A Primer on Medicaid/CHIP Managed Care Reform

The following is a guest blog post by Megan Renfrew, Director in the Cognosante Solutions Lab.
Megan Renfrew - Cognosante
On May 6, 2016, the Centers for Medicare and Medicaid Services (CMS) published a final regulation in the Federal Register concerning managed care in Medicaid and the Children’s Health Insurance Program (CHIP).  The first overhaul of Medicaid and CHIP managed care regulations in more than a decade, the rule “updates how Medicaid works for the nearly two-thirds of beneficiaries who get coverage through private managed care plans,” wrote CMS Acting Administrator Andy Slavitt and Vikki Wachino, CMS Deputy Administrator and Director for the Center for Medicaid and CHIP Services, in a CMS blog post.

Approximately 72 percent of Medicaid enrollees in 39 states and the District of Columbia are served through managed care plans, up 14 percent since 2013.  Combined Federal and state spending on Medicaid managed care exceeds $150 billion annually.  Those figures will grow steadily as states continue to expand Medicaid managed care coverage to include larger geographic areas, additional populations, and services previously covered through fee-for-service Medicaid, such as inpatient and Long-Term Services and Support (LTSS).

While the medical loss ratio and other financial requirements received the lion’s share of attention throughout the rule-making process, the rule’s focus on improving the beneficiary experience and increased reporting and data requirements are equally important.  Beneficiaries will benefit from quality improvement requirements, stricter provider access requirements, and stronger care management programs.  Plans and states will need to adjust contracts and IT systems to meet new data, reporting, and analytics requirements that support CMS’s goals of increased program integrity and transparency.

Beneficiary Experience & Protections

To strengthen the experience of beneficiaries, the rule requires states to address disparities and individuals who need long term care or have special health needs in their quality plans for the Medicaid managed care rule.  The final rule, which will be phased in over several years, also creates the first quality rating system for Medicaid managed care plans, aligning Medicaid with Medicare Advantage and Qualified Health Plans rules.  This will allow beneficiaries to better compare plans before enrollment.

On the care management front, the rule includes standards for care coordination, health assessments for new plan enrollees, and treatment plans for enrollees with special healthcare needs or who receive LTSS.  These rules are designed to make sure that beneficiaries receive appropriate care in the appropriate setting, and are assisted in navigating the complex healthcare system.

The rule helps ensure that beneficiaries have sufficient access to providers by strengthening provider network adequacy requirements.  States must add time and distance standards to their state network adequacy rule (31 states already have time and distance standards in place for primary care providers).  Under the final rule, however, CMS spells out the provider types subject to network adequacy requirements in greater detail.  As a result, states must now create standards for more than seven different provider types.  Plans must also report provider network data at least annually, and maintain an up-to-date provider directory for plan members.

Additional changes focus on targeted beneficiary education and outreach.  States must implement systems that support beneficiaries prior to and after enrollment, a role that will likely be played by enrollment brokers.  Under these systems, beneficiaries are educated about managed care, including benefits covered and choice of plans, and their rights and responsibilities under Medicaid.  The beneficiary support system also provides a venue for current managed care enrollees, including assistance navigating the grievance and appeals process.

Enhanced Data and Systems Needs

Under the final rule, states and plans are required to meet stronger data submission and reporting requirements to support program oversight, program integrity, and increased transparency.  To meet these requirements, states and plans must have adequate IT systems to ensure accurate and timely data delivery and reporting.  Some states and managed care plans will likely need to increase their data collection and analytics capabilities to comply with the new rule.

The most important change is that federal payment for Medicaid managed care is tied to the submission of accurate, complete, and timely encounter data to CMS in a CMS-specified format, likely TMSIS.  Historically, some states have struggled to collect complete and accurate encounter data from managed care plans, and to manage that data in legacy systems designed for fee-for-service claims.  Both states and plans will need to examine their current IT systems, data collection and submission processes, and contract language to ensure that they are well positioned to meet these requirements.

In addition to the encounter data requirements, CMS is requiring that states post information on their Medicaid managed care plans on a public website, including enrollee handbooks, provider directories, and plan contracts.  Also required is information about plan performance, including finances, operational performance, quality indicators, measures of customer satisfaction, and the results of program integrity audits.

To meet the stricter provider network adequacy requirements, plans will need to have, at a minimum, accurate data on their provider network.  As states revise their network adequacy rules to meet the CMS requirements and monitor their plans for compliance, they may benefit from using GIS-based tools that automate network adequacy analysis and allow for easy evaluation of policy options and plan performance.

To support program integrity goals, the CMS rule requires all providers in Medicaid managed care plan networks to enroll with the state Medicaid agency.  Enrollment in Medicaid was previously required only of those providers participating in the Medicaid fee-for-service program.  States may find that they need more automated provider enrollment and verification systems to handle the increased workload that this requirement will generate for state Medicaid agencies.  Luckily, provider enrollment solutions are available in the market.

To help ease the burden of implementing the systems necessary to manage the robust data collection, analysis, exchange, and reporting necessary under Medicaid managed care reform, states can leverage CMS’s previously issued final rule extending 90 percent federal matching funds for Medicaid enterprise system development.  In addition to ensuring the permanent availability of this funding, that rule extends its use to commercial-off-the-shelf and software-as-a-service solutions.  This allows states to take advantage of previously developed and tested products in the marketplace.

21st Century Medicaid

CMS and its stakeholders devoted thousands of hours to crafting sweeping reform that brings Medicaid manage care into the 21st Century, including supporting data-driven decision-making and oversight, and allowing for state innovation in delivery system and payment reform. Doing so solidifies Medicaid’s place as a key driver of health innovation and plans’ roles supporting and implementing that innovation.

About Megan Renfrew
Megan Renfrew is a Director in the Cognosante Solutions Lab.  An accomplished health policy expert who spent more than five years drafting healthcare bills for the U.S. House of Representatives, she previously served as the technical director at CMS responsible for collecting and analyzing Medicaid and CHIP eligibility and enrollment data from states. 

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Will mHealth Apps Replaced by Chatbots?

Michael Yuan has a great post that looks at chatbots for healthcare and uses the great headline that “mHealth apps are so 2014!” Michael makes some great points about the challenges of getting patients to download mobile health apps and to get them to engage with those apps long term. There have been very few breakout hits in the mobile health app space.

For those not familiar with Chatbots, they essentially use artificial intelligence to appropriately respond to you on your favorite chat platform (Facebook Messenger, Kik, Whatsapp, Wechat (China), Google Messenger etc etc etc). Some of you may have seen my post about the way a Chinese Health Tracker integrates with WeChat. There are some really incredible benefits of engaging a patient on a messaging platform that they’re using daily already.

I think that most people just fear that messaging platforms aren’t powerful enough to really engage the patient. They often ask, can a text message change patient behavior? If you look at the WeChat integration mentioned above, you’ll see that most of these messaging platforms are becoming much more than just a set of simple text messages. However, let’s set that aside and just think about the power of a text message.

When Facebook announced their new partner program to allow people to create chatbots on their messaging platform, I asked my friend Melissa McCool from STI Innovations and MindStile if you could change people’s behavior with something as simple as a series of text messages. Her answer was a simple, “Yes.”

Of course, the devil’s in the details, but I trust that Melissa knows about how to influence patient behavior based on her experience doing it in many large healthcare organizations. The challenge isn’t technical though. Sending a text message, building a chat bot, sending a message on any of these platforms is completely academic. My 12 year old son could do it. What’s hard is what you should send, when you should send it and to whom.

While it’s great to see technology become easier and easier, that hasn’t made the challenge of behavior change that much easier. Sure, it’s great that the patient will actually read the message the majority of the time if you send it using one of these popular messaging apps. However, that doesn’t mean that the message will be effective. We still have a lot of work to send the right messages at the right time in the right way to the right people.

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JAMIA Study: Wolters Kluwer Surveillance System Reduces Sepsis Deaths

The Decision Support Software Improved Early Diagnosis Using Automated Data Analysis and Accurate Alerts Sent to Mobile Devices

May 25, 2016 – The Health division of Wolters Kluwer, a leading global provider of information and point of care solutions for the healthcare industry, announced today that The Journal of the American Medical Informatics Association (JAMIA) has published a study by researchers Sharad Manaktala, MD, PhD, et al. detailing a significant reduction in sepsis mortality using automated surveillance and real-time analysis. The study examines how clinicians at Alabama’s Huntsville Hospital decreased sepsis-related deaths by 53% during a 10-month period using a combination of clinical change management and electronic alerting from POC Advisor™, a highly-accurate clinical decision support (CDS) software. The system’s alerts detect sepsis early and guide clinicians to deliver the appropriate treatment, resulting in a breakthrough in alert accuracy, reaching 95% sensitivity and 82% specificity during the study period.

The study, “Evaluating the Impact of a Computerized Surveillance Algorithm and Decision Support System on Sepsis Mortality,” is currently available online and will appear in the June print edition of JAMIA.

Sepsis is the deadliest condition treated in hospital critical care units, claiming approximately 750,000 lives in U.S. hospitals every year. At an estimated $20 billion annually, it is also the country’s most expensive condition to treat. The risk of death increases significantly every hour sepsis goes untreated, yet early diagnosis has long been a struggle because many other acute medical conditions cause similar signs and symptoms.

Using an automated, real-time surveillance algorithm, POC Advisor aggregates, normalizes and analyzes patient data from disparate clinical systems and delivers early sepsis alerts and treatment advice to clinicians via mobile devices and portals. Hundreds of rules built into the platform account for variables specific to individual patients, including comorbidities and medication abnormalities, thereby maximizing the accuracy of alerts and advice.

“There is no single test to identify sepsis; it requires a clinical diagnosis. Delays in diagnosis are very common, resulting in delays in treatment,” said study co-author Stephen Claypool, MD. “Prior to this study, there hasn’t been a study of an electronic system that I’m aware of that has significantly improved mortality. That’s because most systems generate many false positive alerts, so they are ignored and outcomes are not improved. In this study, we used an electronic solution that takes into account existing patient co-morbidities and labs and adjusts the analysis on a patient-specific basis.

“This system is much more accurate, with a highly specific alerting system that minimizes alert fatigue,” added Dr. Claypool, Medical Director of Clinical Software Solutions at Wolters Kluwer. “In this study, Huntsville clinicians acted promptly on the alerting advice, so they were able to more effectively identify and treat sepsis well before a patient’s condition worsened. The end result was a dramatic improvement in mortality.”

The study also incorporated change management practices focused on sepsis education and process improvement for the clinical staff. The education program ensured that the nursing staff was properly trained to respond to sepsis alerts in a timely manner using the latest evidence-based practices.

“Efforts to develop similar CDS tools oftentimes fail because clinicians simply cannot trust the accuracy of the alerts. Either the system has low sensitivity and therefore does not identify all cases of sepsis, or low specificity, which leads to too many false positives resulting in ignored alerts,” said Sean Benson, Vice President and General Manager of POC Advisor at Wolters Kluwer Clinical Software Solutions. “If a tool is going to help doctors and nurses save lives, they have to trust that it works. Most CDS systems fail to achieve sensitivity and specificity levels higher than 50%. However, at the conclusion of our study, POC Advisor achieved alert sensitivity and specificity of 95% and 82%, respectively. That is unprecedented in published literature.”

The study’s publication in JAMIA follows the release of new definitions and clinical criteria for sepsis (Sepsis-3) from the Third International Consensus Definitions Task Force earlier this year. Dr. Claypool noted that while it more accurately defines the condition, Sepsis-3 does little to address the need for improved care.

“Currently, there is no medical evidence to suggest that the Sepsis-3 criteria will detect sepsis earlier than previous methods and in fact may lead to longer delays,” he said. “The reduction in sepsis mortality at Huntsville is a result of effective early alerts that allowed clinicians to treat the patients long before they suffered life-threatening organ dysfunction.”

Follow POC Advisor on Twitter.

About Wolters Kluwer

Wolters Kluwer N.V. (AEX: WKL) is a global leader in information services and solutions for professionals in the health, tax and accounting, risk and compliance, finance and legal sectors. We help our customers make critical decisions every day by providing expert solutions that combine deep domain knowledge with specialized technology and services.

Wolters Kluwer reported 2015 annual revenues of €4.2 billion. The company, headquartered in Alphen aan den Rijn, the Netherlands, serves customers in over 180 countries, maintains operations in over 40 countries and employs 19,000 people worldwide.

Wolters Kluwer shares are listed on Euronext Amsterdam (WKL) and are included in the AEX and Euronext 100 indices. Wolters Kluwer has a sponsored Level 1 American Depositary Receipt program. The ADRs are traded on the over-the-counter market in the U.S. (WTKWY).

Wolters Kluwer Health is a leading global provider of information and point of care solutions for the healthcare industry. For more information about our products and organization, visithttp://www.wolterskluwer.com/, follow @WKHealth or @Wolters_Kluwer on Twitter, like us on Facebook, follow us on LinkedIn, or follow WoltersKluwerComms on YouTube.

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Appointment Scheduling Site Zocdoc Connects With Epic

In a bid to capture hospital and health system business, appointment scheduling site Zocdoc announced that its customers can now connect the site to their Epic EMRs via an API. The updated Zocdoc platform targets the partners’ joint customers, which include Yale New Haven Health, NYU Langone Medical Center, Inova Health System and Hartford HealthCare. And I’ll admit it – I’m intrigued.

Typically, I don’t write stories about vendors other than the top EMR players. And on the surface, the deal may not appear very interesting. But the truth is, this partnership may turn out to offer a new model for digital health relationships. If nothing else, it’s a shrewd move.

Historically, Zocdoc has focused on connecting medical practices to patients. Physicians list their appointment schedule and biographical data on the site, as well as their specialty. Patients, who join for free, can search the site for doctors, see when their chosen physician’s next available appointment is and reserve a time of their choosing. If patients provide insurance information, they are only shown doctors who take their insurance.

As a patient, I find this to be pretty nifty. Particularly if you manage chronic conditions, it’s great be able to set timely medical appointments without making a bunch of phone calls. There are some glitches (for example, it appears that doctors often don’t get the drug list I entered), but when I report problems, the site’s customer service team does an excellent job of patching things up. So all told, it’s a very useful and consumer-friendly site.

That being said, there are probably limits to how much money Zocdoc can make this way. My guess is that onboarding doctors is somewhat costly, and that the site can’t charge enough to generate a high profit margin. After all, medical practices are not known for their lavish marketing spending.

On the other hand, working with health systems and hospitals solves both the onboarding problem and the margin problem. If a health system or hospital goes with Zocdoc, they’re likely to bring a high volume of physicians to the table, and what’s more, they are likely to train those doctors on the platform. Also, hospitals and health systems have larger marketing budgets than medical practices, and if they see Zocdoc as offering a real competitive advantage, they’ll probably pay more than physicians.

Now, it appears that Zocdoc had already attracted some health systems and hospitals to the table prior to the Epic linkage. But if it wants to be a major player in the enterprise space, connecting the service to Epic matters. Health systems and hospitals are desperate to connect disparate systems, and they’re more likely to do deals with partners that work with their mission-critical EMR.

To be fair, this approach may not stick. While connecting an EMR to Zocdoc’s systems may help health systems and hospitals build patient loyalty, appointment records don’t add anything to the patient’s clinical picture. So we’re not talking about the invention of the light bulb here.

Still, I could see other ancillary service vendors, particularly web-based vendors, following in Zocdoc’s footsteps if they can. As health systems and hospitals work to provide value-based healthcare, they’ll be less and less tolerant of complexity, and an Epic connection may simplify things. All told, Zocdoc’s deal is driven by an idea whose time has come.

Posted in Healthcare Integration, Hospital EHR, Hospital EHR Company, Hospital EHR Consulting, Hospital EHR Vendor, Hospital Electronic Health Record, Hospital Electronic Medical Record, Hospital EMR, Hospital EMR Company, Hospital EMR Vendor, Hospital Healthcare IT, Hospital IT Systems | Tagged , , , , | Comments Off on Appointment Scheduling Site Zocdoc Connects With Epic

Avoiding Revenue Crunches During EMR Transitions

Most healthcare leaders know, well before their EMR rollouts, that clinical productivity and billings may fall for a while as the implementation proceeds. That being said, it seems a surprising number are caught off guard by the extent to which payments can be lost or delayed due to technical issues during the transition. This is particularly alarming as more and more hospitals are looking at switching EHR.

Far too often, those responsible for revenue cycle issues live in a silo that doesn’t communicate well with hospital IT leadership, and the results can be devastating financially. For example, consider the case of Maine Medical Center, which took a major loss after it launched its Epic EMR in 2012, due in part to substantial problems with billing for services.

But according to McKesson execs, there’s a few steps health systems and hospitals can take to reduce the impact this transition has in your revenue cycle. Their recommendations include the following:

  • Involve revenue cycle managers in your EMR migration. Doing so can help integrate RCM and EMR technologies successfully.
  • Create a revenue cycle EMR team. The team should include the CFO, revenue cycle leaders from patient access and reimbursement, vendor reps and someone familiar with revenue cycle systems. Once this team is assembled, establish a meeting schedule, team roles and goals for participants. It’s particularly important to designate a project manager for the revenue cycle portion of your EMR rollout.
  • Before the implementation, research how RCM processes will be affected by the by the rollout, particularly how the new EMR will impact claims management workflow, speed of payment and staff workloads. Check out how the implementation will affect processes such as eligibility verification, registration data quality assurance, preauthorization and medical necessity management, pre-claim editing and remittance management.
  • Pay close attention to key performance indicators throughout the transition. These include service-to-payment velocity, Days Not Final Billed, charge trends and denial rates.

The article also recommends bringing on consultants to help with the transition. Being that McKesson is a health IT vendor, I’m not at all surprised that this is the case. But there’s something to the idea nonetheless. Self-serving though such a recommendation may be, it may help to bring in a consultant who has an outside view of these issues and is not blinkered by departmental loyalties.

That being said, over the longer term healthcare leaders need to think about ways to help RCM and IT execs see eye to eye. It’s all well and good to create temporary teams to smooth the transition to EMR use. But my guess is that these teams will dissolve quickly once the worst of the rollout is over. After all, while IT and revenue cycle management departments have common interests, their jobs differ significantly.

The bottom line is that to avoid needless RCM issues, the IT department and revenue cycle leaders need to be aligned in their larger goals. This can be fostered by financial rewards, common performance goals, cultural expectations and more, but regardless of how it happens, these departments need to be interested in working together. However, unless rewards and expectations change, they have little incentive to do so. It’s about time hospital and health system leaders address problem directly.

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Healthcare IT Competitive Landscape Graphic

I recently did an interview with a market research firm about healthcare IT and specifically about patient portals. They sent me their final report and in that report they shared a graphic of the competitive landscape for healthcare IT (which they said I could share):

Healthcare IT Competitive Landscape

I’m sure we could quibble over some of the categories they chose, where a company resides (ie. IBM bought Truven Analytics, so they’re now technically one company), companies left off, etc, but I thought it was an interesting overview of the kind of companies that are trying to make an impact in healthcare.

In fact, what hit me most about this graphic was the diversity of companies that have a foothold in healthcare. I’ve certainly heard and worked with all of the companies on the list. However, I’d never really sat back and thought about the breadth of companies that are trying to do something in healthcare.

Of course, when you think about the trillions of dollars being spent on healthcare, it’s not that big of a surprise that these large companies would want a piece of that large pie. In fact, there are a number of other very large companies that are definitely missing from this graphic (no doubt the graphic wasn’t intended to be comprehensive).

I’d love to hear what other categories of companies you think should be represented on the list. Any other category of companies you see working in healthcare?

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Is Healthcare Overhead Holding Back New #DigitalHealth Solutions?

Earlier this year I wrote an article that questioned whether the Fitbit was really a digital health solution. I essentially came to the conclusion that Fitbit’s health data wasn’t clinically relevant and so that’s why we didn’t see it really impacting healthcare as we know it.

While Fitbit’s data may not be clinically relevant, Fitbit has still gone on to be an extremely successful wearable technology solution for consumers. For some reason we enjoy tracking our steps whether it really improves our health or not. Of course, maybe they’re also riding our own misconception that tracking steps improves health. Regardless, they’ve been extremely successful and haven’t had to prove that they actually do anything to move the needle in healthcare.

I wonder if this is the model that we’ll see happen most with digital health solutions. Instead of trying to actually take part in the ruthless, brutal, and complex healthcare infrastructure, I expect we’ll see most digital health solutions work on the outside.

Think about the overhead that comes with becoming FDA cleared or the overhead that comes with proving to a hospital that your solution really does improve patients’ health. That’s a lot of work compared with just creating the illusion of health and selling it directly to consumers. Maybe the illusion will play out as reality or maybe it will not. From a company’s point of view, all you have to do is keep the illusion in play and you can be successful.

No doubt this later strategy appeals to the startup culture that’s been created in the US. There’s so little that’s “lean startup” of MVP (minimum viable product) in healthcare. Most people in healthcare are afraid of anything that’s not mature. Healthcare regulations certainly discriminate against experimentation and show bias to mature technologies.

The only case that really can be made to entrepreneurs who want to pursue the harder path of proving their technologies is that once they’ve proved it they have a great defense against competitors who haven’t gone to that effort. That’s a powerful incentive, but not one that most will appreciated when starting a digital health startup company.

My gut tells me that the complexities of healthcare are holding many innovations from happening in healthcare. That’s unfortunate.

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Are Current Population Health Tools Becoming Outdated?

These days, virtually all hospitals and health systems are looking at ways to manage population health. Most of their approaches assume that it’s a matter of identifying the right big data tools and crunching the numbers, using the data already in-house. Doing this may be costly and time-consuming, but it can be done using existing databases, integration engines and the appropriate business analytics tools, or so the conventional wisdom holds.

However, at least one health IT leader disagrees. Adrian Zai, MD, clinical director of population informatics at Massachusetts General Hospital, argues that current tools designed to enable population health management can’t do the job effectively. “All of the health IT tools companies call population health today will be irrelevant because the data they look at can only see what goes through hospital, which is far too narrow in scope.”

Zai points out that most healthcare organizations attempt to leverage claims data in doing population health management analyses. But that approach is far from ideal, he told Healthcare IT News. Claims data, he points out, is typically one to two months old, which significantly limits the value healthcare providers can generate from the data. Also, most hospitals’ claims data only covers about 20% to 30% of the area’s population, he notes.

Instead, organizations need to study real-time data drawn from a significantly broader population if they hope to achieve population health management goals, Zai argues. For example, it’s important to look at the Medicaid population, whose members may get most of their care through community health centers. It’s also important to collect data from other consumer touch points. (Zai doesn’t specify which touch points he means, but mobile health and remote patient monitoring data come to mind immediately.)

I think Zai make some excellent points here. In particular, while achieving true real-time analysis is probably well the future for most healthcare organizations, the fresher data you can use the better. Certainly, analyzing archival data has a purpose, but to have a major impact on outcomes, it’s important to foster behavior change in the present.

However, I’d argue that few providers are ready to roll ahead with this approach. After all, to achieve his goals means establishing some new definitions as to what data should be included in population health analysis. And that’s not as simple as it sounds. (For a recent look at how providers look at population health, check out this survey from last summer.)

First, providers need to take a fresh look at how they define the term “population,” and develop a definition that takes in a more comprehensive view of patient data. Certainly, claims data analysis is start, but that by definition is limited to insured patients seen at the hospital. Zai recommends that population health management efforts embrace all patients seen at the hospital, insured or not. In other words, he’s recommending hospitals address the community in which they are physically located, not just the community of patients for whom they have provided care.

Just as importantly, hospitals and health systems need to consider how to collect, incorporate and analyze the exponentially-growing field of digital health data. While some middleware solutions offer to serve as a gateway for such data, it seems likely that providers will still need to do a lot of hands-on work to make use of these data sources.

Finally, providers need to continually improve the algorithms they use to pinpoint problems in a given population, as well as the ways in which they create actionable subsets of the population. For example, it may be appropriate to target patients by disease state today, but other ways of improving outcomes might arise, and providers’ IT solutions need to be flexible enough to evolve with the times.

Over time, the industry will evolve best practices for population health management, and definedthe IT tools best suited to accomplish reasons. And while some existing tools may work, I’d be surprised if most survive the transition.

Posted in Health Information Governance, Healthcare Analytics, Healthcare Big Data, Hospital EHR, Hospital Electronic Health Record, Hospital Electronic Medical Record, Hospital EMR, Hospital Healthcare IT, Hospital IT Systems | Tagged , , | Comments Off on Are Current Population Health Tools Becoming Outdated?

Healthcare Disruption – #HealthDisruptors Blab Chat – May 17, 2016

When Melissa McCool (MindStile and STI Innovations) and I (Healthcare Scene) first started Healthcare Entrepreneurs, I think we both desired to have our discussions be about more than just entrepreneurship. Plus, we both thought of the concept of entrepreneurs in a much broader context. For example, we believe you that you can be an “entrepreneur” even at a large company. We were more interested in the spirit of healthcare entrepreneurship than we were whether someone had started their own company or not.

Plus, as we started to do these interviews with healthcare entrepreneurs on Blab, I got really disappointed by how stagnant the conversations were. One of the things that attracted Melissa and I to blab and why we wanted to host these video chats together was that past video blabs had been so dynamic and unpredictable. We enjoyed the serendipitous nature of the blabs and wildly expansive conversations that took place.

While we enjoyed our initial Healthcare Entrepreneur chats, we realized that they missed out on the dynamic nature of other blabs we’d done. Plus, they were very similar to many other Healthcare Scene interviews I was doing already. I even talked to someone who attended one of our Healthcare Entrepreneur chats and asked why they didn’t hop on camera, ask questions, or join the discussion. The person told me that they felt like they’d be interrupting if they’d joined.

Healthcare Disruptors Launch
With this experience and insight as background, Melissa and I decided that we needed to make a few tweaks to our previous chats. First, we’ve decided to rename our discussion to the Health Disruptors Blab Chat. Soon we’ll convert the website and branding to the new domain. Hopefully this will include anyone interested in doing something interesting and disruptive in healthcare.

New Blab Chat Format
Taking inspiration from Twitter chats which are open, interactive and inclusive, we wanted to create a similar format for our Health Disruptors blab chats. Instead of becoming a formal interview, the goal is to have as many people participate on camera and in the Blab chat area as possible. Melissa and I will just be the organizers and facilitators of the chat, but the video content and discussion will go wherever the community wants to take it. Yes, that will likely lead to some interesting off topic conversations. I won’t be surprised if as much value is gleaned in the chat room as the videos.

We’re planning invite people to host future Health Disruptors chats (let us know if you’re interested). Similar to a Twitter chat, as host you’d come up with the topic and questions that will inspire the discussion and then hop on camera to help us facilitate the discussion. The great thing is that we’re inventing something new. So, there’s no way you can screw it up.

Our First Health Disruptors Blab Chat!
We’re really excited to be holding our first Health Disruptors Blab chat on May 17, 2016 at 11 PM ET (8 PM PT). Yes, we realize this is late for many of you on the east coast, but that should make for some fun late night conversations. Most of the health disruptors I know send me emails at all hours of the day and night, so hopefully this time will work out for most. We can reevaluate it if needed.

Melissa and I will co-host the first Health Disruptors chat where we thought it fitting to talk about “Healthcare Disruption.” To start the discussion, here’s the big overarching question we’d like to discuss along with some questions that dive a little deeper into the topic.

Big Question:

  • Where do you see disruption happening in healthcare?

Diving Deeper:

  • Is there really anything disruptive in healthcare? Are government and regulation killing disruption?
  • What can we do to better facilitate disruption in healthcare?
  • Should healthcare be disrupted?
  • What disruptions will work in combination to shock the health system?
  • Who and what companies are being most disruptive to healthcare?

If you’ve never used blab before, it’s really easy to use. You can watch and participate in the chat on blab itself or in the embed below. Just visit this blog post or the blab page on May 17, 2016 at 11 PM ET (8 PM PT) and you can join in on the conversation.

We’re planning to start off holding these monthly on the 3rd Tuesday of every month. That means you can put June 21st at 11 PM ET (8 PM PT) on your calendars for the 2nd Health Disruptors blab. If people like them enough, we’ll do them more often.

Also, feel free to use the #HealthDisruptors hashtag for things you learn or hear on the blab chat as well. Thanks in advance for those who spread the word about this new endeavor. We think it could grow into a really special community.

Finally, Melissa and I did a quick intro blab where we fleshed out the ideas for Health Disruptors. You can find the recording of it:

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EMR Replacement Frenzy Has Major Downsides

Now that they’ve gotten an EMR in shape to collect Meaningful Use payouts, hospitals are examining what those incentive bucks have gotten them. And apparently, many aren’t happy with what they see. In fact, it looks like a substantial number of hospitals are ripping and replacing existing EMRs with yet another massive system.

But if they thought that the latest forklift upgrade would be the charm, many were wrong. A new study by Black Book Research suggests that in the frenzy to replace their current EMR, many hospitals aren’t getting what they thought they were getting. In fact, things seem to be going horribly wrong.

Black Book recently surveyed 1,204 hospital executives and 2,133 user-level IT staffers that had been through at least one large EMR system switch to see if they were happy with the outcome. The results suggest that many of these system switches have been quite a disappointment.

According to researchers, hospitals doing new EMR implementations have encountered a host of troubles, including higher-than-expected costs, layoffs, declining inpatient revenues and frustrated clinicians. In fact, hospitals went in to these upgrades knowing that they would not be back to their pre-EMR implementation patient volumes for at least another five years, but in some cases it seems that they haven’t even been keeping up with that pace.

Fourteen percent of all hospitals that replaced their original EMR since 2011 were losing inpatient revenue at a pace that would not support the total cost of the replacement EMR, Black Book found. And 87% of financially threatened hospitals now regret the executive decision to change systems.

Some metrics differed significantly depending on whether the respondent was an executive or a staff member.

For example, 62% of non-managerial IT staffers reported that there was a significantly negative impact on healthcare delivery directly attributable to an EMR replacement initiative. And 90% of nurses said that the EMR process changes diminished their ability to deliver hands-on care at the same effectiveness level. In a striking contrast, only 5% of hospital leaders felt the impacted care negatively.

Other concerns resonated more with executives and staff-level respondents. Take job security. While 63% of executive-level respondents noted that they, or their peers, felt that their employment was in jeopardy to the EMR replacement process, only 19% of respondents said EMR switches resulted in intermittent or permanent staff layoffs.

Meanwhile, there seemed to be broad agreement regarding interoperability problems. Sixty-six percent of system users told Black Book that interoperability and patient data exchange functions got worse after EMR replacements.

What’s more, hospital leaders often haven’t succeeded in buying the loyalty of clinicians by going with a fashionable vendor. According to Black Book, 78% of nonphysician executives surveyed admitted that they were disappointed by the level of clinician buy-in after the replacement EMR was launched. In fact, 88% of hospitals with replacement EMRs weren’t aware of gaining any competitive advantage in attracting doctors with their new system.

Now, we all know that once a tactic such as EMR replacement reaches a tipping point, it gains momentum of its own. So even if they read this story, my guess is that hospital executives planning an EMR switch will assume their rollout will beat the odds. But if it doesn’t, they can’t say they weren’t warned!

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