Lab Soft News

Provider Organizations Beginning to Compete on the Basis of Value-Based Care

We are transitioning from a fee-for-service healthcare system to a value-based one. This new approach is not well understood, particularly by patients. Value-based care is characterized by the documentation of organizational efficiency and effectiveness combined with positive outcomes for patients. One of the major goals is cost-savings. This is in contrast to fee-for-service where providers decide which services are provided to patients with insufficient attention to outcomes. In line with these changes, some provider organizations are marketing themselves as value-based organizations. Details about this were provided in a recent article (see: Paladina Health acquires Activate Healthcare, creating large provider of value-based care) with a excerpt below:

Paladina Health, a direct primary care services company based in Denver, has acquired Indiana-based Activate Healthcare, a provider offering customized services to employers and unions for preventive and primary medical care. The collaboration creates one of the largest providers of value-based primary care across the U.S., serving more than 170,000 patients in 18 states....With a growing focus in the marketplace on alternative care delivery models that are patient-centric and value-based, Activate Healthcare has been cited as one of the faster-growing organization-based primary care providers...."This partnership underscores the need for innovation and change to improve the health and well-being of Americans while realizing medical cost savings for employers and unions within the healthcare delivery system," said Paladina Health CEO Chris Miller. 

This approach by Paladina Health and Activate Healthcare strikes me as ground-breaking. They describe themselves as value-based and promise better care combined with a low spend. Such an approach is obviously attractive to companies that contract out the primary care for their employees to these companies. Here are two quotes from the Activate Healthcare web site:

Aligned Incentives

We incentivize our physicians based on quality of care, rather than quantity of services delivered. Our physicians' accountability for the right metrics helps us deliver increased access and engagement for patients—this results in improved health outcomes and healthy, more efficient healthcare system use.

Data-Driven Approach

Our data-driven approach manages overall risk, including population health management, risk stratification and proactive outreach and communications. With this approach, we are able to address the specific health needs of your population—enabling us to drive health outcomes, lower cost and improve patient experiences.

Whether all of this is mere marketing hype will become apparent in time. However, I think that it's an important trend and other health systems may be headed in the same direction. The executives of these health systems will be turning to their quality leadership and IT departments to supply the data to document that they are delivering on the goals of improved outcomes, lower cost, and improved patients experience. Some of this data can be supplied by population health systems (see: Population Health Management: Systems and Success). The clinical diagnostic departments like pathology and radiology will also be key players in this data collection and documentation process.

PCP and Family Physician Wait Times increasing 50% in Many Markets

The majority of physicians in the U.S. are now salaried and working for large health systems (see: For the first time ever, less than half of physicians are independent). Also, wait times for an appointment with a family physician or primary care physician (PCP) are increasing (see: PCP wait times are 50% higher than 2014). This can be the source of great frustration for patients (see: Report: 20% of patients have changed doctors because of long wait times). These two facts may or may not be related. Here is an excerpt from the article on physician wait times:

The average patient waits 29.3 days to see a family medicine physician in large cities, according to a recent survey....This wait has increased 50 percent since 2014, according to the report....Of the 15 major metropolitan areas studied, average wait times for family medicine physicians exceed 14 days in 12 markets. Patients wait the longest to see a family medicine physician in Boston, clocking in 109 days on average. The shortest wait times are in Minneapolis, where patients wait an average of eight days to see a primary care physician, according to the report. Patient wait times have increased most for PCPs, though they are longest still for dermatologists. 

There are a number of possible reasons why appointment wait times are increasing for family physicians and PCPs nationally. For example, there may be fewer physicians functioning as PCPs (see: Can the dwindling numbers of primary care physicians explain decreased life expectancy?). PCPs may be spending an increased amount of time with each patient, attributable perhaps to the burden placed on them by the inefficiency of EHRs (see: 61% of Physicians Say EHR Systems Reduce Clinical Efficiency). Physician practices and appointments may not be managed optimally. Large health systems may be decreasing the number of PCPs in hospitals within a market because of the slim profit margins for their efforts (see: The "Proximity Advantage" Enjoyed by Retail, Walk-In Clinics Over Health Systems; Actions by Amazon May Be a Preview of Expansion into Primary Healthcare). PCPs don't perform procedures (e.g., surgical procedures, colonoscopies) that are more generously remunerated than office visits by payers.

Obviously, long wait time to schedule a visit with a PCP can be frustrating for patients. However, does this necessarily mean that health problems are going unattended? I am sure that this is often the case but, increasingly, healthcare options are available other than physician office visits. One example is CVS/MinuteClinics which are growing rapidly (1,100 MinuteClinics inside CVS Pharmacy and Target stores). Walmart Care Clinics, of which there are about 2,000, is another example (see: 7 statistics on urgent care centers, EDs & retail clinics). There are also about 7,100 urgent care clinics in the U.S. (see: 7 statistics on urgent care centers, EDs & retail clinics). To restate the obvious, the long wait times to see a family practitioner or PCP may be driving patients toward urgent care clinics and walk-in clinics for which no appointment is required.

Recruiting Patients for Clinical Trials Via a Smartphone App

Recruiting subjects for clinical trials has been a recurring challenge over the years including concerns that low-income and minorities are underrepresented in them (see: Low-Income, Uninsured Patients Often Excluded from Clinical Trials; Site-Less Clinical Trials as a Possible Means to Democratize Them). Because of this underrepresentation, the results of trials are often less valid. Here's an excerpt from an article on this topic (see: Barriers to Clinical Trial Recruitment and Possible Solutions: A Stakeholder Survey):

A staggering number of clinical trials fail to meet recruitment goals, which leads to delays, early trial termination, or inability to draw conclusions at trial completion due to loss of statistical power. A recent analysis found that 19% of registered trials that closed or terminated in 2011 either failed to meet accrual goals (85% of expected enrollment) or were terminated early due to insufficient accrual. More than 48,000 patients were involved in those 481 trials that were unable to meaningfully answer their primary research question.

A recent article refers to doc.ai, the developer of a smartphone app that uses AI to guide consumers through their "omics" data and help them optimize their health decisions. The company says that it is pursuing the goal of using AI to assist in the recruitment of subjects for clinical trials (see: Healthcare Artificial Intelligence Puts On A Human Face). Below is an excerpt from this article:

The doc.ai platform uses AI to help people enroll in clinical trials, determine the healthiest places they have lived and eventually see what their genetic data can tell them about health and longevity. The startup has a major deal with Anthem, Inc. the nation's second-largest health insurer, operating Blue Cross and Blue Shield plans in 14 states. Together they are working with Harvard to enable consumer participation in studies best suited to their personal profiles....The company has over 25,000 users who have uploaded personal information and provided access to health records.... If doc.ai continues to demonstrate the ability to quickly enroll clinical trials it could significantly disrupt the $62 billion drug development industry.

This all sounds interesting but I was a little concerned about the following statement on the doc.ai web site: Your data is safe and secure thanks to blockchain technology which anonymizes and decentralizes your data with state of the art encryption. I think that blockchain technology has been over-hyped thus far. I hope that this is not another example of this problem.

The Diagnosis and Treatment of Pre-Diseases: A Look at the Future

One of the interesting aspects of the deployment of new wearable medical devices is the use of sensors attached to patients that have the capability of monitoring disease progression in a manner never before possible. This idea was discussed in a recent article (see: IBM Research develops fingerprint sensor to monitor disease progression). Here is a brief excerpt from it:

IBM...announced that it has developed a small sensor that sits on a person’s fingernail to help monitor the effectiveness of drugs used to combat the symptoms of Parkinson’s and other diseases. Together with the custom software that analyzes the data, the sensor measures how the nail warps as the user grips something. Because virtually any activity involves gripping objects, that creates a lot of data for the software to analyze. Another way to get this data would be to attach a sensor to the skin and capture motion, as well as the health of muscles and nerves that way. 

This new article brought to mind my blog note of about ten years ago in which I discussed what I then referred to as the health continuum ranging from predisposition to disease => diagnosed predisease => acute or chronic disease (see: Predisposition to Disease and Pre-Disease on the Health Continuum). Pertaining to the predisposition to disease and diagnosed predisease, I made the following comment at that time:

[O]ne of the most interesting questions associated with the early disease model is whether it is appropriate to treat patients with pre-diseases. If they are deemed treatable and as we come to better understand the nature of pre-disease, a second question is what drugs to treat them with. As soon as we work out this question, we will then be faced with the new question of how and when to treat patients with a predisposition to disease, genetic or otherwise.

A friend has brought to my attention the idea that pharmaceutical industry and its researchers are showing great interest in the genetic predisposition to disease and also asymptomatic diseases in order to expand the size of the market for drugs. In the past, this has been referred to as disease mongering (see: Disease mongering and drug marketing; Disease Mongering (i.e., Medicalization) by Pharmaceutical Companies; Medical Device Mongering, a Variant of Disease Mongering).There is very little information available about treatment of pre-diseases with the notable exception of pre-diabetes (see: Prediabetes: when the pre-disease becomes the focus of treatment) where the treatment can often be behavioral relating to exercise and weight loss and not the use of drugs. At any rate, we can anticipate much more attention to pre-diseases and probably some controversy whether such patients can and should be treated with drugs.

Why "Virtual Assistants" Won't Remove EHR Pain Points Quickly

In a recent note, I commented on the emergence of "virtual scribes" (see: Virtual Scribe Vendors Remotely Generate EHR Notes and Coding). This is hospital service with physicians dictating the details of a patient office encounter. At a later time, a remote transcriptionist employed by a virtual scribe company enters the essential dictated data into the hospital EHR. These remote transcriptionists have access to the hospital EHR for this data entry. This is in contrast with the original and continuing idea of EHR scribes who are physically present in the examining room with the doctor and patient and perform all EHR keyboard entries.

However, It should not some as a surprise that the term "virtual assistant" is now taking on a new meaning and can refer to a software "assistant" rather than to a person. This new definition was explained in a longish recent article on this topic (see: Can Virtual Assistants Eliminate EHR Usability Pain Points?). Here are two quotes from it:

But dictation software is more or less a one-way street. The challenge for AI developers is to create intelligent systems with bi-directional capabilities: [the development of computerized] virtual assistants that can more or less independently perform background information-gathering work and synthesize those results into a meaningful conversation with providers.

[and]

Virtual assistants could be the answer that fed-up providers are looking for. Ideally, these tools will be able to dig through EHR data to present important nuggets of information, place phone calls and prescription orders, take notes, and help users navigate the EHR system itself. Several well-known EHR vendors, including athenahealth, Epic, and eClinicalWorks, are in the process of launching integrated virtual assistants which will be commercially available to providers in the near future. For now, however, virtual assistants are far from commonplace. The tools are predominately being used by small groups of clinicians participating in limited pilot programs as health systems test the opportunities and limitations of the strategy. 

There are plenty of challenges and advantages to virtual assistants, said leaders from Yale New Haven Health, Beth Israel Deaconess Medical Center in Boston, and Vanderbilt University Medical Center in Nashville. All three health systems are exploring whether virtual helpers can improve the provider experience and reduce physicians’ complaints about the drawbacks of EHR use. The need to address the problem of user burnout is more important than ever, leaders from the health systems stressed, but creating a tool accurate and useful enough to convince providers of its promises requires significant investment, creativity, and commitment.

Do any of the readers of this blog think that a practical and appropriate solution to our EHR complexity problem is to develop a software virtual assistant who will understand EHR idiosyncrasies and make them more user friendly? Because our EHRs are intrinsically complicated with difficult UI's, these proposed virtual assistants will also be extremely complicated and will take years to develop. 

Duplicate Patient Records as a Major and Costly EHR and EMPI Problem

I have posted a number of notes about the use of IT to improve efficiency and effectiveness in healthcare. A gnarly but persistent problem has been duplicate patent records and substantial IT resources are required to correct the problem. Below is an excerpt from an article on this topic (see: Artificial Intelligence and ethics will drive a patient matching revolution in 2019):

Existing patient matching technologies are failing, as evidenced by skyrocketing rates of duplicate records in electronic health record (EHR) and enterprise master patient index (EMPI) systems. In fact, duplicate record rates have nearly doubled in the past decade, from an average of 10 percent in 2008 to 18 percent today....These patient matching technologies are failing at the worst possible time—as more and more of a health system’s strategic initiatives fundamentally rely on accurate and complete patient data. The dire consequences of these failures include a third of claims being denied costing $1.5 million annually; massive operational inefficiencies costing $200,000 annually; lowered return on investment (ROI) of EHR deployments; inhibited value-based care initiatives; and drastic consequences to patient safety, care quality, and patient satisfaction....

Yet nowhere can AI have a more immediate and accessible impact than in patient matching. Currently, health systems have teams of data stewards and health information management (HIM) professionals dedicated to finding, reviewing, researching, and resolving records that their EHR or EMPI has flagged as “potential duplicates.” Essentially, these employees are spending hours each day looking at, for example, a record for Jane Jones and another for Jane Smith, trying to decide if both Janes are actually the same person and if her records should be merged. Referential matching technology can automate 50-to-75 percent of this manual effort by being an intelligent and data-driven technology. It can automatically find and resolve duplicate records that EHRs and EMPIs have missed, enabling data stewards and HIM staff to focus on higher-value projects—while simultaneously lowering the operational costs and inefficiencies plaguing health systems by automating manual work.

Here's the way that a company called Verato has tried to solve the patient matching problem (see: Referential Matching: The Silver Bullet for Patient Identity and Patient Matching):

Verato has pioneered a powerful new patient matching technology called “Referential Matching.” Rather than directly comparing the demographic data from two patient records to see if they match, Verato instead matches that demographic data to its comprehensive and continuously-updated reference database of identities. This proprietary database contains over 300 million identities spanning the entire U.S. population, and each identity contains a complete profile of demographic data spanning a 30-year history.

I am sure that there will be many new solutions to this patient matching problem utilizing AI and ever more sophisticated algorithms that do not require a large, remote, proprietary patient database. Nevertheless, attention is now being paid to this major medical record problem that endangers patient lives -- that's the right direction. I will continue to monitor this field to see what other solutions emerge.

Proposed Classification for Health Information Systems: Provider and Individual

Recent events and some of my recent blog notes have caused me to question whether we need a new, high-level classification that encompasses all health information systems. I am going to give this idea a try. The goal of such a large scale systematic plan is to understand the functionality of current and future health information systems. Details are listed below:

1. Provider health systems (PHS's): The common feature of PHS's is that they are designed as tools for use by healthcare providers. The largest and most complex of these systems are EHR's which are deployed in hospitals and health systems. Also included in this category are office health systems (OHS's) designed to support the office functions needed by physicians and other providers like nurse practitioners. PHS's provide all the necessary IT functionality in health systems ranging from hospital inpatient units to the PCP's managing ambulatory patients.

Subcategories of PHS's include departmental systems deployed in hospitals such as LIS's, RIS's, and PAC's. In recent blog notes, I proposed that standalone LIS's, as opposed to LIS's that are part of the software suites of EHR vendors, could perhaps evolve into LIS-A's (see: Predicting the Future Functions of the LIS-Analytic (LIS-A); Continuing Discussion about the LIS of the Future; Analytics as a Key Feature?). Such systems would change from classic, best-of-breed LIS's to systems that support descriptive, predictive, and diagnostic algorithms. By developing such LIS-A's, LIS companies may cede ground to the LIS's provided by large EHR vendors as part of their enterprise-wide offerings. 

2. Individual (or personal) health systems (IHS's): These are systems designed primarily for consumers. I blogged recently about the Rally system of UnitedHealth Group that initially provided coaching and other health services (see: UnitedHealth Group to Launch Its Own Variant of an EHR in 2019). It's similar to Apple Health which is an app that runs on iPhones and the Apple Watch. Analytics will be a major thrust in the consumer healthcare market and delivered via IHS's (see: The Future of the LIS: Reflections about Consumers Ordering Their Own Lab Tests) particularly when PHS/EHR clinical data can be downloaded by consumers from their EHR accounts. Apple is already providing such a feature for iPhones in collaboration with selected health systems (see: Apple Has Plans to Copy EHR Records to iPhones and Apple Watches).

3. Hybrid health systems (HHS's): These would be systems such as the one being developed by UnitedHealth Group mentioned above that span physican office health systems (OHS's) and individual health systems. The advantage of such systems is that they fulfill the desire of patients to share health measurements obtained in their homes such as EKG tracings recorded by their smart watches or home lab testing performed by devices that plug into their iPhones. 

As to the future of health information systems, most of the development (and consumer market) is going to be related to IHS's and perhaps relatively simple hybrid systems. This is where consumers will be operating as well as health wearables and home testing devices. EHR's are expensive and accessed only via complex user interfaces. Hospitals will continue to use them because they have no substitute products. Consumers will never use them directly because of their complexity and because of the security concerns of the health systems that own and operate them.

UnitedHealth Group to Launch Its Own Variant of an EHR in 2019

I have commented in previous notes about the increasing role of health insurance companies like UnitedHealth Group as healthcare providers (see, for example: Major Trends for the Year: Payers Use IT to Provide Total Care Management; OptumHealth, a Division of UnitedHealth, to Offer Virtual Patient Visits Nationwide). This trend, along with the growth of walk-in clinics in "big box" stores, will provide competition for health systems in the area of primary care. Now comes news that the UnitedHealth Group is launching its own e-health record in 2019 (see: UnitedHealth Group to Launch Electronic Health Records Platform in 2019). Below are the details:

Before the end of 2019, UnitedHealth Group plans to introduce an electronic health records (EHR) system that it developed internally....UnitedHealth Group...CEO David Wichmann announced plans to roll out a “fully individualized, fully portable” EHR platform in 2019 by leveraging Rally, their existing mobile wellness platform....With 20 million registered [health insurance]  users already using Rally, this could encourage adoption and use of the new EHR among UnitedHealth Group’s 50 million fully benefited members....Exact details of the platform’s capabilities are still unclear. However, additional information...indicates that the new platform might function more like Apple’s approach to personal health records (PHRs) and less like a traditional EHR....

Coverage from Forbes [see: UnitedHealth Group: 50M To Access New Personal Health Record In 2019] indicates the UnitedHealth IHR will be available to both patients and healthcare providers, with UnitedHealth Group predicting usage by one million medical care providers by the end of 2019. “A traditional electronic medical record focuses largely on streamlining internal business processes for facilities and medical groups,” Steve Nelson, CEO of UnitedHealthcare (UHC),.... “But the IHR [individual health record] connects numerous EMRs, creating a unified and secure source of truth for both consumers and care providers, and unlocking the value of data that is currently trapped in today’s fragmented healthcare system....This would allow UnitedHealth to utilize the strong points of Optum—a UnitedHealth Group venture focused on providing health services and innovations—to leverage analytics capabilities aimed at both encouraging patients to take an active role in managing their health and finding the best providers in their area.

First of all, its important to understand that OptumHealth, a division of the UnitedHealth Group, is one of the largest employer of physicians in the country (see: OptumHealth, One of the Largest Employer of MDs, Pursues Telemedicine). As such, the company perhaps should develop an office EHR for the use of its MD employees rather than depending on a commercial product. UnitedHealth thus seems to be in the process of deploying an upgraded version of Rally for use in physician offices and simultaneously offering it to its insurance clients where it would function as an IHR (individual or personal health record). This is a strategy similar to that being pursued by Apple for its iPhone Health app absent the office EHR component (see: Apple Has Plans to Copy EHR Records to iPhones and Apple Watches). 

Rally has previously served as an IHR-like product for UnitedHealth insurance clients. One of the previous goals for Rally was to provide wellness coaching. By moving to a more robust platform including heath data, the Rally successor could then provide a higher level of surveillance of health risks. For example, if the consumer has a history of congestive heart failure, the IHR could be designed to accept data from a smart watch monitoring heart function or a home blood pressure device. Using algorithms from Optum, the IHR could also function proactively in terms of its recommendations to healthcare consumers. This may be one of the goals of the new Rally release: to provide an IHR that contains health data and also utilizes algorithms provided by Optum to make recommendations as part of its health coaching feature. 

Cost of Hospital Care in Michigan; Numbers Not Necessary Relevant for Consumers

Hospitals are now being required to reveal their master price lists but these data may not be of much help to consumers (see: Hospitals must post prices online, but they may be more confusing than helpful). That's because the price lists displayed recently on the basis of a federal requirement, called chargemasters, are massive compendiums of the prices set by each hospital for every service or drug that a patient might encounter. However, I did find some of the prices published for a set of hospitals in Michigan by diagnosis were interesting in a general way to assess the cost of healthcare (see: Hospital price lists revealed: The cost of care at 9 Michigan medical centers). Below is an excerpt from this latter article:

....[W]hile a new federal mandate that took effect Jan. 1 requires hospitals to reveal their once-secret master price lists of every service or procedure they provide,...[but an expert of the topic] warned that patients should view the prices only as "context-setting" starting points. "The hospital's charges are not very relevant to the patient, because the patient bill can be significantly discounted, either by the health plan, which is what health plans have been doing for 50 years, or even in some situations where patients have to self-pay, they can negotiate by themselves"....Below, you'll find...[examples] of base and average prices for common hospital procedures provided by hospitals all over Michigan....:

Normal newborn birth:

• Metro Health, Grand Rapids: $1,835
• McLaren Bay Region, Bay City: $2,849
• Mercy Health Saint Mary's, Grand Rapids: $3,339
• Spectrum Health Butterworth, Grand Rapids: $4,088....

Concussions:

• McLaren Bay Region, Bay City: $10,646
• Covenant HealthCare, Saginaw: $13,473
• McLaren Flint: $15,840
• Spectrum Health Butterworth, Grand Rapids: $19,923....

Pneumonia:

• Spectrum Health Butterworth, Grand Rapids: $10,299
• Metro Health, Grand Rapids: $10,411
• Mercy Health Saint Mary's, Grand Rapids: $11,780
• Michigan Medicine, Ann Arbor: $12,796....

Femur fracture:

• McLaren Bay Region, Bay City: $14,206
• Spectrum Health Butterworth, Grand Rapids: $15,545
• Metro Health, Grand Rapids: $15,737
• Bronson Methodist Hospital, Kalamazoo: $16,539....

Just a reminder here for the uninsured. Many hospitals like the University of Michigan (Michigan Medicine) have financial assistance programs. Here's a quote from this institution about their program (see: Financial Assistance): A patient may receive 100% of their services free if their income is below 2½ times the Federal Poverty Guidelines and meets other financial criteria.

23andMe Adds Weight Loss Coaching to Its DNA Testing Service

I have generally been supportive of 23andMe but their latest "wellness" oriented initiative has me wondering. Here's a report about it (see: 23andMe Will Add Weight-Loss Advice to Its DNA-Testing Services) and below is an excerpt from the article:

Consumer DNA-testing giant 23andMe...plans to add new wellness offerings it hopes will help its customers shed a few pounds, but some genetics experts say the jury is still out on the science behind the products....[The company] announced a partnership with Lark Health, an artificial-intelligence coaching service that delivers personalized advice for weight loss and diabetes prevention via an app. Lark will allow customers to incorporate weight-related genetic data from 23andMe into its service....The move will put 23andMe in a crowded -- and oft-criticized -- marketplace of companies that use DNA analysis to give personalized advice on wellness or family history....In Lark’s wellness and diabetes-prevention programs, AI coaches help people track things like meals, exercise and sleep and serve up advice to help meet health goals. Users can message their AI coach to help them decide whether a burger was a good choice for dinner....If their 23andMe genetic weight report suggested limiting red meat, the coach might recommend laying off the burgers....[Lark's] diabetes-prevention program is recognized by the Centers for Disease Control and peer-reviewed research has suggested the AI coach is at least as effective as a human one.....For those that opt-in to sharing their genetic data, Lark’s apps will incorporate data from eight different 23andMe reports, including a weight profile of people with similar genetics, whether they have a heightened sense for bitter-tasting foods, or an associated tendency to sleep deeply.

Although this is the first time I have encountered the phrase AI health coaching, the idea does hold some interest for me. For a start, I believe that there is an important connection between behavioral/lifestyle issues and many chronic diseases including obesity, diabetes, and perhaps even hypertension. I have blogged extensively about the relationship between lifestyle issues and chronic diseases (see, for example: Seeking Solutions to the Chronic Disease Epidemic; Treatment of Patients with Chronic Diseases: Important for the Future of Telemedicine; Relevance of Lifestyle Analytics for Healthcare Organizations). I believe that one of the key ways to ameliorate some chronic diseases like obesity and diabetes is behavioral support via telemedicine. Programs like Lark Health are also promising.

I also think that the proposed connection between the 23andMe DNA analysis and the Lark Health wellness programs like weight reduction is bit of a stretch. Here's the sentence from the article that caught me attention: For those that opt-in to sharing their genetic data, Lark’s apps will incorporate data from eight different 23andMe reports, including a weight profile of people with similar genetics. In time, there may definitely be a link between obesity and one's DNA analysis but I don't think that we are at that point yet.