Wednesday, December 20, 2017

HIMSS18 Preview: What Are This Year’s Hot Topics?

In 2016 and again in 2017 I analyzed the educational sessions at the HIMSS Conference and Expo to determine what the popular topics of conversation would be. Here is this year’s edition.

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Overall there are 300 sessions, a modest 6% increase from last year. The number of categories has now increased to 24, which is higher than 2015’s 22 categories. As we saw between 2015 and 2016, it seems likely that we’ll see some reductions and eliminations next year to reduce the number of categories.
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Privacy and Security

Unsurprisingly, Privacy and Security remains the most popular category. No doubt this reflects the ongoing cybersecurity problems and breaches plaguing the industry. There are 10 fewer sessions in this group, however, (31 vs. last year’s 41) perhaps indicating that the category is running out of steam and may begin trending downward next year.

Emerging Payment Models for Value-Based Care versus Consumer and Patient Engagement

A quick look at the year-to-year changes shows that Changing Payment Models was near the bottom of the list in 2015 and rose to mid-pack (and was renamed to Business of Healthcare and New Payment Models) in 2016 and 2017. This year it drops lower in the rankings (and changes its name again to Emerging Payment Models for Value-Based Care).

This may indicate that 2016 and 2017 were the hot years for talking about risk-sharing arrangements, such as ACOs. Now that providers and payers are better aligned, there is less to talk about in this category. However, the patient remains left out of alignment with the other two members of the payer/provider/patient triad, and we see that Consumer and Patient Engagement has risen to the number 2 position; it was tied for 6th last year. It’s likely this upward momentum will continue into 2019, and the Consumer and Patient Engagement category may overtake Privacy and Security as its hold on the top spot weakens.

Connected Health and Telehealth

Remote patient visits have been trending for quite some time, but in 2017 there were some changes in reimbursement policy and regulation that will make it easier for providers to see patients remotely (and get paid for the encounters).

In addition to the 25 educational sessions about telehealth, over 150 companies will be exhibiting at the Expo in this category.

Data Analytics/Clinical and Business Intelligence

Business intelligence and analytics are the real goals of health IT. The true value of data is in elevating it to actionable information, and that’s why this category has risen to (tied for) third on this year’s list.

Notably, the category was fairly highly ranked in 2015, but it spent 2016 and 2017 toward the bottom of the lists. My interpretation of this pattern is that there was high interest in the topic in 2015, but the implementation was premature. Hospitals needed to finalize and optimize their EHR implementations before being able to turn their attention to the high-value category of analytics and BI. EHR implementations are now fairly mature, and it’s time to return to the topic of converting EHR data into a valuable asset.

Public Policy

One of four new categories in 2018, public policy debuts with 21 sessions. Public policy includes legislation, regulation, and compliance. These are huge drivers in health care, and it’s surprising this category hasn’t been seen before.

Care Coordination, Culture of Care, and Population Health

This was the number 2 category last year, and this year it is split into two separate categories that, together, include 39 sessions (versus 32 in last year’s single category). Although it looks like this category has fallen down the list, it would actually be at the top if it hadn’t been broken up.

The interesting aspect of the category split is where the boundary was drawn. Population Health, which deals with health issues in the aggregate, is separated from Culture of Care and Care Coordination, which concern individual patient needs. These are macro and micro sides of the same coin. Vendors may choose to specialize in one area or the other, but providers will need to master both in order to succeed in a value-based health care system.

Pharmacy Standards and Technology

This is another new category for 2018, and it may reflect a growing emphasis on opioid abuse and treatment. Part of the solution to the epidemic will rely on standards and technology, so this is a category that’s likely to gain in popularity over the next few years.

Social, Psychosocial, Behavior Determinants of Health

Yet another new category, Social Determinants of Health (SDoH) relates to the broader context that impacts a patient’s wellness. As emphasis shifts from treating illness to promoting wellness, it becomes more and more important for caregivers to track social determinants alongside factors such as allergies, problems, and medications.


The Bottom Line

As always, the HIMSS educational sessions reflect the broad trends in health IT. Of course, proposals for sessions are due well in advance of the conference, so trends in the categories are not a leading indicator of emerging priorities. Rather, they reflect trends that are well underway and need to be discussed by the broad audience of stakeholders that the HIMSS Conference and Expo attracts. If the hot topics outlined here are not on your radar, now’s the time to start tracking them!

Tuesday, September 12, 2017

Health Transformation Alliance Update

Last year I wrote about the Health Transformation Alliance (HTA). HTA is a group of large employers that joined together in an effort to control their health care insurance expenses by reducing the costs of services driving premium increases. Last year, the Alliance had approximately 20 members. In a year, the number of participants has doubled, representing more than six million employees.

According to a New York Times opinion column written by HTA’s chief executive, the organization’s member companies account for nearly $25 billion in health care spending. It has projected savings of $600 million by optimizing its spending on prescription drugs, only one of four tools in the Alliance’s toolbox.

A second tool is its data and analytics solutions, provided by IBM, a member company. HTA’s members aggregate their anonymized health care utilization records, forming a huge data set it can analyze to identify and prioritize the sources of waste and overspending most in need of optimization. 

Another tool is “medical solutions that modify and improve the current provider delivery system.” While it sounds ambitious for employers to try to overhaul the provider delivery system, it’s important to understand that the health care system is already in the process of transformation. Providers, payers and regulators are committed to improving outcomes, paying for value, and enhancing the patient experience. HTA can help accelerate these changes by guiding their six million employees toward insurance plans and health care providers that meet these goals. At the same time, they may be able to smooth the transition to risk-based reimbursement for providers that are reluctant to leave the fee-for-service system by providing a large, stable population of patients enrolled in a fee-for-value plan.

The fourth tool is “consumer engagement solutions.” While HTA doesn’t fully describe the details of this solution on its website, one can assume that engaged patients will have better clinical, social, and economic outcomes. For example, engaged patients are more likely to take advantage of preventive and wellness programs and adhere to chronic disease management regimens.

HTA’s approach is a free-market response to the unsustainable growth rate of employers’ health care insurance costs. Although they’re just getting underway, they seem to have the right approach and the right set of tools to make a first, significant impact on health care costs.

There is a temptation to contrast HTA’s success against the federal government’s recent failure to pass a health care reform bill, but in a way, that misses the point . Each initiative is aimed at a different part of the health care landscape. The government is grappling with how to provide insurance coverage through Medicare, Medicaid and individual policies at a reasonable cost to as many Americans as possible and can’t move forward with other parts of health care reform because of bureaucracy. The tools at their disposal are policy, the tax code, and funding. Employers aren’t tied to the reconciliation process and can focus on quickly solving health care issues that incur the most cost and impact care. They are using high tech and economies of scale to drive down the underlying costs through economies of scale. Tackling both aspects of healthcare reform is important, but at the moment only the latter is succeeding because of collaboration in working toward common goals.

Tuesday, August 1, 2017

Artificial Intelligence: What it means for health care

For the past several years, experts have predicted that artificial intelligence (AI) would make a splash in health care.  I decided it’s time to write about it for my blog, Trends in Health IT. Why now? Because it seems like a good time to tackle this topic, given the recent, high-profile debate between prominent tech leaders about whether or not AI poses a threat to humanity.

AI in health care will be a major shift for the industry, but one that happens slowly and gradually reaches a tipping point. It won’t follow the usual hype cycle we’ve seen recently.

Health care customarily embraces technology in big chunks, especially when financially motivated. The recent wave of EHR adoption, largely from Meaningful Use, is an example of a big chunk of technology. All of the record keeping – plus a great deal of workflow, decision support, and clinical best practices – became encapsulated in monolithic systems. EHRs became a recognizable product category as the industry began to agree on a definition of what constitutes an EHR. So too with billing systems, lab information systems, analytics packages, and dozens of other examples. Health care is accustomed to packing up business functions as software products and then categorizing those products. 

AI, however, will not be a standalone product with a strict definition and clean boundaries. “AI solutions” won’t be a product category. Rather, AI will become a built-in feature of each and every product on the market. There will be AI in EHR software, analytics software, patient monitors, and everything else. Users might not even notice that it’s there; they’ll just notice that features work better. Computerized physician order entry systems will recommend more appropriate order sets. Analytics packages will calculate better patient risk scores. Radiology software will provide assistance with interpreting imaging studies.

There are at least two reasons why AI will infiltrate health care as features, rather than separate products. First, AI is not a business function in the same way that record-keeping or order entry is a business function. AI is a collection of techniques for doing various computational tasks. It’s a novel, subtler way of predicting, recognizing, recommending and categorizing. Second, AI is highly specialized. The same AI software that is good at recognizing potential tumors on an x-ray image will not be able to group patients into cohorts based on similar risk factors. As such, it’s a great add-on to existing software, but it’s not great on its own.

Vendors will need to find ways, over time, to improve their software by incorporating AI techniques. It’s a predictable consequence of the competitive drive to deliver better software. By the same token, it’s unlikely that we’ll see software procurement requirements that specifically require AI.

AI will change health care, but it’ll happen without anyone specifically attributing the change to AI.

Will AI be an existential threat to human existence, as Elon and Zuck debated? Not in the five-year timeframe that Trends in Health IT spans, but there will be a number of serious implications to deal with. For example:
  • The first several generations of AI-based features will probably be a nuisance as often as they are a benefit. This can be a big problem when it comes to patient care. “Alarm fatigue” is already a problem in clinical settings. Will “AI suggestion fatigue” become an issue?
  • A key part of many AI techniques is that they are self-training or self-optimizing, and that means there isn’t always a human-comprehensible way to explain how the AI arrived at an answer, recommendation or suggestion. When a patient’s life depends on a critical decision, it’s not satisfactory for a clinician to choose a therapy “because the computer said so.”
  • How will therapeutic devices and systems with advanced AI features be regulated?
  • Many AI processes rely on huge data sets, which might mean pooling data across several institutions. This will need to be done in a way that complies with HIPAA, various state laws and institutional policies.


These are questions that will take a lot of time and careful thought to work through, and that’s why AI adoption in health care has not happened yet. Luckily for prognosticators, this means that they can always copy it from one year’s list of Health IT predictions to the next!



Wednesday, June 21, 2017

The Next Integration Wave: Patient Directed Exchange

Last week’s CNBC story about Apple’s interest in healthcare data is trending right now. For those who have been paying attention, there’s really not much new information. Apple’s Health app has always been a place to collect health and fitness data, and last August’s acquisition of Gliimpse made it clear Apple was committed to that direction.

Apple’s plan is to make the patient the collector, keeper, and controller of their own healthcare data. This strategy is generally known as patient directed exchange (PDEx). My favorite description of PDEx came from Doc Searls in 2008 when he said, “the best way to fix health care is forpatients to be the platform for the care they get from doctors andinstitutional systems.”

In order to clearly perceive the value of PDEx, it’s worth examining a couple of other, unsuccessful attempts in similar areas: personal health records (PHRs) and patient portals.

Personal health records attempt to provide a place for patients to collect their own health data. The two most famous examples are Google Health, which was discontinued in 2012, and Microsoft HealthVault, which still exists but is not widely adopted.

The biggest obstacle these early systems faced was the ability to collect data. Manual data entry is simply too cumbersome for most patients, and electronic methods of exchanging data were just beginning to emerge. Few doctors and hospitals stored records electronically, and even fewer had a way to provide electronic copies of records to patients. The idea of a PHR was ahead of its time.

The Meaningful Use (MU) program in the U.S. helped change the status quo. One of the MU requirements was that doctors and hospitals needed to provide electronic methods for viewing, downloading, and transferring (V/D/T) patient records in a standard format (CCD and later, C-CDA). Most providers chose to expose V/D/T functions through a patient portal that was connected to the institution’s electronic health record. After the provider finished documenting an encounter in the EHR, it would be available in the patient portal. From there it could be viewed in human-readable format or downloaded in machine-readable format.

But this introduced another problem. Patients who receive care in multiple locations would need to manage separate logins to separate patient portals. The problem is compounded by the additional silos introduced by consumer fitness devices like step counters, blood pressure cuffs, and smart scales. Collecting and reconciling data from across these sources is insurmountable for all but the simplest situations.

Perhaps that is one reason why patient portal adoption remains at just 33% in urban areas and 18% in rural communities. PHRs had the right idea – to centralize and standardize data – but the wrong timing. Patient portals are newly possible due to Meaningful Use, but they’ve adopted a model of making it difficult to share data. That’s where PDEx comes to the rescue.

The new generation of PHRs feature built-in connections to existing patient portals and fitness device services. They can simplify and automate the process of collecting data, so that patients can manage and visualize their complete health record all in one place. Best of all, the patient has a central place from which to manage data sharing, privacy and consent. Patients can push all or part of their record to caregivers, new healthcare providers, researchers, or insurance companies. With the patients mediating the exchange, there is no need for data sharing agreements between the entities that send and receive the data.

The approach is not without challenges. Adding the patient to the process of transferring health records introduces a new point of failure and the possibility of data tampering. For example, a patient might choose to hide a portion of his chart that he considers especially sensitive, when in fact it turns out that data is crucial for the treatment he wants to receive. There will still be providers for which HIEs remain relevant. In many cases it makes sense for institutions to share all their patient data with one another instead of relying on all of the patients to participate in a PDEx approach.

Even though traditional interoperability won’t go away, it’s finally practical to use PDEx to augment it, so that we can have the best of both worlds in achieving a longitudinal view of patient health records.