together a panel of experts across the healthcare marketing industry discussing some of the latest topics in the healthcare space including the rise of consumerism, regarding physicians as part of your audience strategy, the role of data and data-driven systems in healthcare. This lively and informative discussion is moderated by co-host Chris Boyer, and features Amanda Bury, Channel Director at Kyruus, Brian Wynne, VP at NRC Health, Mike Linnert, CEO of SymphonyRM and Jared Wilkinson, VP at Doximity.   Mentions from the Show:Amanda Bury on LinkedInAmanda Bury on TwitterKyruus.comBrian Wynne on LinkedInBrian Wynne on TwitterNRCHealth.comMike Linnert on LinkedIn SymphonyRM on TwitterSymphonyRM.comJared Wilkinson on LinkedInDoximity on TwitterDoximity.com Find Us Online: Touchpoint podcast TwitterReed Smith TwitterChris Boyer TwitterChris Boyer websiteSocial Health Institute This episode is made possible by our sponsors, Loyal Health, Influence Health & HealthGrades

with Jorge Conde (@JorgeCondeBio), Julie Yoo (@julesyoo), and Hanne Tidnam (@omnivorousread) Building a software company in healthcare is hard -- and comes along with unique challenges no other entrepreneurs face. In this conversation, a16z bio general partner -- and previous founder of genomics company Knome -- Jorge Conde; and a16z bio partner and former founder Julie Yoo (of patient provider matching system, Kyruus) share their mistakes and hard earned lessons learned with a16z partner Hanne Tidnam. Why is this so damn hard? How should founders think about this space differently? What are the specific things that healthcare founders can do -- when, where, and why? You'll wish you only knew this when you started your own company!

Join us today as we speak with Amanda Bury from Kyruus about the secrets in ProviderMatch search, match and scheduling Amanda Bury Twitter: @ciaogalchicago LinkedIn: https://www.linkedin.com/in/amandabury/ Kyruus Twitter: @kyruus Website: www.kyruus.com

Vinay Seth Mohta is Managing Director at Manifold, an artificial intelligence engineering services firm with offices in Boston and Silicon Valley. Vinay has helped develop Manifold’s Lean AI process to build useful and accurate machine learning apps for a wide variety of customers. During today’s episode, Vinay and I discuss common misconceptions about machine learning. Some of the other topics we cover are: The 3 buckets of machine learning problems and applications. Differences between traditional product development and developing apps with machine learning from Vinay’s perspective. Vinay’s opinion of what will change as a result of growth in the machine learning industry Maintaining a vision of a product while building it Resources and Links: CRISP-DM Ways to Think About Machine Learning by Benedict Evans The Lean AI process Vinay Seth Mohta on LinkedIn Big Data, Big Dupe: A little book about a big bunch of nonsense by Stephen Few Quotes from Vinay on today’s episode: “We want to try and get them to dial back a little bit on the enthusiasm and the pixie dust aspect of AI and really, start thinking about it, more like a tool, or set of tools, or set of ideas that enable them with some new capabilities.” “We have a process we called Lean AI and what we’ve incorporated into that is this idea of a feedback loop between a business understanding, a data understanding, then doing some engineering – so this is the data engineering, and then doing some modeling and then putting something in front of users.” “Usually, team members who have domain knowledge [also] have pretty good intuition of what the data should show. And that is a good way to normalize everybody’s expectations.” “You can really bring in some of the intuition that [clients] already have around their data and bring that into the conversation and that becomes an almost shared decision about what to do [with the data].” Episode Transcript Brian: We got Vinay Seth Mohta on the show today. I’m excited to have you here. Vinay’s maybe a little outside the normal parameters of who we planned to have as a guest on designing for analytics but not entirely. He has an engineering background but he’s done a lot of stuff in the product management space as an executive. Correct me if I’m wrong. You’ve been at MathWorks before, you worked on search at Endeca Technologies, and you were at Kayak, which is one of my favorite sites, actually, for booking travels. I’m sure everybody listening has probably touched Kayak at some point, and you were a product manager there, correct? Vinay: That’s correct, yup. Brian: Okay, and I know you did some healthcare. You were a CTO at Kyruus, and now, you are a Managing Director of Data Platforms at manifold.ai, which is a services company that works on data science, machine learning projects, and artificial intelligence. Is that correct? Vinay: That’s right, yup. Brian: Tell us a bit about what Manifold’s doing and what you’re doing there. Vinay: Sure thing. Manifold, as an organization, is an AI consulting company, as you mentioned. More importantly, we unpack AI into […] really focusing on data engineering, data platforms, getting your data ready, and then also building machine learning models and getting all of that put together into either an internal-facing or an external-facing product. So, I’m looking forward to talking a lot more about that. As a company, we largely work with Global 500 organizations and also a spectrum of organizations. Sometimes, I actually get down to fairly early stage startups, where they’re looking for very specialized help in a particular area like Computer Vision, for example. We are largely a team of experienced product folks and engineering folks who’ve worked at both large organizations like Google and Fullcom as well as venture-backed startups like some of the companies you’ve mentioned in my background. Brian: What kinds of projects are people coming to you guys with? Obviously, the whole AI machine learning thing is a pretty active space right now. Everyone’s trying to jump on to that and you got to invest in this. What kinds of projects are you guys doing? Vinay: That’s a great question in terms of the different places and the different motivations people have when they come to us. I try to demystify AI right from the first conversation. Particularly, when we’re talking to executives, which we often do, we want to try and get them to dial back a little bit on the enthusiasm and the pixie dust aspect of AI, and really start thinking about it more like a tool, or set of tools, or set of ideas that really enable them with some new capabilities that also can be thought of, and what I at least see as some more traditional product development spectrum. That’s really what I like to use to frame where customers are when they come to us. By the product development spectrum, I mean there is a starting point of what are the right questions to ask and what are the right types of business strategy questions I should think about, go to market-type questions that might be relevant to consider. Some customers that we’ve talked to are starting all the way back there. There are folks who’ve answered that question for themselves, and now, they’re actually starting to think more actively about what are the product-related areas I want to invest in based on my overall business strategy, what are some of the technology approaches I can take. Machine learning is not always the right answer for a pretty business problem and then really getting into more of the actual design and architecture pieces, and then the hands-on keyboard of actually building, and then deploying data engineering, related data pipelines, or machine learning models, for example. We’ve really seen clients come to us at all different phases. The parts we generally like to focus on start from the product strategy, technology strategy-type conversations, going all the way to building and delivering software and machine learning models that are going to get deployed into production. So, that’s really our zone of focus. Brian: If I could take it back for one second, you said pixie dust and I thought that was funny. But I also get what you’re saying in there. Do you think, as consultants and service providers working in the space—I work on the design side, you’re working a lot on the engineering side and the data science side—are we propagating the wrong thing when we say artificial intelligence and in the analytic space, the term big data? Stephen Few just wrote a book, I think last year, they called Big Data, Big Dupe. I tend to agree with it. There’s a lot of marketing hype surrounding the term. No one can really even define what makes it big versus regular. Do you think we have to stop using that as that? Does it matter what we call it? I feel kind of silly every time I say “AI” because it has such a loaded meaning to people that maybe don’t know as much about it. What do you think about that? Vinay: I generally agree with the spirit of your question, which is, it’s just good to use words all of us understand that map to things that we can touch when we type with our keyboards and things like that. So, it’s very helpful to talk about software engineering as oppose to AI for example or a machine learning model. I’ve also come to terms with the fact that there is a massive marketing wave that is much larger than what you or I choose to do and I think that creates the context that someone is coming into a conversation with us. When they enter the conversation, they already have some of that context. So, what is more important for us to focus on, as opposed to the specific choice of words, is really taking where people are starting in a known context and then walking them into either a world where we feel we can have a much more real conversation with the types of things that are grounded and the actual work that we do. A lot of people are uncomfortable with terms they don’t understand but they believe they’re supposed to continue using them and they should understand them, et cetera. I also find the other thing that’s nice about taking in marketing term but then really almost using it as an educational opportunity when you’re unpacking those terms. People start to feel more comfortable that, “Oh, okay. These things can be mapped into things I understand,” and then being able to use some much more effectively. At least, in our conversations with them, we have a shared vocabulary. I often bucket those conversations under recognizing that this is a marketing term. “Let’s talk about what you mean by AI and let me unpack what I mean and make sure we have a shared vocabulary.” I think there’s some nice ways to undo the marketing hype in more intimate settings, but at a larger scale, I had found that anytime I try to fight the marketing, the five-year macro trend marketing term, people mostly say, “Oh, you don’t do anything related to that and you do this after-effect.” And it’s like, “What? No, no, no. That’s not what I meant.” I think we have to pick our battles. The other thing which I always have mixed feelings about but it does feel like—and I’ve seen this with several of the major technology trends over the last two to three decades—is that it does motivate organizations that traditionally wouldn’t look at technology as enabling components of their business strategy. It does force them to at least take a look, revisit new ideas that may have been scary before. But now they feel like, “Oh, well, let’s at least take a look because it seems everybody else is getting some value from it.” It does at least stir up things inside organizations where you get some creativity going and people are willing to at least step out of their day-to-day and take a look. I’m definitely not a hype person in general, but it does seem to serve at least some positive purpose in that sense. Brian: I kind of see it—we’ve joked about this in the past offline—like there’s a new hammer at Home Depot and everyone’s racing out to go buy this tool but not everyone knows what it does. It’s just, “I got to have one like everyone else. It does everything.” On that thought, of the ten people, ten clients that come in, what role would your typical client be? And of ten of those, how many of them have either unrealistic expectations of like, “Hey, we want to do this grand project with AI and machine learning to do X,” versus, “Hey, we want to really optimize this one part of our supply chain,” or, “We want to do…” something very specific that’s been thought of in terms of either products or service offering or an internal analytics thing where they want to actually apply an optimization or something like that. How many had fallen to the “educated versus maybe less educated,” in terms of what they’re asking for from you? Vinay: I would probably say order 20% to 30% of folks are in that bucket of, “I have a very targeted need. I know exactly what I want to get out of this state of pipeline. I have this other data pipeline I’d like you to work with to put the whole thing together,” or, “I need a specialized machine learning model that will help me segment some of my customers into more fine grain way for this very particular use case,” things like that. Those tend to be organizations that already have a software engineering capability. There’s some data for other business problems already and they either need more help than they have in house or they need some kind of specialized help. So maybe, they have largely done more structured data marketing-related use cases and now, they want to do more natural language-related or in a different area. They generally have a fairly good feel of the landscape and they know how our work would plug into their work. There is probably roughly 50% of what we get as more where we get people who are VPs of Technology, VPs of Product. They understand operations in a pretty meaningful way. A line of business leader who has a meaningful business case in mind, so they already have one or more business problems in mind that they think will be compelling. They want to know, is this a good fit for a machine learning or not? What would be required to actually get to even trying out machine learning? I would put those folks in the bucket that they have thought through some of the business strategy related, sort of going back to that spectrum idea of starting from business strategy all the way to shipping something to production. I would say they are more in the product and technology strategy bucket where they want to figure out, “I don’t know what I have in the rest of my organization, but I know we have some software, we have some data based on running a website for the last four years, whatever else, or some other kind of operational system. I’d like to figure out if we could use machine learning in some way to do something predictive, for example to improve how a call center handles inbound calls and prioritizes some of the tasks.” There are cases where people have much more thought through use cases in mind, but they don’t have the expertise on: What is the data pipeline? What data do I actually need from machine learning? Have I actually ever built and deployed a model before? They’ve usually not have done that. There’re a lot of folks in that bucket. And then, the third bucket is the remainder, which is really people are starting more in the business strategy side, where they’re saying, “Oh, we’d really like to have an open-ended conversation. Our CEO has a five or ten-year vision around transforming our core business and how we service our customers.” I’ve talked to folks that are in much more traditionally industrial businesses like paper processing, for example, or staffing, or more instrument manufacturing, or other types of manufacturing. Those kinds of areas, there is really this historical model of hardware or some other service that gets provided as opposed to Software as a Service. I think everybody is interested in some kind of move to a subscription model and also some understanding of what is the relevance of these technologies. But they are not at the stage where they’ve identified a particular business case or a use case. Brian: If I’m a product manager or someone that’s in charge of bringing ROI to data within my company, say I’m not a technology company, should I be looking to make an investment in a place where maybe it’s more of a traditional analytics thing or maybe I have humans doing eyeball analysis, making decisions about insights from the data, and then saying, “Okay, what we’d like to do is actually see if we can automate this existing process. So, it’s like A, B, C, D, E, F. We want to swap out stage D with a machine learning solution to free those people to do other work”? Or is more like, “We have this data we’re sitting on. Hey, we could train it and do something with it. We’re not doing anything with it right now.” Is there a strategy or some thinking around one of those maybe being a more successful project to take on, any thoughts? Vinay: I think that’s a great way to pose the question because one of the things I would think about as with any new effort in an organization, is that you want to be successful as the person who’s bringing in some new technology or new approach, whether it’s process or people or technology. I think really having a lower risk, a smaller bite at the apple in some sense to get your first success on the board, and then starting to build on that nucleus would definitely be the way I would think about get it going. There may be different situations where, as a leader of a large organization, you really have a directive to be more transformative and that can be a different type of conversation. But as I’d think about somebody who’s in a product role at—let’s call it just for the sake of brevity—a non-tech organization, I think starting with a smaller project where you can get people used to the idea that you could do more with data, it’s not that scary, it’s like another tool, it’s like buying another piece of software and doing some training around it and those kinds of things, then it gives you a success that you can build on and people around you start to have some familiarity with it, where you get less resistance the next time you go and do some things. I think of the overall change management challenge would frame the choice of project in some ways than not. One of the other frameworks I would use also, Ben Evans from Andreessen Horowitz, recently wrote a really nice blog post about how people can organize their thinking around applications of machine learning. The core of the framework is, there are three buckets in which you can think of the problems and potential applicability of machine learning. The first one, actually, falls very much into exactly the example you gave where I might have an analyst working with existing data, etcetera. That’s ‘a known data, known questions’ bucket. So, you have a set of data already available. You have a set of questions your analysts ask every day. Maybe they’re eyeballing it. Maybe they’re running a simple linear regression or something. What’s nice about applying machine learning in that case is it’s literally like, “Oh, you have a mallet. Here I have a stainless steel hammer. Let’s see what happens if I apply my stainless steel hammer.” It’s relatively easy to get set up to do it. Our organization who knows roughly what’s already involved with that data, the semantics of the data. It’s clean enough that you could probably start working with it. It gives you a relatively easy pathway into trying out machine learning. Just saying like, “Oh, we got 50-basis point lift just by applying this new tool, without really changing anything else.” That’s one bucket. The other two buckets, I definitely encourage folks to read the article, to put in the show notes or something. The other two buckets are ‘unknown data, new questions,’ and then the last one is ‘new data, new questions.’ Just to give you a placeholder for what the last bucket is, those are opportunities that you might be able to apply computer vision or put new sensors in a particular environment. So, gathering entirely novel data streams, unmasking new questions. There’s a handful of organizing ideas like this. We generally suggest a few different articles and I am definitely happy to offer those for the show notes as well, if [you’re looking for 00:17:27] different ways to organize their thinking around approaching machine learning problems. Brian: Great. Yes, I’ll definitely put those links into the show notes. Thanks for sharing those. Also, a follow up to that. Once you’re into a project, what are some of the challenges around for projects that have user interface or some kind of user experience that’s directly accessed? Are there challenges that you see your clients having with getting the design right? Are there challenges about getting the model and the data science part right or getting it into production? I heard a lot about this at Strata Conference that I was at in London, that they’re talking a lot about you can do all this magic stuff with your data sciences in the PhDs. But if they don’t know how to either help the engineers or themselves get that code into a production environment, it’s just sitting in a closet somewhere and it’s never going to really return value. Can you talk about some of the design and the engineering challenges that you might be seeing? Vinay: I’m assuming most people listening to the podcast are familiar with traditional product development processes, design iteration, and so forth. What I’ll offer here is the difference when you start thinking about data and machine learning. We have a process we call Lean AI and what we’ve incorporated into that is this idea of a feedback loop between a business understanding, a data understanding, then doing some engineering—this is the data engineering—then doing some modeling, and then putting something in front of users. The major part here is that, you may have a particular idea around what the ideal user experience might be. But then as we start to get into the data, as we start trying different modeling techniques, we might either surface additional opportunities that there may be something compelling that the user could do in their workflow using what the model has surfaced. Or it may be that the original experience as envisioned is going to have to change because there is not enough predictive power in the data, or a data source that you thought you’d be able to get your hands on is just not going to be available, or things like that. So, there is an additional component to the [iteration 00:19:46] loop that you have to rely on, which is just what is in the data, how much can I get access to, and then some of the more traditional software engineering constraints. If it’s going to take six months to get that particular piece of data cleaned up enough such that we can actually use it, is there something lighter weight that we could at least get started with at something in front of users first, and then continue to refine and iterate over time? That’s probably the big difference in terms of traditional product development that just involves software engineering in apps versus working with the data and machine learning. There’s a little bit of just this science of what is possible inside of the data given the signal inside [00:20:27] datum. The engineering part is definitely, as you said, something that is talked less about historically and it sounds like, based on some of the things you’ve heard at Strata, that is something that is starting to change. What I’ve seen is that a lot of the tutorials, a lot of the content out there has historically been focused on, “Get your first model going,” or, “Take this particular data set and try out building a model or tweaking this or that.” In that sense, there’re also a lot of tools available for doing data science and data science exploration. It’s great that, exactly like you said, Brian, that somebody’s built a model that’s interesting. But one, if we haven’t built the rest of the product around it and then if we haven’t actually got that model to production; as I like to say, if at the end of the day somebody’s not pushing a button differently because of your model or pulling the leverage differently because of your model, it really doesn’t matter that you built it in the first place. That actually goes back to requiring engineering and product development type expertise as opposed to data science type expertise, which I feel a little bit more like traditional on science type disciplines where you’re doing experimentation. Brian: Do you get to the point where you’re midway through a project and just kind of like, “We’re not sure if we can do this,” or “The predictive power is not there”? I imagine you probably try to prevent getting into a situation where that happens. Is there a client training that has to go on if they’re coming to you too early? Like, “We’re ready to build this thing. We want to put a model to do X,” and you’re like, “Whoa.” How do you take them on like, “Come back to us in two months or when you guys have figured this out”? How do you take them on to make sure that doesn’t happen and they don’t spend all this money on hiring data scientist internally to work with you or on their own, or just you and not getting an ROI? How do you educate on that? Vinay: That’s again what we have incorporated into this Lean AI process where we’ve taken the spirit of Agile and some of the ideas around Lean startup, for example. There’s actually an old framework from the late 90s called CRISP-DM—it’s from the data mining community—and really, the idea in all of these things is tackling your big risks early and surfacing them. We take a similar approach where anybody can do this. But it’s getting an understanding of what is the business problem you want to go after and what is the data you have available. We call it a business understanding phase and a data understanding phase. During that phase of the data understanding, it’s really doing a data audit. Particularly, it’s an issue on large organizations. People think they have access to certain data but it may be that somebody in a different organization owns the data and they’re not going to give it to you. You sort of have the human problems that we’ve always had. Then there’s other parts which are, “Is there a predictive power in the data? Is the data clean?” Generally, the first thing we do is just apply a suite of tools that will characterize the data, profile the data, and help us get an understanding of what do we think is there. Usually, we work with clients, team members who have domain knowledge. They generally have pretty good intuition of what should the data show and that oftentimes is a good way to normalize everybody’s expectations. As an example, we’re working on one with an industrial client last year. In addition to sensor data coming off their devices, they also had field notes that people had entered when they were servicing some of the equipment. As we were working with their experts during the data understanding phase, the experts actually said, “You know what? I wouldn’t trust the field notes. People sometimes put them in and sometimes they don’t. The quality varies a lot across who put those notes in and what they put in there. So, let’s just not use that data source.” You can really bring in some of the intuition that people already have around their data and bring that into the conversation. That becomes an almost shared decision about what do we think we can try and get out of this data, what’s in the data, and do you guys agree that this data actually is saying what you think it should say? Those kinds of things. I would say, tackling big risks early is one of the major themes of what we do. The other part really comes from, again, the engineering approach that a lot of us have taken historically from our past experiences. [It’s probably 00:25:48] the best analogy I can do from their product management days is this idea of just doing mockups and doing paper mocks and those kinds of things before you get to higher fidelity mocks. There’s a similar idea in machine learning where we have this idea like, “Okay, get some basic data through your data pipeline. It doesn’t have to be perfect.” Then we build this thing called the baseline model, which is, “Yes, there are 45 different techniques you can use to build a machine learning model. Let’s take one of the simplest ones. Something like random forest where we know that’s not the best performing model for every use case, but it’s really easy to build. It’s really easy to understand at least out of your first version what the model is doing.” You can get some baseline of performance pretty quickly, which is, does it perform at 60% or does it perform at 80%? From there, you can start to have a discussion about, how much more investment do we want to make? Do we need to get more data in here to clean the existing data and transform it in different ways, explore different modeling techniques? Those kinds of things. I draw the analogy to some of the product development processes that we would follow if we were just doing software engineering project, which is, let’s get something built end-to-end then add more functionality over time, things like that and then take it from there. Brian: Regarding the projects you work on, are your clients , most of the time,the actual end users of this service or the direct beneficiaries, or typically, are they building something internally that will be used by other employees or vendors or their customers? How close to that is the person going to benefit from or use the service that you’re building? Vinay: I’m definitely not aware of all of our projects, but the projects I’m aware of and the ones I’m working on right now, they all have enterprise users. None of them are applications that are going to go out to end users. But nonetheless, the enterprise users are folks who are not technology people or not particularly specialized in data or anything like that. They are more folks who are executing on processes as part of a broader workflow. For example, it might be a health coach that is at a particular company, or it might be a call center employee, or it might be the maintenance and repairs center at an industrials company. It’s more internal users or if it’s external users, it’s still again enterprise users who are using a larger product. Brian: Do you ever get direct access to those when you’re working with your clients or typically, is your client the interface to them? How involved do you get with some of these like a call center rep or something like that? Vinay: It actually depends on the type of expertise that our client has. If they have a product owner and a product manager who’s fairly confident about their ability to interface with the end user, we might. Instead of them being part of the user feedback sections, as some of these models go in front of users, there may be at the beginning of a project, having a few conversations to understand the context in which particular operational data was gathered, or the workflow that might surround the model that we’re building, or the data pipeline that we’re building. We might have a few conversations. But again, if they have a strong product function already, we would probably be more isolated from that. If, on the other hand, there isn’t that much of a product function that is familiar with software engineering and product developments, some of these non-tech organizations, product managers, they are maybe much more hardware-oriented or they may not even have a product to roll, depending on the type of operation. There, we would be much closer to the end users understanding the use cases. We also want to partner with whoever is doing the product design and some of the other UX components as well. I would imagine that there’d generally be another partner of some sort. We’re interested in talking to the end users. But we’re definitely not the experts on product design and so forth. We’d expect somebody else to play that role. Either somebody like you where the client is partnered with another organization or individual, or they have capability internally. Brian: One place we think about lots of data, obviously, is in the traditional analytics space for internal companies or even information like SaaS products and information products. Do you see the capabilities of data science and machine learning that have really been enabled in the last few years? Primarily,what I understand is there’s more data availability. There’s more compute power availability. It’s not so much that the science is new. A lot of the science I hear is quite old. The formulas and algorithms have been around. It hasn’t been as feasible to implement them. Now that it is, do you see that traditional analytics deployments over time will start to leverage more and more like predictive capabilities or prescriptive analytics where there’s less report generation, less eyeball analysis? Say, in the next five years, 20% of traditional analytics capabilities will be replaced by more prescriptive and predictive capabilities because of this? Or is it really just it’s going to take a lot longer to do that? I imagine some of it’s just at the mercy of the data you have available. You can’t solve every problem with this, but do you see an evolution happening in that data? Is that making sense? Vinay: Yeah, absolutely. You’ve hit upon a really important idea. I’ll start my answer though taking a slightly different view, which is what is going to stay constant, and then we can talk about what is going to change. The part I found most exciting about business intelligence, analytics reporting, pick your category name, is when you can get it embedded into a workflow. The folks who are actually on the front lines making, running through a workflow, or going through a customer interaction or whatever, they actually have access to that data and they’re able to drive decision-making as part of their process. What we’ve seen in the last order of 20 years, is this continued increase of this notion of a data-driven organization, that people should have more access to data when they’re in these workflows and decision-making. Everything from things you’ve probably heard about, like insurance companies or telco companies, call center folks being able to offer you something if you’re going to turn, for example. An offer pop ups on their screen and they’ll able to give that to you. That’s a nice example where somebody’s actually using the decision-making as part of their production workflow. We’re just generally seeing more of that. So, no matter what, whether it’s prescriptive or descriptive, whatever else, I broadly see continued adoption of analytics and data in more workflows across a whole range of software products. I’m generally excited about that. I wish it would take less time but at least we’re continuing to make progress on that. I think what you hit upon is what’s going to change. I firmly believe we’re seeing this in name today but we’ll see this more in actual. The nature of the work itself in the future, there’s a lot of people who have the business analyst role today and organizations in their supporting different functions. Largely, I think of them as people who have a fairly deep understanding of the business. They generally live in Excel. They’re complete masters of Excel. They can build what-if models, they can do scenario-solving, they can do VLOOKUPs, and do all of those kinds of things in Excel. I think they’re going to get a whole additional set of tools. I tell people this and I’m going to go on the record here and suggest that, I’m almost imagining Excel 2020 is going to have a button that you can hit and you can say, “Here’s my data. Go try out 50 different models or 500 different models.” Excel will go off, ship your data to Azure, it’ll run a whole bunch of different models and come back and tell you, “Here’s the three that seem to fit your data best.” Really, the skill that you need at the end of the day, which is the skill you need today, is understanding the statistics of the data, having some intuition around the business and what’s going on around you, and then really being able to swap ends and these other statistical methods that we group under machine learning, being able to swap those in once those tools are mature enough for broader use in deployment. Because of that, I think yes, in the five-year timeframe, we’ll see the leading edge of more prescriptive analytics entering product workflows just like we’re now. I’d be curious about your opinion on this but I feel like we’re past the earlier doctrine more now in the mainstream phase of descriptive analytics entering some of the different products. Brian: Yes, maybe it’s fed Microsoft a little tip for how to improve their office lead down a couple of years from now. This has been really informative. Thanks for coming on. Do you have any single message or advice you’d give to data product managers or analytics leaders in businesses in terms of how they can design and/or deploy better data products in their organization or for their customers if they are like a SaaS or information provider? Any general tips you’ve seen or something you can offer them? Vinay: Maybe a handful of things just to run through it with different levels of applicability. One of them is that having a good business case, as the way we talked about earlier and taking on something small is definitely very helpful to build some success. Also, maybe squelch some of the visionary enthusiasm that people might have. In general, trying to feed some of the vision component while you’re trying to get a great concrete success on the board, is something just to keep in mind to get people excited about the potential and the future. That’s one bucket. If you have a vision in mind, one of the things your technology teams and your machine learning teams can do, and is something we definitely ask for when we do our engagements, while you’re solving a specific business case and a specific problem, you can do the work in a way that lays the foundation for longer term leverage on the work. So, if we build the data pipeline, we know that you have a specific two-year vision. We can actually start to lay some of the pieces even as part of that project to make investment towards that vision. While you should execute on smaller opportunities, you should also dream big. I think that’s one general thought. Another thing I’ve been starting to form an opinion around is that, to execute successfully on a product and execute data and machine learning component of a product, you have to have a ‘what’ in mind, like, “What is this product going to do with the data?” You need to have a product direction, product sense, product vision, whatever you want to call it to know what’s going to happen in the context of that product. Longer term, when you start to think about the context for these kinds of capabilities you need to think about organizational vision. For this product it may be that you did it with a couple of folks from another team that sat down the hall just to get something out the door. But then, really having an idea in the 18-month timeframe, do you want to build a software engineering organization? Do you want to build a data engineering capability? Do you want to have a data science team? Do you want to work with the finance team to maybe get a couple of business analysts over to a new team? I think really starting to contextualize your product vision with what’s your organizational vision, is important for the longer term picture and having clarity around that even as you tackle on the shorter term opportunities. Those are probably a couple of things that hopefully people find helpful. Brian: Yes, I definitely did. I was actually going to follow this up but it may be an unnecessary question. But one of the services that I’m often asked to come in with clients is to help them either envision a new product, something that they’re working on, and it’s what I call getting from the nothing to something phase where it’s a Word document of requirements or capabilities, features, what have you and getting to that first visual something. It sounds like you still think that that step, even if you don’t bite off the whole thing from an engineering standpoint, having an idea of your goal post about where a service might go that could incorporate some machine learning or AI technology, still is helpful and deploying a small increment of utility into the organization. Would you agree with that still? Vinay: Yes, absolutely. Even for the folks building their models or building your data pipeline to get the data cleaned up and usable, whether it’s for analytics or for your models, it’s really helpful to have that broader context as opposed to having a very narrow window into, “Oh, I need these three fields to be cleaned up and available.” If you can’t provide that broader context, I feel you end up with a lot of disjointed pieces as opposed to something that feels good when you’re done. I would definitely agree with that. Brian: Well, Vinay, thank you so much for coming on. This has been super educational for me and I’m sure for people listening as well. Where can people learn more about what you’re doing? I’ll definitely put the Ben Evans link and your Lean AI process that you talked about. So, send me those links. But where can people learn more about what you do? Vinay: Our website manifold.ai is definitely the best place to start. We have a few things about the type of work we do and some case studies as well as some background of our team. That would be helpful. In terms of my own time, I actually don’t spend that much time on social media. LinkedIn is probably the easiest place to find me. Generally, I post things there occasionally and definitely participate in some conversations there. It would be great to chat with folks there. Brian: All right, great. Well, thanks again and I hope to talk to you soon. Vinay: Thank you, Brian. I really appreciate it. It’s great conversation.

Never miss another interview! Join Devin here: http://bit.ly/joindevin. Read the full Forbes article and watch the interview here: http://bit.ly/2SGOidw. Nonprofit Providence St. Joseph Health, the third largest health care system in the United States, traces its roots back to the Sisters of Providence and the Sisters of t. Joseph of Orange. Their missions were to serve all members of their communities, “especially the poor and vulnerable,” says Aaron Martin, 49, executive vice president and chief digital officer. That motivation now guides the system’s $150 million health care impact investment fund. Martin, who had no health care experience before joining Providence, now leads its efforts to improve health outcomes and improve service levels using technology. Investments are made via Providence Ventures, a fund created by the parent and funded entirely by it to accelerate the digital mission. So far, the fund has invested in 13 companies, two of which were Providence innovations that are being spun out in hopes that they will grow more quickly and benefit not only Providence but all health care providers. Venrock, which raised $450 million in its latest fund, has co-invested with Providence Ventures on two companies: Kyruus and Lyraa Health. Venrock partner Bryan Roberts says, “Aaron is terrific; he has the knowledge of a technology and growth savvy operator with the scale of a health system at his disposal. This allows him to bring a new lens to the change-resistant, defensive technology approach of the healthcare industry while still being grounded in the current practices and having a large sandbox in which to pressure test these new ideas.” Read the full Forbes article and watch the interview here: http://bit.ly/2SGOidw Be a hero! Join the elite group of supporters who ensure that stories like this can continue to be shared! Visit heroes4good.org to become a hero now.

Julie Yoo is the co-founder of Kyruus, a medical technology company that is the developer of ProviderMatch. One of the most frustrating things about the healthcare system is the tendency for patients to be sent to the wrong type of doctor for their health issue. The industry term for this problem is patient access paradox. ProviderMatch is software that directs patients to the proper medical specialist for their specific needs. During today’s episode, Julie and I discuss the components that make ProviderMatch an effective tool. Some of the topics we touch on are: How ProviderMatch has changed the customer service side of healthcare. How ProviderMatch helps combat physician burnout. The 3 major user bases served by the application. The 3 types of tests Kyruus uses to test new and upgraded product features. The 3 levels of analytics that Kyruus uses to measure RIO and value. Resources and Links: Kyruus Kyruus on Facebook Kyruus on LinkedIn Kyruus on Twitter Julie Yoo on Twitter Julie Yoo on LinkedIn Thank you for joining us for today’s episode of Experiencing Data. Keep coming back for more episodes with great conversations about the world through the lens of analytics and design. Episode Transcript Brian: All right so we have Julie Yoo on the podcast today from Kyruus which is based out of Boston. Julie, welcome to the podcast. How’s it going? Julie: Good, thanks Brian. Thank you so much for having me. Brian: I’m excited for you to share some of your backgrounds with our listeners. You’re currently chief product officer at Kyruus. We did some work together several years back as I recall. This is actually news to me, I don’t know this—you’re in the healthcare space and you oversee product and strategy for the company and hospitals. When we all call and we want to schedule an appointment with a doctor, a lot of us get a referral from a friend or whatever and we call them and it’s difficult to get an appointment. Reality, the hospitals often have tons of supply on their end that’s not getting used and those doctors or service providers may be fully qualified to help out those patients if only the people on the scheduling side could help match the patients up with the service provider. Is that basically what your main software, the ProviderMatch software, does? Julie: Yeah absolutely. We’re solving what we’ve coined as the patient access paradox which is that fundamental mismatch between patient demands being told to wait multiple weeks or even months to get an appointment. We all assume that that’s because every slot is booked up solid in whatever market we’re in. But it turns out that on the hospital side of things and the whole system side of things, that typically our customers are operating at anywhere from as low as 70% to 80% capacity utilization. One thing I’ll qualify there, it’s not necessarily just empty slots that are going out completely unused which is certainly an issue. But what we also focus on in best utilizing your resources for the unique expertise and skills that they bring to the table. What we also focus on is are you getting to the right doctor the first time, and that’s from a clinical lens. There’s tons of subspecialties in medicine and we want to make sure you’re getting to the right specialist. Or subspecialist or even within primary care there can be variants in terms of what people focus on. Also level of care which is if you have certain types of conditions, oftentimes part of the reason why you have to wait so long is that you’re sent immediately to a very scarce specialist resource who tends to be harder to book with, has more limited time. Whereas that condition may actually be treatable by a lower acuity provider. Anything from a generalist to primary care provider, maybe even a nurse practitioner, or even a walk-in clinic. This day and age, we see a lot more activity in terms of retail clinics and walk-in care. We look across that entire spectrum of possible options to interpretation and ensure that the patient is getting routed to the most effective place in the most efficient and possible way. Brian: That’s pretty cool. I didn’t realize there is so much missed—I mean obviously the specialists wants to see them. I have any arm problem, I need to go to the best arm doctor in the world kind of thing. We didn’t know that there was so tax, like 70% to 80% under utilization rate is pretty interesting. So why don’t you tell me about your background. I know you studied pre medicine at MIT and you have an MBA from Harvard, is that correct? And you went to MIT Sloan. You have quite a background. What do you do at Kyruus yourself, and can you tell us about your background a little bit? Julie: Yeah, absolutely. It’s blasphemy that you just said that I went to Harvard MBA. I went to MIT for my MBA. Actually, I came to MIT as an undergrad thinking that I wanted to be a doctor when I grew up. I started out as a biology major doing pre med. I’m happy to be in school during the initial original dot-com boom back in the late ’90s and actually got influenced to get computer science and fell in love with it. Just the problem solving aspects of it, and I love coding and building things from nothing. I ended up actually majoring in computer science while also finishing up my premed exam requirement. My first job out of college was actually as a software engineer so I totally focused on the technical side of that track. Always, however, maintaining my personal interests in the intersection of healthcare and technology. The first several years of my career was software engineering. I worked at a company called Endeca Technologies here in Boston which I think is pretty well-known locally. They were an enterprise search technology initially focused and I think probably best known for their work in the ecommerce space. We powered the online search catalog for the major ecommerce companies across the country and even the world. I cut my fuse there and then ultimately figured out that I love being customer facing, I was kind of intrigued by the business side of things. I migrated more into product and eventually now today, I’m more of a product manager is kind of where I would identify myself. Also at the same time about six years since my career at Endeca, that was really when the federal government started pouring resources into the digitization of healthcare and that was really when I had a lightbulb moment myself around the opportunity within healthcare to apply software and technology and data to improve efficiencies as we were talking about earlier but also […] simple outcomes, of course. And so I actually made a career change by way of grad school which is how I ended up at MIT Sloan. The Harvard component is that I did a dual degree program that was a collaboration between Harvard and MIT. By way of that, I got exposure to both the business side as well as the clinical side. The Harvard-MIT HST program is the collaboration between Harvard Medical School and MIT Proper. I did my masters with that program. I initially actually focused on personalized medicine, something that’s completely unrelated to what we do here at Kyruus but it was intuitively an area where I can apply my data analytics and software expertise given that […] where software was being applied at scale in the healthcare and life sciences area. The first couple of companies that I did were in that area of genomics and genetic sequencing and personalized medicine. I had a couple of companies that I worked with there, especially the first employee of both companies on the product side, and both of those companies eventually got acquired. The second company was acquired in 2010, that was when myself and my current cofounder Graham Gardner decided to get together and go after the opportunity that Kyruus has focused on around patient access. I was the founding chief product officer at Kyruus. I wrote the first version of the product with my own two hands and have shaped the road map, user engagement, definitely own design as part of the product management function and have now as the company has scaled moved into more of a strategy role. Really focused on three to five years direction of the business, new market segment, how do we fit into the broader technology ecosystem within the digital health space but really have my anchoring and foundation in product. Brian: Cool. Thanks for sharing that background. You mentioned in there that you own the design as part of your role in product at Kyruus. If I recall correctly with ProviderMatch, the primary end users tend to be people that are scheduling appointments which may include some people with medical background like the nurse managers I believe and you’re trying to provide them with the tool that lets them take in patient requests or things like language of the provider, gender of the provider, location of the provider and obviously dates of availability. Then they are able to type in a condition like skin rash or something and then the scheduler is able to provide them with a response like, “We have these four people available on Tuesday from 11:00 to 3:00, they’re all great, here’s where they went to school.” Is that still what it is and can you tell me about how do you go about designing that experience and how do you guys know if you’re doing a good job besides the fact that the checks clear and they keep renewing. How do you guys evaluate and design for that? Julie: Yeah. You do remember correctly that one of our major user bases is the patient after call center agent who is a front line staff member whose job is to answer the phone all day every day and help patients get matched to the right doctor and then book an appointment. That was our flagship product called ProviderMatch for access centers that we launched over five years ago at this point. That remains a major user constituent that we serve. Since then, we’ve expanded our product portfolio just to make it a little bit more complicated. We actually now I would say have three major users that we serve in addition to that. One being the call center agent that you described, another actually being the patient or the consumer, him or herself. We actually have launched a patient facing product called ProviderMatch for Consumers several years ago at this point, but the idea there is to enable us consumers to self-serve. We have a white label product that our customers will embed in their websites or their mobile apps. They’re kind of public facing digital storefront, so to speak. That allows for us to do our own research on who might be the best provider for me based on my preferences and my criteria. And then also facilitate on my scheduling, being able to actually book an appointment physically online. That’s the second user-base that we serve. Then a third major user-base is actually the physicians and the providers themselves and this has become a very powerful leverage point for us to be able to engage these organizations at scale and really provide a strong value proposition back to the physicians who I would say, traditionally in the digital health world, are sometimes viewed as optical. A lot of companies struggle to really engage with those providers and expect the value proposition that’s big enough to get those individuals to buy in, let alone to actually use product. You may recall originally my philosophy around ProviderMatch was we need to design a product that can be deployed and go live and drive value without any reliance on physicians doing anything in our product. The primary reason for that is that physicians are extremely busy. I think the strategy to depend on the physician to come out of whatever their core workflow is, take away from the time that they’re spending with a patient to learn a new thing and/or using a different app than what is core to their clinical mission through observing the patient. We actually started with that philosophy, but as we matured and as we were demonstrating great outcomes, we were able to kind of pivot into a much more explicit physician engagement approach. Today, they are actually the majority of our users, technically speaking, in terms of the number of users who are accessing our products, that’s another dimension to it. As you can imagine, each of those user bases is extremely different. We could go on and on and I’m happy to go in whatever direction would make sense but we have a pretty distinct framework that we use for each one of those user-bases. Yes, we serve them all through the same uniform platform and there are certain elements of consistencies that we want to drive across user experience across those three user-bases. But as you can imagine, the use cases, the stories, the scenarios that we’re addressing within each of those products can be quite […]. Brian: Can you tell us a little bit about how you design for these different constituencies, if you have like a recent anecdote about maybe a project you guys did and how do you keep all this simple and keep the scheduling time as minimal as possible which I assume would be the goal here, so that the maximum time is spent on patient care? How do you design for those experiences? How do you move through that? Julie: I think just the basic thing we start is just a crisp definition of the actual user personas and certainly each of those user sets is using our product for a very different purpose. Take the call center agent for instance, when they answer the phone, the person on the other end of the phone clearly already has some intention of taking some action because they’ve gone through the work of dialing the member, waiting for someone to answer, and clearly are looking to get served. A lot of message that around that user base is efficiency. You’ve got only a few seconds to capture the attention of that customer and essentially convert them. One of the ways that we define the job of the call center agent that might be distinct from the other users is their primary goal is conversion. They need to drive yields from every 10 calls that come in with a patient looking to get an appointment. We want the number of booked appointments that come out of that to actually be 10. Some of the sort of sad state of affairs in the healthcare industry is that many of the organizations that we engage with are starting at conversion rates as low as 20% meaning every 10 patient that call in, trying to get an appointment, maybe only 2 of them will leave that call with an actual booked appointment in hand. There’s a ton of sort of depth around how do we drive that use case for that user base, which is distinct from the consumer. The consumer, I may just be doing research and I might be early in my funnel, in my patient journey and not yet ready to book an appointment when I’m engaging with ProviderMatch. It might not even be me, I might be doing some research on behalf of someone else or certainly I might be coming with an intention to book. I would say a big challenge that we’re still chipping away at and have tons to learn is how do you effectively segment those user stories and scenarios and serve all those user sets and narrative through a single product. That is a different set of problems. Whereas physicians, on the other hand, the primary goal for them to come into our solution is to optimize the configuration of rules engines that determine which patients get referred or scheduled with them. That’s much more of a personal experience in a lot of ways because the physician is looking to us, our products, to help describe to the world what it is that they do and under what circumstances should a patient be sent to me. That sort of elicits a whole different emotional experience in some ways that relies heavily on an empathy for the perspective of that physician and really a kind of, I would say, caution around making too many assumptions about what that individual is looking to accomplish or how they want to express their clinical expertise through our product. There’s a whole, again, another set of narratives around that piece Just that mere definition, hopefully it paints the picture of just the complexity that results from having to serve such user set. We do have different team that focus on different user experiences as well and that ability to have individuals specialize in certain areas just gives us a lot of depth around how we’re able focus and describe a lot of insight into those varied populations versus kind of diluting it by having teams spread across those areas. Those are some of the types of framework that we use to be able to effectively address those user populations. Brian: Do you have either your designers and/or the product managers, it sounds like you have them assigned to each of the different products that focus on the different personas, do they do any type of interviews or any type of research activities with these, I’m curious, you can like learn anything, have any cool nuggets of stuff that maybe you would have found out through the design process about talking to a doctor, like, “I would never type in that I’m an expert at this even though I totally am because X,” or… Julie: Yeah. Brian: …did you find any nuggets that are kind of interesting? Julie: Yeah, absolutely we do, I would say, three major types of testing. One is we actually are privileged to have lots of folks who are either physicians or ex-hospital administrators at our company, so we have in house team that can serve as sort of test users for a lot of our new concepts, where we do kind of an internal testing when we’re developing new ideas or get designs. That’s one way we do it. We also obviously use external testers as well, whether it be sites like usertesting.com or other service that allow you to recruit ad hoc users and test various concepts. We’ve got a lot of that kind of work as well. We also go observe our users at our customer site and we’ve done a combination of both observation of actual call center agent-type users within their dedicated setting, but also direct consumer research, we’ll giveaway Starbucks cards to regular people off the street who are willing to kind of sit down and give us feedback. All of that is a source of data into our process. So many stories of things were just completely eye opening. Everything from, I mentioned earlier, the emotion that gets elicited when you are working with a physician to try to define what their referral protocols are. Imagine sitting down with an engineer and designing a routing protocol for determining what project they get assigned to and just how personal of an experience that would be. That’s kind of the same lens that we observe and experience with the physician in a period of time where you may have read this or heard this, but certainly in healthcare, one of the major topics and stories that has a lot of buzz right now is physician burnout. We live and breathe it every single day with our users where physicians are really burned out and their job has become less about direct patient care and much more about administrative tasks and tracking of data and submission of billing information, things of that sort. Part of the line that we have to navigate is how do we introduce our solution which we believe has such a strong correlation with less burn out sensation and the ability to actually focus on the types of cases that you want to focus on and leverage your many years of training for the thing that you’re uniquely qualified to do. How do we do that in this context where people have no mental space and energy left to take on new products and new applications in the workforce, a new task. I think the emotional aspect of the finishing engagement piece is definitely something that I distinctly remember from so many of those conversations. And then I think it’s also form a consumer lens, when I think about the patients, I think we’re doing a big role. A part of our role at Kyruus I believe is to really educate market about how to think about doctor appointment booking. I think too often, consumers think that whatever appointment they can get soonest is the best option for them. Obviously, they don’t necessarily realize the downstream negative impact of making a choice to go see one kind of doctor who is available tomorrow versus waiting maybe a few days or maybe a couple of weeks to see the doctor who might be better qualified for you from a clinical end. That’s part of what our product is about, the core philosophy of our solution is, yes, get the patient in efficiently and quickly as possible but never at the expense of getting them to the right clinical provider. That’s another piece that I see come out in droves when we’re doing user-testing is, “Why can’t I just book this one that is the soonest,” before in the workflow two steps ago and just kind of explaining, how do we present that in the user experience has been a big challenge for us. But certainly something that is a primary goal for our product. Brian: Do you find with the service that you provide that’s more doctor facing especially on where they—it sounds like they have to input a bunch of preferences which then enables them to receive more qualified bookings into their calendar so to speak. Is it hard? One of the things I talk about in my list a lot is the need to go out and have direct one-on-one conversations with the people that are going to use your solutions. Especially with analytics products where lots of data—as the data grows, the complexity tends to go up. What one of the problems that enterprise that companies have is access to the actual, not the buyers of these platforms, maybe you’re selling into a CTO or something like that in a hospital network but they’re probably not the ones that are going to be using the interfaces and it’s hard to get access. Do you have that problem and do you have any ways that you’ve worked around to entice them to participate in research? Julie: Absolutely, that is absolutely a challenge for any company in our space with positions in particular at the audience. Even frankly with our call center agents because they have such a real time job that any interruption during the day while they’re on call to answer the phone can be viewed as engagement. Yes, we absolutely deal with that. We have the benefit of a—my cofounder’s position, our CEO, we happen to have a very rich network of physicians who are friendly to Kyruus and are certainly willing to take time out of their day to come tell us what it’s like on the other side and obviously their feedback on our product. We are very careful always to balance the types of physicians. There are physicians who work in organizations like Mass General here in Boston that are highly specialized, highly academic focused, probably have a big focus on research and are really on the leading edge of novel innovative medical treatment paradigm versus many of our clients who are not that and who are just regular old community based hospitals that kind of deal with the general population and are not necessarily seeing the most […] but have to serve millions of consumers and patients who have very basic needs. We’re always careful to balance the type of physicians that we talk to and get feedback from across those various settings. We also, over time I would say, have taken a much more prescriptive approach with our customers around physician engagement. Certainly has to be the case from the first launch that we were tip-toeing around the clinical leadership and didn’t want to bother the folks who were kind of on the clinical frontline. That became a challenge for us to really configure and validate the data within our platform to make sure that we’re driving the right outcome. Now, fast forward many years later, we actually have as part of our implementation playbook a requirement to engage with the clinical side of the business. That was a hard cultural transition to make both internally and with our customers. But now that we have so much data which we can probably talk about but, we have data that shows the benefit of doing that. Not only just data but oftentimes qualitative narrative plays a big role and just getting people to buy into that paradigm. We pretty explicitly sort of I wouldn’t say forcefully but you know, it’s highly recommend to our customers that Kyruus is employed as part of the acquisition process and directly talks to physicians. We’ve taken a pretty hard line on that and it certainly benefited us. Brian: So like when they sign a deal, there’s actually something in the agreement about your right to access their providers to make the service work and that type of thing? Julie: Not contractual at all, it’s part of our implementation playbook is what I’ll call it. Where we lay out here are the four tracks of implementation that we need to accomplish and X number of months. One of them is just purely technical data integration, things of that sort. One might be how do we design our workflow, one might be around analytics and then one is actually physician engagement. It’s really just part of our implementation methodology. Just like almost kind of a consulting mindset. When you hire a consulting firm, they’ve got their recommended way of doing things and you sort of assume that in order to get the best outcomes, you want to follow their playbook. That’s kind of the approach that we’ve used with our acquisition process. Brian: I see. That’s really interesting. I like that idea of encouraging it from the outset as part of a product company. I think that’s a really great idea to bake into your product if you’re on premise deployment type of situation where there’s some kind of set up process and you guys obviously have to go through some level of customization probably with every new hospital network that you guys bring onboard. Julie: We like to say configuration, not customization. But yes, absolutely. Brian: Oh okay. And you mentioned analytics at the end. I actually did want to jump into that. So obviously if you guys are selling this product on—you’re almost like a market maker. You’re bringing supply and demand, you’re optimizing supply and demand. What type of data, or interfaces, or maybe it’s APIs of the hospital. But I imagine they want to know what their ROI is for purchasing these systems. Do you have some type of reporting or analytics dashboard that helps the administrator? Who would be those users and tell me what some of their use cases might be if you indeed have something like that. Julie: Absolutely. Analytics is critical to the value narrative and ROI of our products. We actually do have a webpage in our analytics product, provide and match analytics that comes with our platform. There’s a number of ways by which we deploy it. So first of all, a user, an end user who has the appropriate level of authorization can just log into their browser window and see the analytics dashboard at any point of any day. We’ve obviously optimized it. We have a set of canned reports that we offer out of the box to represent the KPIs that we’ve designed as the leading indicator for the different products that we have. That’s one major component of it. We have a framework where we think about three levels of analytics. One is what I call reflective analytic which is kind of the most basic reporting where we’re sort of almost leading back to the organization what kinds of activity are flowing through our products. It is literally demand and supply. Meaning how many requests for this kind of appointment came in in the last week and then bumping that up against your provider network supply side so to speak saying did you have a sufficient supply to serve that need and what kinds of gaps do you have in that network. That’s kind of the most basic reflective analytics. One level up from that is what we call impact metrics that say okay, of the 1,000 calls that you got for interpolation related services last week, what percentage of them converted into an actual booked appointment? What percentage didn’t convert and what was the outcome of those calls, why weren’t you able to serve those needs? How many new patients were you able to acquire through your web based find a physician application that’s powered by ProviderMatch and how many accomplished customers returns to you, were loyal to you by coming back to you and booking a follow-up appointment. So those are some of the types of impact metrics that are kind of a level up from that requested data but demonstrates some kind of business outcome that our product is associated with. And then the third tier is ROI, true ROI, financial ROI that says, okay, so relative to baseline historically before you can click ProviderMatch, you were able to utilize X percent of your scheduled resources. You had X number patient appointment that were booked in an X period of time of this distribution across primary care and specialty care. There’s actually a benchmark dollar amount that are out there that are well accepted that represents the top line value of each booked appointment. So maybe your specialist cases are worth $2,000 and your primary care is worth $1,000 multiply out the volume that have come through ProviderMatch relative to baseline and determine what did you get for the money that you invested in our product. That obviously is a bit of a holy grail where you’re able to demonstrate what did you get back for how much you spent on Kyruus and obviously if you are willing to invest more. Those are kind of the three levels that we describe. The first two tend to be really self service. You can log in to that web page dashboard, see it, believe it, move on. We have an account management team that has a more of a high touch engagement model with that third tier where we go to the C-level executive team essentially and present that back in an actual face to face meeting on a quarterly basis because there’s a tremendous amount of depth, obviously a tremendous amount of assumption and business context that you need to be wrapped around the presentation of that kind of data. We make sure that we’re doing that in a fairly high touch way versus some of our more self service analytics report. Brian: That’s really interesting about how you called it reflective analytics and kind of moves up the value chain almost in terms of being able to quantify ROI for the investment. Is there a way to tell whether or not any ends that… I totally get hospitals there’s a financial side to healthcare. Obviously it’s a huge financial part of healthcare but in terms of improving patient lives and quality of healthcare and all of that, is there any way to quantify or measure from your service that healthcare is improving or it is that kind of implied from assuming more booked appointments with more qualified. We assume they got better. Is there any way to that you guys can provide that insight or is it too difficult? Julie: Yeah, we have a couple of ways to think about it. First of all, clinical quality measurement is something that we as a society have yet to crack fully. There is no silver bullet. If anything, there are way too many quality standards out there and not yet what I would call a systematic standard for measuring the impact of a good intervention from a clinical quality lens. We look at it from one of two ways. One is definitely a derivative by way of getting you two different doctors at first time in a timely fashion, we’re avoiding A, just making sure that you’re getting the care that you need, first of all and B, if you were to not get that care at a timely manner typically […] the delayed care can have a very detrimental impact in terms of the overall health of the patient. That’s more kind of a derivative way of qualitative learning, one way to think about it. The actual thing that we are looking to quantify and measure and we actually have a couple of academic studies that we published on this topic that were a proof of concept of sorts, what needles we can move. A big part of what we focus on is focus. If you are an orthopedic surgeon and yes you’ve been trained in 40 different type of things and could technically see a lot of different type of patients, you actually might be best to see a certain handful of those things. Maybe five types of procedures that you’re sort of more uniquely qualified to focus on. If you’re not using a system like ProviderMatch, let’s say that you’ll get referred something from that bigger bucket is pretty hard because you booked the orthopedic surgeon. They assume that you can see any of these type of cases and they end up getting pretty varied spectrum of a type of referral. By way of using ProviderMatch, we’re able to deterministically narrow the focus of what gets sent to that physician. There are many studies that show two things. One is if a physician has more experience around a certain procedure type, then they tend to be better in terms of outcome, mortality and morbidity than physicians with less experience, kind of the Malcolm Gladwell 10,000 iteration type rule. So lots of studies show that. The second thing is let’s say you and I, Brian, are both orthopedic surgeons and I do 50 hip replacement surgeries a year. That’s my practice but you do 80 hip replacement surgeries a year but you also do 30 knee replacements and 20 of some other type of procedure. Even though you do more hip replacements than me, the data shows that I’m still going to be the higher quality surgeon because I’m focused on just that procedure. That’s what is our clinical holy grail we call it where through the use of ProviderMatch, we demonstrate that we are allowing physicians to not only drive volume around certain areas but also focus more specifically on the areas that they are uniquely qualified to serve and therefore drive better outcomes. Brian: I could see how you guys could derive that. Someone’s spending all of their time doing their kind of specialization area obviously. They’re probably building more expertise on that. Do you have any advice for other product managers of data products or analytics practitioners in terms of leveraging design to bring more value to your own business, your organization, your customers. Have you seen any positive change that’s come out of a particular design activity that you might have done that you’re like, “I would fully recommend doing this,” or, “I think that’s a really good fit for the product.” Any comments on that? Julie: Sure. I think there’s obviously tons of topics like the ones that I described that you can certainly use on a day-to-day to do design and kind of execute the process. But I think the more global statement I would make is that your focus on design has to be genuine and the only thing […] as the founding head of product, I’ve always looked at design as a critical element of why our product is going to be differentiated and more successful in the market. Part of how I know that that worked out and then played out is that our customers, we do an NPS survey with our customers periodically. The number of comments that we get back that say, “Your solution is the easiest to use that we’ve ever used in this area.” “The design is so simple. That’s what gets us to use the product and stay using the product.” We get that kind of feedback every day. I think oftentimes, I talk to a bunch of product leaders so technically there’s other companies. If that’s not coming from the top, if that’s not a genuine thing and a belief that the person at the top of the totem pole doesn’t have, then I think oftentimes design becomes something that […] and it’s harder in that scenario to make design not just an element of what’s being done but really a core part of the engineering process. That’s kind of the advice I would give. Design shouldn’t be another thing, it should be part of the actual engineering process. Easier said than done but literally, if we think about our teams and how we design some teams in addition to having obviously your engineers, your POs, your project managers, your medreps, a design lead is a required element at each of those teams. That makes it a sticky and fundamental part of the day-to-day process versus someone who calls in as a consultant. Oftentimes after the fact which is kind of the […] after a lot of the fundamental thinking has already been done versus having that person be just part of that core team that’s doing the thinking from day one. That’s kind of how it’s played out with that. That said, I would say it’s a constant struggle when you’re an organization that’s growing rapidly, that has limited resources that has 100 priorities, making sure that you are always emphasizing the value of design which is sometimes very hard to measure in quantitative terms. It’s always a challenge. But I think if you do have a leader who believes in the power of design and that you have properties that make it a core component of how you execute, that you’re much better set up to do that than otherwise. Brian: Yeah. I think there’s some good stuff there. Most of the clients that I work with, you can usually tell from the investment and enthusiasm and importance that’s placed on the discipline at the top how well it’s going to impact, or how much if at all it’s going to impact even if they have a large amount of staff if those staff aren’t properly engaged in the process, they’re not inserted at the right time, they’re not working upstream with business stakeholders to kind of… I always see this, helping to visualize and put the right experience in to reflect the intent of the product manager and the business. It’s the execution, even though it’s a strategic role in a way, it’s executing that vision for engineering so that they build the right stuff. If they’re not deployed properly, then at best, you’re back to maybe painting the pick or doing kind of surface level changes and that can then obviously trick all the way down to your downstream stakeholder like the data that comes out the other end and how useful are those analytics about ROI and stuff at the end. I think some people in the analytics space are still kind of learning. I kind of get this feeling in the data and analytics industry that we talk about data visualization a lot but not necessarily about user experience and what the ROI that good design can bring. You tend to talk about just UI level details but not necessarily the strategic side of aligning the products from the needs of the users and the business to kind of get both of those positive outcomes. Because obviously, if the business is successful, you can then pump more money back into investing in a better product and experience. It’s kind of a win-win for everyone if you have that buy in from the top. Julie: Yeah, exactly. We have the benefit of selling into typically what’s labeled as patient experience budget. More and more health systems these days are realizing that historically they’ve been super optimized for physicians. If you look at the example that I always use is if you go to any traditional hospital website that’s not using a product like ProviderMatch, the first question that they typically ask you as a patient is what department do you need to see and how are you as a consumer supposed to know whether or not you’re supposed to go to cardiology versus pulmonology versus neurology. It’s kind of ridiculous that we put that burden on the patient. Now, organizations are really thinking we can’t do that anymore. We can’t get away with that, consumers expect more because of the bar that has been raised during their experiences in other industries. For better or for worse we always say, “Why is it so easy to book a multi-leg international complex flight using just my thumb and 30 seconds on a mobile app, but it’s so hard to get a primary care doctor appointment in healthcare? “That’s something that our customers are recognizing. Because of that, everyone in our company has had some experience with that. We all have empathy with what difficulty and challenge exist around historical software booking process. That’s really where… it’s not coming out of like what are the pixels and what color are the buttons and what does the UI look like but what does that entire experience that can be emotional and you might have some diagnosis and some crazy disease and be fearful and anxious while you’re going through the experience. We always try to coach our team to remember what it’s like to be on the outside of the table when you’re […] your workflow and whatnot. But yeah, we again have the benefit of being in a space that I think everyone understands and has to some extent experience. You know the bad side of what does it feel like if it’s done poorly so that there’s a lot more kind of fundamental motivation at a higher level than just the UI. Brian: Yeah. You guys have that benefit. I think a lot of people probably don’t get that as much where it’s almost like you’re developing a consumer product in that sense where you can relate them. Like what movie should I go see and checkout and what theatres do I pick and all of that with the whole staff. Everyone at some point is going to go see a doctor so you can empathize with the scheduling process. For listeners that aren’t in that situation where maybe you’re working on something very esoteric or maybe it’s a complete B2B thing where your staff haven’t worked in that industry and don’t know that pain, it’s even more important to go get that one-on-one face time. Especially getting your engineers and designers to talk to these people and kind of start to develop that empathy. It really can change the way they approach their work. That’s cool that you guys are in that space where everyone can probably relate to the pain of the hassle around picking […]. I hate that stuff when it’s like, “Go talk to this department.” I don’t care what department it’s in, I just need to get this thing done and I want to know what the results were of this test and I don’t know who to call, it’s your problem. Julie: Exactly. Brian: Well, cool. This has been super fun. It’s been great to catch up with you and hear what you guys are doing at Kyruus. Can you tell people where they can learn more about you and what you guys are doing? Julie: Absolutely. We’ve got a great website with a ton of resources and videos and white papers and case studies and what not around what we do as a company, kyruus.com. We have a pretty big presence on social, on Twitter, on Facebook, on LinkedIn. Follow us there. And then me personally, I think Twitter is probably the best place for folks to follow along with what I’m up to. I’m @julesyoo on Twitter. Brian: All right, I’ll put that in the show notes, the link to your Twitter account and also over to Kyruus. Julie, thanks for coming on the show. It’s been great to catch up with you and I hope we get to cross paths soon. Julie: Absolutely. Thanks so much for having me, Brian. It was good to chat.

Julie Yoo is the co-founder of Kyruus, a medical technology company that is the developer of ProviderMatch. One of the most frustrating things about the healthcare system is the tendency for patients to be sent to the wrong type of doctor for their health issue. The industry term for this problem is patient access paradox. ProviderMatch is software that directs patients to the proper medical specialist for their specific needs. During today’s episode, Julie and I discuss the components that make ProviderMatch an effective tool. Some of the topics we touch on are: How ProviderMatch has changed the customer service side of healthcare. How ProviderMatch helps combat physician burnout. The 3 major user bases served by the application. The 3 types of tests Kyruus uses to test new and upgraded product features. The 3 levels of analytics that Kyruus uses to measure RIO and value. Resources and Links: Kyruus Kyruus on Facebook Kyruus on LinkedIn Kyruus on Twitter Julie Yoo on Twitter Julie Yoo on LinkedIn Thank you for joining us for today’s episode of Experiencing Data. Keep coming back for more episodes with great conversations about the world through the lens of analytics and design.

We’re thrilled to kick off the first episode of Funding the Future of Healthcare with two very special guests — Julie Yoo, one of the Co-Founders of Kyruus, and Aaron Martin, Board Observer of Kyruus, and Chief Digital Officer at Providence St. Joseph Health.

This week, hosts Reed Smith and Chris Boyer come to you live from the Fifth Annual Thought Leadership on Access Symposium in Boston, MA. They are joined by a panel of experts, including Chi-Cheng Huang of Wake Forest Baptist Health System, Jennifer Melby of Piedmont Healthcare, and Chris Gervais of Kyruus, in which they discuss the concept of “systemness,” how consumerism is impacting health systems today and the differences between patient-focused and patient-centric design. Mentions from the Show: The ATLAS Conference Chi-Cheng Huang on LinkedIn Jennifer Melby on LinkedIn Chris Gervais on LinkedIn Find Us Online: Touchpoint podcast Twitter Reed Smith Twitter Chris Boyer Twitter Chris Boyer website Social Health Institute This episode is made possible by our sponsors, Loyal, Influence Health, & Binary Fountain

We’re thrilled to kick off the first episode of our latest podcast series called Funding the Future of Healthcare with two very special guests — Julie Yoo, one of the Co-Founders of Kyruus, and Aaron Martin, Board Observer of Kyruus, and Chief Digital Officer at Providence St. Joseph Health.

From Salt Lake City, hosts Reed Smith and Chris Boyer welcome a panelists of guests from the Healthcare Marketing & Physicians Strategy Summit: Dan Dunlop (Principal at Jennings), JK Lloyd, President and Co-Founder of Eruptr, Andrew Rainey, EVP of Strategy for Binary Fountain, and Travis Moore, SVP, Market Solution Sales at Kyruus. In this episode, the guests discuss the potential fallout of the Facebook/Cambridge Analytica news, dive into a deep discussion on the concept of the “digital front door,” and end the episode with a spirited debate. Mentions from the Show: Dan Dunlop on LinkedIn JK Lloyd on LinkedIn Andrew Rainey on LinkedIn Travis Moore on LinkedIn Find Us Online: Touchpoint podcast Twitter Reed Smith Twitter Chris Boyer Twitter Chris Boyer website Social Health Institute This episode is made possible by our sponsors, Loyal, Influence Health, & Binary Fountain

This interview is part of our HIMSS18 coverage. We'll be talking with thought leaders and vendors all week at the annual Health Information Management Society conference in Las Vegas. On this episode we talk with Travis Moore, SVP of Market Solutions at Kyruus and Matt Gove, Chief Consumer Officer at Piedmont Healthcare, about provider data and patient access. We discuss how to address provider data inconsistencies across systems so that you can enable a better patient experience. Topics include: Self-scheduling and why your patients are ready for it Call-center scheduling Doctor-to-doctor referrals and in-office scheduling Why at Piedmont Quick Care Retail Clinics in Walgreens more than 50% of the volume is booked online. The big take away for me is that patients are ready for online scheduling and they want to be seen on their own terms. This is evident in Piedmont's high online booking rates, a preference to have a scheduled time even at walk-in retail clinics and in how millennials seem to be embracing asynchronous telemedicine options. About Travis Moore, SVP of Market Solutions at Kyruus Travis Moore is Senior Vice President of Market Solutions at Kyruus, where he is responsible for working with existing, and future clients, to provide them with insight into how the Kyruus platform can be used to improve patient access. Prior to joining Kyruus, Travis was with Influence Health for 12 years – starting his career as a Sales Account Executive, then transitioning into the Director of Sales role, and later becoming the VP of their Sales / Product Specialty team. Additionally at Influence Health, Travis was VP of Product Management and Strategy before eventually focusing on the clinical aspects of the business as the SVP of Clinical Solutions and Sales. Prior to Influence Health, Travis was responsible for Product Management over the patient education and nursing solutions at Truven. Travis started his career in healthcare as a Pediatric Nurse on the Neurotrauma and Orthopedic unit at Children's Hospital in Denver, CO. Travis has his Bachelor's degree in Nursing from University of Wisconsin-Milwaukee and MBA from University of Phoenix-Denver. Twitter: https://twitter.com/tmoore634RN LinkedIn: https://www.linkedin.com/in/travis-moore-mba-rn-4651b11/ About Matt Gove, Chief Consumer Officer at Piedmont Healthcare Matt Gove is Chief Consumer Officer for Atlanta-based Piedmont Healthcare, where he oversees marketing, communications, patient experience, community benefit and government relations for the seven-hospital system. As Piedmont's Chief Consumer Officer, Matt shapes the system's approach to healthcare consumerism, working closely with physician practices, hospitals and outpatient services to provide a better understanding of Piedmont's customers, how to better meet the consumer's needs around access and experience, and how the system can best use emerging technologies to engage consumers. Under Matt's leadership, the Piedmont team has won more than three dozen local and national marketing awards since 2013, and he has been individually recognized as AMA/Atlanta Corporate Marketer of the Year and American Business Awards Marketing Executive of the Year. Twitter: https://twitter.com/gove LinkedIn: https://www.linkedin.com/in/mattgove3/ About Kyruus Kyruus delivers proven provider search and scheduling solutions that help hospitals and health systems match patients with the providers best suited to care for them. The ProviderMatch suite of solutions—for consumers, access centers, and referral networks—enables a consistent patient experience across multiple points of access, while aligning provider supply with patient demand. The company's proprietary provider data management platform forms the foundation of its solutions, powering them with accurate data by coupling data processing with administrative applications. To find out why a Better Match Means Better Care, please visit www.kyruus.com. You can find the rest of our HIMSS18 Interviews here. Subscribe to Weekly Updates If you like what we're doing here, then please consider signing up for our weekly newsletter. You'll get one email from me each week detailing: New podcast episodes and blog posts. Content or ideas that I've found valuable in the past week. Insider info about the show like stats, upcoming episodes and future plans that I won't put anywhere else.   Plain text and straight from the heart :) No SPAM or fancy graphics and you can unsubscribe with a single click anytime. The #HCBiz Show! is produced by Glide Health IT, LLC in partnership with Netspective Media. Music by StudioEtar

Welcome to Episode 15 of The VentureFizz Podcast, the flagship podcast of Boston's most trusted source for startup and tech jobs, news, and insights! On this episode, VentureFizz Founder Keith Cline is joined Julie Yoo, Co-Founder and Chief Product Officer at Kyruus. Kyruus is a healthcare tech company that is ultimately solving some critical issues when it comes to not only getting the right doctor or specialist but helping to improve the access to these experts so you can get treated sooner. The company has 120 employees, and has raised over $60M in funding from Highland Capital, Venrock, McKesson, and others. In this podcast, we cover lots of topics, like the early days of her career at Endeca, how Moneyball was an inspiration behind Kyruus, advice for women raising venture capital, and lots more! Lastly, if you like the show, please remember to subscribe to and review us on iTunes, or your podcast player of choice! And make sure to follow Kyruus on Twitter @Kyruus and VentureFizz @VentureFizz.

People don't come to hospital websites for fun - they are there for a purpose. More times than not, that purpose is to engage and interact with the health system - finding a doctor, paying a bill, signing up for classes...even applying for a job. In this episode, hosts Reed Smith and Chris Boyer discuss how organizations can begin improving the online transaction. From understanding and defining users needs to diving deep into some of the principles of usability, this episode outlines important takeaways you can use to ensure you are delighting users looking to transact with your organization. Featuring an expert interview with Julie Yoo of Kyruus, in which she shares best practices in developing an effective online appointment scheduling system. Notes:: - KPMG 2017 study “The Truth About Online Consumers” https://assets.kpmg.com/content/dam/kpmg/xx/pdf/2017/01/the-truth-about-online-consumers.pdf - 10 Principles for Creating Amazing Online Retail Experiences https://econsultancy.com/blog/68839-the-10-principles-for-creating-amazing-online-retail-experiences - How to Address Shopping Cart Abandonment Rates: https://econsultancy.com/blog/69318-how-do-we-find-a-solution-to-the-great-shopping-cart-abandonment-problem/ - Julie Yoo LinkedIn: https://www.linkedin.com/in/juliekyoo/ - Julie Yoo Twitter: https://twitter.com/julesyoo - Kyruus: https://www.kyruus.com/ - ATLAS Conference: http://www.atlasconference.com/ - Content Marketing World Conference: http://www.contentmarketingworld.com/ - HealthCare Internet Conference 2017: https://www.hcic.net/ - Vanity Fair Generation Gap: https://www.vanityfair.com/culture/2015/10/generation-gap-guide - Curious Collection Note Cards: http://amzn.to/2vYieci Links: - Touchpoint podcast Twitter: https://twitter.com/touchpointpcast - Reed Smith Twitter: http://www.twitter.com/reedsmith - Chris Boyer Twitter: http://www.twitter.com/chrisboyer - Chris Boyer website: http://www.christopherboyer.com/ - Social Health Institute: http://www.socialhealthinstitute.com/ Sponsors: - Transparently: https://www.transparently.com/ - Influence Health: http://www.influencehealth.com/ - Binary Fountain:https://www.binaryfountain.com/

A few of the industry's tech luminaries, Julie Yoo, Chief Product Officer at Kyruus, Dave Hodgson, President of Design & Development at Oxeon Partners, and Jeremy Delinsky, Chief Technology Officer at Wayfair (Former Chief Technology Officer at athenahealth), explore what it means to take an innovative approach to building technology within the healthcare landscape. They describe ways to drive meaningful use, create less friction and bring humanity back into healthcare through a more consumer-centric approach. This episode exemplifies what A Healthy Dose is meant to be: a forum for for experts to shoot the s**t about healthcare's most important topics.

Brian Oneill has been a product designer for more than twenty years and in the last ten years has been an independent consultant and started his company Designing For Analytics last year. Brian has helped designed products for companies ranging from startups to enterprises including NetApp, TripAdvisor, Infinio, Fidelity, and DataXu.   In this episode, Brian talks about:   The differences between UI and UX and what the role of the product designer is   How to measure the user experience and go about discovering UX issues   Common mistakes he sees people make   How being a musician influences the way he approaches product design   Links from today’s episode:   Designing For Analytics   How to Self-Assess the UI/UX Design of Products Using Analytics   Contact Brian   Brian on Twitter   Harvest   Waze   Kyruus   Dispatch   Jonathan Stark   Brennan Dunn   Jared M. Spool   Sketch and Invision   Sketching User Experiences   Beautiful Evidence   If you liked this episode:   Follow the podcast on Twitter   Subscribe on iTunes or your podcast app and write a review Get in touch with feedback, ideas, or to say hi: nic {AT} startupbostonpodcast [DOT] com   Music by: Mr Ho’s Orchestrotica  

This week Chris Bevolo and Chris Boyer are joined by special guest Julie Yoo, Kyruus co-founder and chief product officer. This trio kicks off the conversation by diving into the details surrounding Kyruus’ second Annual Thought Leadership on Access Symposium (ATLAS). Focusing on hot topics such as clinical impact of patient access, along with operational and financial facets of how healthcare organizations can improve their patient experience. Boyer continues the conversation noting that he will be speaking at ATLAS on consumerism and how it continues to affect healthcare organizations. It’s no secret that access to the World Wide Web has changed the way patients attempt to find the care they need. What’s the best way to break that barrier and provide the access and care your patients are searching for? Tune in to find out!