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Yale New Haven Hospital Partners With Epic On Centralized Operations Center

Posted on February 5, 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.

Info, info, all around, and not a place to manage it all. That’s the dilemma faced by most hospitals as they work to leverage the massive data stores they’re accumulating in their health IT systems.

Yale New Haven Hospital’s solution to the problem is to create a centralized operations center which connects the right people to real-time data analytics. Its Capacity Command Center (nifty alliteration, folks!) was created by YNHH, Epic and the YNHH Clinical Redesign Initiative.

The Command Center project comes five years into YNHH’s long-term High Reliability project, which is designed to prepare the institution for future challenges. These efforts are focused not only on care quality and patient safety but also managing what YNHH says are the highest patient volumes in Connecticut. Its statement also notes that with transfers from other hospitals increasing, the hospital is seeing a growth in patient acuity, which is obviously another challenge it must address.

The Capacity Command Center’s functions are fairly straightforward, though they have to have been a beast to develop.

On the one hand, the Center offers technology which sorts through the flood of operational data generated by and stored in its Epic system, generating dashboards which change in real time and drive process changes. These dashboards present real-time metrics such as bed capacity, delays for procedures and tests and ambulatory utilization, which are made available on Center screens as well as within Epic.

In addition, YNHH has brought representatives from all of the relevant operational areas into a single physical location, including bed management, the Emergency Department, nursing staffing, environmental services and patient transport. Not only is this a good approach overall, it’s particularly helpful when patient admissions levels climb precipitously, the hospital notes.

This model is already having a positive impact on the care process, according to YNHH’s statement. For example, it notes, infection prevention staffers can now identify all patients with Foley catheters and review their charts. With this knowledge in hand, these staffers can discuss whether the patient is ready to have the catheter removed and avoid related urinary tract infections associated with prolonged use.

I don’t know about you, but I was excited to read about this initiative. It sounds like YNHH is doing exactly what it should do to get more out of patient data. For example, I was glad to read that the dashboard offered real-time analytics options rather than one-off projections from old data. Bringing key operational players together in one place makes great sense as well.

Of course, not all hospitals will have the resources to pull something off something like this. YNHH is a 1,541-bed giant which had the cash to take on a command center project. Few community hospitals would have the staff or money to make such a thing happen. Still, it’s good to see somebody at the cutting edge.

Texas Hospital Association Dashboard Offers Risk, Cost Data

Posted on January 22, 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.

The Texas Hospital Association has agreed to a joint venture with health IT vendor IllumiCare to roll out a new tool for physicians. The new dashboard offers an unusual but powerful mix of risk data and real-time cost information.

According to THA, physician orders represent 87% of hospital expenses, but most know little about the cost of items they order. The new dashboard, Smart Ribbon, gives doctors information on treatment costs and risk of patient harm at the point of care. THA’s assumption is that the data will cause them to order fewer and less costly tests and meds, the group says.

To my mind, the tool sounds neat. IllumiCare’s Smart Ribbon technology doesn’t need to be integrated with the hospital’s EMR. Instead, it works with existing HL-7 feeds and piggybacks onto existing user authorization schemes. In other words, it eliminates the need for creating costly interfaces to EMR data. The dashboard includes patient identification, a timer if the patient is on observational status, a tool for looking up costs and tabs providing wholesale costs for meds, labs and radiology. It also estimates iatrogenic risks resulting from physician decisions.

Unlike some clinical tools I’ve seen, Smart Ribbon doesn’t generate alerts or alarms, which makes it a different beast than many other clinical decision support tools. That doesn’t mean tools that do generate alerts are bad, but that feature does set it apart from others.

We’ve covered many other tools designed to support physicians, and as you’d probably guess, those technologies come in all sizes. For example, last year contributor Andy Oram wrote about a different type of dashboard, PeraHealth, a surveillance system targeting at-risk patients in hospitals.

PeraHealth identifies at-risk patients through analytics and displays them on a dashboard that doctors and nurses can pull up, including trends over several shifts. Its analytical processes pull in nursing assessments in addition to vital signs and other standard data sets. This approach sounds promising.

Ultimately, though, dashboard vendors are still figuring out what physicians need, and it’s hard to tell whether their market will stay alive. In fact, according to one take from Kalorama Information, this year technologies like dashboarding, blockchain and even advanced big data analytics will be integrated into EMRs.

As for me, I think Kalorama’s prediction is too aggressive. While I agree that many freestanding tools will be integrated into the EMR, I don’t think it will happen this or even next year. In the meantime, there’s certainly a place for creating dashboards that accommodate physician workflow and aren’t too intrusive. For the time being, they aren’t going away.

Using Geography to Combat the Opioid Crisis

Posted on January 10, 2018 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.

When it comes to the opioid crisis, the numbers aren’t good. According to the latest CDC numbers, over 66,000 Americans died from drug overdoses between May 2016 and May 2017. Unfortunately this continues the rapid upward trend over the past five years.

Credit: New York Times, The First Count of Fentanyl Deaths in 2016: Up 540% in Three Years, 2 Sept 2017, https://www.nytimes.com/interactive/2017/09/02/upshot/fentanyl-drug-overdose-deaths.html

One of the biggest drivers for this increase is the prevalence of opioids – a class of drugs that includes pain medications, heroin and fentanyl (a synthetic opioid). The opioid crisis is not the stereotypical street-drug problem. It is not confined to inner cities or to any socio-economic boundaries. It affects all neighborhoods…and therein lies one of the greatest challenges of dealing with the crisis, knowing where to deploy precious resources.

As governments and public health authorities begin to take more aggressive action, some are wisely turning to geographic information systems (GIS) in order to determine where the need is greatest. GIS (also called geospatial mapping) are designed specifically to capture, store, manage and analyze geographical data. It has been a mainstay in mining, engineering and environmental sciences since the early 1990’s. For more information about GIS, please see this excellent PBS documentary. In recent years, GIS has been applied to a number of new areas including healthcare.

Esri is one of the companies doing pioneering GIS work in healthcare and recently they have focused on applying their ArcGIS technology to help tackle the opioid crisis. “One of the basic challenges that public health authorities face is clearly defining the scope of the opioid problem in their local area.” says Estella Geraghty MD, Chief Medical Officer & Health Solutions Director at Esri. “The good news is that the information to map the extent of the problem is available, it’s just stored in disparate systems and in incompatible formats. We help bring it all together.”

Geraghty points to their work with the Tri-County Health Department (TCHD) as an example of how effective GIS can be. TCHD is one of the largest public health agencies in the US, serving 1.5 million residents in three of Denver’s metropolitan counties: Adams, Arapahoe and Douglas. Using Esri’s ArcGIS solution, TCHD created an open data site that allows internal teams and external partners to pool and share their opioid health information using a visual map of the region as a common base of reference.

According to Esri: “Since the creation of the Open Data site, there has been a dramatic increase in both the information available to the public and the community’s understanding of the opioid crisis.” You can see the Open Data site here and if you scroll down you will see six different maps available to the public. Particularly sobering is the Opioid Overdose Deaths from 2011-2016, which allows you to zoom in down to specific streets/blocks. Another interesting map is the Household Medication Take-Back Locations which seems to indicate there is a lack of coverage for the city of Denver.

Esri itself has created its own site to bring attention to the opioid crisis at a national level. Two maps in particular stand out to me. The first is the map of Opioid Prescriptions per Provider. The red zones on that map represent areas where a high number of opioid prescriptions are being made by relatively few providers. This points to potential areas where opioid abuse may be occurring.

By mapping the data in this way, some interesting insights emerge. Take Taliaferro County in Georgia for example where 2,069 claims out of a total of 29,016 were for opioids, yet the county only has 2 providers. Or Clinch County in Georgia where a whopping 10% of all claims were for opioids.

The second interesting map is Lost Loved Ones (located at the bottom of the Esri site). This is a completely open map where anyone can pay tribute to a loved one who has been lost to the opioid crisis. Each dot is a person – a stark reminder that behind each statistic is a son, daughter, mother, or father who has died from opioids. Anyone can add to the map by clicking the button at the top of the map.

There is something to be said about seeing data overlaid onto an interactive map. It takes data from abstract lines, bars or numbers on a page and transforms it into something more tangible, more “real”. I suspect that for many on the front lines of this crisis, having the opioid data visualized in this manner helps to drive home the need for additional resources.

“Esri is helping public health officials all over the country make better decisions,” continued Geraghty. “We are helping them determine if they have enough coverage for places where people can drop off expired drugs, places where Naloxone is available and mental health program coverage. We can visually present the types of drugs being dropped off by region. We can track where first responders have had to use Naloxone. We plan on continuing to collaborate closely with customers, especially with public health authorities. This opioid crisis is impacting so many neighborhoods. We can make a difference.”

Given the continued upward trend in opioid-related deaths, healthcare can use all the difference makers it can get.

Pennsylvania Health Orgs Agree to Joint $1 Billion Network Dev Effort

Posted on December 27, 2017 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.

If the essence of deal-making is putting your money where your mouth is, a new agreement between Pennsylvania healthcare giants fit the description. They’ve certainly bitten off a mouthful.

Health organizations, Penn State Health and Highmark Health, have agreed to make a collective investment of more than $1 billion. That is a pretty big number to swallow, even for two large organizations, though it very well may take even more to develop the kind of network they have in mind.

The two are building out what they describe as a “community-based healthcare network,” which they’re designing to foster collaboration with community doctors and keep care local across its service areas.  Makes sense, though the initial press release doesn’t do much to explain how the two are going to make that happen.

The agreement between Penn State and Highmark includes efforts to support population health, the next step in accepting value-based payment. The investors’ plans include the development of population health management capabilities and the use of analytics to manage chronic conditions. Again, pretty much to be expected these days, though their goals are more likely to actually be met given the money being thrown at the problem.

That being said, one possible aspect of interest to this deal is its inclusion of a regionally-focused academic medical center. Penn State plans to focus its plans around teaching hospital Milton S. Hershey Medical Center, a 548-bed hospital affiliated with more than 1,100 clinicians. In my experience, too few agreements take enough advantage of hospital skills in their zeal to spread their arms around large areas, so involving the Medical Center might offer extra benefits to the agreement.

Highmark Health, for its part, is an ACO which encompasses healthcare business serving almost 50 million consumers cutting across all 50 states.  Clearly, an ACO with national reach has every reason in the world to make this kind of investment.

I don’t know what the demographics of the Penn State market are, but one can assume a few things about them, given the the big bucks the pair are throwing at the deal:

  • That there’s a lot of well-insured consumers in the region, which will help pay for a return on the huge investment the players are making
  • That community doctors are substantially independent, but the two allies are hoping to buy a bunch of practices and solidify their network
  • That prospective participants in the network are lacking the IT tools they need to make value-based schemes work, which is why, in part, the two players need to spend so heavily

I know that ACOs and healthcare systems are already striking deals like this one. If you’re part of a health system hoping to survive the next generation of reimbursement, big budgets are necessary, as are new strategies better adapted to value-based reimbursement.

Still, this is a pretty large deal by just about any measure. If it works out, we might end up with new benchmarks for building better-distributed healthcare networks.

Amazon May Soon Announce Major Cloud Deal With Cerner

Posted on November 27, 2017 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 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.

Healthcare Execs See New Digital Health Technologies As Critical To Success

Posted on October 30, 2017 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.

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 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.

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.

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 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 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.

A New Hospital Risk-Adjustment Model

Posted on August 23, 2017 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.

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.