Unbiased Analysis of Today's Healthcare Issues

Access to credible information on schizophrenia patients’ medication adherence by prescribers can change their treatment strategies

Written By: Jason Shafrin - Jun• 27•17

Below is the abstract for my most recent publication titled “Access to credible information on schizophrenia patients’ medication adherence by prescribers can change their treatment strategies: evidence from an online survey of providers“.  It is work with Suepattra G May, Anshu Shrestha, Charles Ruetsch, Nicole Gerlanc, Felicia Forma, Ainslie Hatch, Darius N Lakdawalla, and Jean-Pierre Lindenmayer.  The video abstract is also posted below.

Objective: Overestimating patients’ medication adherence diminishes the ability of psychiatric care providers to prescribe the most effective treatment and to identify the root causes of treatment resistance in schizophrenia. This study was conducted to determine how credible patient drug adherence information (PDAI) might change prescribers’ treatment decisions.
Methods: In an online survey containing 8 clinical case vignettes describing patients with schizophrenia, health care practitioners who prescribe antipsychotics to patients with schizophrenia were instructed to choose a preferred treatment recommendation from a set of predefined pharmacologic and non-pharmacologic options. The prescribers were randomly assigned to an experimental or a control group, with only the experimental group receiving PDAI. The primary outcome was the prescribers’ treatment choice for each case. Between-group differences were analyzed using multinomial logistic regression.
Results: A convenience sample (n=219) of prescribers completed the survey. For 3 nonadherent patient vignettes, respondents in the experimental group were more likely to choose a long-acting injectable antipsychotic compared with those in the control group (77.7% experimental vs 25.8% control; P<0.001). For 2 adherent but poorly controlled patient vignettes, prescribers who received PDAI were more likely to increase the antipsychotic dose compared with the control group (49.1% vs 39.1%; P<0.001). For the adherent and well-controlled patient vignette, respondents in both groups made similar treatment recommendations across all choices (P=0.099), but respondents in the experimental arm were more likely to recommend monitoring clinical stability (87.2% experimental vs 75.5% control, reference group).
Conclusion: The results illustrate how credible PDAI can facilitate more appropriate clinical decisions for patients with schizophrenia.


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Trials in Health Policy

Written By: Jason Shafrin - Jun• 26•17

Scientists often use randomized controlled trials (RCT) to examine whether certain treatments have a causal effect on patient outcomes.  For social scientists, however, conducting an RCT is more difficult.  Nevertheless, there have been a number of health policy trials.

In a recent NEJM paper, Newhouse and Normand (2017) review some of these trials.  A summary is below:

Trials that vary prices paid by patients:

Trials that vary reimbursement.

  • RAND Health Insurance Experiment. This experiment also randomized people between traditional fee-for-service practices and an HMO where physicians were salaried employees and the HMO received a flat per-member, per-month payment.  Their study found that patients in the HMO had fewer hospitalizations compared to those in FFS practices.
  • Randomization for treatment of LDL cholesterol (LDL-C) . Physicians in the incentives arm were eligible to receive bonus payments when their patients met LDL-C goals and in the control arm no incentative payments were made.  The physician incentives did lead to a reduction in LDL-C.

The article also provides a summary of some of the key decisions researchers need to make when designing a health policy trial.  These decisions include:

  • What Inducement, if Any, Should Be Offered to Participants?
  • How Many Sites Should There Be?
  • How Long Should the Experiment Run?
  • How Should Individual Patients or Families Be Assigned to Treatments?
  • To What Degree Should Groups of Special Interest Be Oversampled?
  • What Baseline Physiological Characteristics, if Any, Should Be Measured?

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Medicare’s value-based purchasing fail?

Written By: Jason Shafrin - Jun• 25•17

Value-based payment is the latest hot topic.  One question remains, however, does it work?  Does paying for quality improve quality.  A study by Zuckerman et al. (2016) finds that the hospital readmissions reduction program (HRRP) did appear to reduce re-hospitalization rates among the targeted conditions.

What about the hospital value-based purchasing program (HVBP).  Beginning in fiscal year 2013, the Affordable Care Act mandated that Medicare payments to acute care hospitals be tied to some performance metrics.  Initially the incentive payment was 1% of total reimbursement, but by FY2017, this figure has climbed to 2%.  A question is, did HVBP improve patient outcomes?

According to a study by  Ryan et al. (2017):

Our results are consistent with those from studies that have shown that HVBP did not increase quality with regard to clinical process or patient experience in its first 9 months 15 and more recent research indicating that HVBP did not reduce mortality over the first 30 months of the program.

The authors reached this conclusion by running a difference-in-difference analysis of acute care hospitals.  They compared differences in these key outcomes before and after the implementation of HVBP for acute care hospitals subject to bonuses and penalties and compared them against critical access hospitals (CAH), which were not subject to the HVBP financial incentives.

What would have worked? To be honest, that is not known.  However, the authors hypothesize that:

…alternative incentive designs — including those with simpler criteria for performance and larger financial incentives — might have led to greater improvement among hospitals.

 

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Will Better Care deliver better care?

Written By: Jason Shafrin - Jun• 23•17

The Senate’s new health care bill, the Better Care Reconciliation Act of 2017, proposes a number of changes to the Affordable Care Act.  The Kaiser Family Foundation has a detailed breakdown of the bill and compares it with the Affordable Care Act that President Obama passed and the American Health Care Act that was proposed by the House of Representatives. How should we evaluate these changes?

From an economist’s point of view, there are generally two dimensions over which one evaluates economic policy: efficiency and equity.   Efficiency asks whether the bill will increase market efficiency and improve overall social welfare.  Efficiency is not everything.  As a society we value providing support for the least fortunate among us.  Whereas maximizing efficacy is generally a good thing, equity depends on societal preferences.  No redistribution would provide little support to the poor, complete equity would lead to a communist society with little incentives for innovation or hard work.

Now back to the Better Care bill.

In terms of efficiency of health insurance markets, there is little to like.  The bill keeps in place premium subsidies for the working poor, but the value of these subsidies drops from 70% of the plan’s actuarial value to 58%.  Additionally, provisions to reduce cost sharing provisions for the poor  have been stripped.  Thus, fewer people are likely to buy insurance, particularly healthy people.  Second, the bill eliminates the individual mandate.  Thus, fewer people are likely to buy insurance, particularly healthy people.  Third, the employer mandate will be repealed meaning that fewer employers will offer insurance.   Many people may claim that the Obamacare health insurance exchanges were suboptimal.  For instance, community rating gives health insurers an incentive to provide poor care to the sickest patients to get them off their plan.  Nevertheless, a suboptimal but functional insurance market is better than one likely to go into a premium death spiral, which is likely what we have with the Better Care plan.

In terms of overall societal efficiency–taking into account things besides health care–there are some small things to like.  Taxes are lowered, which is a positive due to the deadweight loss taxes create.  For instance, distortionary taxes on specific services (e.g., health insurers, pharmaceuticals, medical devices) are dropped.  Allowing individuals to buy health insurance at 58% of actuarial value will allow more people to buy insurance, and still have funds left over for other expenses (even though some of those expenses will inevitably be out-of-pocket health care costs not covered by insurance).

In terms of equity, the plan is certainly bad for the poor.  Medicaid expansions will be rolled back over time (although not as quickly as in the AHCA).  As described above, premium and cost sharing support will decrease.   As described by Axios, the biggest winners of the bill are young healthy people who either no longer need to buy health insurance or who can buy less generous but less expensive (58% actuarial value) coverage.  The biggest losers are the poor and elderly, who will face some combination of higher premiums, or more cost sharing.  Better Care does provide some funds to States to set up high risk pools–which could be separate from the general health insurance exchanges and thus could drive down premiums–through the State Stability and Innovation Program.

In short, despite some tax cuts, there is a serious risk that the health insurance exchanges  collapse and poor and near elderly individuals are left with either no insurance or much less generous insurance.

Politically, this was much less of a repeal and replace, rather just more of the same.  According to Megan McArdle:

I called the House health care bill “Obamacare Lite,” but compared to the Senate bill, the House was offering a radical new taste sensation. The Senate bill touches very little of the underlying architecture of Obamacare; all it does is eliminate the insurance mandates, cut spending and give states somewhat more autonomy in how those dollars are spent. Repeal Obamacare, you say? They’re barely even worrying it.

 

Health Wonk Review is up

Written By: Jason Shafrin - Jun• 23•17

Joe Paduda has posted  this week’s version of the Health Wonk Review (HWR) – The double edition at Managed Care Matters.  Check it out.

I also found this very honest discussions of effects of concussions in the NFL from former player and Hall of Famer Warren Sapp.  The video is below and the article here.

Mid-week Links

Written By: Jason Shafrin - Jun• 21•17

Can physician quality be captured by a single composite measure?

Written By: Jason Shafrin - Jun• 20•17

Value-based payment for providers is often predicated on being able to measure physician quality with a single composite measures.  For instance, Medicare s Value-Based Payment Modifier (Value Modifier) combines a variety of individual quality metrics across domains to create a single quality score.  Payment to physicians is adjusted based on a combination of physician quality and resource use.

The question remains, however, whether these composite scores do a good job of measuring quality.  Martsolf, Carle, and Scanlon (2017) notes that this may not always be the case.

However, the creation of such global composite measures is not without risk. When multiple indicators measuring distinct aspects of quality are inappropriately combined into a single measure, the resulting composite measure is not useful or even completely uninterpretable. For example, when indicators measuring unrelated constructs are included in a single score, the high score on some indicators could hide low scores on other indicators or vice versa. In this case, the composite measure does not provide a clear quality signal. Inclusion of invalid composite measures could actually hurt quality reporting by leading to physician practice misclassification.”

To take a simple example, Physician A could be excellent at diagnosing a condition but poor at treatment and Physician B could be excellent at treatment but poor at diagnosis.  If this information where known to patients, and all patients went to Physician A for diagnosis and Physician B for treatment, they would both be excellent at treating the patients they do even though a composite score could rank both physicians as average. This example captures cases where quality is multidimensional.  Quality metrics also must be reliable as well and accurately capture underlying physician quality when measured across a reasonable sample size of patients.

While this argument is theoretical, the Martsolf, Carle, and Scanlon (2017) paper examines whether “HEDIS process indicators [can] be used to measure a single construct for the purpose of creating an internally valid global composite measure of physician practice quality.”  The authors use physician quality scores from the Puget Sound Health Alliance’s (PSHA) Community Checkup scorecard.  Their analytical approach was as follows:

We used measurement models (e.g., confirmatory factor analysis) to investigate the dimensionality of 19 specific physician practice quality indicators. In this case, dimensionality refers to the extent to which multiple indicators can be used to assess a single construct or multiple constructs. Specifically, the measurement model approach is used to assess the extent to which a single factor accounts for the observed covariance among indicators. Models that “fit well do a good job of reproducing the observed covariance matrix.

Using this approach, the authors’ results “…did not support the psychometric validity of a single unidimensional composite.”  The implications of these results are very interesting.  Although many payers and researchers have argued for a single quality measure for physicians and other providers, in practice this single measure may work poorly.  Thus, tying reimbursement to quality–if quality is measured using HEDIS process measures–is problematic.  In the words of the authors:

Our results may call into question efforts to create and use single unidimensional measures of physician practice quality, as using such measures can lead to spurious conclusions about quality by hiding important aspects of quality and to increased physician misclassification by exacerbating the measurement error inherent in any given measure. Particularly, performance on an invalid global measure of physician practice quality may obscure practices performance on more specific areas of clinical care.

For more details, do read the whole article.

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The Future of Oncology Treatment and Value Assessment

Written By: Jason Shafrin - Jun• 19•17

Value frameworks are all the rage of late.  But are payers really using them?

According to my colleague Jeremy Schafer, the answer is yes.  From an article in Drug Topics:

“Value assessment may become more important as the health-care market shifts to outcomes and value-based reimbursement models,” said Jeremy Schafer, PharmD, MBA, Senior Vice President and Director for Payer Access Solutions at Precision for Value… “Our research has also found that payers currently not using value frameworks either anticipate doing so in the future or are relying on internal cost-effective analyses within their organizations…The most common way payers are using value frameworks is in choosing preferred therapies, comparing products within a class, and policy/pathway development.”

The articles continues to notes a number of limitations of the current value framework, such as their ability to accurately capture a treatment’s effect on patient quality of life as well as the medication’s convenience factor (e.g., injection vs. oral).  Schafer even cites the work of the Innovation and Value Initiative, where I serve as the Director of Research.

New initiatives around value, such as one currently under development from the Innovation and Value Initiative, may also help to add transparency by allowing pharmacists and other stakeholders to measure value from a variety of perspectives within a single tool. They may also allow value measurement to be adjusted based on different methodological assumptions.

Do read the whole article.

Does more spending improve outcomes?

Written By: Jason Shafrin - Jun• 18•17

A number of studies have claimed that increased health expenditures may result in no better, or even worse outcomes.  For instance, a paper by Fisher et al. (2003) looking at patients with acute myocardial infarction, colorectal cancer, or hip fracture finds that “Quality of care in higher-spending regions was no better on most measures and was worse for several preventive care measures.”  This analysis, however, examined variation in spending and quality by hospital referral region (HRR) and could suffer from the ecological fallacy.

A recent paper by Watson et al. (2017) examines the effect of increased spending out outcomes at the individual level among patients in neonatal wards.  The authors use the National Neonatal Research Database (NNRD).  The data contain information from infants treated in neonatal units in England between 2009 and 2013.  Costs were estimated based on Helathcare Reseource Group (HRG) codes and costs per intensive care cot day were estimated.  The key outcome variable was overall mortality and a secondary outcomes were in-hospital mortality and moribidity free survival.  The key explanatory variable cost per intensive care cot day.  The regression also controlled for the baby’s gender, gestational age, birth weight, and mother’s receipt of steroids as well as year, ward, and ward-year fixed effects. To control for the potential endogeneity, the authors also ran a fixed-effects instrumental variables (FE-IV) regression using patient distance to the nearest hospital as a instrument for the unit providing the treatment.

Using this approach, they found:

…a £100 increase in the cost per intensive care cot day (sample average cost: £1,127) is estimated to reduce the risk of mortality of 0.38 percentage points (sample average mortality: 11.0%) in neonatal intensive care. This translates into a cost per life saved in neonatal intensive care of approximately £420,000.

Their estimates for their secondary outcome also suggest that “reductions in the mortality rate are accompanied by equivalent rises in morbidity.”

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Quotation of the day: Health as capital

Written By: Jason Shafrin - Jun• 15•17

The thought that health is a form of capital goes way back to the 19th century.  Max von Pettenkofer compares health and economics and health states with capital in the following quotation:

Just as the effort to obtain greater profits, an not merely fear of losses, is the driving force in economics, so too it must be in hygiene as a doctrine of health.  Hygiene (as a subject) must establish and investigate all the influences exerted on the organism by its natural and artificial environment, in order to increase its well-being through this knowledge.  Health really is a form of property or capital, which is to be sure usually inherited, but which must also be acquired by its owner and can be increased as well as reduced.

This is quoted  from Death in Hamburg by Richard J. Evans, p. 242.

Pettenkofer–a Bavarian innovator– even called the subject of hygiene “health economics” to make the parallel even more explicit.