HealthLawProf Blog

Editor: Katharine Van Tassel
Akron Univ. School of Law

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Thursday, October 17, 2013

Dartmouth Institute Publishes Atlas of Medicare Part D Areal Variations

The Dartmouth Institute has just published its Atlas of areal differences in utilization of prescription drugs by Medicare Part D recipients.  The Atlas--unsurprisingly but disturbingly--details significant differences.  Pharmaceutical interventions are classified as effective, discretionary (where there is diagnostic or therapeutic uncertainty), and likely to be harmful in the patient population at issue.  A caveat, however, is that the report measured prescriptions filled and thus may underestimate actual provider behavior.

An initial variation involved sheer numbers of prescriptions, with a high average of 63 per year in Miami and a low average of 39 per year in Colorado (overall, the average was 49 standardized 30 day prescriptions filled per year per Part D beneficiary).  In general, the Mountain West had the lowest prescription average and the Rust Belt and Appalachian states the highest.  These differences could not be explained primarily by overall burden of disease but instead appear to reflect variations in provider prescribing practices.  For example, the American Heart Association recommends use of beta blockers in heart attack patients for three years post-attack.  However, rates of prescriptions for these drugs in the first six months ranged from highs of 94% to lows of under 68%, and persistence in the next six months was only slightly lower, ranging from highs of 92% to lows of under 68%.  Variations in statin use were even greater, ranging from just over 91% in Ogden, Utah, to below 45% in Abilene, Texas.  Interestingly, there was little correlation between effective use of beta blockers and effective use of statins.

The other two therapies analyzed in the Atlas were treatment of diabetes and treatment of patients with fragility fractures.  Diabetic patients fared somewhat better than heart attack patients, albeit still with significant variations.  Osteoporotic patients, however, fared dismally, receiving a high of 28% and a low of 7% with filled prescriptions for drug to combat osteoporosis after fragility fractures in sites other than the hip (such treatment is recommended to decrease the risk of future hip fractures).

Most interesting of all, there was no correlation between drug expenditures and measures of effective care.  In other words, patients in some regions may be spending a great deal on their drugs (paid for under Part D), but receiving far less benefit that patients in other regions who spend a great deal less.

[LPF]

 

October 17, 2013 in Access, Chronic Care, CMS, Consumers, Cost, Drug and Device, Health Care, Health Care Costs, Medicare, Prescription Drugs, Quality, Spending | Permalink | Comments (0) | TrackBack (0)

Monday, September 23, 2013

Chilling Thoughts from Chilmark about Data Analytics and Patients

Chilmark Research produces evidence-based reports of health IT and market trends in the health IT industry.

A recently issued Chilmark report, 2013 Clinical Analytics for Population Health Market Trends Report, which I have not read because it costs $4500, details the conflicting interests of clinicians and payers with respect to insights gleaned from data analytics.  The hope of EHRs in combination with data analytics is better patient health, for example through alerts about needed preventive measures or care management strategies.  But different payment may reimburse categories of care differently--so a diabetic covered by one type of payment structure might get reminders when her counterpart with different coverage might not.  Even worse, patients whose prognosis is seen as "hopeless" through the predictive lens of analytics might get very different treatment recommendations under cost-conscious reimbursement structures.

Cora Sharma's post on the Chilmark blog details these likely conflicts with chilling precision.

[LPF]

September 23, 2013 in Access, Accountable Care Organizations, Chronic Care, Consumers, Cost, Coverage, Disparities, Electronic Medical Records, Health Care Costs, Insurance, Prevention, Private Insurance | Permalink | Comments (0) | TrackBack (0)