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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.

Rush Sues Patient Monitoring Vendor, Says System Didn’t Work

Posted on August 25, 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.

Rush University Medical Center has filed suit against one of its health IT vendors, claiming that its patient monitoring system didn’t work as promised and may have put patients in danger.

According to a story in the Chicago Tribune, Rush spent $18 million installing the Infinity Acute Monitoring Solution system from Telford, PA-based Draeger Inc. between 2012 and early 2016.  The Infinity system included bedside monitors, larger data aggregating monitors at central nursing stations, battery-powered portable monitors and M300 wireless patient-worn monitors.

However, despite years of attempting to fix the system, its patient alarms were still unreliable and inaccurate, it contends in the filing, which accuses Draeger of breach of contract, unjust enrichment and fraud.

In the suit, the 664-bed hospital and academic medical center says that the system was dogged by many issues which could have had an impact on patient safety. For example, it says, the portable monitors stopped collecting data when moved to wireless networks and sometimes stole IP addresses from bedside monitors, knocking the bedside monitor off-line leaving the patient unmonitored.

In addition, the system allegedly sent out false alarms for heart arrhythmia patients with pacemakers, distracting clinicians from performing their jobs, and failed monitor apnea until 2015, according to the complaint. Even then, the system wasn’t monitoring some sets of apnea patients accurately, it said. Near the end, the system erased some patient records as well, it contends.

Not only that, Draeger didn’t deliver everything it was supposed to provide, the suit alleges, including wired-to-wireless monitoring and monitoring for desaturation of neonatal patients’ blood oxygen.

As if that weren’t enough, Draeger didn’t respond effectively when Rush executives told it about the problems it was having, according to the suit. “Rather than effectively remediating these problems, Draeger largely, and inaccurately, blamed them on Rush,” it contends.

While Draeger provided a software upgrade for the system, it was extremely difficult to implement, didn’t fix the original issues and created new problems, the suit says.

According to Rush, the Draeger system was supposed to last 10 years. However, because of technical problems it observed, the medical center replaced the system after only five years, spending $30 million on the new software, it says.

Rush is asking the court to make Draeger pay that the $18 million it spent on the system, along with punitive damages and legal fees.

It’s hard to predict the outcome of such a case, particularly given that the system’s performance has to have depended in part on how Rush managed the implementation. Plus, we’re only seeing the allegations made by Rush in the suit and not Draeger’s perspective which could be very different and offer other details. Regardless, it seems likely these proceedings will be watched closely in the industry. Regardless of whether they are at fault or not, no vendor can afford to get a reputation for endangering patient safety, and moreover, no hospital can afford to buy from them if they do.

A New Hospital Risk-Adjustment Model

Posted on August 23, 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.

Virtually all of the risk adjustment models with which I’m familiar are based on retrospective data. This data clearly has some predictive benefits – maybe it’s too cliché to say the past is prologue – and is already in our hands.

To look at just one example of what existing data archives can do, we need go no further than the pages of this blog. Late last year, I shared the story of a group of French hospitals which are working to predict admission rates as much as 15 days in advance by mining a store of historical data. Not surprisingly, the group’s key data includes 10 years’ worth of admission records.

The thing is, using historical data may not be as helpful when you’re trying to develop risk-adjustment models. After all, among other problems, the metrics by which evaluate care shift over time, and our understanding of disease states changes as well, so using such models to improve care and outcomes has its limitations.

I’ve been thinking about these issues since John shared some information on a risk-adjustment tool which leverages relevant patient care data collected almost in real time.

The Midas Hospital Risk Adjustment Model, which is created specifically for single organizations, samples anywhere from 20 to 600 metrics, which can include data on mortality, hospital-acquired complications, unplanned readmission, lengths of stay and charges. It’s built using the Midas Health Analytics Platform, which comes from a group within healthcare services company Conduent. The platform captures data across hospital functional areas and aggregates it for use in care management

The Midas team chooses what metrics to include using its in-house tools, which include a data warehouse populated with records on more than 100 million claims as well as data from more than 800 hospitals.

What makes the Midas model special, Conduent says, is that it incorporates a near-time feed of health data from hospital information systems. One of the key advantages to doing so is that rather than basing its analysis on ICD-9 data, which was in use until relatively recently, it can leverage clinically-detailed ICD-10 data, the company says.

The result of this process is a model which is far more capable of isolating small but meaningful differences between individual patients, Conduent says. Then, using this model, hospitals risk-adjust clinical and financial outcomes data by provider for hospitalized patients, and hopefully, have a better basis for making future decisions.

This approach sounds desirable (though I don’t know if it’s actually new). We probably need to move in the direction of using fresh data when analyzing care trends. I suspect few hospitals or health system would have the resources to take this on today, but it’s something to consider.

Still, I’d want to know two things before digging into Midas further. First, while the idea sounds good, is there evidence to suggest that collecting recent data offers superior clinical results? And in that vein, how much of an improvement does it offer relative to analysis of historical data? Until we know these things, it’s hard to tell what we’ve got here.