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Montefiore Health Makes Big AI Play

Posted on September 24, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

I’ve been doing a lot of research on healthcare AI applications lately. Not surprisingly, while people find the abstract issues involved to be intriguing, most would prefer to hear news of real-life projects, so I’ve been on the lookout for good examples.

One interesting case study, which appeared recently in Health IT Analytics, comes from Montefiore Health System, which has been building up its AI capabilities. Over the past three years, it has created an AI framework leveraging a data lake, infrastructure upgrades and predictive analytics algorithms. The AI is focused on addressing expensive, dangerous health issues, HIA reports.

“We have created a system that harvests every piece of data that we can possibly find, from our own EMRs and devices to patient-generated data to socio-economic data from the community,” said Parsa Mirhaji, MD, PhD, director of the Center for Health Data Innovations at Montefiore and the Albert Einstein College of Medicine, who spoke with the publication.

Back in 2015, Mirhaji kicked off a project bringing semantic data lake technology to his organization. The first pilot using the technology was designed to find patients at risk of death or intubation within 48 hours. Now, clinicians can also see red flags for admitted patients with increased risk of mortality 3 to 5 days in advance.

In 2017, the health system also rolled out advanced sepsis detection tools and a respiratory failure detection algorithm called APPROVE, which identifies patients at a raised risk of prolonged ventilation up to 48 hours before onset, HIA reported.

The net result of these efforts was dubbed PALM, the Patient-centered Analytical  Learning Machine. PALM “represents a very new way of interacting with data in healthcare,” Miraji told HIA.

What makes PALM special is that it speeds up the process of collecting, curating, cleaning and accessing metadata which must be conducted before the data can be used to train AI models. In most cases, the process of collecting data for AI use is largely manual, but PALM automates this process, Miraji told the publication.

This is because the data lake and its graph repositories can find relationships between individual data elements on an on-the-fly basis. This automation lets Montefiore cut way down on labor needed to get these results. Miraji noted that ordinarily, it would take a team of data analysts, database administrators and designers to achieve this result.

PALM also benefits from a souped-up hardware architecture, which Montefiore created with help from Intel and other technology partners. The improved architecture includes the capacity for more system memory and processing power.

The final step in optimizing the PALM system was to integrate it into the health system’s clinical workflow. This seems to have been the hardest step. “I will say right away that I don’t think we have completely solved the problem of integrating analytics seamlessly into the workflow,” Miraji admitted to HIA.

A Nursing Informatics Perspective on Healthcare Analytics – Interview with Charles Boicey

Posted on September 21, 2018 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.

Healthcare informatics has been around for a long time. However, from my perspective, it feels like there’s something different in the air when it comes to healthcare informatics. I get the feeling that we’re on the precipice of something really special happening. In fact, I think we already start to see value being created by healthcare informaticists.

As Healthcare Scene continues to explore this subject, we sat down with informatics expert, Charles Boicey, Chief Innovation Officer at Clearsense, to talk with him about what’s changed in healthcare informatics that makes it different today than in the past. We also talk about what’s needed to make healthcare analytics efforts successful at organizations and what analytics trend he’s watching most. Plus, we had to talk about his background as a nurse and how a nursing background really helps his informatics work.

If you want to hear of some practical uses of healthcare analytics and how your organization can benefit from it, you’ll enjoy our interview with Charles Boicey.

Be sure and subscribe to all of Healthcare Scene’s videos on YouTube. Also, take a minute to check out EXPO.health and join us in Boston to mix and mingle with amazing healthcare IT professionals like Charles Boicey.

Health IT Consulting Demand To Explode This Year

Posted on August 24, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

As payment models shift from fee-for-service to value-based care, hospitals are having to adopt new technologies and tweak existing ones. The thing is, it takes a mighty team of IT pros to make all this happen. In some cases, a provider has enough resources to handle this kind of big transition, but most need some help, especially when they’re handling major infrastructure improvements or even switching out technologies.

This seems to be at least part of what’s driving a dramatic increase in spending on health IT consulting, according to a new study from Black Book Research. The study drew on input from 1,586 professionals with knowledge of the US health IT industry.

Black Book concluded that health IT management consulting spending has grown from $20 billion in 2016 to $45 billion last year. Not only that, the firm expects to see this number climb to nearly $53 billion for 2018. That’s a massive increase, particularly given that providers were already spending heavily on consultants as they beat their enterprise EHRs into shape.

According to the analyst firm, 64% of last year’s spending paid for implementation of software, information systems, systems integration and optimization and support for mergers and acquisitions. This summary covers a lot of ground, but it’s hardly surprising given the drastic changes underway.

Going forward, respondents expect three key forces to drive healthcare consulting spend, including a lack of highly-skilled IT professionals (cited by 81% of respondents), adoption of cloud technology in healthcare (74%) and growing industry digitalization (71%). (I’d also expect to see investment in new organizational infrastructures — for, let’s say, ACOs)  — will continue to increase in importance as well.)

Providers responding to the study said that they expect to hire health IT consultants for EHR and RCM system optimization (61%) and to offer expertise in software training and implementation (46%) next year. Other areas providers hope to address include value-based care (39%), cloud infrastructure (36%), compliance issues (33%) and a grab bag of big data, decision support and analytics projects (31%).

The vast majority of respondents (84%) said they expect to enter into a wide range of consulting agreements to include work with single-shop consultants, single freelancers, group purchasing organizations, HIT vendors, networks of freelancers, boutique advisory firms and traditional major consultancies, Black Book reported. In other words, it’s all hands on deck!

3 Key Steps to Driving your Revenue Strategy

Posted on July 9, 2018 I Written By

The following is a guest blog post by Brad Josephson is the Director of Marketing and Communications at PMMC.

For healthcare providers struggling to accurately collect reimbursement, developing a revenue strategy based off a foundation of accuracy is the most efficient way to ensure revenue integrity throughout the revenue cycle.

Currently, many hospitals operate under multiple systems running for their different departments within the organization. This type of internal structure can threaten the accuracy of the analytics because data is forced to come into multiple systems, increasing the chances that the data will be misrepresented.

By maintaining revenue integrity, not only does it give hospitals assurance that the data they’ve collected is current and accurate, but it also provides invaluable leverage with the payer when it comes time to (re)negotiating payer contracts.

Let’s begin by starting from the ground up…

Here are the 3 steps needed for maintaining revenue integrity:

  • Creating a foundation backed by accurate analytics
  • Breaking down the departmental siloes
  • Preparing ahead of time for consumerism and price transparency

Accuracy Drives Meaningful Analytics

The first step toward maintaining revenue integrity is to assess whether your data is accurate. We know that accurate data drives meaningful analytics, essentially functioning as the engine of the revenue cycle.

And what happens when you stop taking care of the engine regularly and it no longer works properly? It not only costs you a lot of money to repair the engine, but you may also have to pay for other parts of the car that were damaged by the engine failure.

What if, however, you were able to visualize pie charts and bar graphs on your car’s dashboard that showed the current health of the engine to inform you when it requires a maintenance check?

You would be better informed about the current state of your engine and have a greater urgency to get the car repaired.

This same principle applies to healthcare organizations looking to increase the accuracy of their data to drive meaningful analytics. While some organizations struggle to draw valuable insight from pieces of raw data, data visualization tools are more efficient because it allows the user to see a complete dashboard with a drill-down capability to gain a deeper and clearer understanding of the implications of their data analytics.

Data visualization allows healthcare providers to quickly identify meaningful trends. Here are the 4 key benefits of implementing data visualization:

  • Easily grasp more information
  • Discover relationships and patterns
  • Identify emerging trends faster
  • Directly interact with data

Figure 1: Payer Dashboard

Removing Departmental Siloes  

While data visualization does generate helpful insight into current and future trends, it begins with storing the data in one integrated system so that different departments can easily communicate regarding the data.

System integration is crucial to maintaining revenue integrity because it dramatically lowers the likelihood of data errors, missed reimbursement, and isolated decisions that don’t look at the full revenue picture. Here is a list of other issues associated with organizations running revenue siloes:

  • No consistent accuracy metrics driving performance and revenue.
  • Different data sources and systems drive independent and isolated decisions without known impact on the rest of the revenue cycle.
  • Departments cannot leverage analytics and insight into contract and payer performance.

In the spirit of the recent international World Cup games, think of revenue siloes like playing for a professional soccer team.

Similar to the structure of a hospital’s revenue team, soccer teams are large organizations that need to be able to clearly communicate with each other quickly in order to make calls on-the-spot. These quick decisions can be the difference in turning the ball over to the other team or scoring a goal in the final minutes so it’s crucial that everyone knows their role on the team.

If other players don’t understand the plays that are being called, however, then mistakes will be made that could cost them the game. Each player on the team needs to study the same playbook so they stay on the same page and decrease the chances that a costly mistake will be made.

A hospital’s Managed Care department works in a similar way. If Managed Care is preparing to renegotiate payer contracts, they need to fully understand and have insight into underpayment and denial trends across multiple payers.

Preparing Now for Consumerism and Price Transparency

Now that we know the reimbursement rate is accurate, how do we communicate an accurate price to patients in order to encourage upfront payment?

Studies have shown that by increasing accuracy in pricing estimates, it increases the likelihood that patients pay upfront, which can help your organization lower bad debt.

In an effort to migrate to a more patient-centric approach, these accurate online estimates also enable hospitals to address the patient’s fear of the unknown with healthcare of ‘how much is this procedure going to cost?’ By giving the patient more control over their financial responsibility, hospitals can become a leader in pricing transparency for their entire community while expanding on their market share.

At the end of the day, what this all comes down to is maintaining accuracy to help drive your revenue strategy. By integrating all data into a single system, the hospital is positioned to identify trends more quickly while increasing the accuracy of their patient estimates, ultimately driving your revenue strategy to new heights.

With many healthcare organizations still making the transition away from the traditional fee-for-service model, now is the time to prepare for consumerism and value-based care. Take some time to evaluate where your organization currently stands in the local market as well as any pricing adjustments that need to be made.

About Brad Josephson
Brad Josephson is the Director of Marketing and Communications at PMMC, a provider of revenue cycle software and contact management services for healthcare providers. Brad received a Bachelor of Arts, Public Relations and Marketing Degree from Drake University. He has worked at PMMC for over three years and has a deep knowledge of hospital revenue cycle management tools which improves the financial performance of healthcare organizations.

Healthcare Interoperability Insights

Posted on June 29, 2018 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.

I came across this great video by Diameter Health where Bonny Roberts talked with a wide variety of people at the interoperability showcase at HIMSS. If you want to get a feel for the challenges and opportunities associated with healthcare interoperability, take 5 minutes to watch this video:

What do you think of these healthcare interoperability perspectives? Does one of them stand out more than others?

I love the statement that’s on the Diameter Health website:

“We Cure Clinical Data Disorder”

What an incredible way to describe clinical data today. I’m not sure the ICD-10 code for it, but there’s definitely a lot of clinical data disorder. It takes a real professional to clean the data, organize the data, enrich the data, and know how to make that data useful to people. IT’s not a disorder that most people can treat on their own.

What’s a little bit scary is that this disorder is not going to get any easier. More data is on its way. Better to deal with your disorder now before it becomes a full on chronic condition.

Healthcare Interoperability is Solved … But What Does That Really Mean? – #HITExpo Insights

Posted on June 12, 2018 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.

One of the best parts of the new community we created at the Health IT Expo conference is the way attendees at the conference and those in the broader healthcare IT community engage on Twitter using the #HITExpo hashtag before, during, and after the event.  It’s a treasure trove of insights, ideas, practical innovations, and amazing people.  Don’t forget that last part since social media platforms are great at connecting people even if they are usually in the news for other reasons.

A great example of some great knowledge sharing that happened on the #HITExpo hashtag came from Don Lee (@dflee30) who runs #HCBiz, a long time podcast which he recorded live from Health IT Expo.  After the event, Don offered his thoughts on what he thought was the most important conversation about “Solving Interoperability” that came from the conference.  You can read his thoughts on Twitter or we’ve compiled all 23 tweets for easy reading below (A Big Thanks to Thread Reader for making this easy).

As shared by Don Lee:

1/ Finally working through all my notes from the #HITExpo. The most important conversation to me was the one about “solving interoperability” with @RasuShrestha@PaulMBlack and @techguy.

2/ Rasu told the story of what UPMC accomplished using DBMotion. How it enabled the flow of data amongst the many hospitals, clinics and docs in their very large system. #hitexpo

3/ John challenged him a bit and said: it sounds like you’re saying that you’ve solved #interoperability. Is that what you’re telling us? #hitexpo

4/ Rasu explained in more detail that they had done the hard work of establishing syntactic interop amongst the various systems they dealt with (I.e. they can physically move the data from one system to another and put it in a proper place). #hitexpo

5/ He went on and explained how they had then done the hard work of establishing semantic interoperability amongst the many systems they deal with. That means now all the data could be moved, put in its proper place, AND they knew what it meant. #hitexpo

6/ Syntactic interop isn’t very useful in and of itself. You have data but it’s not mastered and not yet useable in analytics. #hitexpo

7/ Semantic interop is the mastering of the data in such a way that you are confident you can use it in analytics, ML, AI, etc. Now you can, say, find the most recent BP for a patient pop regardless of which EMR in your system it originated. And have confidence in it. #hitexpo

8/ Semantic interop is closely related to the concept of #DataFidelity that @BigDataCXO talks about. It’s the quality of data for a purpose. And it’s very hard work. #hitexpo

9/ In the end, @RasuShrestha’s answer was that UPMC had done all of that hard work and therefore had made huge strides in solving interop within their system. He said “I’m not flying the mission accomplished banner just yet”. #hitexpo

10/ Then @PaulMBlack – CEO at @Allscripts – said that @RasuShrestha was being modest and that they had in fact “Solved interoperability.”

I think he’s right and that’s what this tweet storm is about. Coincidentally, it’s a matter of semantics. #hitexpo

11/ I think Rasu dialed it back a bit because he knew that people would hear that and think it means something different. #hitexpo

12/ The overall industry conversation tends to be about ubiquitous, semantic interop where all data is available everywhere and everyone knows what it means. I believe Rasu was saying that they hadn’t achieved that. And that makes sense… because it’s impossible. #hitexpo

13/ @GraceCordovano asked the perfect question and I wish there had been a whole session dedicated to answering it: (paraphrasing) What’s the difference between your institutional definition of interop and what the patients are talking about? #hitexpo

14/ The answer to that question is the crux of our issue. The thing patients want and need is for everyone who cares for them to be on the same page. Interop is very relevant to that issue, obviously, but there’s a lot of friction and it goes way beyond tech. #hitexpo

15/ Also, despite common misconception, no other industry has solved this either. Sure, my credit card works in Europe and Asia and gets back to my bank in the US, but that’s just a use case. There is no ubiquitous semantic interop between JP Morgan Chase and HSBC.

16/ There are lots of use cases that work in healthcare too. E-Prescribing, claims processing and all the related HIPAA transactions, etc. #hitexpo

17/ Also worth noting… Canada has single payer system and they also don’t have clinical interoperability.

This is not a problem unique to healthcare nor the US. #hitexpo

18/ So healthcare needs to pick its use cases and do the hard work. That’s what Rasu described on stage. That’s what Paul was saying has been accomplished. They are both right. And you can do it too. #hitexpo

19/ So good news: #interoperability is solved in #healthcare.

Bad news: It’s a ton of work and everyone needs to do it.

More bad news: You have to keep doing it forever (it breaks, new partners, new sources, new data to care about, etc). #hitexpo

19/ Some day there will be patient mediated exchange that solves the patient side of the problem and does it in a way that works for everyone. Maybe on a #blockchain. Maybe something else. But it’s 10+ years away. #hitexpo

20/ In the meantime my recommendation to clinical orgs – support your regional #HIE. Even UPMC’s very good solution only works for data sources they know about. Your patients are getting care outside your system and in a growing # of clinical and community based settings. #hitexpo

21/ the regional #HIE is the only near-term solution that even remotely resembles semantic, ubiquitous #interoperability in #healthcare.
#hitexpo

22/ My recommendation to patients: You have to take matters into your own hands for now. Use consumer tools like Apple health records and even Dropbox like @ShahidNShah suggested in another #hitexpo session. Also, tell your clinicians to support and use the regional #HIE.

23/ So that got long. I’ll end it here. What do you think?

P.S. the #hitexpo was very good. You should check it out in 2019.

A big thank you to Don Lee for sharing these perspectives and diving in much deeper than we can do in 45 minutes on stage. This is what makes the Health IT Expo community special. People with deep understanding of a problem fleshing out the realities of the problem so we can better understand how to address them. Plus, the sharing happens year round as opposed to just at a few days at the conference.

Speaking of which, what do you think of Don’s thoughts above? Is he right? Is there something he’s missing? Is there more depth to this conversation that we need to understand? Share your thoughts, ideas, insights, and perspectives in the comments or on social media using the #HITExpo hashtag.

Making Healthcare Data Useful

Posted on May 14, 2018 I Written By

The following is a guest blog by Monica Stout from MedicaSoft

At HIMSS18, we spoke about making health data useful to patients with the Delaware Health Information Network (DHIN). Useful data for patients is one piece of the complete healthcare puzzle. Providers also need useful data to provide more precise care to patients and to reach patient populations who would benefit directly from the insights they gain. Payers want access to clinical data, beyond just claims data, to aggregate data historically. This helps payers define which patients should be included in care coordination programs or who should receive additional disease management assistance or outreach.

When you’re a provider, hospital, health system, health information exchange, or insurance provider and have the data available, where do you start? It’s important to start at the source of the data to organize it in a way that makes insights and actions possible. Having the data is only half of the solution for patients, clinicians or payers. It’s what you do with the data that matters and how you organize it to be usable. Just because you may have years of data available doesn’t mean you can do anything with it.

Historically, healthcare has seen many barriers to marrying clinical and claims data. Things like system incompatibility, poor data quality, or siloed data can all impact organizations’ ability to access, organize, and analyze data stores. One way to increase the usability of your data is to start with the right technology platform. But what does that actually mean?

The right platform starts with a data model that is flexible enough to support a wide variety of use models. It makes data available via open, standards-based APIs. It organizes raw data into longitudinal records. It includes services, such as patient matching and terminology mapping, that make it easy to use the data in real-world applications. The right platform transforms raw data into information that that aids providers and payers improve outcomes and manage risk and gives patients a more complete view of their overall health and wellness.

Do you struggle with making your data insightful and actionable? What are you doing to transform your data? Share your insights, experiences, challenges, and thoughts in the comments or with us on Twitter @MedicaSoftLLC.

About Monica Stout
Monica is a HIT teleworker in Grand Rapids, Michigan by way of Washington, D.C., who has consulted at several government agencies, including the National Aeronautics Space Administration (NASA) and the U.S. Department of Veterans Affairs (VA). She’s currently the Marketing Director at MedicaSoft. Monica can be found on Twitter @MI_turnaround or @MedicaSoftLLC.

About MedicaSoft
MedicaSoft  designs, develops, delivers, and maintains EHR, PHR, and UHR software solutions and HISP services for healthcare providers and patients around the world. MedicaSoft is a proud sponsor of Healthcare Scene. For more information, visit www.medicasoft.us or connect with us on Twitter @MedicaSoftLLC, Facebook, or LinkedIn.

Improving Data Outcomes: Just What The Doctor Ordered

Posted on May 8, 2018 I Written By

The following is a guest blog post by Dave Corbin, CEO of HULFT.

Health care has a data problem. Vast quantities are generated but inefficiencies around sharing, retrieval, and integration have acute repercussions in an environment of squeezed budgets and growing patient demands.

The sensitive nature of much of the data being processed is a core issue. Confidential patient information has traditionally encouraged a ‘closed door’ approach to data management and an unease over hyper-accessibility to this information.

Compounding the challenge is the sheer scale and scope of the typical health care environment and myriad of departmental layers. The mix of new and legacy IT systems used for everything from billing records to patient tracking often means deep silos and poor data connections, the accumulative effect of which undermines decision-making. As delays become commonplace, this ongoing battle to coordinate disparate information manifests itself in many different ways in a busy hospital.

Optimizing bed occupancies – a data issue?

One example involves managing bed occupancy, a complex task which needs multiple players to be in the loop when it comes to the latest on a patient’s admission or discharge status. Anecdotal evidence points to a process often informed manually via feedback with competing information. Nurses at the end of their shift may report that a patient is about to be discharged, unaware that a doctor has since requested more tests to be carried out for that patient. As everyone is left waiting for the results from the laboratory, the planned changeover of beds is delayed with many knock-on effects, increasing congestion and costs and frustrating staff and patients in equal measure.

How data is managed becomes a critical factor in tackling the variations that creep into critical processes and resource utilization. In the example above, harnessing predictive modelling and data mining to forecast the number of patient discharges so that the number of beds available for the coming weeks can be estimated more accurately will no doubt become an increasingly mainstream option for the sector.

Predictive analytics is great and all, but first….

Before any of this can happen, health care organizations need a solid foundation of accessible and visible data which is centralized, intuitive, and easy to manage.

Providing a holistic approach to data transfer and integration, data logistics can help deliver security, compliance, and seamless connectivity speeding up the processing of large volumes of sensitive material such as electronic health records – the kind of data that simply cannot be lost. These can ensure the reliable and secure exchange of intelligence with outside health care vendors and partners.

For data outcomes, we’re calling for a new breed of data logistics that’s intuitive and easy to use. Monitoring interfaces which enable anyone with permission to access the network to see what integrations and transfers are running in real time with no requirement for programming or coding are the kind of intervention which opens the data management to a far wider section of an organization.

Collecting data across a network of multiple transfer and integration activities and putting it in a place where people can use, manage and manipulate becomes central to breaking down the barriers that have long compromised efficiencies in the health care sector.

HULFT works with health care organizations of all sizes to establish a strong back-end data infrastructure that make front-end advances possible. Learn how one medical technology pioneer used HULFT to drive operational efficiencies and improve quality assurance in this case study.

Dave Corbin is CEO of HULFT, a comprehensive data logistics platform that allows IT to find, secure, transform and move information at scale. HULFT is a proud sponsor of Health IT Expo, a practical innovation conference organized by Healthcare Scene.  Find out more at hulftinc.com

Health Orgs Were In Talks To Collect SDOH Data From Facebook

Posted on April 9, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

These days, virtually everyone in healthcare has concluded that integrating social determinants of health data with existing patient health information can improve care outcomes. However, identifying and collecting useful, appropriately formatted SDOH information can be a very difficult task. After all, in most cases it’s not just lying around somewhere ripe for picking.

Recently, however, Facebook began making the rounds with a proposal that might address the problem. While the research initiative has been put on hold in light of recent controversy over Facebook’s privacy practices, my guess is that the healthcare players involved will be eager to resume talks if the social media giant manages to calm the waters.

According to CNBC, Facebook was talking to healthcare organizations like Stanford Medical School and American College of Cardiology, in addition to several other hospitals, about signing a data-sharing agreement. Under the terms of the agreement, the healthcare organizations would share anonymized patient data, which Facebook planned to match up with user data from its platform.

Facebook’s proposal will sound familiar to readers of this site. It suggested combining what a health system knows about its patients, such as their age, medication list and hospital admission history, with Facebook-available data such as the user’s marital status, primary language and level of community involvement.

The idea would then be to study, with an initial focus on cardiovascular health, whether this combined data could improve patient care, something its prospective partners seem to think possible. The CNBC story included a gushing statement from American College of Cardiology interim CEO Cathleen Gates suggesting that such data sharing could create revolutionary results. According to Gates, the ACC believes that mixing anonymized Facebook data with anonymized ACC data could help greatly in furthering scientific research on how social media can help in preventing and treating heart disease.

As the business site notes, the data would not include personally identifiable information. That being said, Facebook proposed to use hashing to match individuals existing in both data sets. If the project were to have gone forward, Facebook might’ve shared data on roughly 87 million users.

Looked at one way, this arrangement could raise serious privacy questions. After all, healthcare organizations should certainly exercise caution when exchanging even anonymized data with any outside organization, and with questions still lingering on how willing Facebook is to lock data down projects like this become even riskier.

Still, under the right circumstances, Facebook could prove to be an all but ideal source of comprehensive, digitized SDOH data. Well now, arguably, might not be the time to move ahead, hospitals should keep this kind of possibility in mind.

Health Leaders Go Beyond EHRs To Tackle Value-Based Care

Posted on March 30, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

In the broadest sense, EHRs were built to manage patient populations — but largely one patient at a time. As a result, it’s little wonder that they aren’t offering much support for value-based care as is, as a recent report from Sage Growth Partners suggests.

Sage spoke with 100 healthcare executives to find out what they saw as their value-based care capabilities and obstacles. Participants included leaders from a wide range of entities, including an ACO, several large physician practices and a midsize integrated delivery network.

The overall sense Sage seems to have gotten from its research was that while value-based care contracts are beginning to pay off, health execs are finding it difficult support these contacts using the EHRs they have in place. While their EHRs can produce quality reports, most don’t offer data aggregation and analytics, risk stratification, care coordination or tools to foster patient and clinician engagement, the report notes.

To get the capabilities they need for value-based contracting, health organizations are layering population health management solutions on top of their EHRs. Though these additional PHM tools may not be fully mature, health executives told Sage that there already seeing a return on such investments.

This is not necessarily because these organizations aren’t comfortable with their existing EHR. The Sage study found that 65% of respondents were somewhat or highly unlikely to replace their EHR in the next three years.

However, roughly half of the 70% of providers who had EHRs for at least three years also have third-party PHM tools in place as well. Also, 64% of providers said that EHRs haven’t delivered many important value-based contracting tools.

Meanwhile, 60% to 75% of respondents are seeking value-based care solutions outside their EHR platform. And they are liking the results. Forty-six percent of the roughly three-quarters of respondents who were seeing ROI with value-based care felt that their third-party population PHM solution was essential to their success.

Despite their concerns, healthcare organizations may not feel impelled to invest in value-based care tools immediately. Right now, just 5% of respondents said that value-based care accounted for over 50% of their revenues, while 62% said that such contracts represented just 0 to 10% of their revenues. Arguably, while the growth in value-based contracting is continuing apace, it may not be at a tipping point just yet.

Still, traditional EHR vendors may need to do a better job of supporting value-based contracting (not that they’re not trying). The situation may change, but in the near term, health executives are going elsewhere when they look at building their value-based contracting capabilities. It’s hard to predict how this will turn out, but if I were an enterprise EHR vendor, I’d take competition with population health management specialist vendors very seriously.