Showing posts with label JAMA. Show all posts
Showing posts with label JAMA. Show all posts

Tuesday, July 12, 2016

President Obama Writes About Health Care Reform in JAMA

All aboard!
In a first for the Journal of the American Medical Association ("JAMA"), President Obama has authored a Special Communication on "United States Health Care Reform."

As the Population Health Blog would expect of any modern sitting President's essay on any political achievement, there are no new insights, no new useful lessons learned and no regrets. The reader is instead treated to an Affordable Care Act (ACA) legacy-building "bus tour" of selected facts and gratuitous framing of the Affordable Care Act (ACA). a

Briefly, Mr. Obama points out that, thanks to the ACA, the national uninsured rate dropped by 7% from 16% to 9%, which was accompanied by a 3.5% increase in the number of individuals with a personal physician and 2.4% increase in access to medicine. He takes credit for declines in the inflation rate for health care spending, decreases in consumer out-of-pocket health care spending, the rise of value based care, and improvements in quality of care.

The President goes on to putter around the edges with some suggestions for "building on progress to date":
He closes with "lessons for policymakers":
  • While change is difficult, "hyperpartisanship" makes it doubly so. The tools of hyperpartisan sabotage include "inadequate funding, opposition to routine technical corrections, excessive oversight, and relentless litigation."
  • Special interests "like the pharmaceutical industry" still "pose a continued obstacle to change."
  • The ACA is an example of American middle ground pragmatism between the extremes of vouchers for all and single payer. It should continue.
The PHB's Take

As years of over-lawyering has taught Americans (indeed, JAMA has put the academic credential "JD" after Barack Obama's name), real peer-reviewed policymaking benefits not only from the truth, but the whole truth.

What makes this JAMA piece less than the whole truth is failure to mention (other than in passing) how lingering of the Great Recession is what blunted the majority health care inflation, that a shocking amount of treasure as well as political capital was used for a seemingly modest 7% absolute reduction in the uninsured rate, that government sponsored plans will likely put the remaining regional insurers out of business, and that the prospect that any company doing business in the U.S. being legally compelled to share proprietary cost information is highly unlikely.

Oh, and by the way, short of firing up some more money-printing presses or some real reforms, Uncle Sam has no money to pay for any of the additional proposed suggested goodies.  There is no political appetite for shoveling any more federal money toward health care.  

Last but not least, the ACA was midwifed by a hyperpartisan ramrod that failed to get even one Republican vote in either chamber of Congress. This Special Communication does nothing to diminish that legacy.
Was this a squandered opportunity to set the record straight and address some meaningful reforms?

You be the judge.

But don't take the PHB's word it. Appearing in the same issue of JAMA is this editorial by the Brooking Institution's Stuart Butler.  He points out that Medicaid and not the marketplaces was responsible for a significant majority of newly insured Americans, that, even with premium support (or its expansion), commercial insurance enrollees are now saddled with very high out-of-pocket costs.

Oh, and then there is a consensus - now that the Recession is waning and the ACA is taking hold - that health care inflation is poised to accelerate.

Image from Wikipedia

(Updated July 14)

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Monday, January 4, 2016

2016 is the Breakout Year for mHealth: Savings vs. Value

In this post, the Population Health Blog predicts how and why mHealth will be covered by more commercial health insurers in 2016, and why the retail "over the counter" mHealth market outside of insurance coverage will also continue to grow. 
 
While you're reading, consider this simple question: What are the revolutions per minute (RPMs) of your automobile's engine as you ascend from stationary idling to freeway speed?
 
The Definition of mHealth: "the delivery of healthcare services via mobile communication devices." Other definitions can be found here.  Elements include handhelds, wireless communications, software, hardware, networking, social media, sensor technology, apps and cloud-based services. The World Health Organization says it's global and much is still in its infancy.
 
Three Population Health Blog predictions for mHealth in the United States:
 
1) 2016 will be a breakout year, because both the savings and value propositions will be clarified.
 
What does the PHB mean by this? 
 
The ultimate question for health services buyers, payers, providers and patients is whether mHealth technology is: 
 
Substitutive: achieving savings from displacing present or future high cost services,
 
or
 
Additive: co-existing with present, or increasing future utilization.
 
The same is true for many pharmaceuticals, population health programs and the medical home.   
 
2) Faced with the reemergence of unsustainable health care cost inflation, commercial health insurers will deploy today's premium to sponsor tomorrow's substitutive mHealth cost reductions.
 
Commercial insurers will look for mHealth that is "S3" or Smart, Synergistic and Scalable.
 
1. Smart: addresses the tailored needs of selected population segments; instead of being all things to all patients, think focusing mHealth on high risk patients with special needs. 
 
2. Synergistic: enhances, not replaces other incumbent resources, such as one-on-one care management or outreach telephony.  
 
3) Scalable: uses the economies of scale to provide a lower-cost service to larger numbers of consumers.  As more patients in a select population use mHealth, the cheaper it becomes. 
 
3) But.....Value-driven mHealth will also flourish in the direct-to-consumer, over-the-counter or retail market for three reasons:
 
1) Consumer notions of value: 
 
Interest in personal wellness, a cultural belief in the pervading merits of technology and the allure of every more innovative gadgetry will continue to outpace the underlying mHealth abandonment rate.
 
2) As Obamacare acquaints consumers with real healthcare costs, #mHealth will be viewed as a relative bargain.
 
Comparatively pricey physician encounters, emergency room visits or a hospital stays - especially for Bronze Plan enrollees - will only increase consumer appreciation for  mHealth's "over the counter" benefit-to-cost ratio: for a few extra bucks, why not have that weight-loss, blood-pressure, medication-management app or wearable, especially when you already have a handheld smart device and the bandwidth?
 
3) Some commercial insurers will "cover" wellness #mHealth, not because their actuaries support it, but because their customers (purchasers, brokers and consumers) demand it. 
 
"Coverage" will be in the form of a volume-based discount pricing borne by the consumer, not a value-based benefit covered by the insurer. If it increases customer loyalty/"stickiness," all the better.
 
Plus there's the mHealth "X-Factor." mHealth sponsors and their allies will collect, sell and use consumer data for marketing and surveillance.   The PHB calls it mining and monetizing. 
 
Back to the tachometer: Even though its dashboard displays it, the PHB doesn't know the vehicle's RPMs either. Aside from  the use of the tachometer by some car enthusiasts  to optimize manual gear shifting, it adds little to car performance or safety. 
 
Yet, it's standard and in the dashboard of just about every automobile being sold in the U.S.A.  Could gadgets, wearables, apps and mHealth physiologic monitoring become the healthcare tachometer?  Useful to a critical few and standard for everyone else?
 
So, What is the the Basis of the PHB's Predictions?
 
Growth potential:
 
 
If you think it's all about "Fitbit" or managing diabetes, think again. How about promoting mindfulness, monitoring medication compliance, home-based high-risk pregnancy monitoring, in-home safety for the frail elderly, heart rhythm management, and home-based "pervasive" monitoring. Plus, mHealth style technology is being used outside of healthcare, such as in the automobile, for elite athletes and to promote safety in high-risk worksites
 
S3  = Savings
 
Smart: Here's a just-published JAMA study of a randomized clinical trial (RCT) that showed text-prompts had an clinically relevant impact on blood pressure in a group of select persons with coronary heart disease. Here's an rigorously conducted RCT that showed persons with Type 1 diabetes mellitus achieved better blood glucose control.  How about socioeconomically vulnerable patients with diabetes? Or patients with heart failure being discharged from a hospital?  The list of special populations with special needs goes on and on.
 
Synergy - This exhaustive peer-reviewed publication examining the merits of wellness mHealth for weight management, physical activity promotion, tobacco cessation, and cholesterol control shows that there's little evidence that it's better than existing therapies over the long-term.  Rather, the greatest promise appears to be in complementing existing interventions.  By the way, synergy does not mean overwhelming the system with data, but assisting the system with insight.
 
Scalable: While economists, policymakers and pundits legitimately worry whether bigger is better for healthcare in general, health system C-suites and boards of directors and their consultants are counting on information technology to drive economies of scale.  Papers like this and this suggest mHealth can be a part of that, especially if it can mitigate manpower constraints.
 
And an easy way to assess whether the insurer  really believes that it's sponsoring an S3 initiative is asking whether it pays for a handheld device for consumers that don't have one
 
Value:
 
Consumerism? Call it "the quantified patient." Here's a telling survey that shows the abiding faith in health information technology and a lack of privacy concerns.
 
 Bargain? The title of this peer-reviewed paper says it all" "It's like having a physician in your pocket!"
 
 Insurer discounts? The same thing happened to health club memberships.
 
The X-Factor: CIOs everywhere agree that they're not only apps, but software "vacuuming up data."
 
 
 
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Wednesday, December 2, 2015

The Limits of Financial Incentives for Docs

"It is written: Man shall not live by bread alone."
Luke 4:4

No matter what you think of the source of that quote, the idea that there may be limits to "aligning incentives" has some merit. In healthcare settings, physicians seem to be  supportive of being fairly compensated for their work, but also seem to be quite skeptical about the use of "carrot and stick" style economic rewards to influence clinical practice.

Case in point is this interesting paper describing the results of a randomized clinical trial that used blood cholesterol-level control to assess the relative merits of a) rewarding just the patients vs. b) rewarding just the doctors vs. c) rewarding both patients and doctors vs. d) usual practice, or a control group.

The study took place in three marquee institutions, involving 340 primary care physicians who were already taking care of 1503 adult patients with 1) elevated cholesterol levels who 2) either had coronary artery disease or were at high risk for coronary artery disease.

About half of the patients were already on cholesterol-lowering pills.

The purpose of the study was to determine if real money could be used to increase the rate and level of prescribing a statin drug aimed at achieving levels of cholesterol control that were consistent with national guidelines.

The 358 patients in the first group (a above) were cared for by 58 physicians; these patients rewarded by participation in a daily lottery system that gave $10 or $100 if the right number was hit and a wireless-enabled pill bottle indicated that it had been opened.

The 64 docs in the second group (b above) caring for 433 patients with no incentives were rewarded with $256 for each patient per quarter who successfully lowered their cholesterol to target levels. 

In the third group (c above) 346 patients got $5 or $50 if they hit the lottery, while their 58 physicians got $512 per patient at target.

A fourth comparison group of patients and physicians served as the control group with no economic incentives.

All patients received their statin drugs in a radio-enabled pill bottle that signaled each time the container was opened.. This allowed researchers to track medical usage.

The results?

12 months later, compared to the control group, the only patients that lowered their cholesterol in a statistically significant manner were the ones in the third "shared incentives" group.  What's more, while the drop was greater than would expected through chance alone, the absolute change was relatively small and wouldn't be expected to result in a big change in the likelihood of a future heart attack.  Last but not least, while the shared incentives group opened their pill bottles more frequently, the average level of medication compliance for all groups was less than 50%.

The authors correctly point out that the usual care control group of patients (N=366) being cared for by their control physicians (N=58) were exposed to the wireless-enabled pill bottles and that the lowering of their cholesterol levels made the three intervention groups look bad by comparison. 

The Population Health Blog's take? 

While notions of "pay for performance," "value, not volume," and "skin in the game" are attractive notions to policymakers and health leaders, their top-down impact at the one-on-one doctor-patient level defies linear economic logic. The PHB suspects that the physicians caring for these patients had already talked to their patients about starting or increasing the cholesterol medicines and that that quality care had already occurred independent of any fancy monetary incentives.  In other words, they were already doing their best. 

On an unrelated note, simply monitoring medication compliance with the radio-controlled pill bottle seemed to have an outsized impact on the study.  The PHB wonders if that can't be used to help patients who are already trying to do their best.

This study should give pause to anyone who thinks that physicians can be manipulated with more money.  They live by more than bread alone.

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Thursday, August 27, 2015

"Fusing" Randomized Clinical Trials and Big Data: Another Value Proposition for Population Health?

Randomized controlled trials are the crown jewel of clinical research.  By allocating patients to one of two or more treatment protocols (or "arms"), they can ascertain cause and effect while also eliminating any known or unknown bias from the results.  As a result, they often provide "the" answer to the big questions about the true value of medical interventions.

Unfortunately, they're also difficult, expensive, time-consuming, can only gauge average impact, often exclude many "real world" patients, require patient consent and have made little impact on day-to-day health care. 

Enter Big Data.

Defined as the "rapid analysis of (multiple) data sets using sophisticated machine-learning strategies," it is inexpensive, fast, uses readily available information, can give insight at an individual level, don't necessarily require patient consent, and also have had little impact on day-to-day health care.

So, Derek Angus suggests in the latest issue of JAMA that the two approaches can be fused:

1. Use electronic record based machine intelligence to scour the clinical data bases to find candidates for the trials, prompt the doctors to recruit the patients and then enter them immediately at the point of care;

2. Change the entry criteria as the application of Data to the randomized trial results begin to show that one arm is showing greater promise versus other arms;

3. Tilt the randomization toward one arm of the randomized trial if it begins to show a clinical advantage;

4. Have organizations commit to recruit ALL patients who would meet entry criteria to participation in the randomized trial.

To his credit, the author points out that there would be some challenges. Increased complexity could increase the threat of hacking of electronic health records. Convoluted recruitment, assignment and data analysis could be vulnerable to manipulation.  Without high numbers of participants, heterogeneity could introduce hidden biases and undermine confidence that any observed results are real. Despite assurances that there is increased odds of actually benefitting from participation, physicians and their patients may still be reluctant to cooperate.

While this paper is really about using Big Data to help increase the efficiency of randomized trials, the Population Health Blog finds the concept intriguing. It wonders if large academic centers and traditional research sponsors have the flexibility to change their usual way of doing business.

The PHB makes note of one additional barrier: a small but additional burden on clinical workflows. While it may only take a few more minutes for a physician or nurse to deal with the prospect of a clinical trial, the multiple inefficiencies of the EHR have already added up to a significant burden. While the merits of clinical research are significant, front-line nurses and docs could view this as just one more hassle.

Since Population Health Management service providers already possess expertise in big data and electronic records, applying this to randomized trials may represent a new value proposition for the industry. Now that would be a big impact.
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Tuesday, November 4, 2014

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 2012. 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.
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Monday, September 15, 2014

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.

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Friday, September 12, 2014

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.

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Wednesday, July 23, 2014

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.
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Wednesday, July 16, 2014

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.
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Wednesday, June 11, 2014

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.
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Tuesday, June 3, 2014

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. 
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Tuesday, May 27, 2014

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.

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Tuesday, May 20, 2014

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.

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Wednesday, May 14, 2014

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.
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Tuesday, May 6, 2014

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.
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Monday, April 28, 2014

Commitment Devices, Behavior Change and Population Health

A new addition to the
behavior change tool box
Whenever the Population Health Blog encountered a tobacco user in its clinic, it would gauge the patient's readiness to quit. For those patients who were ready, it then established a future "quit date" (to facilitate planning), a "contract" (a jointly signed prescription for display on the home fridge) and advice to use any money savings (tobacco is expensive) for a nice reward once seven days of success (for example, a restaurant dinner) was achieved.

The PHB didn't know it at the time, but that seven-day reward was a variation of a "commitment device."  That's what it learned after reading this just-published JAMA manuscript by Todd Rogers and colleagues.

Commitment devices are a way that "present" persons can commit their "future selves" to a sufficient level of needed behavior change.  The threat of a penalty, such as the loss of a night out on the town, imposes a limit on future choices and makes success more likely. 

Other examples of commitment devices described by the authors include applying cash to a success contract (for example, employers could link a bonus to participation in a exercise program that would otherwise be lost), "temptation" bundling that limits access to a gratifying experience in exchange for "consistent" behaviors (used with repeated success by the crafty PHB spouse), limiting bad choices to small packages (smaller portion sizes) and partnering (to avoid disappointing a buddy who shares the commitment).

In retrospect, "commitment devices" have been used in population health for decades.  As Rogers et al point out, however, despite some good research on how effective this approach is, they're generally underused by providers and patients.  One potential way to overcome that is to offer them routinely on an "opt-out" basis, 401k savings-plan style.  The authors also point out that a series of commitment devices on a longitudinal basis could be used to blunt drop outs and maintain long-term behavior change. Last but not least, leveraging social networks with or without handheld "apps" remains an area ripe for future research.

As medical homes spread and shared-risk payment reforms gain traction, the art and science of commitment devices will likely grow. Not only is it a cool piece of insider jargon ("Hey, Mary, I like this care management proposal, but have you any plans to develop commitment devices?"), but any addition to the behavior-change tool box can only help.

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Monday, April 21, 2014

I'm From CMS and I'm Here to Help

Writing in JAMA "online first," CMS Administrator Tavenner and colleagues offer a payment reform "framework" that includes "multipayer collaboration."  The article is wonky, so the Population Health Blog dons its universal adminispeak translator so us normal humans can better understand what CMS is up to.

According to the writers, CMS has a history of innovatively implementing reforms that were later adapted by other insurers. The most famous example is the hospital "DRG" system that, starting in 1983, paid for a diagnosis in lieu of a daily room rate.  Suddenly, hospitals had an incentive to shorten hospital stays, which is precisely what happened in the years that followed.

Buoyed by this success, the authors describe the merits of championing Medicare's transition from "category 1" fee-for-service without any link to quality to "category 4" population-based payments that are linked to quality. And, as CMS embarks on this excellent payment journey toward accountable care, they'll get other commercial insurers to mirror their efforts by:

"Being conveners" as in "working with" other insurers in a region or a state to implement large payment reforms.  Working with may include grants;

"Incentivizing," as in requiring the participation of other payers prior to funding any large pilot programs.

"Working with states" to implement additional reforms, when the state has sufficient influence over the health insurance or delivery system.

The Population Health Blog's take:

"Category 4 population-based payments" are a form of capitation that are ultimately designed to transfer insurance risk from CMS to providers. The PHB hopes the bureaucrats at CMS are aware of the risk re-introducing some 1990s-style managed care abuses. 
 
What also goes unmentioned by the JAMA article are examples of CMS payment reform unintentionally gone awry, including RVUs, regional payment variation and the SGR with lingering fraud. While CMS has had its successes, it's also had more than its share of problems.  Time will tell which track record will apply to population-based payments.

Convening was an art developed by Medicaid programs.

Ms. Tavenner implies that population-based payments (a form of capitation) are intrinsically linked to quality.  Nothing could be further from the truth, since it's possible to reward quality while also relying on a FFS methodology. 

Accountable population-based care remains a large experiment.  Ms. Tavenner implies that there is an aura of inevitability.  The PHB learned long ago that the sign of a good plan is an exit strategy in case things go south.  The PHB didn't read that here.
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Monday, April 7, 2014

For-Profit Meets For-Publication For Big Data

The "for-profit" research side of health care and the academics have always had a strained relationship. The Population Health Blog witnessed it first-hand when it recruited volunteer participants for an protocol that was sponsored by a pharmaceutical company. It was a good experience, but the company made it abundantly clear who was in charge of the data.

As "big data" research grows, will large pieces of it be likewise run by self-serving and deep-pocketed healthcare corporations?

That's the question explored in this JAMA "online first" piece by Sachin Jain et al. Huge electronic health record and insurance claims data sets involving tens of thousands of patients can provide academically (publishable) as well as commercially (profitable) insights on treatment safety and effectiveness in the real world. The JAMA authors use Indiana School of Medicine's Regenstrief Institute's collaboration with pharma giant Merck as an example of how the relationship doesn't have to be anything but collaborative.

Their 5 year agreement centers on mining a statewide information exchange involving over 11 million patients. Scientists from both companies with similar interests - such as melanoma, heart disease in persons with diabetes, medication adherence, the progression of heart failure, treatment of osteoporosis, natural language processing and vaccinations - are encouraged to jointly present ideas to a steering committee that ultimately okays and funds projects.

What are some of the lessons learned?

1. Academics prefer funding that lasts 12 to 18 months, while pharma wants an answer ASAP. The fix was to create sustainable funding "cycles."

2. Protection of individually identifiable data is a priority; Merck has "arms length" access only to de-identified data, and that's just for starters.

3. Both institutions have to agree on the release of any research findings into the public domain.  Any disagreements are handled by the steering committee.

4. A separate operations committee keeps track of all the projects and their timelines.

5. Some research questions on the natural progression of chronic disease can only be answered over the course of years.  One big data project beats a gold-standard randomized clinical trial.

The PHB's take:

This may be a template for population health vendors to follow.

Because they're interested in the association of multiple risk factors with multiple outcomes, the vendors likewise have a lot to gain from mining big data. The good news is that many already have contracts with health care systems and other entities that are sitting on terrabytes of clinical and claims data. Smart vendors should be asking how to move past their for-profit reputation, leverage these relationships and take big data - with their academic colleagues - to the next level.

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Tuesday, March 25, 2014

More JAMA Drama: The Medical Home Reduces Costs, But Only For High Risk Patients

A medical home
candidate?
Just when the Population Health Blog decided to take a break from all the JAMA drama, along comes this study "Medical Homes and Cost and Utilization Among High-Risk Patients" that was just published in American Journal of Managed Care (AJMC).

It cannot resist.

As readers will recall, the offending JAMA article described how a large three year-long Patient Centered Medical Home (PCMH) multi-payer pilot involving approximately 64,000 patients failed to reduce health care costs or increase quality. The pilot program was called the "Chronic Care Initiative" (CCI), and was the brainchild of then Governor Rendell's reform-minded "Prescription for Pennsylvania."

In the AMJC study, 6940 "intervention" patients with a) at least 3 months of primary care physician follow-up, plus b) at least 6 months of assignment to one of the medical home practices were retrospectively compared to 6940 similar "control" patients from a single non-participating practice. The control patients were matched using "DxCG" risk adjustment software* that was combined with propensity matching.

Pediatric practices were excluded, as were outlier patients with more than $100,000 in medical expenses.

In addition to looking at those patients, the top 10% of risk DxCG patients from the medical home (654 patients) were compared to matched high-risk non-medical home practices (734 patients). 

The analysis was complicated by the later attainment of NCQA medical home recognition among some clinics that were taking some of the control patients.  This limited the pool of patients in the 3rd year to just over a thousand in both arms, and just over 100 patients in the high risk groups.

Results?

There was no difference in the evolution of health care costs among all patients included in the analysis.  This confirmed the JAMA drama.

But......

For the top 10% high-risk patients, there were reductions of 61, 48 and 94 hospitalizations per thousand over each of the three years study. This was accompanied by a difference of the per member per month (PMPM) inpatient costs of $115 and $62 in years 1 and 2.  While there was also an increase in outpatient specialist visits, the downward change in inpatient utilization drove the difference in combined overall costs in years 1 and 2 of $107 and $75 PMPM. 

All these differences were statistically significant.  The 3rd year was not because there were too few patients to achieve statistical significance.

While the study was retrospective, the matching methodology is credible enough for the peer reviewers of AJMC and for the PHB. Using control patients from just one clinic is problematic, but no study is perfect. 

Which brings us to the punchlines:

1. Two years ago, the prescient Population Health Blog described how modern Ver. 2.0 "disease" (better described as "population") health management can financially succeed.  It said that one key ingredient is risk segmenting the population and targeting services at the highest risk patients. This AJMC article says it was right.  Most patients won't benefit, but vulnerable patients will.  They are the PCMH's customer.

2. The AMJC article also comports with an accompanying JAMA editorial that is discussed here.  As the PHB quoted, the JAMA drama....

".... has done a great service for the advocates of the Patient Centered Medical Home by effectively ending promotion of this care model as a generic, low-level, unselective approach to health care delivery for all.  The next critical phase of PCMH development should focus on its strategic deployment for the care of high-utilization patients...."

* This uses "linear additive formulas obtained from ordinary least squares regression to combine expenses associated with clinical groups and demographic factors to generate predictions." Wasn't that easy?
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Monday, March 24, 2014

Ten Things to Know About the mHealth App Ecosystem.

A mHealth app walled garden:
enter at your own risk?
If, like the Population Health Blog, you're interested in the hand-held mHealth app ecosystem, you may want to check out this just published JAMA review article "In Search of a Few Good Apps." 

Naturally, for time-pressed readers who'd rather not read it all, your PHB is happy to provide this ten point summary.

1) There are more than 40,000 of mHealth apps and the industry is still in its infancy.

2) Despite their faddish sexiness, there is very little hard evidence that many of the commercially available apps to lead to measurable improvements in clinical or economic outcomes. However, some of the underlying technology (such as pedometers) does provide a benefit.

3) The Food and Drug Administration (FDA) will assert its regulatory authority if the app "acts" like a "medical device" or as an accessory to a "medical device." Logging data, retrieving content or communicating won't be regulated, but medication dosing guides or the provision of diagnostic information will be.

4) 3) Little is known about the physician prescribing patterns for apps.  We also haven't figured out if or how a patient's access to an app should depend on a licensed professional's approval/prescription.

5) There is a possibility that many currently available apps are putting users' privacy at risk.

6) Little is known about apps' compatibility with electronic health records (EHRs).  This may be less of an "ecosystem" and more a bunch of isolated "walled gardens."

7) One vulnerability to any app's usefulness is data overload. Hundreds of food entries, for example, may do little to increase user insight about his or her diet.

8) Other than the FDA and its fussing over apps' medical "deviceness", there is no agency or entity that provides certification for apps. Consumers are on their own, based largely on on-line reviews and word of mouth.  One organization tried to do it and conspicuously failed.

9) The time is right to create "guidelines" for app developers, such as how to provide useful data summaries as well as visual displays, maximize patient safety, ensure information accuracy and protect consumer privacy.

10) The time is also right for funding agencies to support research on apps, especially for persons with chronic illness.

Naturally, the PHB offers commentary:

It remains to be seen if the FDA can keep up, especially with apps that are in the "grey zone" between offering advice/possibilities vs. diagnosis/treatment. That shortcoming is vulnerable to overlawyering and regulatory overreach. That means prolonged time to market, increased uncertainty, hampered innovation and the threat of retroactive and potentially capricious reviews.

As you are reading this, many apps are undoubtedly being developed by the population health service providers.  It may be time for entities like the Population Health Alliance or stakeholder organized medicine organizations to take the lead in establishing app benchmarks, best practices and guidelines.  If they don't lead on this, someone will do it to them. 

While vendors that offer apps along with their coaching may be inclined to regard them as proprietary and shield them from the scrutiny of peer review research, apps that are proven to improve outcomes will ultimately rise to the top.  It's not just the funding agencies but the companies that offer these apps that have a stake in "proving it," while also advancing medical knowledge for the betterment of all of us.

Finally, wouldn't it be neat if there was a generic mHealth app that could be used by medical homes to facilitate nurse-patient coaching, link the patient to the EHR and enhance communication with providers?  If there is one that the PHB isn't aware of, it wants to know about it.

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