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When Hospitals Leak Money

Posted on October 20, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

A couple of weeks ago I was skimming healthcare business headlines and stumbled across this guaranteed showstopper: You’re probably leaving $22 million on the table. That headline is from a column by Jim Lazarus, who works in the Advisory Board’s Revenue Cycle Solutions division. In his column, he named four ways in which hospitals could recapture some of this lost revenue.

In the article, Lazarus notes that hospitals aren’t following best practices in four key areas, namely denial write-offs, bad debt, cost to collect and contract yield.  Unsurprisingly, Advisory Board benchmarks also demonstrate that median performing organizations are having trouble reducing net days in accounts receivable. The Advisory Board has also found that the overall average cost to collect has worsened by 70 points of net patient revenue from 2011 to 2015.

To turn the stats around, he suggests, hospitals should focus on four critical issues in revenue cycle management. They include:

  • Preventing denials rather than responding to them. “Hospitals are losing, on average, five percentage points of their margin to underpayments, denials and suboptimal contract negotiations,” Lazarus writes.
  • Collecting more from patients by improving their financial experience. According to Lazarus, between 2008 and 2015 the portion of patient obligations being written off as bad debt has climbed from 0.9% to 4.4%. To boost patient collections, hospitals must offer price estimates, convenient payment methods and a positive care encounter, he says.
  • Being sure not to take a hit on MACRA compliance. See that doctors, including those coming on board as employed physicians, get up to speed on documentation performance standards as quickly as possible.
  • Building the value of merged RCM departments. If multiple RCM organizations are being integrated as part of consolidation, look at ways to improve the value they deliver collectively. One approach is to create a shared services organization providing a common business intelligence platform across entities and service lines systemwide.

If you’re an IT leader reading this, it’s probably pretty clear that you have a substantial role in meeting these goals.

For example, if your hospital wants to lower its rate of claims denials, having the right applications in place to assist is critical. Do your coding and billing managers have the visibility they need into these processes? Does senior management?

Also, if the hospital wants to improve patient payment experiences, it takes far more than offering a credit card processing interface to make things work. You’ll want to create a payment system which includes multiple consumer touch points and financing options, which is integrated with other data to offer sophisticated analyses of patient payment patterns.

Of course, the ideas shared by Lazarus are just the beginning. While all organizations leave some money on the table, they have their own quirks as to why this happens. The important thing is to identify them. Regardless, whether you are in RCM, operations or IT, it never hurts to assume you’re losing money and work backward from there.

Visible and Useful Patient Data in an Era of Interoperability Failure

Posted on October 13, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

Health record interoperability and patient data is a debated topic in Health IT. Government requirements and business interests create a complex exchange about who should own data and how it should be used and who should profit from patient data. Many find themselves asking what the next steps in innovation are. Patient data, when it is available, is usually not in a format that is visible and useful for patients or providers. The debate about data can distract from progress in making patient data visible and useful.

Improvements in HealthIT will improve outcomes through better data interpretation and visibility. Increasing the utility of health data is a needed step. Visibility of patient data has been a topic of debate since the creation of electronic health records. This was highlighted in a recent exchange between former vice president Joe Biden and Judy Faulkner, CEO of Epic Systems.

Earlier this year at the Cancer Moonshoot, Faulkner expressed her skepticism about the usefulness of allowing patients access to their medical records. Biden replied, asking Faulkner for his personal health data.

Faulkner was quick to retort, questioning why Mr. Biden wanted his records, and reportedly responded “Why do you want your medical records?” There are a thousand pages of which you understand 10.”

My interpretation of her response-“You don’t even know what you are asking. Do not get distracted by the shiny vendor trying to make money from interpreting my company’s data”

As reported in Politico Biden–and really, I think that man can do no wrong, responded, “None of your business.”

In the wake of the Biden Faulkner exchange, the entire internet constituency of Health IT and patient records had an ischemic attack. Since this exchange we’ve gone on to look at interoperability in times of crisis. We’ve had records from Houston and Puerto Rico and natural disasters. The importance of sharing data and the scope of useful data is the same. 

During what I call the beginning of several months of research about the state of interoperability I started reading about the Biden and Faulkner exchange. This was not the first time I had been reading extensively about patient data and if EHR and EMR data is useful. It just reminded me of the frustrations I’ve heard for years about EHR records being useless. Like many of us, I disappeared down the rabbit hole of tweets about electronic health records for a full day. Patient advocates STILL frustrated by the lack of cooperation between EHR and EMR vendors found renewed vigor; they cited valid data. Studies were boldly thrown back and the exchange included some seriously questionable math and a medium level of personal attack.

Everyone was like, Are we STILL on this problem where very little happens and it’s incredibly complex? How? How do we still not have a system that makes patient data more useful? Others were like, Obviously it doesn’t make sense because A) usefulness in care, and B) money.

Some argued that patients just want to get better. Others pointed out that acting like patients were stupid children not only causes a culture of contempt for providers and vendors alike, but also kills patients. Interestingly, Christina Farr CNBC reported that the original exchange may have been more civil than originally interpreted. 

My personal opinion: Biden obviously knew we needed to talk about patient rights, open data, and interoperability more. It has had more coverage since then. I don’t know Faulkner, but it sounds like a lot of people on Twitter don’t feel like she is very cooperative. She sounds like a slightly savage businesswoman, which for me is usually a positive thing. I met Peter from Epic who works with interoperability and population health and genomics and he was delightful.

Undeniably, there is some validity to Judy’s assertion that the data would not be useful to Biden; EHR and EMR data, at least in the format available from the rare cooperative vendors, is not very useful. They are a digital electronic paper record. I am willing to bet Biden–much as I adore the guy–didn’t even offer a jump drive on which to store his data. The potential of EHR data visualization to improve patient outcomes needs more coverage. Let’s not focus on the business motivations of parties that don’t want to share their data, let’s look at potential improvements in data usefulness. 

It was magic because I had just had a conversation about data innovation with Dr. Michael Rothman. An early veteran in the artificial intelligence field, Dr. Rothman worked in data modeling before the AI winter of the 80s and the current resurgence in investment and popularity. He predates the current buzz cycle of blockchain and artificial intelligence everything. With many data scientists frustrated by an abandonment of elegant, simple solutions in favor of venture capital and sexy advertising vaporware, it is timely to look at tools that improve outcomes.

In speaking with Dr. Rothman, I was surprised by the cadence of his voice, he asked me what I knew about the history of artificial intelligence, and I asked him to tell his data story. He started by outlining the theory of statistical modeling and data dump in neural net modeling. His company, PeraHealth, represents part of the solution for making EMR and EHR data useful to clinicians and patients.

The idea that data is going to give you the solution is, in a sense, slightly possible but extremely unlikely. If you look at situations where people have been successful, there is a lot of human ingenuity that goes into selecting and transforming the variables into meaningful forms before building the neural network or deep learning algorithm. Without a framework of understanding, a lot of EHR data is simply a data dump that lacks clinical knowledge or visualization to provide appropriate scaffolding.  You do need ingenuity, and you do need the right data. There are so many problems and complexities with data that innovation and ingenuity is lagging behind with healthIT.

The question is – is the answer you are looking for in the input data? If you have the answer in the data, you will be able to provide insights based on it. Innovation in healthcare predictions and patient records will come from looking at data sets that are actually predictive of health.

Dr. Rothman’s work in healthcare started with a medical error. His mother had valve replacement surgery and came through in good shape. Although initially she was recovering quickly, she started to deteriorate after a few days. And the problem was that the system made it difficult to see.  Each day she was evaluated.  Each day her condition was viewed as reasonable given her surgery and age.  What they couldn’t see was that each day she was getting worse.  They couldn’t see the trend.  She was discharged and returned to the ED 4-days later and died.

As a scientist, he recognized that the hospital staff didn’t have everything they needed to avoid an error like this. He approached the hospital CEO and asked for permission to help them solve the problem. Dr. Rothman explained, I didn’t feel that the doctors had given poor medical care, this was a failure of the system.

The hospital CEO did something remarkable. They shared their data. In a safe system they allowed an expert in data science to come in to see what he could find in their patient records, rather than telling him he probably wouldn’t understand the printout. The hospital was an early adopter of EHR records, so they were able to look at a long history of data to find what was being missed. Using vital signs, lab tests, and importantly, an overlooked source of data, nursing notes, Dr. Rothman (and his brother) found a way to synthesize a unified score, a single number which captures the overall condition of the patient, a single number which was fed from the EMR and WOULD show a trend.  There is an answer if you include the right data.  

Doctors and nurses look at a myriad of data and synthesize it, to reach an understanding.  Judy is right that a layman looking at random pieces of data will not likely gain much understanding, BUT they may.  And with more help they might.  Certainly, they deserve a chance to look.  And certainly, the EMR and EHR companies have an obligation to present the data in some readable form.

Patients should be demanding data, they should be demanding hospitals give them usable care and normalize data based on their personal history to help save their lives.

Based on this experience, Michael and Steven built the Rothman Index, a measure of patient health based on analytics that visualizes data found in EHRs. They went on to found PeraHealth, which enables nursing kiosks to show the line and screens to see if any patients decline. In some health systems, an attending physician can get an alert about patients in danger. The visualization from the record isn’t just a screen by the patient, it is also on the physicians and nurses’ screens and includes warnings. Providers have time to evaluate what is wrong before it is too late. The data in the health record is made visual and can be a tool for providers.


Visualization of Patient Status with the Rothman Index and Perahealth

Is Perahealth everywhere? Not yet. For every innovation and potential improvement there is a period of time where slow adopters wait and invest in sure bets. Just like interoperable data isn’t an actuality in a system that desperately needs it, this is a basic step toward improving patient outcomes. Scaling implementation of an effective data tool is not always clear to hospital CMIO and CEO teams.  The triage of what healthIT solution a healthcare system chooses to implement is complex. Change also requires strong collaborative efforts and clear expectations. Often, even if hospital systems know something provides benefits to patients, they don’t have the correct format to implement the solution. They need a strategy for adoption and a strong motivation. It seems that the strongest motivations are financial and outcomes based. The largest profit savings with the minimum effort usually takes adoption precedent. This should also be aligned with end users- if a nurse uses the system it needs to improve their workflow, not just give them another task.

One of the hospitals that is successfully collaborating to make patient data more useful and visual is Houston Methodist. I spoke to Katherine Walsh, Chief Nursing Officer from Houston Methodist about their journey to use EHR data with Perahealth. She explained it to me- Data is the tool, without great doctors and nurses knowing the danger zone, it doesn’t help. This reminded me of Faulkner’s reaction that not all patient data is useful. Clinical support should be designed around visible data to give better care. Without a plan, data is not actionable. Katherine explained that when nurses could see that the data was useful, they also had to make sure their workflow included timely records. When EHR data is actually being used in the care of patients, suddenly data entry workflow changes. When nurses and doctors can see that their actions are saving lives, they are motivated.
The process to change their workflow and visualize patient data did not happen overnight. In the story of Houston Methodist’s adoption of Perahealth, Walsh said they wanted to make sure they helped doctors and nurses understand what the data meant.  “We put large screens on all the units- you can immediately see the patients that are at risk- it’s aggregated by the highest risk factor.” If you are waiting for someone to pull this data up on their desktop, you are waiting for them to search something. But putting it on the unit where you can see it makes it much easier to round, and makes it much easier to get a sense of what is going on. You can always identify what and who is at risk because it’s on a TV screen. The Houston Methodist team showed great leadership in nursing informatics, improving outcomes and using an internal strategy for implementation.

They normalize the variants for each person- a heart rate of 40 for a runner might be normal- then on the next shift 60 seems normal- then at 80 it also seems normal- you can tell them when you want an alert. To help with motivation, Walsh needed to make the impact of PeraHealth visual. They hung 23 hospital gowns around a room, representing the patients they had saved using the system.
The future of electronic health records will be about creating usable data, not just a data dump of fields. It is transforming EHRs from a cost hemorrhage to a life-saving tool through partnerships. Physicians don’t want another administrative task or another impersonal device. Nurses don’t want to go through meaningless measures and lose track of patients during shift changes. Show them the success they’ve had and let the data help them give great care.

Hospital administrators don’t want another data tool that doesn’t improve patient outcomes but has raised capital on vaporware. Creators don’t want more EHR companies that don’t know how to work with agile partners to create innovation.

The real ingenuity is in understanding – what data do you need? What data do patients need? Who can electronic healthcare record companies partner with to bridge the data divide?

We can bridge the gap of electronic health records that aren’t legible or useful to patients and create tools to save lives. Tools like those from PeraHealth are the result of a collaborative effort to take the data we have and synthesize it and visualize it and let care providers SEE their patients.  This saves lives.

Without this, the data is there, it’s just not usable.

Don’t just give the patients their data, show them their health.

Geisinger Partners With Pharmas To Improve Diabetes Outcomes

Posted on October 10, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Geisinger has struck a deal with Boehringer Ingelheim to develop a risk-prediction model for three of the most common adverse outcomes from type 2 diabetes. The agreement is on behalf of Boehringer’s diabetes alliance with Eli Lilly and Company.

What makes this partnership interesting is that the players involved in this kind of pharma relationship are usually health plans. For example:

  • In May, UnitedHealth Group’s Optum struck a deal to model reimbursement models in which payment for prescription drugs is better structured to improve outcomes.
  • Earlier this year, Aetna cut a deal with Merck in which the two will use predictive analytics to identify target populations and offer them specialized health and wellness services. The program started by focusing on patients with diabetes and hypertension in the mid-Atlantic US.
  • Another example is the 2015 agreement between Harvard Pilgrim health plan and Amgen, in which the pharma would pay rebates if its cholesterol-control medication Repatha didn’t meet agreed-upon thresholds.

As the two organizations note in their joint press statement, cardiovascular disease is the leading cause of death associated with diabetes, and diabetes is the top cause of kidney failure in the U.S. population. Cardiovascular complications alone cost the U.S. more than $23 billion per year, and roughly 68 percent of deaths in people with type 2 diabetes in the U.S. are caused by cardiovascular disease.

The two partners hope to improve the odds for diabetics by identifying their condition quickly and treating it effectively.

Under the Geisinger/Boehringer agreement, the partners will attempt to predict which adults with type 2 diabetes are most likely to develop kidney failure, undergo hospitalization for heart failure or die from cardiovascular causes.

To improve the health of diabetics, the partners will develop predictive risk models using de-identified EHR data from Geisinger. The goal is to develop more precise treatment pathways for people with type 2 diabetes, and see that the pathways align with quality guidelines.

Though this agreement itself doesn’t have a value-based component, it’s likely that health systems like Geisinger will take up health plans’ strategies for lowering spend on medications, as the systems will soon be on the hook for excess spending.

After all, according to a KPMG survey, value-based contracts are becoming a meaningful percentage of health system revenue. The survey found that while value-based agreements aren’t dominant, 36 percent of respondents generated some of their revenue from value-based payments and 14 percent said the majority of revenue is generated by value-based payments.

In the meantime, partnerships like this one may help to improve outcomes for expensive, prevalent conditions like diabetes, high blood pressure, arthritis and heart disease. Expect to see more health systems strike such agreements in the near future.

KLAS Summit: Interoperability Doing the Work to Move HealthIT Forward

Posted on October 9, 2017 I Written By

Healthcare as a Human Right. Physician Suicide Loss Survivor. Janae writes about Artificial Intelligence, Virtual Reality, Data Analytics, Engagement and Investing in Healthcare. twitter: @coherencemed

I had the privilege of attending the KLAS research event with leaders in patient data interoperability. From the ONC to EHR vendors- executives from EHR vendors and hospital systems made their way to a summit about standards for measurement and improvement. These meetings are convened with the mutual goal of contributing to advancement in Health IT and improvement of patient outcomes. I’m a big fan of collaborative efforts that produce measurable results. KLAS research is successfully convening meetings everyone in the HealthIT industry has said are necessary for progress.

The theme of Interoperability lately is: Things are not moving fast enough.

The long history of data in health records and variety in standards across records have created a system that is reluctant to change. Some EMR vendors seem to think the next step is a single patient record- their record.

Watching interactions between EHR vendors and the ONC was interesting. Vendors are frustrated that progress and years of financial investment might be overturned by an unstable political atmosphere and lack of funding. Additionally, device innovation and creation is changing the medical device landscape at a rapid rate. We aren’t on the same page with new data and we are creating more and more data from disparate sources.

Informatics experts in healthcare require a huge knowledge base to organize data sharing and create a needs based strategy for data sharing. They have such a unique perspective across the organization. Few of the other executives have the optics into the business sense of the organization. They have to understand clinical workflows and strategy., as well as financial reimbursement. Informatics management is a major burden and responsibility- they are in charge of improving care and making workflows easier for clinicians and patients. EMR use has frequently been cited as a contributor to physician burnout and early retirement. Data moving from one system can have a huge impact on care delivery costs and patient outcomes. Duplicated tests and records can mean delayed diagnosis for surgeons and specialists. Participants of the summit discussed that patients can be part of improving data sharing.

We have made great progress in terms of interoperability but there is still much to be done. Some of the discussion was interesting, such as the monumental task the VA has in patient data with troop deployment and care. There was also frank discussion about business interests and data blocking ranging from government reluctance to create a single patient identifier to a lack of resources to clean duplicated records.

Stakeholders want to know what the next steps are- how do we innovate and how do we improve from this point forward? Do we create it internally or partner with outside vendors for scale? They are tired of the confusion and lack of progress. Participants want more. I asked a few participants what they think will help things move forward more quickly. Not everyone really knows how to make things move forward faster.

Keith Fraidenburg of CHIME praised systems for coming together and sharing patient data- to improve patient outcomes. I spoke with him about the Summit itself and his work with informatics in healthcare. He discussed how the people involved in this effort are some of the hardest working people in healthcare. Their expertise in terms of clinical knowledge and data science is highly specialized and has huge implications in patient outcomes.

“To get agreement on standards would be an important big step forward. It wouldn’t solve everything but to get industry wide standards to move things forward the industry needs a single set of standards or a playbook.”

We might have different interests, but the people involved in interoperability care about interoperability advancement. Klas research formed a collaborative of over 31 organizations that are dedicated to giving great feedback and data about end users. The formation of THE EMR Improvement Collaborative can help measure the success of data interoperability. Current satisfaction measures are helpful, but might not give health IT experts and CMIOs and CIOs the data they need to formulate an interoperability strategy.

The gaps in transitions of care is a significant oversight in the existing interoperability marketplace. Post acute organizations have a huge need for better data sharing and interorganizational trust is a factor. Government mandates about data blocking and regulating sharing has a huge impact on data coordination. Don Rucker, MD, John Fleming, MD, Genevieve Morris and Steve Posnack participated in a listening session about interoperability.  Some EMR vendors mentioned this listening session and ability to have a face to face meeting were the most valuable part of the Summit.

Conversations and meetings about interoperability help bridge the gaps in progress. Convening the key conversations between stakeholders helps healthcare interoperability move faster. There is still work to be done and many opportunities for innovation and improvement. Slow progress is still progress. Sharing data from these efforts by the KLAS research team shows a dedication to driving interoperability advancement. We will need better business communication between stakeholders and better data sharing to meet the needs of an increasingly complex and data rich world.

What do you think the next steps are in interoperability?

AHA Asks Congress To Reduce Health IT Regulations for Medicare Providers

Posted on September 22, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

The American Hospital Association has sent a letter to Congress asking members to reduce regulatory burdens for Medicare providers, including mandates affecting a wide range of health IT services.

The letter, which is addressed to the House Ways and Means Health subcommittee, notes that in 2016, CMS and other HHS agencies released 49 rules impacting hospitals and health systems, which make up nearly 24,000 pages of text.

“In addition to the sheer volume, the scope of changes required by the new regulations is beginning to outstrip the field’s ability to absorb them,” says the letter, which was signed by Thomas Nickels, executive vice president of government relations and public policy for the AHA. The letter came with a list of specific changes AHA is proposing.

Proposals of potential interest to health IT leaders include the following. The AHA is asking Congress to:

  • Expand Medicare coverage of telehealth to patients outside of rural areas and expand the types of technology that can be used. It also suggests that CMS should automatically reimburse for Medicare-covered services when delivered via telehealth unless there’s an individual exception.
  • Remove HIPAA barriers to sharing patient medical information with providers that don’t have a direct relationship with that patient, in the interests of improving care coordination and outcomes in a clinically-integrated setting.
  • Cancel Stage 3 of the Meaningful Use program, institute a 90-day reporting period for future program years and eliminate the all-or-nothing approach to compliance.
  • Suspend eCQM reporting requirements, given how difficult it is at present to pull outside data into certified EHRs for quality reporting.
  • Remove requirements that hospitals attest that they have bought technology which supports health data interoperability, as well as that they responded quickly and in good faith to requests for exchange with others. At present, hospitals could face penalties for technical issues outside their control.
  • Refocus the ONC to address a narrower scope of issues, largely EMR standards and certification, including testing products to assure health data interoperability.

I am actually somewhat surprised to say that these proposals seem to be largely reasonable. Typically, when they’re developed by trade groups, they tend to be a bit too stacked in favor of that group’s subgroup of concerns. (By the way, I’m not taking a position on the rest of the regulatory ideas the AHA put forth.)

For example, expanding Medicare telehealth coverage seems prudent. Given their age, level of chronic illness and attendant mobility issues, telehealth could potentially do great things for Medicare beneficiaries.

Though it should be done carefully, tweaking HIPAA rules to address the realities of clinical integration could be a good thing. Certainly, no one is suggesting that we ought to throw the rulebook out the window, it probably makes sense to square it with today’s clinical realities.

Also, the idea of torquing down MU 3 makes some sense to me as well, given the uncertainties around the entirety of MU. I don’t know if limiting future reporting to 90-day intervals is wise, but I wouldn’t take it off of the table.

In other words, despite spending much of my career ripping apart trade groups’ legislative proposals, I find myself in the unusual position of supporting the majority of the ones I list above. I hope Congress gives these suggestions some serious consideration.

Predictive Analytics with Andy Bartley from Intel

Posted on September 20, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

#Paid content sponsored by Intel.

In the latest Healthcare Scene video interview, I talk with Andy Bartley, Senior Solutions Architect in the Health and Life Sciences Group at Intel. Andy and I talk about the benefits of and challenges to using predictive analytics in healthcare.

Andy offers some great insights on the subject, having had a long and varied career in the industry. Before joining Intel, he served in multiple healthcare organizations, including nurse communication and scheduling application startup NurseGrid, primary care practice One Medical Group and medical device manufacturer Stryker.

In my interview, he provides a perspective on what hospitals and health systems should be doing to leverage predictive analytics to improve care and outcomes, even if they don’t have a massive budget. Plus, he talks about predictive analytics that are already happening today.

Here are the list of questions I asked him if you’d like to skip to a specific topic in the video. Otherwise, you can watch the full video interview in the embedded video at the bottom of this post:

What are your thoughts on predictive analytics? How is it changing healthcare as we know it? What examples have you seen of effective predictive analytics? We look forward to seeing your thoughts in the comments and on social media.

Open Source Tool Offers “Synthetic” Patients For Hospital Big Data Projects

Posted on September 13, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

As readers will know, using big data in healthcare comes with a host of security and privacy problems, many of which are thorny.

For one thing, the more patient data you accumulate, the bigger the disaster when and if the database is hacked. Another important concern is that if you decide to share the data, there’s always the chance that your partner will use it inappropriately, violating the terms of whatever consent to disclose you had in mind. Then, there’s the issue of working with incomplete or corrupted data which, if extensive enough, can interfere with your analysis or even lead to inaccurate results.

But now, there may be a realistic alternative, one which allows you to experiment with big data models without taking all of these risks. A unique software project is underway which gives healthcare organizations a chance to scope out big data projects without using real patient data.

The software, Synthea, is an open source synthetic patient generator that models the medical history of synthetic patients. It seems to have been built by The MITRE Corporation, a not-for-profit research and development organization sponsored by the U.S. federal government. (This page offers a list of other open source projects in which MITRE is or has been involved.)

Synthea is built on a Generic Module Framework which allows it to model varied diseases and conditions that play a role in the medical history of these patients. The Synthea modules create synthetic patients using not only clinical data, but also real-world statistics collected by agencies like the CDC and NIH. MITRE kicked off the project using models based on the top ten reasons patients see primary care physicians and the top ten conditions that shorten years of life.

Its makers were so thorough that each patient’s medical experiences are simulated independently from their “birth” to the present day. The profiles include a full medical history, which includes medication lists, allergies, physician encounters and social determinants of health. The data can be shared using C-CDA, HL7 FHIR, CSV and other formats.

On its site, MITRE says its intent in creating Synthea is to provide “high-quality, synthetic, realistic but not real patient data and associated health records covering every aspect of healthcare.” As MITRE notes, having a batch of synthetic patient data on hand can be pretty, well, handy in evaluating new treatment models, care management systems, clinical support tools and more. It’s also a convenient way to predict the impact of public health decisions quickly.

This is such a good idea that I’m surprised nobody else has done something comparable. (Well, at least as far as I know no one has.) Not only that, it’s great to see the software being made available freely via the open source distribution model.

Of course, in the final analysis, healthcare organizations want to work with their own data, not synthetic substitutes. But at least in some cases, Synthea may offer hospitals and health systems a nice head start.

Hospital EMR Adoption Divide Widening, With Critical Access Hospitals Lagging

Posted on September 8, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

I don’t know about you, but I was a bit skeptical when HIMSS Analytics rolled out its EMRAM {Electronic Medical Record Adoption Model) research program. As some of you doubtless know, EMRAM breaks EMR adoption into eight stages, from Stage 0 (no health IT ancillaries installed) to Stage 7 (complete EMR installed, with data analytics on board).

From its launch onward, I’ve been skeptical about EMRAM’s value, in part because I’ve never been sure that hospital EMR adoption could be packaged neatly into the EMRAM stages. Perhaps the research model is constructed well, but the presumption that a multivariate process of health IT adoption can be tracked this way is a bit iffy in my opinion.

On the other hand, I like the way the following study breaks things out. New research published in the Journal of the American Medical Informatics Association looks at broader measures of hospital EHR adoption, as well as their level of performance in two key categories.

The study’s main goal was to assess the divide between hospitals using their EHRs in an advanced fashion and those that were not. One of the key steps in their process was to crunch numbers in a manner allowing them to identify hospital characteristics associated with high adoption in each of the advanced use criteria.

To conduct the research, the authors dug into 2008 to 2015 American Hospital Association Information Technology Supplement survey data. Using the data, the researchers measured “basic” and “comprehensive” EHR adoption among hospitals. (The ONC has created definitions for both basic and advanced adoption.)

Next, the research team used new supplement questions to evaluate advanced use of EHRs. As part of this process, they also used EHR data to evaluate performance management and patient engagement functions.

When all was said and done, they drew the following conclusions:

  • 80.5% of hospitals had adopted a basic EHR system, up 5.3% from 2014
  • 37.5% of hospitals had adopted at least 8 (of 10) EHR data sets useful for performance measurement
  • 41.7% of hospitals adopted at least 8 (of 10) EHR functions related to patient engagement

One thing that stood out among all the data was that critical access hospitals were less likely to have adopted at least 8 performance measurement functions and at least eight patient engagement functions. (Notably, HIMSS Analytics research from 2015 had already found that rural hospitals had begun to close this gap.)

“A digital divide appears to be emerging [among hospitals], with critical-access hospitals in particular lagging behind,” the article says. “This is concerning, because EHR-enabled performance measurement and patient engagement are key contributors to improving hospital performance.”

While the results don’t surprise me – and probably won’t surprise you either – it’s a shame to be reminded that critical access hospitals are trailing other facilities. As we all know, they’re always behind the eight ball financially, often understaffed and overloaded.

Given their challenges, it’s predictable that critical access hospitals would continue lag behind in the health IT adoption curve. Unfortunately, this deprives them of feedback which could improve care and perhaps offer a welcome boost to their efficiency as well. It’s a shame the way the poor always get poorer.

Did EMRs Help Hospitals Hit By Hurricane Harvey?

Posted on September 5, 2017 I Written By

Anne Zieger is veteran healthcare editor and analyst with 25 years of industry experience. Zieger formerly served as editor-in-chief of FierceHealthcare.com and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

On August 25, 2005, Hurricane Katrina made landfall. Over the next few days, it devastated communities from Florida to Texas, generating massive storm surges and triggering levee failures that drowned cities like New Orleans. It was the costliest natural disaster in the history of the United States.

At the time, virtually all healthcare providers used paper medical records, many of which were destroyed by flooding. According to an AHIMA article, the flood waters destroyed roughly 400,000 paper records, a catastrophic loss by any standard.

The situation wasn’t nearly as dire at facilities like Tulane University Hospital and Clinic, though. The New Orleans-based organization had implemented an EMR before the storm hit. In the trying weeks afterward, physicians at these hospitals had access to medical records, while many other hospitals were struggling to gather patient information for months or even years after Katrina.

Now, we’re facing the aftermath of Hurricane Harvey, which has all but submerged the city of Houston. Days after the storm’s peak, which dumped a record 51.88 inches of rain on Texas, roughly a third of the Houston area was covered in water, and Texas officials estimated that close to 49,000 homes had suffered flood damage.

During the worst of the storm, some 20 Houston hospitals transferred some or all of their patients to facilities outside of the area as water rose in their basements or levees seemed ready to burst. In its immediate aftermath, many of the area’s 110 facilities shut down outpatient services and canceled elective surgeries.

But despite the challenges they faced, the majority of Houston-area hospitals remained open for business.  One reason for their ability to function: unlike the hospitals battered by Katrina, they have EMRs in place. The area didn’t see any major power outages and the systems seem to stayed online.

It’s hard to say whether New Orleans would’ve fared better if the city’s hospitals had already implemented EMRs. Houston hospitals were apparently better prepared for hurricane flooding, having put a host of storm fortifications in place after Tropical Storm Allison wreaked massive damage sixteen years ago.

That being said, it seems likely that the EMRs have helped hospitals keep the doors open and keep caring for patients. If nothing else, they gave facilities a giant head start over New Orleans hospitals post-disaster, which in some cases had virtually nothing to go on when delivering care.

Of course, digital data offers some significant advantages over paper records of any kind, including but not limited to the ability to backup records to off-site facilities well out of a given disaster zone.  But organizing patient data in an EMR, arguably, offers additional benefits, not the least of which is the ability to access existing workflows and protocols. Few tools are better suited to capturing, sharing and preserving care records in the midst of a catastrophic event like Harvey.

Over the next few decades, some observers predict that care will become massively decentralized, with remote nurses, telemedicine and connected health doing much of the heavy lifting day-to-day. If that comes to pass, and health IT intelligence is distributed across mobile devices instead, the EMR of today may be far less important to healthcare organizations hoping to rebound after a disaster. But until then, it’s safe to say that it’s a good thing Houston’s hospitals don’t rely on paper records anymore.

Hospital EMR and EHR Supporters

Posted on September 1, 2017 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

As I’ve been preparing to launch a new secret healthcare IT event into the wild, I’ve been going through all the various connections Hospital EMR and EHR and Healthcare Scene have made in the world of Healthcare IT.  It’s really quite extraordinary what 11 years of blogging about healthcare IT provides as far as relationships.  Many people wonder if they should waste their time blogging.  I can assure you that the relationships I’ve made blogging here at Hospital EMR and EHR have provided some of the most amazing opportunities and experiences well beyond what I could have ever imagined.

With this in mind, we want to specifically thank each of the Hospital EMR and EHR sponsors for their support.  If you enjoy the content we create on this site, take a minute to look through these sponsors and see if any of them can help you with some of your pressing challenges.

Galen Healthcare Solutions – We’ve long been admirers of the work they do at Galen Healthcare Solutions.  They were one of the first organizations we interacted with on a blog when talking about EHR conversions.  They’re experts in that space and have also been doing a lot of work in the legacy health IT application space.  Plus, they’ve been providing a bunch of EMR optimization services as well.  If any of these are challenges in your organization, check out how Galen Healthcare Solutions can help.

Intel Health – Most of you have probably seen our series of CIO video interviews that we did that was sponsored by Intel. We have another video coming out shortly where we interviewed one of Intel’s predictive analytics experts as well.  He offers some real practical insights into predictive analytics, where it’s happening today, and where it’s going in the future.  Watch for that video interview coming out shortly.

Conduent – Together with Conduent, we’ve been publishing the Breakaway Thinking blog post series that’s sponsored by the Breakaway Learning Solutions (A Conduent Company). When it comes to EHR training, I know of no one that understands how to train a hospital or healthcare system better than this group.

FormFast – Every healthcare organization uses forms.  However, a lot of them still haven’t realized the value of purchasing a real forms management solution.  If you’re not one of the 1100 healthcare organizations already using FormFast’s forms technology, then take a look at what they offer and how they can make your forms management experience better.  I love how well FormFast has been able to integrate with EHR vendors and now even offer a solution that goes out to patients.

Iron Mountain – Healthcare Scene has been doing a whole series of blog posts for the Iron Mountain blog.  Many of you know Iron Mountain, but did you know they have a whole suite of IT and data center services along with their records management, document imaging, data management, secure shredding, etc?

MRO – Since we started HIM Scene, we’ve gotten deeper and deeper into the world of Health Information Management (HIM…or Medical Records if you’re old school like that).  We’re really happy to have MRO sponsoring HIM Scene including providing some great HIM related content.

HIPAA One – HIPAA One’s goal is to make managing HIPAA Risk Assessments easy and effective.  If you’re an organization that’s had to think about how to manage a large array of business associates and if those business associates have done a proper HIPAA risk assessment, take a minute to look at what HIPAA One can offer.  If you ever get a HIPAA audit, you’ll be glad you did your risk assessment using HIPAA One.

MedicaSoft – This is a brand new sponsor for us, but we’re happy to have them sponsoring Healthcare Scene. Along with offering a full EHR solution, Medicasoft also is seeing a lot of traction with their Paitent Portal solution and their interoperability solutions. I love the way MedicaSoft describes their solutions: “Innovative Healthcare IT Products Built with Modern Technology.” I know this is what many would like to see in healthcare.

Stericycle Communication Solutions – A lot of people know of Stericycle, but not enough people know about Stericycle Communication Solutions. They provide a wide variety of communication solutions for healthcare including patient reminders, call center services, patient self scheduling and much more.  Be sure to check out their Communication Solution Series of blog posts.

Hopefully I didn’t leave anyone out. As you can see we have a great group of companies that support Hospital EMR and EHR. We’re lucky to have them as supporters of the work we do. I’m sure that some of these companies can help you deal with the challenges you’re facing at your hospital or health system.  If you want to join this great group of companies, you can find information about advertising on Hospital EMR and EHR here.