Baltimore won one of the 31 national Tech Hub federal grants from the Biden Administration to create a partnership of several organizations (led by the Greater Baltimore Committee) to create opportunities for diverse organizations.  At this session, representatives from the Greater Baltimore Committee, Fearless, UpSurge Baltimore Conscious Venture Partners, LLC, and Coppin State University.  They are now preparing the Phase 2 applications for $70 million.  Equity is embedded as a core concept in these programs.  What is exciting is that they won the first grant – out of hundreds of applications.  This go-round will be able to feature the accomplishments of the first grant and how this funding will continue the efforts.  Listening to Ron Williams, PhD, Director of the Center for Strategic Entrepreneurship, speak about the goals of these grants – to move away from the “big organizations” and move to more grassroots development — was inspiring.

Then hearing about the “thinking” within the Maryland Department of Health was informative and lent a very different approach to how the Department is working to identify disparity gaps that often not considered at the depth needed to make a difference. This was a forward-thinking discussion with meaty points and challenges being faced.

My bottom line was partly disappointment.  The information given in this April 18^th meeting was so much more than I expected (realizing I wasn’t sure what to expect) but the number of hospitals participating was too low – meaning that many will not be knowledgeable about what is happening in Maryland.  Let’s see if we can broaden the number of attendees for next year!

This blog post was created and shared by: Charlotte L. Kohler, President.

So, I’ll start with Roderick King, MD, MPH, SVP, Chief Equity, Diversity & Inclusion Officer for UMMS.  Yes, he had a lot to say about diversity.  Yes, I already know that the diversity with Kohler HealthCare provides me with personal and professional enjoyment and enrichment.  Through this diversity I have learned about an entirely different approach to strangers than what I grew up with.  The greetings and acknowledgement that others are “seen” and spoken to.   But he didn’t talk about that – it could be because he already knows and is part of that cultural difference.  What I found fascinating was how he challenges each member of the diversity work at UMMS, at each hospital, about whether their assumptions are correct.  Yes, he expects assumptions to be backed up with real data for the specific hospital.  The approach is not that whatever is going on with the downtown UMMS hospital should be applied to every other hospital.  It needs to be thought through to describe the impact on the community and to the cost of care.  What I heard was that diversity is important, but it should be meaningful and measurable.    It made me think about news articles that tell us that the “diversity officer” position in hospitals are being eliminated.  And, I think “why” – but with Dr. King’s approach, it must be that the “diversity” itself was the only goal rather than the many requirements found in Dr. King’s approach.

I have to admit that Dr. King came to this position with a lot of background and experience.  Not many organizations could be so fortunate to have some lead this goal of inclusion and diversity and understand the financial measurement as well as the theoretical (and well meaning) concept of a balanced work force.  (Ok, remember I’m A CPA, too.)

On another BLOG, I will talk about some of the other speakers and what I learned, but I want to make a few comments about our last speaker, Antionette Williams, Founder & CEO of Williams Consulting, who provides a lot of innovative AI work with the federal government and in particular with CMS.  I have noticed for years that the investigation of health providers has become much more focused on using real data from billing records.  I have had the belief that every health care provider should do their own analytics and “know themselves”.  Now I know that Williams Consulting has been instrumental in upping the government’s ability to see the data for potential fraud and abuse.  Ms. Williams started out as a nurse.  She has a passion for doing “right” – billing for the services actually provided.  This is the future, and it’s needed.

This blog post was created and shared by: Charlotte L. Kohler, President.

Many others are taking on the burden themselves and utilizing their inhouse team of Regulatory, Finance, and IT staff.

For you, KHC can help in the following areas:

• Answering questions regarding the rules and their specific application.
• Performing a review of your results – as a quality check.
• Help you handle certain portions of the updates needed – you define and you control.
• Training staff on ways to facilitate the data burdens and the Hospital Price Transparency rules.

If these or other areas of assistance are needed, please contact Sara Rivenburgh (srivenburgh@kohlerhc.com) or Linker Mills (lmills@kohlerhc.com).

That doesn’t mean that every practice will or should be ready to be acquired.  But is also means that the acquiror needs to have a much better understanding of: (1) how do medical practices really work (and its often not as you believe); (2) how will the transition really happen easily (depends on…); and (3) what are you really acquiring?

Medical practices for the most part have been running on their own -often with far less formality than larger organizations.  More often a practice will measure success in terms of dollars in the bank and if the physicians are earning fair wages.  The sophistication that larger (investor) organizations use to measure financial performance is often not measured at all, even if their management software can support it.

So, bottom line: learn about the practice before you buy it.   It doesn’t just magically happen or work. The financial analysis generally used is important, but the really important part is the way the practice functions:  the culture will stay – will it fit your expectations?

Kohler HealthCare Consulting performs many due diligence reviews every year.  Beyond the Income Statement and Balance sheet – the culture, the compliance, the functioning.

Are there different rules for different types of providers and different protections for different consumers? YES. Is it easy to figure out which rules apply to which scenarios? NO.

There are many healthcare representatives who have been following the regulations as they’ve unfolded and been updated and been challenged and changed over the past year. I have provided many informational webinars on the topics and I always attend every webinar I can find – from CMS, healthcare finance and advocacy associations, attorneys, anybody who knows anything and is willing to share! I read every article that comes across my desk and have schooled my personal providers as well as clients and friends in the industry on all things NSA. Do I know everything? NO… but I do try to keep abreast of all developments and am constantly seeking information from any and every resource.

Last week, I paid to virtually attend a webinar presented by a National healthcare finance organization. The presentation was fast-paced and full of great information on implementation of the NSA requirements. There was a Q&A session at the end and many participants asked thoughtful questions that pertained to their specific situations. This legislation can be very confusing as there are many moving parts — some only apply to certain providers and consumers. Therefore, it’s easy to mix things up and we look to the presenter to keep everything straight.

For example, the balance billing rules protect individuals with private or commercial health plans from balance billing and out-of-network cost-sharing with respect to emergency services, non-emergency services furnished by out-of-network (OON) providers at in-network facilities, and air ambulance services. The distinguishing factor is whether or not the facility/provider is in the plan’s network or OON. Bottom line: if an insured patient seeks emergency services (and some non-emergency ancillary services) at an in-network facility, that patient will only be required to pay their in-network cost-sharing portion of the medical bill. If an out-of-network provider treats the patient at an in-network facility, they may not balance bill the patient for the portion of their bill that is not covered. There are other factors at play here, but I’m going to stay at a high-level for this post or we’ll be here all day!

The Good Faith Estimate (GFE) requirements of the NSA currently only apply to uninsured (or self-pay) patients. An important note: a patient is considered “uninsured” under the NSA when seeking a service which is not covered by their health plan. In- and out-of-network designations do not apply in these situations. If the service is never covered (e.g., cosmetic procedures), the patient is self-pay for the service and a claim is not filed with the health plan.

Back to the webinar I attended. Right from the start, I was thrown off by the speaker’s explanation of the agenda! The speaker explained that they were going to discuss NSA responsibilities including “providing Good Faith Estimates to patients whose insurance is out-of-network.” As stated, that is NOT a provider responsibility under the NSA and, in my opinion, it plants the seed for further misinterpretation of the regulations.

During the presentation, the speaker stated that the GFE must be signed by the patient. That is news to me! In fact, during the Q&A session, I asked when the Departments stipulated this requirement as it was not part of the initial rules. The answer I was given was, “in October.” I still haven’t been able to find this information… anywhere… and the speaker did not provide the needed citation.

Another participant asked, “Self-pay patients in the ER [absolutely no insurance] – are we allowed to bill?” The speaker replied, “With no insurance, you have to give them a Good Faith Estimate. And they have to sign the notice and consent form.” This response is completely incorrect! GFEs are only required for services that are scheduled at least three days in advance (or upon request). ER visits by definition are not scheduled! The Notice and Consent form applies to balance billing scenarios under the NSA – for insured patients!

Don’t get me wrong – the speaker provided vital information and answered most questions correctly. No matter how well you understand the rules, it can get jumbled in your head, especially during the Q&A session where there’s no structure to the conversation. I know this from experience. This is the kind of bad information that perpetuates the confusion that many providers and facilities have with the NSA regulations. I am left shaking my head and yelling at my computer!

On December 2^nd, I presented a quick NSA overview and moderated a panel discussion for a local healthcare finance association chapter. We mostly discussed the all-inclusive GFE requirement that was set to be “enforced” as of January 1, 2023. Later that day, the Departments issued guidance extending their enforcement discretion in situations where GFEs do not include expected charges from co-providers/facilities…pending further rulemaking. This is great news for providers and facilities struggling to operationalize this requirement.

Even though there was no way for me to know this was going to be announced, I sent an email to all registered participants describing the update with a link to the official notification. I do not like to leave misinformation out there!   That means that reading our free monthly newsletter and our weekly Top Five can help you stay up to date. Sign up for both at https://mailchi.mp/kohlerhc.com/0oma58sv9t.  Hoping to hear from you!

A study by the management consulting firm of McKinsey, “The New Growth Game: Beating the Market with Digital and Analytics” revealed that companies using digital analytics generate on average 50% more revenue than those not using these analytics.  Digital analytics also provides practical solutions for high-growth industries such as life sciences and healthcare by providing granular insights into customer behavior and purchase trends.

 Increased Data Accuracy

Increased data accuracy is another reason why providers should invest in digital analytics as it will provide accurate data insights that can be utilized for decision making purposes; lead qualifying activities; market segmentation; and prospecting campaigns.

In light of the significant benefits resulting from the use of digital analytics, it is no surprise that healthcare providers are swiftly converting to make use of this technology.

 Insights into Patient Behavior

The number of people in the United States who suffer from chronic diseases is skyrocketing. This increased demand on providers can equate to more pressure on them, especially financially. To make sure they meet the needs of their patients, healthcare providers can employ digital analytics to gain insights into their patients’ behaviors and needs and leverage those insights to spearhead chronic illness.

 Collecting Data is Not enough

Collecting data is not enough. They need to know how to analyze it and use it for their benefit. The right digital analytics can help them understand their patients better; identify potential new services; predict trends; and improve conversion rates on their website.

The right analytics can help providers answer questions like: What is happening with our website traffic?  How many people are calling in for appointments? What is happening with our ad campaigns? The answers to these questions requires a specific skill set in analytics.

 More Efficient Services

Analytics helps healthcare providers in making their services more efficient and effective.

Metrics such as conversion rates; average visit duration; and call bounce rates can assist healthcare providers to identify improvements to their services. Furthermore, analytics can be used to monitor the effectiveness of advertisement campaigns and how it affects the overall revenue and business performance.

Reference:

1. A Look at Challenges and Opportunities of Big Data Analytics in Healthcare https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/Marketing%20and%20Sales/Our%20Insights/The%20new%20growth%20game/The-new-growth-game-Web.pdf

In recent years, most people in the healthcare industry have heard of HCCs (Hierarchical Condition Categories).  HCCs are conditions and diseases that are grouped together into categories by body system or disease process to measure the health status of a patient.  In medical coding, this is known as Risk Adjustment.  The current Center for Medicare & Medicaid Services (CMS) HCC model includes nearly 10,000 ICD-10 codes that map to 79 HCC Categories.

CMS utilizes HCCs to reimburse Medicare Advantage plans based on the health status of their enrollees. The plan pays for the predicted healthcare costs of a patient or population of patients.  Costs are estimated based on the demographical profile and  the health status of the patient.   The data that is utilized to determine health status is based on the diagnoses codes from billed claims and medical records which are collected by physician offices, hospital inpatient visits, and outpatient settings.

In order to categorize HCC data, we need to look at qualitative text data that is usually present in medical coding and survey methodologies.¹   HCCs are dependent  upon the assigned risk scores from ICD-10 coding and demographic information and in order to determine those costs a RAF (Risk Adjustment Factor) score is calculated for that patient.

Insurance companies use algorithms to predict the cost of care for patients. For example, a patient with few serious health conditions could be expected to have average medical costs for a given period of time.  However, a patient with multiple chronic conditions would be expected to have higher utilization of services and a corresponding higher rate of health care costs. ²

How does AI factor into HCCs?

The term AI (Artificial Intelligence) is becoming a more commonplace and recognized term.  AI utilizes machine learning to simulate human processes.  Using ,  AI makes human processes more efficient. As AI relates to HCCs, machine learning natural language processing, disease detection algorithms, and suggestion scoring are terms for the technical processes that are  utilized to identify otherwise unfound data in a patient’s history that help assist in determining the RAF score.

At the end of the day, many companies are limited by time and resources when analyzing and optimizing RAF scores.  An established patient may have a new diagnosis for this current year, but it is possible that the prior year’s diagnoses have progressed and should be coordinated to a new non-progressed diagnoses and be recaptured. This over-time look at the patient’s history creates opportunities that would have been previously missed.

Natural Language Processing is one of the must-have tools for disease discovery. By leveraging the natural language processing for chart abstraction, we improve the efficiency of identifying underlying disease burden ³  

The Future of HCCs

HCCs are the future of better health management.  Medical coding professionals should be sure they stay up to speed on the latest advancements in coding in order to ensure that the level and intensity of the services provided to patients is aligned with the reimbursement. CMS has some great HCC software that ensures appropriate diagnosis codes are reported for the patient.  Companies that utilize natural language processing software have introduced new tools that can discover insights previously locked in unstructured data like surveys in the form of PDFs and text notes. ⁴  

As we move forward, let’s consider the complete picture of the risk adjustment factors and how the HCC score reduces the need to request additional medical details and audits of claims. If you want to know more about reimbursements and HCCs or you currently participate in a value-based reimbursement model. Let us know and we can help you get a handle on high-quality care and sustainable profits.

1. https://www.tandfonline.com/doi/abs/10.1080/01930826.2015.1105035
2. https://www.aafp.org/family-physician/practice-and-career/getting-paid/coding/hierarchical-condition-category.html#:~:text=Hierarchical%20condition%20category%20(HCC)%20coding%20is%20a%20risk%2Dadjustment,health%20care%20costs%20for%20patients.&text=Along%20with%20demographic%20factors%20(such,adjustment%20factor%20(RAF)%20score.

So how do we navigate this new landscape?  Financial markets, hospitals, and the hospitality industry have been hardest hit with some of the most radical disruptions we have seen in decades. How can we continue to find innovation and opportunity in this extremely difficult environment?

Learn How to Digital Partner Differently

What exactly is the meaning of to digital partner differently? This means going all in.  Grab the cameras, set up the lights, it’s GO time!  People have been learning very rapidly how to digital partner better.  Years ago, interviews were constrained to being in person and in the same room.  Businesses spent millions of dollars traveling to meet clients and today we are holding these same meeting from our phones and tablets from our home office.  Now is the time to innovate around the pandemic to create those much-needed digital partnerships.  Offer things that no one else in the industry is offering perhaps by adding some flair to your training offerings.  Create a new service that is even more digitally driven than your competitors.  Automate your customer ending processes and show them what you know.  Partner with a company that offers something exciting like introductory videos or adds soothing background music to your virtual webinars.  We could all use it.  Make your company stand out with digital partnerships that are different.

Launch Now

Great companies can be born as a result of disruptive events, for example, Uber, Groupon, and Slack, that fall into this category.  Look at the changes in the real estate marketplace where a prospective buyer can access a completely virtual tour of a home and meet with their client  over a Zoom meeting.  The need no longer exists to even step foot into the home.  Many transactions are occurring without ever visiting the property and thus becoming a completely virtual experience.

Where do we get the confidence to trust these services?  I think that it is from knowing that someone smarter than us innovated and created a process around something that assists in our life progression.  We hope that they have thought out all of the bugs and errors along the way.

This means that we have the potential opportunity to find those bugs and address those errors in a way that is more meaningful today than perhaps previously thought.  Can you find the gaps?  Today, some might say we have a bigger voice because everyone has been upgraded or downgraded (depending how you look at it) to the same video-enabled internet platform.  Here, in the digital arena, we are on a level playing field and as we approach the issues.  There is no better time than now to humbly innovate in the industries most impacted by the crisis. Spend the time now!  Launch something that the future will need and thank you for it!

Do More with Less

Can we increase operational efficiency without spending another $10,000-$20,000 on a product or service for the year?  I’m sure we can do this.  Drill down into your existing team and focus on the technologies that are already in use.  Help everyone become more efficient. For example, have your administrative support team member or Excel Analyst host a virtual training class and invite the entire team.  Have your analyst guru instruct everyone how to addresses problems in Excel and perhaps how to model data to answer specific questions about their projects.  Share this information far and wide.   Repeat, repeat, repeat and hope that the team recalls some specifics of the training and brings that learning into their own processes.

Are you utilizing Microsoft Teams or Slack?  Are you actually using Teams for the complete project setup and project management or are you just using Team to communicate like Skype?  Microsoft Teams is a very powerful collaboration tool and integrates many facets of a solid project management or workflow foundation.  Having colleagues working within those boundaries, although difficult, allows for a more fluid and easier project administration.  It fosters centralization and conversations around the work product which makes things easy to find and reference later.

Balance Your Short-Term Versus Long-Term Needs

As we continue to search for solutions to the problems that a company encounters, we should always consider the ways in which we can reduce risk without adding additional overhead and ensure that our team adapt to the ever-changing needs of the crisis.  Setting goals for the business, much like setting personal goals, requires strategy, tactics and communication in order to make it a reality.  Set your sights for a one-year goal on business operations. How do we envision our organization to be operating one year from now?  At first, this question may seem nuanced and this question should be asked every year as part of a progress check to determine the reasonableness of that future vision.

What must be kept in mind is how we can change the current state which involves thinking about the systems that are currently in place. Those systems may have been flushed out and work really well or they might not be working well.  The job of innovators on the team is to determine how things can work better.

Don’t Make Small Problems Bigger Than They Are

Finally, do not make problems bigger than they need to be.  Solve for the immediate need of the client or supervisor and make sure not to put the task off until it is too late which could result in a missed deadline.  Ask those tough questions now while you have the time to solve the problem. Think about what you are doing and don’t forget to be present in the problem solving.  Sometimes the only thing stopping us from solving the problem is being fully present in the moment of solving that problem.  Be a good team member by being the change agent that you would want to see in others.

References

1. The Digital Transformation Playbook: Rethink Your Business for the Digital Age By. David L. Rogers.
2. Scaling New Heights: A Toolkit for SME’s Preparing for Post-COVID-19 Business By. Craig

Today, many applications are utilizing machine learning, but we don’t always know how or to what capacity.  How do we integrate machine learning at our business?  How do we get from A, not using any supplemental machine learning tools to B, full integration and adoption?

Although not widely realized or known, many tools we utilize every day already integrate many facets of machine learning, we just don’t see it.  The algorithms behind intelligent search, suggestions on Netflix, Social Platform Censorship, and even Microsoft PowerPoint, are all powered by machine learning.  Most of the time when you see a PowerPoint referencing A.I.  What you really want to know about is the machine learning. So, what’s the difference between machine learning and AI?

Artificial Intelligence is more of a buzzword these days, you can buy a domain and claim to use AI in a presentation, but in all honestly, there’s probably a good amount of fluff mixed in. Many claim to use AI but have minimal achievements.  In application development, especially with AI and Data Science, we can often put the cart before the horse.  Most AI today is a pitch in a slide deck.  More recently, we’ve seen models as a series of regressions or neural networks, attempting to solve some really complex decision-making issues.  But at the enterprise business level these tools have a long way to go to reach unencumbered adoption.

The reality is that in order for AI to be true and robust, it would need to enable in-the-moment decision making with an influx of new data all the time.  The entire artificial intelligence module must be embedded at every layer of the company’s ecosystem.  To be truly effective, it would have to live in the Operating System (OS) of your computer, your e-mail, your devices, and company work product. It would have to integrate back with cloud services in real-time and analyze potentially terabytes of data in seconds. It would need a feedback system that tells it whether it did a good job or not, and some serious looks at how often re-training of the models is necessary.

Today, this is not only possible, it’s frequently happening at every level of the industry.  However, many tools that sit on top of those big players simply don’t have the in-depth subject matter expertise to solve the problem.  Maybe the model is too broad, or maybe the data isn’t internally consistent, it might not get you the answers you need when you need them.  Don’t get me wrong it’s here already but more so for the bigger market players than the niche consulting or legal firms.

While looking at these products and tools there’s a few things we should especially look out for, and questions to ask:

• Vet the Executive Team: Evaluate startups and review backgrounds. Look for technical expertise and many years of statistics and data science background. Bonus points for specializations in certain fields and certifications that are specific to you.
• Is it internally consistent? Ask some basic technical questions, and some tough ones. There are AI products that are totally bogus out there.  Talk to the vendors about where they get the data they use in the models, what models and techniques they use, and how they validate the model.  What would you check in our data to ensure the models work the same?
• Consider the fit within the organization. Can all the people at my organization use the tool, or is it specific to a select few “power users”? It’s not enough to just ask someone in the tech team if this will solve our problems, you need a team if you want it to work for a team. Start slow, with a use case. Some early adopters and supporters who share in your frustration may help bring the solution to life and assist in implementation. You need allies.
• Will the product evolve with the organization?

Now more than ever the importance of explaining business outcomes hits home for me.  Next time you see a company saying they do AI, ask them questions, make them prove it.

Ask about these processes to ensure that the data your next tool plans on integrating is being used in a way that makes sense to the business.  Where does your data live?  How will this tool extract it and how frequently?

Finally, are the models robust enough to actually get you an answer?  Many models out there are broad in nature and only provide probabilities.