Episodes
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Take your CDI efforts to new heights. Discover how technology can serve as a catalyst for success, unlocking the next level of performance for your CDI program and elevating its impact. Uncover key metrics to monitor and track, enabling you to effectively demonstrate the value and success of your CDI initiatives within your healthcare organization and solidifying its position as a critical component of revenue integrity and achieving recognition for quality care delivery.
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Explore the complex landscape of implementing new healthcare technology. Weâll delve into the challenges and concerns healthcare providers face, from confusion surrounding AI/ML to complacency with existing solutions. Gain a deeper understanding of the crucial role leadership plays in fostering a culture of adaptability, remaining flexible in the face of challenges, and mitigating resistance to change. Learn how adherence to best practices and robust tracking and measurement strategies are essential to garnering staff buy-in.
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Episodes manquant?
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In an era where consumer awareness and freedom of choice regarding healthcare is on the rise, having the quality of care you deliver be reflected accurately across the variety of scoring and ranking systems is more important than ever. In this client featured presentation lead by Iodineâs Carmel Murphy, Clinical Product Consultant, we explore how accurate and complete documentation serves as the foundation for good quality metrics. Learn firsthand from our valued clients about their journey towards improving quality scores by prioritizing documentation integrity, and how technology has been instrumental in driving this shift.
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Every year Iodine Software conducts a client wide cohort study measuring various key metrics in the clinical documentation integrity space and the impact that Iodine has had. In this month's episode we're joined by Iodine's Chief Customer Officer, Brad Wensel, and Chief Operating Officer, Joshua Toub, to review the most recent cohort study of 2022 data and explain the metrics, methodology and discuss the most recent findings.
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Clinical documentation integrity teams play a critical role in ensuring quality healthcare and impacting a hospital's quality ranking. In this podcast episode of Iodine Intelligence, Fran Jurcak, Iodine's Chief Clinical Officer, and Tanya Motsinger, the System Director of Clinical Documentation Integrity at OhioHealth, discuss the importance of CDI programs and how AI-powered prioritization tools can help improve efficiency and impact quality metrics.
OhioHealth is a nationally recognized non-profit health system composed of 14 hospitals and over 200 outpatient and physician offices based out of central Ohio. Motsinger explains that their CDI program is focused on capturing severity of illness and risk of mortality while securing what's not being set in the chart very explicitly to help coders capture accurate diagnoses.
Motsinger shares that by implementing additional workflows while still maintaining high query and review rates, Ohio Health has been able to take on more work from a quality standpoint, with their team putting DRGs in a special calculator to understand variables and track specific quality metrics. Being able to report back on how many queries are impacting quality metrics directly has resulted in significant improvements in Ohio Health's CDI program.
In conclusion, prioritizing queries over review rates and finding ways to efficiently get the right case to the right CDI specialist at the right time can lead to significant improvements in healthcare quality metrics while freeing up bandwidth for second level reviews and other roles. The implementation of AI-powered prioritization tools can help achieve these goals without compromising established success or increasing staff FTEs.
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The healthcare industry is facing significant challenges as it navigates economic uncertainties in 2021 and beyond. In a recent Iodine Intelligence podcast, Troy Wasilefsky of Iodine Software, Harold Mueller of BJC Healthcare, and Robin Damschroder of Henry Ford Health discussed strategies for building financial resilience and tackling the financial issues facing the industry.
The pandemic has led to a decline in overall CMI due to both a decrease in medical CMI and surgery volumes that have not yet returned to pre-pandemic levels. Cost-cutting is one approach to stabilize health system economics, but experts have agreed that it cannot be solely relied upon to achieve financial performance targets. Therefore, it is essential for organizations to pursue other strategies such as generating new revenue streams, capturing revenue for existing work, and leveraging technology such as AI.
Organizations can turn to management consultancies to help identify and stabilize their finances while also focusing on cost reduction efforts and growth strategies. Additionally, value-based care contracts incentivize better care coordination, higher-quality outcomes and cost reduction while improving documentation accuracy remains critical for reimbursement optimization and quality factors such as CMS payments.
In conclusion, healthcare organizations face significant challenges as they navigate economic uncertainties require balancing efforts between cost reduction and creating new revenue streams or capturing revenue appropriately for existing work. While there is no one-size-fits-all solution, organizations can leverage their resources and implement strategies such as management consultancies, growth initiatives, and technology to improve their financial resilience and help them face the current economic crisis.
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Artificial intelligence (AI) is not just for gamers or factory warehouse robotsâit can, quite literally, save lives in the healthcare sector. AI in healthcare can be used to improve diagnostic detection speed for diseases, improve personalization of medical treatments, and automate drug discoveries.
How should healthcare companies be approaching AI use, and what benefits and drawbacks can they expect to see when deploying AI?
On todayâs episode of Iodine Intelligence, Empowering Intelligent Care, host Lauren Hickey, Content Strategist at Iodine Healthcare, is joined by Priti Shah, Chief Product & Technology Officer at Iodine Software, to discuss applications for AI in healthcare and how healthcare companies can approach use cases for AI models.
Hickey and Shah also discussedâŠ
Applications of AI in automation, improving efficiency of judgement, timeliness, and consistency of results A framework for guiding questions in approaching AI use Real-world examples of how a company might answer questions about their AIShah knows AI in healthcare is not the end-all, be-all. âWe have to understand that no model is perfect, and you have to choose one balance of false negatives and false positives you can live with.â She suggested, âOne of the biggest things people should hone in on is how much data was this AI model trained on, and what is the quality and diversity of that data?â
Priti Shah is Chief Product & Technology Officer at Iodine Software. She is an experienced General Management Executive with more than two decades of experience in revenue growth and market expansion. Before her current role, Shah was Chief Product Officer of Finvi, VP, Product & Solutions at Wolters Kluwer Health, and VP, Product Strategy & Corporate Development, amongst other positions. Shah attended Harvard Business Schoolâs General Management Program and the Rochester Institute of Technology, where she earned an MBA in Marketing & Strategic Management.
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Since OpenAI debuted ChatGPT in November of 2022, there has been a ton of discussion on its potential, and the implications on everything from schoolwork to medicine, marketing to law school. Fran Jurack, Iodine's Chief Clinical Strategist discusses ChatGPT's potential in the clinical documentation space and it's limitations.
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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 isnât being utilized simply because the existing technology doesnât 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 OâConnor, 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 works
3. 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 CDSâs 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.â
âQuiet 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 doesnât immediately get reprioritized again,â 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. Dianaâs 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. Itâs 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 configurationsâRetrospect being an example.
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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
âI think the challenge is, as we figure out ways to better automate and create efficiency, it isnât 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,â 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.
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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. âI really think that product management is all about empathizing with users, identifying opportunities, and collaborating with others,â 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. âI 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 thatâs when I started getting introduced into this real discipline of product management and thatâs where my career trajectory started into this field of bringing ideas to market from concept to delighting customer needs,â she explained.
Focused on making products and technologies that positively impact peopleâs 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.
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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. âThere continues to be anywhere from 4 Âœ 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,â stated Jurak.
Beisel concurred, adding that Integris Health has âbeen scrutinized in the mid-revenue cycle quite a bit in recent years and I think thatâs for good reason because there is so many places for revenue to leak in the process.â 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, Iodineâs various software solutions, and Integris Health systems journey to date.
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As hospital profit margins continue to shrink, achieving ROI, especially after investment in new technology, is critical. After implementing new software to help their CDI team prioritize and manage cases, West Tennessee Healthcare saw improvements to key metrics and achieved a financial return almost 3x more than expected.
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When applying artificial intelligence (AI) and machine learning to problems, accuracy is critical. If a modelâs predictions arenât precise, then they canât 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, âIodine Intelligenceâ Host Hilary Kennedy spoke with Lance Eason, Chief Data Scientist.
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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 Womenâs 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. âAll of this documentation translates into publicly reported information that is driving hospital reputation and consumer decisions about where they will receive care,â Jurcak said. âItâs 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.â
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. âFirst and foremost, itâs about documentation accuracy; ensuring the basic CDI, that all conditions are being monitored and treated are capturable.â
Improvements in quality ranking and scoring of documentation allow systems to capture an accurate patientâs clinical picture. âThere are conditions that are now important to these methodologies in terms of identifying risk that historically in the documentation world we didnât worry about,â Jurcak said. âToday, itâs about capturing the true clinical picture about whatâs happening to patients so you can best reflect yourself as an organization to the outside world.â
Iodine created a documentation accuracy index to determine if whatâs in the medical record is happening to the patient. This index can solve documentation issues, close gaps, and increase reimbursement.
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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 OâHara, 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. âWhat we have had to do is establish ourselves in a category, in this case the category of clinical documentation integrity,â stated Chan. âWe started out with an innovative product, and now we are an innovative platform.â
So, what does this to award mean to Iodine? âItâs 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,â said OâHara. Chan explained that this success showed that Iodineâs product worked, delivered value, and was used repeatedly.
Being the best is not everything, though. Iodine places emphasis on upholding values. âI think it really comes down to making sure youâre delivering a product that people really want to use and that the promises that you make in the product, you actually deliver on,â said Chan. âWe are never too proud of listening to the feedback, good and bad.â
Iodine plans to stay the best through one wordâobsession. âItâs 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,â said Chan. He added, âItâs 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.â
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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 Softwareâs 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 â not selling products â administrators need to analyze whatâs clinically happening with the patient to address the problem.
âMost software is built for workflows, which causes revenue and quality indicator leakage. What it should actually do is solve the underlying problems,â 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 thereâs a correction opportunity. Iodine Softwareâs solution involves sending the notification directly to the doctorâs 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 canât collect the nuances of diagnosis, as diseases can present differently in patients. However, as Eason explained, âmachine learning is good at picking up on subtle patterns and looking at multiple different patterns.â
Subscribe to the Iodine Intelligence podcast and visit https://iodinesoftware.com to learn more.
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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.
âHealthcare systems are truly on very tight margins now, and that requires real close attention to efficiency and appropriate utilization of resources,â Jurcak explained. âSo, 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.â
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 isnât easy to know what to do next
Accuracy is the name of the game in all aspects of healthcare, especially in the documentation. âDocumentation drives the final reporting of codes, and without that clear, consistent, and complete documentation, itâs impossible to accurately code whatâs really happening and results in inaccurate reimbursement,â Jurcak said.
So, what can healthcare organizations do to minimize documentation leakage and increase accuracy? âTo solve this leakage issue, you got to focus first on documentation integrity across all records,â Jurcak said. âWe canât be targeting a particular metric or particular condition to say this is how Iâm going to solve all problems because itâs only solving a very small problem.â
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.
