Guidelines for Guidelines

"Guidelines" (like these) drive health leaders, policymakers, politicians and caregivers crazy. They're supposed to describe "evidence-based" "best practices" for diagnosis, treatment and overall management for hundreds of medical problems. Yet, it's been known for years they often go ignored by many practicing physicians who are unaware of them, would rather rely on their individual independent judgment and experience, doubt their validity or would rather continue with what they've done for years.

What's the problem? Is it the guidelines or is it the docs?

Johns Hopkins' Peter Pronovost, writing in the Dec. 5 JAMA wonders if both can be helped with some common sense guidelines for guidelines:

1. Any guideline should prioritize its recommendations (based on patient benefit) and explicitly link them to "time and space" of a specific point in the course of an episode of care  The author points out that it's not uncommon for guidelines to be more than a hundred pages and simply list all the recommendations.

2. Guidelines should identify the barriers to their adoption and recommend strategies for their successful implementation.  Naturally, the developers of these guidelines would need to climb down from their ivory towers and actually think (and maybe perform research) on getting the guideline into the front lines of real-world health care.

3. Guidelines need to contemplate co-existing conditions and stop focusing on single diseases or risks.  In a hospital, it's not unusual for safety checklists to deal with single issues, resulting in dozens of lists.

4. Automate automate automate and use "systems" of care instead of relying on the memory and best intentions of human beings.  Robotics can do a lot of routine monitoring, patient work flows can incorporate safety and docs and nurses should be freed to be..... docs and nurses!

5. Develop "practice strategies" that integrate multi-disciplinary teaming and pools expertise in the related sciences of epidemiology, implementation and engineering.

The DMCB agrees with the ideas and wonders if these recommendations can't also be used by Accountable Care Organizations, health care systems and population-based service providers as they seek to disseminate best practices for the care. It's one thing to "post" or "link" a standard guideline in an intranet or an electronic health record "prompt," it's another to make it useful at the point of care.

Follow-Up on Electronic Health Record Portals: We're Asking the Wrong Question (and the DMCB is guilty)

Researchers pondering the EHR portal

Thanks to Twitter, the @DisMgtCareBlog had a highly rewarding tweetologue with tweetociates @Paulflevy (with an insightful bit of bloggery here), @granitehead and @subatomicdoc about a recent DMCB post on the topic of electronic health record (EHR) patient portals. As readers will recall, yet another notion of the Lilliputian Order of Unquestioning EHR Believers failed to pass scientific muster when The Annals published a negative review on patient portals. Tweeples took note with a series of tweets that simultaneously advanced the DMCB's social media chops and the antipathy of the how-does-this-make-money? DMCB spouse.

To tell the truth, however, the skeptical DMCB took unfair advantage of this latest EHR kerfuffle. It confesses that it couldn't resist this latest addition to the target-rich environment of HIT disappointments in quality, cost and governmental overreach.

So, upon further reflection, just because almost 15 years of high quality research failed to establish any lasting value doesn't mean portals should go the way of the Dodo, low-cost medical malpractice insurance or Mr. Obama's credibility.

In other words, the DMCB does think that portals have a role to play in the health care reform landscape, and it said so in front of a huge audience at the recent Star Ratings Conference in Fort Lauderdale.

Portals, thinks the DMCB, have little value as stand-alone interventions. Just dropping it into a clinic's patient population is unlikely to significantly increase communication and shift behaviors enough to produce enough of a "signal" that cost or quality outcomes are better compared to usual care.

But when EHR portals are part of a multi-channel outreach strategy that includes (but is not limited to) mailings, interactive voice response-based calls, secure messaging, emails, social media, "anniversary" time-for-your-appointment cards, live telephony as well as home visits that are all backed by predictive modeling (who is at greatest risk) that informs "impactability" (how they're at greatest risk) that's all tethered to care management that is also closely aligned with marketing and builds brand, then portals mostly likely do add value.

Unfortunately, traditional health services research cannot assesses the multiple simultaneous interventions described above.  As Dr. Donald Berwick presciently noted in this classic JAMA article:

Experimentalists have pursued too single-mindedly the question of whether a [social] program works at the expense of knowing why it works. Thus, although [traditional research] seeks generalizable knowledge...it relies on removing most of the local details about “how” something works and about the “what” of contexts. It therefore reveals little about mechanisms or about factors that affect generalizability. Studying a few covariates, or using stratified designs, or probing for interactions can mitigate this loss, but these are inadequate tools for studying complex, unstable, nonlinear social change.

As the DMCB has noted before, absence of any proof is not the same as proof of absence.  The studies that the DMCB ultimately quoted were based on traditional research, which is simply not up to the task of the non-linear intervention of patient-doc-team communications.

Don Berwick recommends a more insightful approach:

Health care researchers who believe that their main role is to ride the brakes on change—to weigh evidence with impoverished tools, ill-fit for use—are not being as helpful as they need to be. “Where is the randomized trial?” is, for many purposes, the right question, but for many others it is the wrong question, a myopic one. A better one is broader: “What is everyone learning?” Asking the question that way will help clinicians and researchers see further in navigating toward improvement.

When it comes to EHR portals, it's time we ask just what are we learning.

Health Care Cost Insights and Capitation for the Patient Centered Medical Home (PCMH)

The Population Health Blog finally caught up with the Oct 22/29 "Price, Cost and Competition" issue of JAMA. 

One of the more interesting articles was a Viewpoint editorial on the Patient Centered Medical Home (PCMH). After tut-tuting fee-for-service payment as antithetical to meaningful payment reform, the author admits what the PHB has been saying all along: a global payment that covers all the medical, coordinating as well as non-physician services of the PCMH is tantamount to old fashioned "capitation." As we learned in the 1990s, capitation's unintended consequences are a) signing up too many patients, b) limiting access to primary care and c) over-referring to specialists.  To counter that, the editorial's author suggests the PCMH movement seeks "accountability." 

We'll see about that.

In the meantime, some other interesting articles:

Are "for-profit" hospitals evil?  Not necessarily.....

237 hospitals that converted from not-for-profit to for-profit anytime between 2003 and 2010 were compared to 631 hospitals that had not converted.  Converting hospitals improved their financial margins (practically all were in the red and subsequently became break-even) vs. the comparison group, and did so without increased utilization, restricting access to care, higher death rates or declines in quality for their Medicare patients. Their path to profitability may have been lined by renegotiated commercial insurance contracts, cutting costs or moving non-performing assets off the balance sheet.

Can physician groups become monopolistic? In a word, yes.

Commercial insurance preferred provider organization (PPO) charges for ten types of physician office visits in ten different specialties across 50 states were correlated with a measure of local market dominance dubbed the "Hirschman-Herfindahl Index" (more on that here).  As the HHI index increased, payments also increased, suggesting that as much as additional $3 to $12 in fees for the same services were the result of monopolistic contracting.

Monopolies aside, if docs are in charge vs. the hospitals, can they reduce health care costs?  Also yes.

This study compared average "per-patient expenditures" of physician-owned versus hospital-owned integrated medical groups and independent practice associations in California from 2009 to 2015. Among the 158 groups, 118 were owned by docs; their expenditures were over a thousand dollars less compared to hospital owned groups.  Larger physician groups had higher expenditures than the smaller ones.  More on that in a future post.

Does price transparency help patients chose to spend less?

Over 500,000 insurance plan enrollees had special on-line access to prices for medical services prior to using them.  There were over 250,000 households and of these, approximately 7500 accessed the information. Compared to households that didn't check the information, the price-shoppers seemed to choose cheaper labs (a few dollars per test) and imaging options (about a hundred dollars per test).  In looking at the data, the DMCB suspects some may have also deferred testing by choosing to use them less frequently or not at all.

More on Health Apps: Opportunities, Risks and the Implications for Population Health Management

It's called "mHealth" but others may call it "health apps." The FDA calls it a target rich regulatory opportunity. Others may call it hype.

The Disease Management Care Blog calls it inevitable.

Writing in JAMA, Drs. Steinhubl, Muse and Topol of Scripps agree and say that the future is bright for mHealth. Its adoption is being driven by the threefold convergence of:

1) the search for solutions that address otherwise unaffordable levels of healthcare spending,

2) the availability of broadband wireless connectivity, and

3) consumer demand for individualized care.

The DMCB suspects any one of the DMCB's 5000 regular readers could have written this article. Like Steinhubl et al, they already know that patients want self-diagnosis and condition monitoring. Health consumers want greater efficiencies and enhanced patient-physician collaboration.

Even tech-skeptics have to admit that it's possible that mHealth could lead to a utilization trifecta of fewer office visits, avoided emergency room visits and decreased hospitalizations. Imagine the handheld that can accurately catalog signs and symptoms that help the user discern between a simple self-limited cold vs. a more serious case of pneumonia, or benign skipped heart beats vs. a more worrisome arrythmia.

Handheld apps for chronic conditions are more available than realized. They are on the cusp of going mainstream with assisting hypertensives, diabetics and asthmatics monitor and act on their blood pressure, insulin dosing and inhalants.

If they work right, providers could review summary data and offer guidance via emails and texts in lieu of adding a patient on to the schedule at 5 PM. If done right, the background algorithms could liberate physicians to pay greater attention to the important stuff that requires their complex cognitive or procedural skills.

The authors point out that that doesn't mean it's going to be easy. Medicine is complex and getting paid for it is more so. There's also worry - warranted or not - about the decline of face-to-face doctor-patient relationship. mHealth can lead to overwhelming data gluts characterized by a lot of numbers with little actionable insight. Finally, there's the danger that an app can offer ineffective, inaccurate or dangerous guidance that leads to patient harm.

Bravo to the editors of JAMA for recognizing the importance of the topic and committing precious space to this manuscript.

That being said, however, this article fails to give a full accounting of all the opportunities as well as risks for "mHealth."

First off, as this Kaiser Health News article demonstrates, there are two additional opportunity dimensions that draw on the population health management business model:

1) Apps are not just for diagnosis and monitoring, but also for wellness, and

2) They're being principally sponsored by commercial health insurers who not only readily embrace innovation, but probably consider apps a "sticky" way to maintain customer loyalty. That is doubly true for engaged enrollees who ultimately represent a better insurance risk.  In fact, the DMCB suspects that value proposition is so compelling that insurers are willing to use apps as a "loss leader."

Oh, and while mHealth can be built, it's far more likely it's being bought. As in population health management vendors.

Risks?  You bet.....

1) The fit of mHealth with the electronic health record (EHR) remains an open question.  The DMCB is no coding geek, but it's safe to say that it's not automatic that two independently contrived technologies can automatically "speak" to each other or that the data from an app can by downloaded, summarized and coherently presented to a user at the point of care.

2)  As noted in this article on telemonitoring, it's also not necessarily true that mHealth can be equated with stand-alone technology. Depending on the condition and the need, mHealth will have to be often tethered to human support services.

3) As even casual observers are aware, allegations of "malpractice" are not unusual in health care.  Rather than comment on its friends who make a living off of contingency fees, the DMCB will only point out that mHealth may offer a target-rich rich environment for personal injury attorneys intent on using the legal theory of joint and several liability to maximum effect.  That threat may slow adoption of mHealth.

Image from Wikipedia

Taking Patient Preferences Into Account When It Comes to Pursuing and Measuring Quality

Here's a thought: ask them what they want

One of the intellectual underpinnings of population health management is that the biopsychosocial dimensions of care is a huge determinant of real-world outcomes. As any doctor who takes care of flesh-and-blood patients knows, national treatment guidelines like these typically fall short of taking the human dimension into account. While there are plenty of good and bad reasons why docs are failing to take advantage of guidelines, one is their sterile one-size-fits-all approach that often fails to account for physician awareness of their patients' risk tolerances and economic circumstances. What's more, many widely promoted treatments only offer a small absolute benefit.

Fortunately, this disconnect is bubbling up into the mainstream scientific literature. The latest example is this Viewpoint that appears in the October 28 issue of JAMA. The authors point out that the perspectives of expert physicians who develop guidelines are typically different than the general public, caregivers or persons with a disease. For example, while the NCQA promotes an A1c threshold as a important measure of diabetes care quality, a compelling survey of patients with diabetes suggests that that emphasis may be displaced.

Where to from here? The JAMA authors offer three commonsense recommendations. Future guidelines should:

1. be developed with the input of patients and frontline clinicians.

2. encompass the full range of patient experiences, not outcomes. This means accounting for the  burden, impact on quality of life and role function dimensions of any treatment recommendations.

3. avoid strong recommendations when the best course of action depends on the patients' context, goals, values and preferences.. Lacking a clearly advantageous outcome with minimal side effects, guidelines should offer a conditional suggestions.

The DMCB modestly offers up three additional suggestions for the population health community and other stakeholders:

1) Absent a satisfactory guideline process from the usual national organizations, it would not be a bad idea to take this bull by the horns and develop a parallel set of guidelines that meet the principles outlined in this JAMA article.

2) Organizations like the NCQA and NQF need to be more flexible in promoting evidence-based guideline-based metrics by moving away from a reliance on their monodimensional clinical measures and toward more nuanced measures of meeting patient preferences.

3) Finally, while national variation in health care delivery is a huge challenge as we continue to build a coherent health system, it may be time to reconsider the notion that all variation is bad. Human beings are variation, and the likelihood of imposing local "best practices" across the U.S. will not be in the best interest of patients with different views of what it best for them.

Image from Wikipedia

The Remarkable Consensus Over the Next Steps for Health Reform, Including the Role of Population Health Management

Let's fix it!

While noisy media leprechauns dispense blame and declare winners in the government shutdown imbroglio, the Disease Management Care Blog remains focused on the next steps for meaningful health reform. So are JAMA authors Jack Lewin, Lawrence Atkins and Larry McNeely who, other than one lapse in their editorial, get it mostly right.

Their important insight is that the Bipartisan Policy Center, Brookings Institution, Commonwealth Fund, Kaiser Family Foundation, the National Coalition on Health Care, Partnership for Sustainable Health Care and Urban Institute all have a remarkable degree of overlap in their recommendations for the next phases of health reform. 

Most of these expert organizations agree on the merits of value-based payment as well as insurance reform (pay for quality), information technology, competition, tort reform, evidence-based benefit design (paying when there's evidence that it works), workforce changes (greater efficiency), reforming Medicare, changing tax policy (the exemption for health insurance) and instituting regional or local caps (stick to a budget or there's consequences).

The DMCB wholeheartedly agrees and hopes that the bipartisan consensus evident among these think-tank institutions leads Congress (if not this one, the next) and the President (if not this one....) to use these ingredients to build on the successes and correct the many deficiencies of the Affordable Care Act.

And the lapse? 

Jack Lewin et al were missing one thing. The DMCB looked in each of these organizations' web sites and found that there was also considerable support for population health management.

To wit:

The Bipartisan Policy Center - while the emphasis of this report is on health information technology, the real dividends are pretty clear when it mentions "population health" 14 times:

This plan should address the development and adoption of policies and standards needed for the delivery of care, the empowerment of individuals, and improvements in population health based on national health and health care priorities.

The Commonwealth Fund:

 Effective population health management requires fundamental change in care delivery that must be supported by changes in payment.

National Coalition

Real reform means engaging consumers in their own health and health care choices. In both Medicare and too many private plans today, benefit design neither supports self-management of chronic disease nor distinguishes between care that is effective and care that is not.

Partnership for Sustainable Health Care - see page 22:

Federal nurse education funding should be refocused to equip registered nurses to assume the roles of case manager and population health coordinator.

The Urban Institute - see page 17 on the topic of Medicaid reform:

States can start in select geographic areas or specific population groups (adults and children or specific chronic conditions), and then incrementally expand them after learning from experience and making program improvements and adjustments. Broader efforts typically mean additional stakeholders, increased collaboration and communication.

Is One DIet Program Better Than Another for Weight Loss?

As a doctor, the Population Health Blog was often asked by overnourished patients to help find a "best" diet.  Its advice to simply eat less and skip desert, however, was insufficient to overcome the commercial programs' allure of word-of-mouth, dubious advertising and fanciful on-line marketing . As a result, many desperate PHB patients fell into closed loops of pseudoscience, anecdotal testimonials and expertly crafted statements "not evaluated by the FDA."

As a population-health skeptic, the outcomes-focused PHB was never convinced that one commercial diet plan was "better" than any other.  Not only are excess calories very efficiently turned into corpulence by a very efficient human metabolism, it didn't make sense that that persons could eat their way to weight loss with more [insert one of the following: protein, fat, fiber, pre-packaged meals or vitamins].  Last but not least, if all these commercial weight loss outfits spent a tenth of their marketing budget on real science, the PHB may have had the evidence it needed to make a recommendation.

Well, a meta-analysis of "Named" (you'd recognize the brands) diet program outcomes has been published in JAMA and the results are decidedly unimpressive.  The good news is that all of the household-name programs result in modest weight loss compared to no diet.  The bad news is that the loss of two to six pounds for each program was no better or worse compared to the others.

The PHB's take?  It's up to the consumer to weigh their personal preferences for one type of diet plan vs. another.  In addition, out-of-pocket costs may also play a role in helping sustain the dieter's motivation in getting their money' worth. 

Beyond those two considerations, however, it's just a matter of eating less calories, not more of the latest nutritional fad.

Of Risk Stratification, Health System Variation and "Stupid" Decision-Making

A fly in the ointment

Years ago, a middle-aged Population Health Blog patient came in for a routine follow-up appointment.  Since his last visit, he had developed iron deficiency anemia. Since slow blood loss can be a sign of an early and curable cancer in the gastrointestinal tract, the PHB recommended a series of unpleasant tests. After a rather routine explanation of the time, expense and inconvenience of those tests, the patient surprised the PHB with a one-word answer: "No."

He went on to live for decades.

Which brings the PHB to this JAMA article on individually-tailored screening for another type of cancer. While even screening for prostate cancer is controversial, it's possible to stratify a man's risk of the condition with some questions, examination data and test results.  That risk can be portrayed in lay terms (there is a "42-in-100 chance" that cancer is present, but doing a biopsy has a "4-in-100 chance of causing an infection..."). 

The points of the well-written article is that 1) risk-stratification can be used to identify persons at high vs. low risk, 2) the decisions to screen, perform additional testing and embark on treatment can be, based on that risk, "tailored" to maximize a good outcome and 3) patients can use their level of risk to ultimately decide how they want testing and treatment to achieve the outcome they want.

Bravo, says the PHB.  While we're on the cusp of understanding whether a more sophisticated approach to screening ultimately leads to better outcomes than the standard all-or-none guideline (USPSTF "recommends against prostate-specific antigen (PSA)-based screening for prostate cancer"), there is enough face-validity to believe that patients will ultimately benefit.

But there is a fly in the ointment and a monkey in this wrench.

The fly? Variation will not go away. While health system bureaucrats everywhere would prefer that 0% of men undergo prostate screening, that 100% women over 50 get mammograms, and that 0% of us have a body mass index in excess of 25, individuals - after looking as the risk-benefit here, here and here, may choose otherwise.  We don't know what the "right" screening rates are.  In fact, we may not be asking the right questions.

The monkey?  Some "bad" decisions will occur. Once persons truly understand the benefits, risks and alternatives (including not dying prematurely of a preventable illness and side-effect risks that are less than driving in a car), they are allowed to make "stupid" decisions.  Physicians and bureaucrats may not like it when anemic patients, like the one described above, refuse no-brainer recommendations, but in a free country that's the price we pay. Our challenge is to make sure that our patients have all the information they need (which is apparently not the case here) to make a truly informed decision.

Image from Wikipedia

Care Management: What a Bargain

They did it again!

Sound familiar?

Patients' intake into the program was initiated with a face-to face meeting with a nurse care manager.  After a physician-approved care plan was in place, the patients were telephoned and engaged in the protocol.  The patients could then use a voice-activated system or a website to report disease status.  Outbound nurse calls were prompted if the patients requested it, reported a problem, didn't have adequate disease control, if the medications were not being taken as prescribed or if there were side effects.  After 12 months, patients in the care management program, compared to a control group, had clinically and statistically significant improvements in the control of their condition .

To the Population Health Blog, this narrative has been repeated dozens of times involving numerous chronic health conditions.  In this latest example, Dr. Kroeknke and colleagues randomly allocated 250 patients with three months or more of chronic musculoskeletal pain to either a) state-of-the-art pain care or b) state-of-the-art pain care plus nurse led care management. 

Twelve months later (and after only one drop-out), patients in the first group rated their pain as having dropped from a baseline of 5.1 to 4.6 out of ten (zero is no pain, 10 is awful), while the second care management group rated their pain as having dropped from 5.3 to 3.6.  Total time spent by the care manager averaged 3-4 hours per patient.

While patients in the care management group were taking more medications, there was no difference between the two groups in narcotic use.  There was also no difference in health care utilization.

The PHB's take:

While the authors credited the care plans that triggered increases in medications that were tailored to patient preferences, the PHB wonders if a greater sense of control combined with the perceived support of a sympathetic listener also contributed to the greater improvement in pain.

Once again, there wasn't hard "savings" or a "return on investment."  However, the expense of only three to four hours of nurse care manager time to achieve a one-point improvement on a 0-10 scale of pain not only seems like a wise investment, it's a comparative bargain.

Professional Physician Organizations: A Continuing Necessary Ingredient for Ongoing Health Reform

This JAMA article on "Professional Organizations' Role in Supporting Physicians to Improve Value in Health Care" reminds readers that "organized medicine" continues to have an important role in national health reform.  The Population Health Blog agrees and adds that these doctor professional organizations have not only been underestimated recently, but will continue to be a force to be reckoned with - both a national and state level.

The article points out that groups like the American Medical Association (AMA) along with the various sister specialty physician organizations, along with health systems, practice associations and various non-governmental entities, are critical to the success of the Affordable Care Act.  These doc groups been long-time advocates for health reform, are still trusted by a significant number of providers, collectively represent a majority of docs and bring insights to a complicated health system.

And what are they doing to help with reform?  According to the authors, they've been serving as "conveners," helping to marshal resources, are creating standards and helping regulators.  While the JAMA article naturally mentions a number of national initiatives (such as Choosing Wisely), the PHB points out the same kind of important activity is occurring at the state level.  A good example can be found here.

Before some PHB readers tut-tut the faux importance of the AMA and its many national and local affiliates by having you believe that docs have transitioned their loyalty from their profession to their employers, the PHB would point to three sentinel events that say otherwise:

1. Even the White House believed that organized medicine was important enough that it sought to circumvent the influence of the AMA by fostering its own professional doctor group called "Doctors for America."  While it hasn't worked so well, imitation is the sincerest form of flattery.

2. The Patient Centered Primary Care Collaborative's Board of Directors has a significant number of members with deep roots in organized medicine.  It's testimony to a vital constituency on which the success of the Patient Centered Medical Home depends.

3. While tort reform has been outside the scope of this blog, an important ballot initiative dealing with California's benchmark Medical Injury Compensation Reform Act (MICRA) will be put before the state's voters this fall.  The lead organization of an impressive coalition of labor, business and consumer groups that has been created to defeat the proposition and preserve MICRA is, you guessed it, a state medical association.

The lesson for population health providers?  Reach out to and work with the physician groups at all levels of reforming the system.

Another Randomized Controlled Clinical Trial Proves Outsourced Population Health Care Management Works: Hypertension

Here's another high quality randomized controlled clinical that confirms the benefits of outsourced care management.

Margolis and colleagues accessed Minnesota's HealthPartners' electronic records to identify all patients who had had two sequential primary care clinic blood pressure readings that were more than 140 systolic or 90 diastolic.  These patients with hypertension were asked by letter and then phone calls to participate in the research trial.  Those who agreed were rechecked by research assistants who re-measured the blood pressures to confirm the hypertension.

16 clinics participated. 8 were assigned to the intervention group. 8 served as comparison (control) "usual care" clinics that relied on usual physician care.

In the intervention clinics, a pharmacist interviewed each patient and sought agreement to lower the blood pressure by 5 points. The patients received a home BP monitor that transmitted data to AMCHealth six times a week. The pharmacist and patient met by telephone every 2 weeks. Based on the BP monitoring and the telephone interviews, the pharmacist used a standardized medication algorithm to adjust medications until control was achieved for 6 weeks.  Telephone calls were then reduced in frequency to monthly.

The research assistants reassessed the participants' blood pressures at 6, 12 and 18 months.

Over 14,000 patients were identified and 2020 agreed to be screened. 450 met criteria for persistently elevated blood pressures. 228 were cared for in the intervention clinic and 220 were cared for in the usual care. The mean age was 61 years, 45% were women, 82% were white and 48% had a college degree. The average blood pressure was 148/85.

Both groups had a similar frequency of follow-up visits. 380 patients had completed both 6 and 12 month follow-up visits with the research assistants. 

The proportion of patients with controlled BPs at both visits in the intervention clinics was 57.2% vs. 30% in the control clinics. If those patients lost to follow-up were counted as blood pressure "failures," the success rate was 48.5% vs. 25.1%. Both sets of measures were statistically significant.  The relative proportions held up at 18 months.

Unsurprisingly, intervention patients were taking more medications over the duration of the study and at 6 months were statistically more significantly more likely to report that they were taking them. 

Six patients in the intervention group vs one in the control group had "events" related to low blood pressure, dizziness and loss of consciousness.

The cost, based on pharmacist time, was $1350 per patient.

The Disease Management Care Blog's take:

This adds to a growing body of evidence that non-physicians working under clinical protocol side-by side with busy primary care physicians can achieve control of a chronic condition - in this instance, hypertension.  This is a core attribute of population health.

Another piece of good news is the emergence of the electronic health record as a means to identify patients who are program candidates.  Now that's "meaningful."

The bad news:

The cost was $1350.  It is unlikely that those direct costs were mitigated by hypertension-related "savings" within the same fiscal year.  On the other hands, thinks the DMCB, the use of other types of non-physicians with or without IT-based decision support and higher throughput could lessen that cost.  The DMCB is sure that the population health service providers are already on it.

Even with state of the art population health, the rate of hypertension control was ultimately 50%.

A small excess of participants experienced an excess of treatment side effects.  While this may be the inevitable consequence of more aggressive treatment, it could expose the program to liability.

This was Minnesota: we don't know if this would work in, say, Los Angeles.  This needs to be tested elsewhere.

Image from Wikipedia

Population Health Management to Screen and Treat Patients with Elevated BNP at Risk for Heart Failure

An echocardiogram of the heart

The shortness of breath just wasn't going away.

After years of being treated for persistent asthma, Dr. Smith (name changed) found his usual mix of inhalers and pills was no longer working.  Unable to comfortably sleep at night and finding he couldn't hustle as quickly up and down his clinic's hallways, he decided it was time to see the Disease Management Care Blog.  After a quick look and a listen to his heart and lungs, the DMCB tapped its heuristics and made a shortcut bet that this wasn't asthma.  The echocardiogram that was obtained that afternoon proved that it was right: Dr. Smith had heart failure.

Heart failure is the leading cause of hospitalizations in the elderly and is a huge cost to the U.S. health care system.  Therefore, if docs like the DMCB on an individual basis - or the U.S. on a health care policy basis - could prevent heart failure, that would be a big deal.

"Natriuretic Peptide–Based Screening and Collaborative Care for Heart Failure - The STOP-HF Randomized Trial" that was just reported in JAMA may be a step in that direction.

The DMCB explains.

First off, there is a hormone that is made by a stressed heart (yes, the human heart secretes hormones) called "naturetic peptide" (or NP) that signals the kidneys to excrete more salt and water. "BNP" is one type of naturetic peptide that can be detected using a simple blood test.

The STOP-HF trial set out to examine whether BNP levels could identify otherwise well-appearing persons with stressed hearts who were at future risk for the development of clinically evident heart failure.  By catching these persons early and getting them into treatment, the hope was that these patients wouldn't turn out like Dr. Smith.

39 practices in the catchment area of Dublin Ireland's St Vincent's Hospital referred patients who were older than 40 years and had one of the following cardiovascular risk factors: high blood pressure, high cholesterol, an obese body mass index, documented (by an angiogram or a known heart attack) coronary artery disease, history of stroke, peripheral vascular disease, diabetes, arrythmia or heart valve disease.  Persons with known heart failure were excluded from the study.

After entry into the study, patients had a BNP level drawn and were then referred to either a "control" (observation only) group or to an intervention group.

In the intervention group, patients with an elevated BNP level of 50 pg/ml or more were referred to a cardiology service and had a cardiac function study using echocardiography. In addition, any of the cardiovascular risk factors were aggressively managed with medications and a specialist nurse-coach.

In the control group, physicians and patient were not told about the BNP level and were cared for on a routine basis.  Patients were not referred for any cardiology care unless another reason supervened.

1374 patients were randomized, 697 in the intervention groups and 677 in the control group. High blood pressure was the most prevalent risk factor and most patients had two risk factors. 263 (38%) and 235 (35%), in the two groups respectively, had BNP levels greater than 50 pg/ml.  Average follow-up was 4.2 years and all patients eventually had an echocardiogram to assess their heart function

During follow-up, 8.9% of the control group patients and 5.3% of the intervention patients developed heart failure as determined by echocardiography.  That difference was statistically significant and was due to a higher level of treatment with drugs that help control risk factors and prevent heart failure. When the DMCB uses a number needed to treat analysis, the works out to 28 patients needing to be screened and treated for an elevated BNP to avoid one case of heart failure.  That's not bad, even if you compare it to aspirin and heart attacks.  There were also fewer emergency room visits and hospitalizations in the intervention group.

The DMCB's take:

1. This is classic population health management: This study was not only about using BNP to find patients at risk for heart failure, it was about relying on nurse coaches to manage the underlying clinical drivers, such as high blood pressure or underlying coronary artery disease.  If the DMCB suggests a better title for this article would have been "Population Health Management to Screen and Treat Patients with Elevated BNP at Risk for Heart Failure."

2. An appealing value proposition with a return on investment: Given a NNT of 28 and the future costs of heart failure, combined with statistically significant reductions in emergency room use and hospitalizations, the DMCB expects population health management service providers as well as medical homes to use BNP and non-physicians to screen and treat patients to prevent heart failure.

3. Still imperfect: Despite aggressive management by a specialized team, 5% of patients in the intervention groups went on to develop disease.  We have a ways to go. 

Image from Wikipedia

The Link Between Personalized Medicine and Worksite Wellness

Critics look at employee wellness

Only the Disease Management Care Blog can link population health, a JAMA "Viewpoint" article on personalized medicine and a Wall Street Journal editorial on the alleged futility of worksite wellness.

The DMCB explains.

The JAMA article, written by Drs. Goldberger and Buxton, illuminates the cognitive dissonance over guideline-based vs. personalized medicine. 

The former represents the best care advice for a condition based on a published body of evidence.  Makes sense, but that evidence is typically based on multiple research studies involving populations that are both broad (able to generate statistically significant data) and representative (similar to other patients with the same disease). 

The latter describes tailored medical treatment that is suited to the individual characteristics (and personal preferences) of each patient.  This suggests that within the flow of "populations" that form the basis of a generalized guideline, there are circumstances for some persons that might make a particular treatment of greater or lesser benefit.

While Goldberger and Buxton use a complicated example involving implantable cardioverter defibrillator therapy to illustrate the conundrum, the DMCB has a simpler example.  Current guidelines support yearly mammography in every woman over the age of 50 years. Does that apply for the terminally ill woman in hospice or for a woman who, despite the advice from her physician, decides to forgo the test?

Intellectually reconciling competing policies of guidelines, such as "best practice," "reducing variation," "benchmarks" and "pay-for performance" on one side vs. personalized "informed consent," "patient empowerment" and "clinical judgment" involves subpopulations.  In other words, within any population-based study that shows an intervention is of benefit (mammograms save lives) there are subpopulations where the intervention is of little to no benefit (exceptions to every rule).

Which brings the DMCB to this provocative Wall Street Journal editorial condemning the entire worksite wellness industry. It recycles a number of tiresome criticisms, including outcomes tainted by regression to the mean, over-reliance on process-based outcomes, selection bias, employee discrimination, savings vs. program costs and overdiagnosis.  

Another criticism of the industry is the need for workforce-level (total) savings vs. per-participant savings. Since wellness programs typically focus on subpopulations of employees at greatest risk who are most likely to benefit and willing to participate, the observed savings can be limited to a few patients.  Unless those savings are culled from the large pool of total health insurance claims, they are otherwise invisible and critics will unfairly pounce.

Worksite wellness offers personalized care for limited numbers of patients.  That is its essential value proposition and its curse.  Until we can reconcile the total care via standardized guidelines vs. a more nuanced approach using personal care, it will continue to be criticized.

Insulin for Persons Already on Metformin: A Population Health Perspective

As most population health providers know, diabetes guidelines tend to focus on shorter-term or "intermediate" outcomes, such as average blood sugar levels or A1c levels.  That's because these short-term measures are surrogates for "long term" outcomes, such as blindness and kidney disease.

Two inconvenient facts have complicated the focus on intermediate outcomes:  

1) Once a threshold has been achieved, lower short-term blood glucose control doesn't necessarily lead to better long term outcomes;

2) The side effects of drugs - that otherwise work quite well at achieving short-term blood glucose control - may outweigh any long-term advantages. 

And now a just-published research study from JAMA raises the possibility that insulin has additional long-term side-effects.

According to diabetes mellitus treatment guidelines from organizations like the American Diabetes Association, the first medication option for Type 2 diabetes should be metformin.  If that doesn't work, the ADA suggests that there are several options for a second drug, including one of several sulfonylureas (glyburide, glipizide or glimepiride) or insulin. 

Sulfonylureas are pills, but have a reputation for not leading to the same level of diabetes control as insulin.  Unfortunately, while it's a more potent means of blood glucose control, insulin has to be injected.

Further details on the methodology are below.* Basically, Veterans Affairs electronic records were "mined" to find thousands of persons with diabetes who were using metformin and then had to start either insulin or a sulfonylurea.  Propensity scoring was then used to create two otherwise similar cohorts of patients and neutralize the impact of the diabetes control and disease burden.

2436 patients on metformin and insulin were compared to 12,180 patients on metformin and a sulfonylurea. 

After a median of 50 months of observation, the risk of a heart atttack, stroke or death from all causes was 43 per 1000 person-years in the insulin group vs. 33 in the sulfonylurea group.  That difference was statistically significant.  When deaths alone were examined, there was likewise an increased number in the insulin group (34 per 1000 person years) vs. the sulfonylurea group (23 per 100 person years).

The Population Health Blog's take:

This study raises the possibility that, among persons with diabetes on metformin, insulin is associated with an increased absolute risk of about 1 per 100 person years (10 per thousand person years, or one person out of a hundred persons followed for one year) of heart attack, stroke or death vs. the sulfonylurea pill.  Yikes.

Before we ban insulin in this population, however, the PHB is reminded that this was an observational study.  As an accompanying editorial points out, propensity scoring is not perfect and other unmeasured and confounding factors in the population could be biasing the results.  Short of a randomized clinical trial, there are other databases that could be mined the same way.  That includes those of the population health vendors, who also have a stake in risk stratification and long-term follow-up.

In the course of coaching persons with diabetes on metformin who are considering insulin, the additional risk of heart attack, stroke or death should be raised.  While the study above isn't perfect, the possibility is something that health care consumers need to weigh.

++++++++++++++++++++++

*Methodology:

Veterans 18 years and older who.....

1) were followed for at least two years with provider visits every 6 months,

 2) who had been placed on metformin and regularly used it between 2001 and 2008,

3) had one year of records prior to the first prescription for metformin and

4) were not on dialysis or in hospice

Once a vet filled a prescription for either insulin (long acting, premixed or short/long acting) or a sulfonylurea (glyburide, glipizide or glimepiride) and continued it for 6 months, their records became eligible for the study.  Patient records were excluded if there was no follow-up for six months, if the meformin was stopped for 3 months or a third diabetic drug was prescribed.

52% (approximately 92,000) of the 178,000 vets on metformin did not use another medicine.  Most were men (95%) and white (70%).  2948 were started on insulin and 39,990 started a sulfonylurea. The persons placed on insulin had, on average, worse diabetes control (A1c 8.5% vs. 7.5%) and a higher disease burden.

Perspectives on Exercise for Elders

Despite its busy travel schedule, the Population Health Blog had a chance to check out "Lifestyle Interventions and Independence for Elders" (or "LIFE") study that was published online in the May 27 issue of JAMA.

Over 14,000 persons over the age of 70 were screened at 8 medical centers for participation in the study.  To be eligible, candidates had to be sedentary (less that 20 minutes a week of regular physical activity), mobile (could walk 400 yards over 15 minutes), without any cognitive impairments and otherwise medically fit.

Participants were randomly assigned to either:

1) The exercise intervention, which consisted of 2 classes per week plus individualized home-based activity 3 to four times a week.  The goal was to achieve 30 minutes of walking daily, 10 minutes of leg lefts using ankle weeks and 10 minutes of balance training.  The cost was $1815 per participant per year.

2) The education intervention, which consisted of weekly workshops for 26 weeks with monthly sessions for follow up.  The classes included 10 minutes upper extremity stretching and flexibility exercises

Of the 1635 who were accepted, 818 were randomly assigned to the "exercise" group, while 817 were assigned to the "education" group. The average age of the participants was 79 years, approximately two thirds were women, 18% were African-American and the average body mass index was a hefty 30.

After an average of 2.6 years, more than half (59%) went on medical leave of variable duration.  Ultimately 63% of the sessions were attended. Loss to follow-up averaged 4% per year. Yet, using an intention to treat analysis, the authors found that ultimately 70% of those in the physical activity group were able to complete the 400 yards vs. 65% in the health education group. 

That 5% difference amounts to a "number necessary to treat" or NNT of approximately 20.

The PHB's takeaways:

1) This was an elegant study that demonstrates exercise for the elderly can lead to a clinically and statistically significant reduction in age-related declines in mobility.  We've intuited that "exercise is a good thing" for grandma, but now we know it.

But there is bad news:

2) Lest anyone believe that this single piece of evidence will prompt the U.S. health care system to cover preventive exercise classes for the elderly: it won't.  Medicare's definition of "medically necessary" is too full of loopholes ("condition," "accepted standards" and "coverage decisions") and is being held hostage by  Medicare's vast and hidebound bureaucracy.

3) The criteria were relatively narrow (already able to walk 400 yards and without any co-morbid conditions) and the exercise program was unique.  Would persons only able to walk 300 yards benefit from a less proscribed version of LIFE?  How about persons with diabetes? We don't know.

4) $1815 per member per year or $151 per member per month, whatever the merits of LIFE, is unaffordable.  If that was 818 persons in an average Medicare Advantage health plan, that's almost $1.5 million in additional expense to ultimately benefit 5%, or about 40 individuals.

5) The bad news is that with or without exercise, about a third (30% and 35%) of otherwise mobile, if sedentary, healthy seniors are destined to experience a significant decline in that mobility. 

Big Data, Definitions and Population Health

What's the likelihood of diabetes?

Utter the term "big data" at any ACO, care management or managed care meeting, and one of two things will happen:

1) Your colleagues will admire your population health chops and your boss will be reminded that you deserve a raise, or

2) Your colleagues will tire of your faddism and your boss will wonder, once again, just what "big data" means

Either way, you may want to refer your colleagues and boss to this readable "on-line first" article appearing in JAMA.

Here's a handy PHB summary:

"Big data" can be defined as the linking of disparate large data sets to provide insight at the individual level.

It's been used by political campaigns (swing voters), business (expectant mothers) and the NSA (potential terrorists). Once they are identified, amenable voters can be individually lobbied, expectant mothers can be sent personalized coupons and evil-doers can be visited by Jack Bauer.

According to Weber and his co-authors, how should health care providers approach big data?

1) Inventory the available data sets.  Traditional examples include electronic health records, insurance claims and pharmacy data.  Big data architects should also be aware of non-traditional examples including social media, census records and credit card purchases (such as grocery store purchases, fitness club memberships or over-the-counter meds).

2) Anticipate "probabilistic matching," since two or more individuals may fulfill criteria.  This will involve trade-offs between accuracy and feasibility, since two individuals matching "John Smith" in a single zip code may appear to have the same risk. 

3) Worry about HIPAA. Unfortunately, while medical data sets are disparate, they're also walled off by privacy concerns and special regulations that govern genetic and mental health data. It's not insurmountable. The health care industry should also participate in the public square to and help shape evolving societal and legislative standards over privacy.

Fortunately, the population health industry (here's a modest example) is already engaged. They understand that big data can be used to estimate individual risk which can, in turn, guide outreach to individual patients.

Image from Wikipedia

Medical Marijuana and Population Health

Many population health providers may deal with the chronic conditions of HIV, Alzheimer disease, multiple sclerosis cancer, epilepsy, inflammatory bowel disease and mental illness. For those who do, it's only a matter of time until they have to deal with medical marijuana.

Here's a good summary that provides some useful insights:

1) There is precious little peer-reviewed clinical trial data.  Much of the political and regulatory support is based on patient testimonials and the luster of tax revenue. 

2) Dosing is highly variable and dependent on a mix of over a hundred active ingredients, some of which are intentionally manipulated to develop different plant strains.

3) A marijuana pill has been approved by the FDA, but typically goes unmentioned by advocates. Small wonder, since smoking weed allows the user to not only titrate any medical effects, but the euphoria that goes along with them.

4) Absent clinical trial data, short and long term harms are also largely unknown.  There are worrisome reports of structural brain changes, decline in IQ, mental illness and respiratory disease.  Legalization would further increase the public's perception of safety.

5) FDA involvement is minimal.  If contamination occurs (pesticides, herbicides or fungal infestation), there is little hope of a recall.

The authors conclude with the usual academic call for more research.  The Population Health Blog wholeheartedly agrees.

The PHB also predicts the population health vendors and their outcomes registries may become an important factor in better understanding the role of medical marijuana in the management of chronic illness.  In the meantime, an evidence-based approach would suggest that until we have better data, informed skepticism should prevail in the course of patient coaching and decision-making.

Image from Wikipedia

The Politicizing of Preventive Health Care: Whither the US Preventive Health Services Task Force?

Here comes the camel nose!

Kudos to JAMA for tackling what the Disease Management Care Blog has been saying for years: now that the Washington DC's camel nose is under the tent, there is no way health insurance coverage - and the care it pays for - isn't going to become politicized.

That's the bigger issue in this just-published article by Steven Wolf and Doug Campos-Outcalt. They're focusing on the political pressure that is being brought to bear on US Preventive Services Task Force (USPSTF). As readers may recall, the Affordable Care Act requires health insurers to fully cover screening services that are deemed effective by the USPSTF. Drs. Wolf and Campos-Outcalt point out that politics rudely intruded on the USPSTF's determination that the evidence supporting mammography for women under age 50 years was lacking. The resulting firestorm not only prompted Congress to not only waive the USPHSTF recommendation, but led some of its members to question the Task Force's integrity.

As academics writing in peer-reviewed journals are wont to do, the authors suggest that this can be remedied by another layer of bureaucracy. They want a new "firewall" committee to be inserted between the "pure" evidence-based USPHSTF and the "political" fisticuffs of the public square.  It'd be the job of this a new entity to insulate USPHSTF by reconciling the proof and the politics prior to the upload of the final recommendations to the mandarins that are running CMS.

"Another committee?" asks the dismayed DMCB. While that would end the Obamacare fiction that health reform was ever going to be truly "based on science," the real Achilles heel of the JAMA proposal is that it literally doubles the opportunity for political meddling. The smartest political operatives will see this as a target-rich environment and naturally seek to influence all of the committees with any jurisdiction over the medical-industrial complex of laboratory medicine, radiological imaging and medical devices.

The DMCB has bad news for its colleagues who thought that they could have the Washington DC "cake" of enlightened government involvement along with the "icing" of scientific independence. Uncle Sam's been given a clinical inch and now he'll take a political mile to influence clinical guidelines and define standards of care with a one-size-fits-all mentality sprinkled with a healthy dose of cronyism.  Surprise!

The DMCB has an alternative solution: CMS should tread very carefully when it comes to insurance design.  Congress needs to reengineer the preventive health part of the ACA. Instead of building new infrastructure to make up for the emerging failures of the old infrastructure, Washington should be pushing benefit design down, not up, to the local level. It can partner with commercial health insurers to assure that the USPSTF recommendations are considered, but with local committee assessments of market demand, provider opinion and community input to determine what's best for its covered population. It should do this while simultaneously promoting the use of shared decision making to help every patient ponder for themselves when testing is in their best interest.
 
Let a thousand flowers bloom.

Image from Wikipedia

Aren't All Physicians Supposed to Be Experts in Clinical Informatics?

It was just a matter time.  "Clinical informatics" has become another medical specialty.

It seems that the clinical informaticians have their own organization (the "American Medical Informatics Association"or "AMIA"), an American Board of Medical Specialties-backed specialty designation, an accredited fellowship process and even a board examination.

And, like many other medical specialties, their experts are projecting a shortage of themselves and are naturally advocating for an expansion of their training programs.

The JAMA paper linked above provides a useful definition of the science:

"... a body of knowledge, methods, and theories that focus on the effective use of information and knowledge to improve the quality, safety, and cost-effectiveness of patient care as well as the health of both individuals and populations."

While the PHB appreciates the evidence-based definition, it can't help but be slightly disappointed at how this has played out. 

Years ago, when the promise of electronic records still exceeded their reality, there was an assumption among many of the PHB physician colleagues that a few strokes of the the electronic record keyboard would generate on-screen data roll ups. Possible examples included the percent of patients with high blood pressure who weren't controlled, the fraction of persons with diabetes who hadn't had basic immunizations or the number of persons with depression who weren't regularly filling their prescriptions. Us docs could use that information to improve quality, reduce care gaps and optimize costs, both at the point of care and for the entire panel.

In other words, the PHB assumed the EHR would enable all of us docs to become clinical informaticians. 

Alas, it was wrong.  To get the information, physicians will be expected to rely on another specialty to make up for the EHR's lingering shortfalls.

Egads.

Additive, Not Substitutive, Health Care Innovation

Sirens calling the unsuspecting
to their doom

If, like many of our policy and political elite, you have also been seduced by the siren call of health care "innovation" as a cost-saving panacea for the United States, you may want to check out this JAMA Viewpoint.

"Transcatheter aortic valve replacement" (TAVR) was supposed to be a less invasive and presumably safer and cheaper alternative to open heart surgery or "surgical aortic valve replacement."  Prospective clinical research trials demonstrated that TAVR was an option for small numbers of persons who may be too frail to tolerate open heart surgery.  Academics and regulators anticipated that TAVR use would be limited to carefully selected patients cared for at high-end "center of excellence" hospitals. 

That's not what happened in the Philadelphia region. Large and small hospitals that were only blocks apart followed the money and quickly established TAVR programs.

New York City turned out to be different.  Since health systems in Manhattan seem to have a higher degree of "integration," the authors wonder if TAVR was functionally rationed.  In addition, New York apparently has an aggressive "certificate of need" program for new technology.

True to their academic pedigree, the authors advocate for 1) further research trials to better define the risks and benefits, 2) the creation of TAVR registry databases that are populated by long-term outcomes, 3) the participation of "expert panels" that can opine on the best use of this technology, 4) "safe harbor" regulations that promote centers of excellence and 5) helping physicians do a better job of educating patients about the risks vs. the benefits.

Based on its limited knowledge, the Population Health Blog has a different take:

1) New technology is a genie that cannot be bottled. If it offers patients a new treatment option in an unfettered market, it will be rapidly adopted.  The impact is not substitutive, but additive.  It's Say's Law, turbocharged with Medicare financing and paid for by the U.S. taxpayer.

2) The PHB isn't sure "integration" played much of a role in New York City's slow uptake, since the Philadelphia region is likewise dominated by regional "integrated systems."  More likely was the top-down regulation imposed by certificate of need.  Other top-down approaches include utilization management.

3) Research, registries, panels, safe harbors and physician education are about as likely to stem the demand for TAVR as much as nicely asking 24's Jack Bauer to stop being so mean.