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Hospital Takes Step Forward Using Patient-Reported Outcome Data

Posted on December 6, 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 usually summarize stories from other publications — I don’t want to bore you! — and I like to offer you a surprise or two. This time, though, I thought you might want to hear about an interesting piece appearing in Modern Healthcare. This item offers some insight into how understanding patient-generated determinants of health could improve outcomes.

The story tells the tale of the Hospital for Special Surgery, an orthopedics provider in New York City which provides elective procedures to treat joint pain and discomfort. According to the MH editor, HSS has begun collecting data on patient-reported outcomes after procedures to see not only how much pain may remain, but also how their quality of life is post-procedure.

This project began by doing a check in with the patient before the procedure, during which nurses went over important information and answered any questions the patient might have. (As readers may know, this is a fairly standard approach to pre-surgical patient communication, so this was something of a warm-up.)

However, things got more interesting a few months later. For its next step, the hospital also began surveying the patients on their state of mind and health prior to the procedure, asking 10 questions drawn from the Patient-Reported Outcomes Measurement Information System, or Promis.

The questions captured not only direct medical concerns such as pain intensity and sleep patterns, but also looked at the patient’s social support system, information few hospitals capture in a formal way at present.

All of the information gathered is being collected and entered into the patient’s electronic health record. After the procedure, the hospital has worked to see that the patients fill out the Promis survey, which it makes available using Epic’s MyChart portal.

Getting to this point wasn’t easy, as IT leaders struggled to integrate the results of the Promis survey into patient EHRs. However, once the work was done, the care team was able to view information across patients, which certainly has the potential to help them improve processes and outcomes over time.

Now, the biggest challenge for HSS is collecting data after the patients leave the hospital. Since kicking off the project in April, HSS has collected 24,000 patient responses to nursing questions, but only 15% of the responses came from patients who submitted them after their procedure. The hospital has seen some success in capturing post-surgical results when doctors push patients to fill out the survey after their care, but overall, the post-surgical response rate has remained low to date.

Regardless, once the hospital improves its methods for collecting post-surgical patient responses, it seems likely that the data will prove useful and important. I hope to see other hospitals take this approach.

Amazon May Soon Announce Major Cloud Deal With Cerner

Posted on November 27, 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 I’ve previously noted, Amazon is making increasingly aggressive moves into the healthcare space of late. While it hasn’t been terribly public with its plans—and why should it, honestly?— there been some talk of its going into the healthcare technology space. There’s also much talk about angles from which Amazon could attack healthcare sectors, including its well-publicized interest in the pharmacy business.

Though interesting, all of this has been vaguely defined it best. However, a new deal may be in the works which could have a very concrete effect. It could change not only the future of Amazon’s healthcare industry efforts but also, potentially, have an impact on the entire health IT world.

Think I’m exaggerating? Check this out. According to a story on the CNBC site, Amazon is about to announce a “huge” deal with Cerner under which the two will work together on building a major presence in enterprise health IT for Amazon Web Services. Put that way, this sounds a bit hyperbolic, but let me lay this out a bit further.

As things stand, the online retailer’s Amazon Web Services is already generating almost $20 billion a year, boasting clients across major industries such as technology, energy and financial services. Its only stumbling point to date is that it’s had trouble cracking the healthcare market.

Apparently, at the re:Invent conference in Las Vegas next week, AWS’s CEO will announce that Amazon is teaming up with Cerner to convince senior healthcare leaders to use AWS for key initiatives like population health management.

Sources who spoke to CNBC that the partnership will initially focus on Cerner’s HealtheIntent population health product, presumably as a door into convincing hospitals shift more of the cloud-based business to AWS.

Now why, you ask, is this deal bigger than the average bear?  is it one of those vaporware partnerships that fly a flag and promise a lot but don’t really go anywhere?

Yes, I admit that’s always possible, but in this case, I don’t think it’s going to turn out that way. The fit simply seems to work too well for this to be one of those much-ballyhooed deals that fade away quietly. (In fact, I could visualize a Cerner/Amazon merger in the future, as crazy as that might sound. It’s certainly less risky than the Whole Foods deal.)

For one thing, both Amazon and Cerner have significant benefits they can realize. For example, as the story notes, Amazon hasn’t gotten far in the healthcare market, and given its talent for doing the impossible, it must be really stuck at this point. Cerner, meanwhile, will never pull together the kind of cloud options AWS can offer, and I doubt Epic could either, which gives Cerner a boost in the always next-and-neck competition with its top rival.

If this agreement goes through, the ripples could be felt throughout the healthcare industry, if for no other reason than the impact it will have on the enterprise EHR market. This one should be fun to watch. I’m pulling out the popcorn.

AMIA17 – There’s Gold in Them EHRs!

Posted on November 13, 2017 I Written By

Colin Hung is the co-founder of the #hcldr (healthcare leadership) tweetchat one of the most popular and active healthcare social media communities on Twitter. Colin speaks, tweets and blogs regularly about healthcare, technology, marketing and leadership. He is currently an independent marketing consultant working with leading healthIT companies. Colin is a member of #TheWalkingGallery. His Twitter handle is: @Colin_Hung.

If even 10% of the research presented at the 2017 American Medical Informatics Association conference (AMIA17) is adopted by mainstream healthcare, the impact on costs, quality and patient outcomes will be astounding. Real-time analysis of EHR data to determine the unique risk profile of each patient, customized remote monitoring based on patient + disease profiles, electronic progress notes using voice recognition and secondary uses of patient electronic records were all discussed at AMIA17.

Attending AMIA17 was an experience like no other. I understood less than half of the information being presented and I loved it. It felt like I was back in university – which is the only other time I have been around so many people with advanced degrees. By the time I left AMIA17, I found myself wishing I had paid more attention during my STATS302 classes.

It was especially interesting to be at AMIA17 right after attending the 3-day CHIME17 event for Hospital CIOs. CHIME17 was all about optimizing investments made in HealthIT over the past several years, especially EHRs (see this post for more details). AMIA17 was very much an expansion on the CHIME17 theme. AMIA17 was all about leveraging and getting value from the data collected by HealthIT systems over the past several years.

A prime example of this was the work presented by Michael Rothman, Ph.D of Pera Health. Rothman created a way to analyze key vital signs RELATIVE to a patient’s unique starting condition to determine whether they are in danger. Dubbed the Rothman Index, this algorithm presents clinicians and caregivers with more accurate alarms and notifications. With all the devices and systems in hospitals today, alarm fatigue is a very real and potentially deadly situation.

Missed ventilator alarms was #3 on ECRI Institute’s 2017 Top 10 Health Technology Hazards. It was #2 on the 2016 Top 10 list. According to ECRI: “Failure to recognize and respond to an actionable clinical alarm condition in a timely manner can result in serious patient injury or death”. The challenge is not the response but rather how to determine which alarms are informational and which are truly an indicator of a clinical condition that needs attention.

Comments from RNs in adverse-event reports shared in a 2016 presentation to the Association for the Advancement of Medical Instrumentation (AAMI) sums up this challenge nicely:

“Alarm fatigue is leading to significant incidents because there are so many nuisance alarms and no one even looks up when a high-priority alarm sounds. Failure to rescue should be a never event but it isn’t.”

“Too many nuisance alarms, too many patients inappropriately monitored. Continuous pulse oximetry is way overused and accounts for most of the alarms. Having everyone’s phone ring to one patient’s alarm makes you not respond to them most of the time.”

This is exactly what Rothman is trying to address with his work. Instead of using a traditional absolute-value approach to setting alarms – which are based on the mythical “average patient” – Rothman’s method uses the patient’s actual data to determine their unique baseline and sets alarms relative to that. According to Rothman, this could eliminate as much as 80% of the unnecessary alarms in hospitals.

Other notable presentations at AMIA17 included:

  • MedStartr Pitch IT winner, FHIR HIEDrant, on how to mine and aggregate clinically relevant data from HIEs and present it to clinicians within their EHRs
  • FHIR guru Joshua C Mandel’s presentation on the latest news regarding CDS Hooks and the amazing Sync-for-Science EHR data sharing for research initiative
  • Tianxi Cai of Harvard School of Public Health sharing her research on how EHR data can be used to determine the efficacy of treatments on an individual patient
  • Eric Dishman’s keynote about the open and collaborative approach to research he is championing within the NIH
  • Carol Friedman’s pioneering work in Natural Language Processing (NLP). Not only did she overcome being a woman scientist but also applying NLP to healthcare something her contemporaries viewed as a complete waste of time

The most impressive thing about AMIA17? The number of students attending the event – from high schoolers to undergraduates to PhD candidates. There were hundreds of them at the event. It was very encouraging to see so many young bright minds using their big brains to improve healthcare.

I left AMIA17 excited about the future of HealthIT.

Healthcare Execs See New Digital Health Technologies As Critical To Success

Posted on October 30, 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.

Healthcare organizations have spent massively on HIT in recent years, in hopes of preparing for success by building next-generation tech infrastructure.  If a new survey is any indication, while the current set of efforts haven’t born as much fruit as their leaders like, they remain hopeful that the next wave will better support their goals.

The SAP Digital Transformation Executive Study, which surveyed about 400 healthcare executives, looked at whether the healthcare industry was prepared for the digital economy.

Respondents told SAP (and survey partner Oxford Economics) that the existing technology investments weren’t delivering the value they wanted, with only 22% saying they supported customer satisfaction efforts and 23% saying that they helped foster innovation.

Fortunately for health IT vendors, however, that wasn’t the whole story. Perhaps because hope springs eternal, healthcare leaders predicted that in two years thing should look different.

In fact, 70% said that the latest technologies were essential to growth, competitive advantage and customer experience. In two years, 61% expect technology investments to boost customer satisfaction, and 59% believe the technologies will help support innovation.

This may be, at least in part, because many healthcare organizations are in the process of kicking off digital transformation efforts and are relying on new technologies to achieve their goals. Though the process hasn’t advanced too far in many organizations, respondents all seem to be making some progress.

According to the survey, healthcare execs expect the importance of digital transformation to climb over the next several years. While 61% said it’s important today, 79% expect it to be important in two years and 86% believe that it will be important in five years.

To prepare for these eventualities, 23% of respondents said are planning digital transformation initiatives and 54% are piloting these approaches. In addition, 32% reported that their efforts were complete in some areas and 2% said their process was complete in all areas. Almost half (48%) said a lack of mature technology was holding back their efforts.

When asked to name the technologies they expected to use, 76% of healthcare leaders predicted that big data and analytics will help them transform their business. They also named cloud computing (65%), IoT technologies (46%) and AI (28%) as tools likely to foster digital transformation process.

I don’t know about you, but personally, I’d be pretty upset if I’d spent tens or hundreds of millions of dollars on this wave of health IT and felt that I’d gotten little value out of it. And given that history, I’d be reluctant to make any new investments until I was confident things play out differently this time.

Under these circumstances, it’s not surprising that healthcare execs are taking their time with implementing digital transformation, as important as this process may be. With any luck, the next wave of digital technology will be more flexible and offer greater ROI than the previous generation.

Predictive Analytics Will Save Hospitals, Not IT Investment

Posted on October 27, 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.

Most hospitals run on very slim operating margins. In fact, not-for-profit hospitals’ mean operating margins fell from 3.4% in fiscal year 2015 to 2.7% in fiscal year 2016, according to Moody’s Investors Service.

To turn this around, many seem to be pinning their hopes on better technology, spending between 25% and 35% of their capital budget on IT infrastructure investment. But that strategy might backfire, suggests an article appearing in the Harvard Business Review.

Author Sanjeev Agrawal, who serves as president of healthcare and chief marketing officer at healthcare predictive analytics company LeanTaaS, argues that throwing more money at IT won’t help hospitals become more profitable. “Healthcare providers can’t keep spending their way out of trouble by investing in more and more infrastructure,” he writes. “Instead, they must optimize the use of the assets currently in place.”

Instead, he suggests, hospitals need to go the way of retail, transportation and airlines, industries which also manage complex operations and work on narrow margins. Those industries have improved their performance by improving their data science capabilities.

“[Hospitals] need to create an operational ‘air traffic control’ for their hospitals — a centralized command-and-control capability that is predictive, learns continually, and uses optimization algorithms and artificial intelligence to deliver prescriptive recommendations throughout the system,” Agrawal says.

Agrawal predicts that hospitals will use predictive analytics to refine their key care-delivery processes, including resource utilization, staff schedules, and patient admits and discharges. If they get it right, they’ll meet many of their goals, including better patient throughput, lower costs and more efficient asset utilization.

For example, he notes, hospitals can optimize OR utilization, which brings in 65% of revenue at most hospitals. Rather than relying on current block-scheduling techniques, which have been proven to be inefficient, hospitals can use predictive analytics and mobile apps to give surgeons more control of OR scheduling.

Another area ripe for process improvements is the emergency department. As Agrawal notes, hospitals can avoid bottlenecks by using analytics to define the most efficient order for ED activities. Not only can this improve hospital finances, it can improve patient satisfaction, he says.

Of course, Agrawal works for a predictive analytics vendor, which makes him more than a little bit biased. But on the other hand, I doubt any of us would disagree that adopting predictive analytics strategies is the next frontier for hospitals.

After all, having spent many billions collectively to implement EMRs, hospitals have created enormous data stores, and few would argue that it’s high time to leverage them. For example, if they want to adopt population health management – and it’s a question of when, not if — they’ve got to use these tools to reduce outcome variations and improve quality of cost across populations. Also, while the deep-pocketed hospitals are doing it first, it seems likely that over time, virtually every hospital will use EMR data to streamline operations as well.

The question is, will vendors like LeanTaaS take a leading role in this transition, or will hospital IT leaders know what they want to do?  At this stage, it’s anyone’s guess.

Waiting For The Perfect “Standard” Is Not The Answer To Healthcare’s Interoperability Problem

Posted on October 16, 2017 I Written By

The following is a guest blog post by Gary Palgon, VP Healthcare and Life Sciences Solutions at Liaison Technologies.

Have you bought into the “standards will solve healthcare’s interoperability woes” train of thought? Everyone understands that standards are necessary to enable disparate systems to communicate with each other, but as new applications and new uses for data continually appear, healthcare organizations that are waiting for universal standards, are not maximizing the value of their data. More importantly, they will be waiting a long time to realize the full potential of their data.

Healthcare interoperability is not just a matter of transferring data as an entire file from one user to another. Instead, effective exchange of information allows each user to select which elements of a patient’s chart are needed, and then access them in a format that enables analysis of different data sets to provide a holistic picture of the patient’s medical history or clinical trends in a population of patients. Healthcare’s interoperability challenge is further exacerbated by different contextual interpretations of the words within those fields. For instance, how many different ways are there to say heart attack?

The development of the Health Level Seven (HL7®) FHIR®, which stands for Fast Healthcare Interoperability Resources, represents a significant step forward to interoperability. While the data exchange draft that is being developed and published by HL7 eliminates many of the complexities of earlier HL7 versions and facilitates real-time data exchange via web technology, publication of release 4 – the first normative version of the standard – is not anticipated until October 2018.

As these standards are further developed, the key to universal adoption will be simplicity, according to John Lynn, founder of the HealthcareScene.com. However, he suggests that CIOs stop waiting for “perfect standards” and focus on how they can best achieve interoperability now.

Even with standards that can be implemented in all organizations, the complexity and diversity of the healthcare environment means that it will take time to move everyone to the same standards. This is complicated by the number of legacy systems and patchwork of applications that have been added to healthcare IT systems in an effort to meet quickly changing needs throughout the organization. Shrinking financial resources for capital investment and increasing competition for IT professionals limits a health system’s ability to make the overall changes necessary for interoperability – no matter which standards are adopted.

Some organizations are turning to cloud-based, managed service platforms to perform the integration, aggregation and harmonization that makes data available to all users – regardless of the system or application in which the information was originally collected. This approach solves the financial and human resource challenges by making it possible to budget integration and data management requirements as an operational rather than a capital investment. This strategy also relieves the burden on in-house IT staff by relying on the expertise of professionals who focus on emerging technologies, standards and regulations that enable safe, compliant data exchange.

How are you planning to scale your interoperability and integration efforts?  If you're waiting for standards, why are you waiting?

As a leading provider of healthcare interoperability solutions, Liaison is a proud sponsor of Healthcare Scene. While the conversation about interoperability has been ongoing for many years, ideas, new technology and new strategies discussed and shared by IT professionals will lead to successful healthcare data exchange that will transform healthcare and result in better patient care.

About Gary Palgon
Gary Palgon is vice president of healthcare and life sciences solutions at Liaison Technologies. In this role, Gary leverages more than two decades of product management, sales, and marketing experience to develop and expand Liaison’s data-inspired solutions for the healthcare and life sciences verticals. Gary’s unique blend of expertise bridges the gap between the technical and business aspects of healthcare, data security, and electronic commerce. As a respected thought leader in the healthcare IT industry, Gary has had numerous articles published, is a frequent speaker at conferences, and often serves as a knowledgeable resource for analysts and journalists. Gary holds a Bachelor of Science degree in Computer and Information Sciences from the University of Florida.

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.

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.

Interoperability: Is Your Aging Healthcare Integration Engine the Problem?

Posted on September 18, 2017 I Written By

The following is a guest blog post by Gary Palgon, VP Healthcare and Life Sciences Solutions at Liaison Technologies.
There is no shortage of data collected by healthcare organizations that can be used to improve clinical as well as business decisions. Announcements of new technology that collects patient information, clinical outcome data and operational metrics that will make a physician or hospital provide better, more cost-effective care bombard us on a regular basis.

The problem today is not the amount of data available to help us make better decisions; the problem is the inaccessibility of the data. When different users – physicians, allied health professionals, administrators and financial managers – turn to data for decision support, they find themselves limited to their own silos of information. The inability to access and share data across different disciplines within the healthcare organization prevents the user from making a decision based on a holistic view of the patient or operational process.

In a recent article, Alan Portela points out that precision medicine, which requires “the ability to collect real-time data from medical devices at the moment of care,” cannot happen easily without interoperability – the ability to access data across disparate systems and applications. He also points out that interoperability does not exist yet in healthcare.

Why are healthcare IT departments struggling to achieve interoperability?

Although new and improved applications are adopted on a regular basis, healthcare organizations are just now realizing that their integration middleware is no longer able to handle new types of data such as social media, the volume of data and the increasing number of methods to connect on a real-time basis. Their integration platforms also cannot handle the exchange of information from disparate data systems and applications beyond the four walls of hospitals. In fact, hospitals of 500 beds or more average 25 unique data sources with six electronic medical records systems in use. Those numbers will only move up over time, not down.

Integration engines in place throughout healthcare today were designed well before the explosion of the data-collection tools and digital information that exist today. Although updates and additions to integration platforms have enabled some interoperability, the need for complete interoperability is creating a movement to replace integration middleware with cloud-based managed services.

A study by the Aberdeen Group reveals that 76 percent of organizations will be replacing their integration middleware, and 70 percent of those organizations will adopt cloud-based integration solutions in the next three years.

The report also points out that as healthcare organizations move from an on-premises solution to a cloud-based platform, business leaders see migration to the cloud and managed services as a way to better manage operational expenses on a monthly basis versus large, up-front capital investments. An additional benefit is better use of in-house IT staff members who are tasked with mission critical, day-to-day responsibilities and may not be able to focus on continuous improvements to the platform to ensure its ability to handle future needs.

Healthcare has come a long way in the adoption of technology that can collect essential information and put it in the hands of clinical and operational decision makers. Taking that next step to effective, meaningful interoperability is critical.

As a leading provider of healthcare interoperability solutions, Liaison is a proud sponsor of Healthcare Scene. It is only through discussions and information-sharing among Health IT professionals that healthcare will achieve the organizational support for the steps required for interoperability.

Join John Lynn and Liaison for an insightful webinar on October 5, titled: The Future of Interoperability & Integration in Healthcare: How can your organization prepare?

About Gary Palgon
Gary Palgon is vice president of healthcare and life sciences solutions at Liaison Technologies. In this role, Gary leverages more than two decades of product management, sales, and marketing experience to develop and expand Liaison’s data-inspired solutions for the healthcare and life sciences verticals. Gary’s unique blend of expertise bridges the gap between the technical and business aspects of healthcare, data security, and electronic commerce. As a respected thought leader in the healthcare IT industry, Gary has had numerous articles published, is a frequent speaker at conferences, and often serves as a knowledgeable resource for analysts and journalists. Gary holds a Bachelor of Science degree in Computer and Information Sciences from the University of Florida.