The Good and the Bad of Risk-Based Contracting: Large Integrated Groups Are Adapting Another Form of Managed Care with Limited Consumer Choice and Restricted Networks?

"Should I refer out of network?"

What is the secret health reform sauce of those famous large integrated medical groups?  Come to think of it, do they even have secret sauce?

To better understand the apparent success of household names like Dean, Geisinger, Group Health, and Mayo, Rob Mechanic and Darren Zinner surveyed and then interviewed the CEO or the Chief Medical Officer (CMO) of 21 famous large provider groups to understand their operational approach to risk based contracting.
 
That's important because emerging payment public and private insurer reform will include "bundled payments," upside risk-sharing and forms of capitation.  In these kinds of arrangements, the financial "risk" from high overhead, overutilization or excess costs will be the provider groups' problem, not the insurers'.

In other words, if ACO wannabes want to succeed when it comes to risk-based contracting, they may learn about the good and the bad of the large integrated group business model.

The authors discovered that about half of these groups had less than a third of their income coming from risk-based contracting (RBC).  In these ten groups, an average 88% of income was fee-for-service.

The other half (eleven) had more than a third of their income coming from risk based contracting.  In these groups, 71% of income was risk-based.

The authors then compared the approaches of the "low" risk and "high" risk groups.

While Disease Management Care Blog readers will be very familiar with elements making up the "good" secret sauce of risk-based contracting, they may be surprised at the reemergence of two bad downsides.

The good ingredients included 1) blunted physician financial incentives to "churn" patient visits, 2) a slight but significant increased emphasis on using quality measures to reward physicians and 3) a significant investment in data warehousing, analytics, patient registries and point-of-care patient-tracking.

In particular:

9 out of 10 low risk contracting groups based the "majority" of physician income on productivity. In contrast, five of the capitated groups paid 80% of their PCPs with a salary, while the other half paid 80% of income based on productivity

"Quality" measures drove a small percent of PCP income in both groups, though it was higher in the capitated groups (5% vs. 12%)

85% of all groups had invested in electronic health records; 100% of the capitated groups had invested in data warehouses with analytic software and two thirds had patient registries.  Only one of the FFS groups had those capabilities. While both types of groups had a low rate of "patient engagement" programs, the high risk groups were more likely to have care management programs in place. 

And the bad? 

The DMCB was surprised to read that the risk-based groups were far more likely to have mechanisms in place to limit their patients' out of network utilization (90 vs. 20%) and 2/3 vs. 1/3 had preferred relationships with "efficient" hospitals and providers.  In other words, these role-model and state-of-the-art organizations could be limiting patient choice and economically credentialing their provider groups.

Much depends on the details.  Insurers have probably not forgotten the abuses and resulting backlash that arose from unfettered capitation.  Good risk contracting typically includes quality and satisfaction metrics side by side with utilization targets and specifically prohibits windfall profits. Modern consumer protections at the state and federal oversight level are also far more rigorous.

That being said, the DMCB points out that it's no accident that this study shows risk-based contracting is associated with limits on choice and restricted networks.  We may not call it "managed care," but in many respects it is.

The Latest Health Wonk Review Is Up!

"Baseball isn't boring, you are!" goes the adage. While the DMCB struggles with the implications of that, the Wing of Zock has a baseball-themed Health Wong Review that certainly isn't boring.  What's more, after you read all the submissions of other health policy bloggers, you'll be more exciting.

Enjoy!

The Perils of Government Involvement in Health Care

A Disease Management Care Blog spawn is implacably opposed to a Romney Presidency.  The argument is that while there's admiration for Mitt's successes as a businessman, running a government is better left to accountable politicians.

Which the DMCB appreciates. That doesn't mean there isn't a downside to the meddling of Republicans as well as Democrats.  Take health care for example.

Turbocharged by decades of direct government funding and favorable tax policies, insatiable healthcare consumer demand has created a medical-industrial bubble that is eating close to 20% of the U.S. economy.  Since Washington DC's direct costs are outstripping tax receipts, the same political process that got us into trouble is now supposed to get us out.  While the President's proposed 2013 budget has some painful cuts, that's nothing compared to the looming havoc being threatened by the coming fiscal cliff.  This is government accountability?

For a smaller example of the dysfunction created by government meddling, consider the electronic health record (EHR) mess.  Despite warnings from the DMCB that EHRs' documentation capabilities enable increased billings for the same care, both Presidents Bush and Obama promoted the EHR as an informatics cost-reducing panacea. 

It turns out the DMCB was right. This OIG report raised the possibility that EHRs are behind a recent coding uptick, which was further examined in this telling New York Times article by Reed Abelson et al. 

Government response? This threatening warning to stop using a product as designed that our political class had promoted all along.

(Latest update: Reversing course on years of being conspicuously silent in the face of the Adminstration's health reform bullying, the hospitals are pushing back.   Nothing like the threat of budget cuts to clarify just who your allies are - and aren't.  The cliff promises to be an interesting ride.)

Will the Roll Out of the Affordable Care Act's Health Insurance Exchanges Be Delayed?

While the Governor's Mansion in Pennsylvania is currently under the control of the Republicans, the Disease Management Care Blog knows the state's Insurance Department is relatively apolitical. That's why this September statement by Pennsylvania Commissioner Consedine before the U.S. House Ways and Means' Subcommittee on Health is quite telling. 

In it, Mr. Consedine describes how the Keystone state is encountering difficulties implementing an health insurance exchange. As DMCB readers will recall, exchanges are a key feature of the Affordable Care Act, because they'll provide an online market that will enable individuals to obtain coverage.

According to Mr Consedine, CMS is failing to support a good law with the many regulatory details that turn a vague idea into a functioning reality. These failings include:

1. "Interim," not "final" rules on eligibility, tax credit calculations, cost sharing and the role of brokers

2. Little formal guidance on the determination of the essential health benefit.

3. Delays in issuance of regulations on how states and Uncle Sam will split or mutually indemnify the myriad costs of the exchange and the Federal Data Hub.

4. Delays in the issuance of regulations on how states can exit a federally run exchange to set up one of their own.

5. Lack of clarification of CMS' impact on insurance markets operating outside the exchanges.

6. Little understanding of who's in charge of consumer protection statutes.

7. Confusion over reconciliation of multiple states' insurance laws and regulations in multi-state exchanges.

8. No guidance on how to roll long-extablished and well functioning state-subsidized insurance programs into the exchanges.

9. Concern that funding of the information technology could be clawed back if Medicaid eligibility does not meet CMS' criteria.

10. Little guidance on whether exchanges will need to provide consumers with a list of providers who are accepting new patients.

The concerns are also damning in the context of the the normal tug of war between the states and Washington DC. That's because in his testimony, Mr. Consedine states he wrote to HHS weeks ago and has not received a reply.  While its' not unusual for the Feds to stiff politically inconvenient inquiries, the Disease Management Care Blog is fearful that the reason why HHS seems unwilling to provide a timely reply is because it doesn't know the answers.

If Pennsylvania's experience is typical, that means the roll out of the exchanges could be significantly delayed.

You read it here first.

9/26/12 Update: Senator Hatch agrees with the DMCB

The Limits of Decision Analysis in Real World Health Care

Decision tree logic

Tired of hyper-rational experts using opaque decision logic to pass judgement on the value of your favorite medical tests or treatments?  Do you disagree with the Disease Management Care Blog's infatuation with Quality Adjusted Life-Years (QALYs)?  Then you may want to check out this article on "There Is More to Life Than Death" by Pamela Hartzband and Jerome Groopman.

Classic decision analysis combines "probability" and "utility" to mathematically compare multiple care options that lead to hard outcomes such as death, disability or cure (an example is here).  Unfortunately, say the authors, this imposes numbers on a narrow set of possibilities that fail to account for the full range of outcomes.  For example, the recent controversial and arguably nihilistic breast and prostate cancer screening recommendations were informed by decision analysis. While that methodology may have its place, "More to Life" argues that this sterile approach fails to account for the full range of physical and psychological burdens that can result from delayed diagnosis and inappropriate treatment.

While decision analysis attempts to make up for its shortcomings with additional analytics, Drs. Hartzband and Groopman argue that much of the underlying premise is fundamentally flawed by its failure to capture highly individual interpretations of what it means to be sick and how that can vary over time.  Distilling this down to a limited set of uni-dimensional outcomes centered on death, disability or cure ignores the "vital dimensions of life that are not easily quantified."

Yikes.

It's it own defence, the DMCB's fondness for decision analysis has been based on its insights, not on its answers.  In other words, it's a tool can open one window on the truth.  What Drs Hartzband and Groopman charge, however, is that the science of clinical guidelines is being hijacked by an over reliance on decision analysis by out-of-touch experts.  That's a serious charge that will complicate the national effort to disseminate scientific guidelines into every nook and cranny of medical practice.

Which leads the DMCB back to another fond topic that ultimately trumps all others: the need for an informed and engaged patient to process clinical guideline recommendations, the advice of a physician, the opinions of friends and family and their own personal values to ultimately make the decision for themselves about testing and treatment. 

Decision analysis alone is not up to the task.

Pay for Performance and Physicians may be like taking Cats for a Walk

 

The look of cooperation

Medicare continues to move forward with its PRQS "value-based" fee schedule modifier that will adjust physician payments up or down by 2% and 1%, respectively. 

As the Disease Management Care Blog understands it, 2013 physicians' quality and cost data will be compared to peers, and the docs who are above and below the mean will be correspondingly financially rewarded or dinged starting in 2015.  While the American Medical Association continues to quibble over the details, this Affordable Care Act pay-for-performance (P4P) train has left the station.

Unfortunately for CMS, plenty of research suggests that it remains an open question whether PRQS will have much of an impact. For example, findings from this Ontario study indicate that incentives tend to reward physicians who have already achieved the quality thresholds, doing little for the docs who are behind.  Additional research shows physicians may not agree with the underlying methodology and distrust the reliance on insurers' data, leading to a willful disregard of the incentives.  And then there's this expert survey that suggests that the effort it takes to achieve low single digit digit changes in income may be viewed as not worth the trouble.

The DMCB also thinks there may be another under-recognized issue at stake. While fee schedule changes in the 1% to 2% range can make a big difference to large hospital-physician organizations, that money, thanks to these organizations' byzantine internal accounting and transfer pricing, is unlikely to trickle down in a meaningful way to their employed physicians' paychecks. 

Ouch.

Physicians and P4P may turn out to be like cats and going for a walk.



Image from Wikipedia

Swaying Brains for Behavior Change

Here's looking at you!

The Disease Management Care Blog appears to be reaching a critical mass of readership. IP address traffic statistics are showing that the DMCB is part of many home, university and business readers' morning internet surfing. After unlocking their computer, more and more savvy health care leaders are accessing their company's intranets and clicking on browsing favorite "DMCB" for insights that buck the prevailing wisdom.  

The DMCB isn't surprised because its postings are tailored for a select readership on the front lines of program development, management and research.  Even if readers disagree with the DMCB's biases, they'll know what the opposition is thinking.

To those of you who are consistently returning day after day and week after week, the DMCB thanks you!

+++++++++

After reading the DMCB's shameless self promotion, check out this Wall Street Journal weekend essay on "Five Ways to Sway Voters' Brains."  It seems political consultants on both sides of the partisan divide are brazenly stealing a decade's worth of disease management behavior change technology to manipulate voters.

The italicized text above is an exercise in their subterfuge:

1. Make the voter/patient/reader "visualize" the preferred behavior (accessing the intranet with the DMCB as a browser favorite)

2. Portray the preferred behavior as cool ("savvy" and "select" health care "leaders.")

3. Predict voter/patient preferences ("development, management and research") and tailor the messaging ("insights").

4. Manage any negativity with an alternative rationale ("know what the opposition is thinking")

5. Let them know they are being watched (IP addresses from your universities, businesses and homes)

Image from Wikipedia

The Latest Health Wonk Review Is Up!

.... thanks to Louise Norris of the Colorado Health Insurance, who is hosting an "Inside Football" version of the Health Wonk Review. She sets, she kicks and she scores with a wide number of linked posts that provide insights you'll find no where else!

Enjoy!

Bipartisan Health Care Cost Control By Diktat: Insurers or Providers or Both

According to the Kaiser Foundation, health care costs are continuing to go up. Assuming Uncle Sam is doing everything he can to "increase efficiency" and "reduce waste," what are the options that can quickly control costs?

It's simple: leverage the insurance companies or the providers or both.

1. Tell the insurance companies what they can charge: While the ability of the Feds to regulate insurance remains murky, the Affordable Care Act enables CMS to require that insurance companies "justify" a premium increase of 10% and keep their administrative costs below 15%.

What is less appreciated is that the Medicare premium support plan being championed by Republican Paul Ryan is a variation of this same strategy. Thanks to a voucher that is indexed to the rate of inflation, insurance companies would be essentially told what they can charge for the bulk of their insurance. If the health insurers need to charge more, they'll have to wrestle that out of the beneficiary.

2. Tell the providers what they can charge: For an excellent example of this at the state level, check out this article in JAMA that describes Massachusetts's just-passed law that aims to control the Bay State's $9278 per capita health spending. Large providers (with more than 15,000 patients or $25 million in revenue) are now subject to cost controls that are tied to the state's inflation rate.  Enforcement mechanisms will include "performance plan" reviews for violators, public reporting and the threat of civil penalties.

Of course, Medicare's fee schedule functionally dictates what providers can charge for their services at the federal level, but up until now, Congress has been unwilling to leverage that. While a softer and gentler approach of "upside risk arrangements" and "global fees" are being developed, the paranoid DMCB suspects that they'll be ultimately calculated to cover a predetermined charge that is supplemented with a small profit margin.

While Democrats and Republicans have been supportive of a limited number of options ultimately reflecting their ideology, the DMCB predicts that, over time and with a worsening fisc, both parties will converge on using all of the options described above.  That's because they'll have no choice.

Heluva way to achieve bipartisanship, but there you go.

More On "Why No One Believes the Numbers" and the Uncertainty of Measuring Return on Investment in Disease Management

Measuring ROI

In yesterday's posting on Al Lewis' book Why No One Believes the Numbers, the Disease Management Care Blog pointed out that the measurement of population health management (PHM) outcomes remains an inexact and still evolving science. While that can be a source of endless fascination for the DMCB, the inability of the industry to rustle up credible "return on investment" numbers has prompted some observers to condemn PHM as a waste of money.

The search for simple answers explains much of the appeal of this book.

According to author, one important solution is the "dummy year analysis" (DYA). This relies on repeated year-over-year measurements of utilization that use multiple comparison pairings of all patients with the condition of interest. When that's combined with a "plausibility" check list, Mr. Lewis says purchasers of the Patient Centered Medical Home (PCMH), disease management or wellness programs should be able to get a better fix on whether they saved any money. You can a sense of that perspective here.

The DMCB isn't too sure about that because a) other factors that have nothing to do with population health management can also impact utilization during and after the dummy years, making it difficult to assign an attributable ROI and b) entire health plan populations can likewise regress toward a regional or national mean.

The DMCB also sees three additional reasons why there may be less to this book's methodology than meets the eye:

1. When employers, health plans, accountable care organizations or other buyers have a list of names that have been through a care program, they typically want to understand the outcomes for the individuals on that list. If that's the case, the challenge is to find an adequate comparator that portrays what would have happened in the absence of the care program. Multiple options for identifying a parallel comparator have been used in published science for decades. That's difficult, imperfect, but not broken.  It remains an option.

2. While the book is replete with examples of "actuaries behaving badly," it is impossible to underestimate the influence of actuarial science and trending on premium rate setting, statutory accounting, and the regulation of insurance. As a result, if the actuaries say money is - or is not - being saved, health system leaders ignore their insights at their peril.

3. Isolating the impact of PCMH, disease management or wellness program out of all the other "noise" of a changing economy, evolving consumerism, benefit changes, electronic health record databases, medical advances, inflation and the news media is a function of an increasingly sophisticated and changing statistical sciences and computational technology. It's ironic, but one outcome has been a better description and measurement of the uncertainty surrounding a result.
 
To the author's credit, Why No One Believes the Numbers is not being promoted as the single best methodology that will lead PCMH, disease management and wellness programs to outcomes certainty. Rather, it is one option among many in asking whether a program had any financial impact.

Ultimately, therefore, that's why the DMCB advises that measuring outcomes in PHM - absent an ironclad methodology - comes down to using multiple approaches to triangulate on the truth. After reading Why No One Believes the Numbers, some readers may choose it as one of those approaches.

Why Everybody Should Read Why Nobody Believes the Numbers

Music of the Spheres

Back in the early 1900s, Albert Einstein had a problem. Sophisticated instruments were unexpectedly showing that the measured speed of light was the same if the source or the observer were moving or stationary.  In other words, if one were moving away from a bullet, it should look (to the observer) that the bullet had slowed down. Light's refusal to conform to the prevailing common sense about how the universe should work ultimately forced Einstein in 1905 to conclude that, in order for the speed of light to be constant, time and mass had to be elastic. This ushered in a new field of relativity mathematics that is still being used to plumb the known universe's Music of the Spheres.

While the controversies surrounding the effectiveness of "population health management" (PHM) are quite minor compared to Einstein's Theory of Relativity, the comparison is still instructive. The similar mismatch between what is assumed, what is observed and how to mathematically describe the ultimate truth also underlies Al Lewis' book, Why Nobody Believes the Numbers.  In other words, we assume care management-based patient coaching always yields savings, increasingly sophisticated observations often fail to show it and, as a result, we need new mathematics to reconcile what we assume and what we observe.

Interestingly, author Al Lewis of the Disease Management Purchasing Consortium never doubts the speed of light or that high quality PHM ultimately can save money. While PHM vendors may interpret his long history of skepticism as some sort of shakedown, Al's passion is clearly evident: Why Nobody Believes the Numbers is ultimately driven by a search for the truth. For that he deserves a lot of credit.

The good news is that Mr. Lewis does a masterful job of examining the prevailing assumptions underlying the PHM universe by relying on layman's logic, simple examples, real world anecdotes and clever insights. As a result, even the mathematically challenged can come away with a better grasp of the pitfalls that surround selection bias, regression to the mean, invalid comparators and calculation of trend. As a result, the first chapter on "Actuaries Behaving Badly" is arguably "must reading" for human resources managers, sales personnel or C-suite types that are contemplating the "return on investment" from a company wellness or a disease management program.

That bad news is that Al Lewis is no Einstein. He suggests that a solution is at hand thanks to a simplistic "dummy year adjustment" methodology that is based on serial observations over a long period of time that includes all patients with the index condition.  When this is combined with a series of common-sense based "plausibility" tests, Al proclaims his mix of common sense and fundamental mathematics will yield a single, yes or no, black or white, it did or did not reduce insurance-claims expense-truth.

Unfortunately that ain't necessarily so. Even Einstein's insights couldn't explain all of the sublime harmonics that make up the Spheres. There'll be a future Disease Management Care Blog posting with more on how Why Nobody Believes the Numbers falls short.  That will address the unavoidable impreciseness that surrounds measures of central tendency, the challenges of measuring subgroups and the moving-target realities of an insurance industry that continue flummox those of us who are trying to explaining the health care universe.

In the meantime, if you're a buyer or a vendor, the DMCB recommends Why Nobody Believes the Numbers for your bookshelf.  DMCB readers will come away with a better grasp of the good, the bad and the ugly of outcomes measurement, understand what it can and cannot tell us and appreciate the underlying and still evolving debate over the ultimate value of the PHM industry.

Shared Decision Making for Hip and Knee Replacement Candidates

Osteoarthritis (a.k.a "degenerative arthritis) of the hip and knee just... sucks. Characterized by activity-related pain in the affected joint, many otherwise physically fit persons have to resort to pills, injections and, finally, an appointment with an orthopedic surgeon to talk about joint replacement surgery.

What is less appreciated is that osteoarthritis can have a waxing and waning course with periods of relative remissions. What's more, conservative treatment options can lessen or delay the need for surgery. Last but not least, the surgery itself involves months of recovery and the possibility of a nasty complication.

The primary care physician Disease Management Care Blog presided over this many times with its arthritis patients.  It was generally reluctant to refer a patient to an orthopedic surgeon because it knew that the patients would be more interested in the potential benefits and pay less attention to the downsides of surgery.

Enter shared decision making (SDM). Defined as care that is respectful of and responsive to individual patient preferences, needs, and values and ensures that patient values guide all clinical decisions, the premise is that by giving patients the information they need, they'll be able to ultimately determine the course of their care.  That would include patients with severe hip or knee osteoarthritis who are thinking about surgery but who also need to consider the option of conservative management.

That's why this just-published Health Affairs study is noteworthy. All the 27 orthopedic surgeons in the 5 Group Health Cooperative clinics introduced shared decision making (SDM) for patients who were being evaluated with knee or hip osteoarthritis.  The intervention consisted of DVDs and booklets (from this company) that were ordered by the surgeon prior to an appointment.  The materials could also be viewed on Group Health's website at any time.

The study itself was quasi-experimental.  To be included in the study, patients had to 1) have knee or hip arthritis, 2) ) be continuously enrolled in the Group Health Plan for 12 months prior to the orthopedic clinic visit and 3) have a visit itself that was first index visit by the patient for that problem being evaluated by that particular specialty.

Outcomes from the 18 months of the SDM intervention period (January 2009 through July of 2010) were compared to the observation period of January 2007 through July of 2008.

Recall that the surgeon had to proactively order the SDM prior to the visit.  As a result, only 41% of the hip patients and 28% of the knee patients received the DVD, pamphlet or viewed the on-line materials.
 
Nonetheless, during the 6 months after the initial visit, the SDM patient population had 0.34 hip operations per 180 person-days (your DMCB offers an explanation of this counter-intuitive metric below*), compared to the control population of 0.46.  The difference was statistically significant. 

There was also a statistically significant reduction in knee operations: 0.09 per 180 person-days vs 0.16 per 180 person-days. 

All the differences held up after the authors statistically adjusted for differences in age, sex, obesity, co-morbid conditions, use of prior x-rays, joint injections, insurance factors and the clinic site.

Like all good authors writing in a high quality journal, they point out that this research was not pristine. The comparison period may not have been a representative baseline and, from 2008 to 2009, other factors may have caused a drop in hip and knee surgeries.

Nonetheless, this is an example of a "real world" study that credibly demonstrates that when osteoarthritis patients are exposed to SDM, more will opt for conservative management.  While that helps decrease health care utilization and ultimately costs, that's not the most important point: the patients who really wanted surgery got it and the patients who were less sure about the benefits of surgery chose not to have it.  What's more, this didn't involve a lot of expensive face-to-face care management, it involved some DVDs.

The DMCB cautions that this successful study was carried out in a highly integrated delivery system and may not be transferable to other practice settings.  That being said, as Accountable Care Organizations struggle to meet their patients' expectations and save money, this application of SDM may represent an important option.

*The DMCB interprets "180 patient days" as one patient being followed for the entire 6 months of the study.  If that's correct, the average SDM knee patient referred to a Group Health orthopedist had a 34% chance of getting surgery versus a 46% chance in the prior control group.  For the knee patients, it was 9% vs. 16%

Disease Management for Hypertension: A Call to Action

While the population health management service industry has a successful track record when it comes to chronic heart failure, diabetes and asthma, the Disease Management Care Blog thinks, after a quick scan of the literature, that there are fewer studies of its impact on hypertension.

 A recent Morbidity and Mortality Weekly Report (MMWR) reminds us that that's a problem.

The National Health and Nutrition Examination Survey(NHANES) performs interviews and physical examinations of a representative sample of U.S. households.  This particular report on the prevalence and treatment of high blood pressure was based on a sample of 20,811 individuals from four 2-year survey cycles that were performed from 2003 to 2010.

Extrapolating from the sample, 66.9 million persons or 30.4% of the U.S. populationn have high blood pressure. Of this population, just over half (54% or 35.8 million) have uncontrolled hypertension.  Of these persons, 31 million (or 88%) had been seen by a health care provider in the preceding year. The prevalence of uncontrolled hypertension among those hypertensives with Medicare was 52%. Not having health insurance or having seen a health care provider in the past year increased the risk of untreated and uncontrolled high blood pressure.

What's more, the DMCB discovered control of hypertension doesn't appear to be getting better over time.

The good news is that the treatment of high blood pressure is not all that complicated and that team-based non-physicians can play an important role.  Patients should be engaged on weight control, a DASH diet, restricting salt, exercise and moderating alcohol intake. Medication therapy can be individualized and tailored to meet mutually agreed-upon goals and to minimize any barriers.  Check out this MMWR table and you'll see references to "lifestyle counseling," "self monitoring," "self-management education."

Given the looming shortage of primary care care settings and the coming influx of newly insured persons, the DMCB believes population health management will need to be part of the solution.  In addition to the established science, the industry 1) understands the importance of risk stratification, 2) can be bolted onto accountable care arrangements and 3) understands that optimal outcomes are somewhere between 46% and 100% control.

Hopefully, given the relative dearth of high quality studies, this opportunity will be accompanied by ongoing studies of outcomes.

Another Endorsement of Population Health Management

While it's not an explicit endorsement of the population health management industry, it comes pretty darn close.

Writing in the New England Journal, David Asch and Kevin Volpp point to three market "signals" that are being missed by the traditional medical-industrial complex:

1. There is growing consensus that the doctors have it wrong: being healthy is not a merely a "biologic" process.  Rather, social circumstances, environmental influences and personal behavior account for the bulk of well being. 

2. While providers are being called to task on a host of specific process and outcome measures, communities and employers are more interested in and getting better at measuring overall health.

3. While there are short-term approaches to reducing waste and increasing efficiency in the health care system (like bundled payments or episodes of care), everyone agrees on the long-term solution: a healthier population.

Drs. Asch and Volpp predict health systems will transition from selling product-oriented sickness treatment "within their walls" to customer-oriented "health" delivery. They better, or they'll end up like bankrupt Eastman Kodak, which thought it was the film, not imaging, business

And the Disease Management Care Blog agrees. Look no further than this web site of an outsider business devoted to the very services described in this Journal article.  In fact, as far back as March of 2009, the DMCB described one PHM industry veteran's challenge to make America rank #1 in the world in an overarching, comprehensive and easy understood measure of health status.

It sounded like a good idea back then.  This timely Journal article reminds us it still is.

And the good news is that the PHM service providers are already working on it.

Image from alaska.gov