Iodine Intelligence - Empowering Intelligent Care

Artificial intelligence (AI) and Natural Language Processing (NLP) are taking over the health industry and renovating healthcare technology. It has for some time now being a Lodestar into improving and delivering quality healthcare. A ton of information is being collected but isn't being utilized simply because the existing technology doesn't know what to do with the data. A recent report from RBC Capital Markets states 30% of the world's data is generated in the healthcare industry, and it is expected to surpass 36% in the next three years. Handling this sort of information is a challenge as most healthcare AI technology relies on simple technologies like rules and checklists.On this episode, Lauren Hickey, the content strategist at Iodine, chats with Diana O'Connor, the clinical product consultant manager at Iodine, and Justin Geradot, the client service operations manager at Iodine, about their new flagship technology, CONCURRENT. Hickey, Diana, and Justin chat about...1. What can prevent CDIs from fully adopting concurrent.2. How auto-assignment works3. Barriers and quiet periods. "CONCURRENT is our flagship software that utilizes artificial intelligence and machine learning to prioritize patients concurrently while in-house. It uses, at a high level, different amount of misalignment of information between clinical evidence that support a certain condition and the actual expectation documentation of those conditions and uses the difference to prioritize," said Justin."CDI is complex. There is a lot of different workflow strategies that people use. CONCURRENT is more than just a technical implementation, we are taking account of different philosophies and workflows," said Diana. Lauren then asked Justin about auto-assignment and quiet periods, and he went on to say:"Auto assignment is a way concurrent distributes cases to CDS's for review. It is one of the oldest features for CONCURRENT specifically to address the problem that scope changes as a result of CONCURRENT. Before CONCURRENT, CDIs way to locate cases was through location or service line. When prioritization is added, balancing for caseloads gets more difficult. Auto assignment instead of using service line to distribute cases uses priority status, assigning cases with more priority first then working their way down.”“Quiet period is how much period a case must incubate before its considered for auto-assignment. This is a change for a lot of CDI departments. A lot of CDI teams want to see cases every two days at a minimum. With prioritization, we set a 24hr quiet period to get the necessary information. After a case has been reviewed, it goes into another quiet period for 12hrs to make sure it doesn't immediately get reprioritized again,” Justin continued. Lauren then talks about query hesitancy and asks Diana about CDSs not querying as much even when Iodine AI says a query is needed. Diana's reply:"One of the things we are looking for is a complete, intact medical record that tells the story of the patient and the sooner we get the documentation in, the better. And with denials coming up the way they are, you want continuity of them in the medical record. It's a shift from getting querying away as a penalty into more as a prompt and querying sooner."At the end of the episode, Justin says Iodine and Concurrent are always changing, adding new functionalities, platforms, and configurations—Retrospect being an example.

The healthcare industry continues to become more and more tech savvy. Technologies like Machine Learning and Artificial Intelligence can help drive significant improvements in healthcare and with organizations like Leapfrog Group weighing in on hospital standards and ratings with a variety of scoring metrics, healthcare facilities continue to innovate. Perhaps one of the most important details, often overlooked in the face of shiny new tools, is the need for facilities to continue to improve upon their clinical documentation and improve patient outcome. But should specialists query if there is no direct impact?On this episode of Iodine Intelligence -Empowering Intelligent Care, host Lauren Hickey chats with Chief Clinical Strategist at Iodine, Fran Jurcak, about the importance of queries for improving patient outcomes and expectations. Hickey and Jurcak discuss... 1)Calculating impacts to queries 2)How to accurately represent every patient 3)Why it is important to identify risks and outcomes“I think the challenge is, as we figure out ways to better automate and create efficiency, it isn't so much about the volume of queries or the actual number of queries but maybe more about the process by which they have to answer them, that maybe we could potentially address so that it is easier,” said Jurcak.Jurcak has been with Iodine for over six years, and has held numerous Director positions in the healthcare environment and was the Assistant Professor in the nursing program at Madonna University for more than 14 years. She holds her BSN in Nursing from the University of Michigan and her MSN in Nursing from Wayne State University. Jurcak also holds a post-master certificate from Madonna University in Health Education and the Certificate in Health Care Finance for Nurse Executives.

Iodine, a company dedicated to transforming the healthcare industry with AI-enabled technology welcomes Priti Shah to the organization as Chief Product and Technology Officer. Shah came to the organization with 20-plus years of corporate and product strategy experience. In her role at Iodine, she will be guiding the platform strategy vision while overseeing the product and engineering teams. Driven by a passion to serve people and improve lives Shah works from a position of strength when managing product portfolios. “I really think that product management is all about empathizing with users, identifying opportunities, and collaborating with others,” said Shah. This intriguing podcast will certainly delight listeners as Shah passionately discusses the career journey that led her to Iodine, her product management methodology, and the importance of customers in the product development lifecycle. Shah began her career as a product analyst where she focused on research, pricing models and crunching numbers. “I realized really quickly that all this analysis that I was doing was being leveraged by product leaders to make prioritization and tread-off positions. I think that's when I started getting introduced into this real discipline of product management and that's where my career trajectory started into this field of bringing ideas to market from concept to delighting customer needs,” she explained. Focused on making products and technologies that positively impact people's lives, Shah noted that the motivation that guided her and her teams throughout her career to work harder and smarter was the knowledge that the work they were doing empowered people. Her obsession with customers and empowering people continues to drive her within the healthcare technology space.

In this episode of Iodine Intelligence, Fran Jurcak, Chief Clinical Strategist at Iodine Software and Kati Beisel, Director of Health Information for Integris Health, which is Oklahoma's largest state-owned not-for-profit health care system and ranked one of the top 25 health care systems in the US, discuss the difficulties associated with solving the challenges presented by mid-revenue cycle leakage. There are many costs associated with mid-revenue cycle leakage both immediate and long-term. Not only that, but the negative impact can also be felt throughout an organization. Everything from day-to-day operations, budget planning, resource allocation, patient outcomes, and staffing initiatives suffer from ineffective processes and systems. Fran Jurcak took a moment to speak to the significant issue of quantifying costs, noting that it is not a perfect process. “There continues to be anywhere from 4 ½ to half a million dollars lost in revenue in the average 250 bed hospital. So, fairly significant loss based upon workflows even after investments in areas to try and diminish that leakage,” stated Jurak. Beisel concurred, adding that Integris Health has “been scrutinized in the mid-revenue cycle quite a bit in recent years and I think that's for good reason because there is so many places for revenue to leak in the process.” She goes on to mention common areas of loss including physician documentation, staffing shortages, coding requirements, and reporting methods. Despite the significant challenges associated with implementing processes and software to improve CDI and reduce mid-revenue cycle leakage, both women agreed that the work is important. Noting that every dollar and dime counts, Beisel spoke of the need to reinvest in talent to better serve patients and communities while improving quality of patient care. Additional points of conversation included potential solutions, Iodine's various software solutions, and Integris Health systems journey to date.

When applying artificial intelligence (AI) and machine learning to problems, accuracy is critical. If a model's predictions aren't precise, then they can't contribute to better outcomes, which is vital in the delivery of better care. The objective is for the predictive models to become more accurate through an iterative process. To discuss the evolution of and objectives for iodine AI models, “Iodine Intelligence” Host Hilary Kennedy spoke with Lance Eason, Chief Data Scientist.

There are six domains of health care quality outlined by the IOM (Institute of Medicine.) These include Safe, effective, patient-centered, timely, efficient, and equitable. Fran Jurcak, Chief Clinical Strategist, Iodine Software, and Deborah Jones, Director of Clinical Documentation Improvement at Brigham and Women's Hospital, spoke with Lauren Hickey on how documentation accuracy can help achieve quality processes and outcomes in health care. People want to go where they are going to get the best care, so having the ability to determine which hospitals offer optimum quality is essential. “All of this documentation translates into publicly reported information that is driving hospital reputation and consumer decisions about where they will receive care,” Jurcak said. “It's about ensuring that the world can see the level of care you provide, and what level of acuity patients are experiencing, and whether or not they have positive outcomes.” More and more, these quality outcome metrics and reimbursement are tied together. Penalties, payment, and accreditation withholdings could occur if healthcare organizations do not meet specific benchmarks. Without proper accreditation, healthcare organizations may not be able to offer certain services. Jones said that in Boston, where Brigham Health is one of many renowned healthcare institutions, they constantly need to prove to their consumers that they are delivering the best care. “First and foremost, it's about documentation accuracy; ensuring the basic CDI, that all conditions are being monitored and treated are capturable.” Improvements in quality ranking and scoring of documentation allow systems to capture an accurate patient's clinical picture. “There are conditions that are now important to these methodologies in terms of identifying risk that historically in the documentation world we didn't worry about,” Jurcak said. “Today, it's about capturing the true clinical picture about what's happening to patients so you can best reflect yourself as an organization to the outside world.” Iodine created a documentation accuracy index to determine if what's in the medical record is happening to the patient. This index can solve documentation issues, close gaps, and increase reimbursement.

Iodine Software, a healthcare AI company, recently received the number one rating for clinical documentation integrity from KLAS Awards. William Chan, CEO and Co-Founder, and Tim O'Hara, Vice President of Client Experience at Iodine, joined Host Lauren Hickey to explain the significance of this.KLAS was first unsure how to categorize Iodine when they came on scene. “What we have had to do is establish ourselves in a category, in this case the category of clinical documentation integrity,” stated Chan. “We started out with an innovative product, and now we are an innovative platform.” So, what does this to award mean to Iodine? “It's not enough for us to think that we have a great product, a great service. That needs to be validated by healthcare professionals who hold us to a very high standard as they should,” said O'Hara. Chan explained that this success showed that Iodine's product worked, delivered value, and was used repeatedly.Being the best is not everything, though. Iodine places emphasis on upholding values. “I think it really comes down to making sure you're delivering a product that people really want to use and that the promises that you make in the product, you actually deliver on,” said Chan. “We are never too proud of listening to the feedback, good and bad.”Iodine plans to stay the best through one word—obsession. “It's important for the Iodine team to continue to obsess over all of these details. To obsess over customer usage, obsess over the feedback that we get, we need to obsess over all those details,” said Chan. He added, “It's that obsession of wanting to hit the mark with the customer that I think is going to allow us to continue to be the best in KLAS.”For the latest news, subscribe to Iodine Intelligence.

The use of technology and data in healthcare decision-making is on the rise. Unfortunately, most systems think like computers, not clinicians. However, machine learning can deliver insights that rules-based prioritization cannot. Discussing this topic, Iodine Software's Chief Data Scientist Lance Eason and Chief Revenue Officer Troy Wasilefsky joined host of Iodine Intelligence, Hilary Kennedy. First, Eason explained some of the issues with revenue cycle management, such as not recognizing the clinical cycle. Because hospitals earn revenue via quality of care — not selling products — administrators need to analyze what's clinically happening with the patient to address the problem. “Most software is built for workflows, which causes revenue and quality indicator leakage. What it should actually do is solve the underlying problems,” Wasilefsky added. One example of this is documentation integrity, or lack thereof, while patients are in the hospital, and machine learning could help fill that gap. The challenge is that the physicians provide context to improve the quality of records while machine learning simplifies it by pre-populating queries with a high degree of confidence that there's a correction opportunity. Iodine Software's solution involves sending the notification directly to the doctor's phone or EHR record. When comparing rules-based approaches to machine learning, there are clear benefits for the latter. Rules-based has even more issues because it can't collect the nuances of diagnosis, as diseases can present differently in patients. However, as Eason explained, “machine learning is good at picking up on subtle patterns and looking at multiple different patterns.” Subscribe to the Iodine Intelligence podcast and visit https://iodinesoftware.com to learn more.

Frank Jurcak, MSN, RN, CCDS, CCDS-O, the Chief Clinical Strategist for Iodine Software, brought the goods on the secrets of mid-revenue cycle management. With hospitals operating on tighter and tighter margins, clinical documentation improvement programs (CDIs) must optimize to take advantage of every savings opportunity.“Healthcare systems are truly on very tight margins now, and that requires real close attention to efficiency and appropriate utilization of resources,” Jurcak explained. “So, with the increasing demands put on accuracy and depth of documentation, records need to be reviewed daily to identify discrepancies between the clinical evidence and the accuracy of the documentation.”Because human resources are at a premium in healthcare, there are not enough people to keep up with the need for this type of daily review. Between documentation, changing regulations, and new evolving technology, it isn't easy to know what to do next Accuracy is the name of the game in all aspects of healthcare, especially in the documentation. “Documentation drives the final reporting of codes, and without that clear, consistent, and complete documentation, it's impossible to accurately code what's really happening and results in inaccurate reimbursement,” Jurcak said.So, what can healthcare organizations do to minimize documentation leakage and increase accuracy? “To solve this leakage issue, you got to focus first on documentation integrity across all records,” Jurcak said. “We can't be targeting a particular metric or particular condition to say this is how I'm going to solve all problems because it's only solving a very small problem.”According to Jurcak, AI technology could play a role in assisting by emulating the clinical brain of a provider and in the identification of the correct records.