Dataset Information

Visualizing nationwide variation in medicare Part D prescribing patterns.

ABSTRACT:

Background

To characterize the regional and national variation in prescribing patterns in the Medicare Part D program using dimensional reduction visualization methods.

Methods

Using publicly available Medicare Part D claims data, we identified and visualized regional and national provider prescribing profile variation with unsupervised clustering and t-distributed stochastic neighbor embedding (t-SNE) dimensional reduction techniques. Additionally, we examined differences between regionally representative prescribing patterns for major metropolitan areas.

Results

Distributions of prescribing volume and medication diversity were highly skewed among over 800,000 Medicare Part D providers. Medical specialties had characteristic prescribing patterns. Although the number of Medicare providers in each state was highly correlated with the number of Medicare Part D enrollees, some states were enriched for providers with >?10,000 prescription claims annually. Dimension-reduction, hierarchical clustering and t-SNE visualization of drug- or drug-class prescribing patterns revealed that providers cluster strongly based on specialty and sub-specialty, with large regional variations in prescribing patterns. Major metropolitan areas had distinct prescribing patterns that tended to group by major geographical divisions.

Conclusions

This work demonstrates that unsupervised clustering, dimension-reduction and t-SNE visualization can be used to analyze and visualize variation in provider prescribing patterns on a national level across thousands of medications, revealing substantial prescribing variation both between and within specialties, regionally, and between major metropolitan areas. These methods offer an alternative system-wide and pattern-centric view of such data for hypothesis generation, visualization, and pattern identification.

SUBMITTER: Rosenberg A

PROVIDER: S-EPMC6245567 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Publications

Visualizing nationwide variation in medicare Part D prescribing patterns.

Rosenberg Alexander A Fucile Christopher C White Robert J RJ Trayhan Melissa M Farooq Samir S Quill Caroline M CM Nelson Lisa A LA Weisenthal Samuel J SJ Bush Kristen K Zand Martin S MS

BMC medical informatics and decision making 20181119 1

<h4>Background</h4>To characterize the regional and national variation in prescribing patterns in the Medicare Part D program using dimensional reduction visualization methods.<h4>Methods</h4>Using publicly available Medicare Part D claims data, we identified and visualized regional and national provider prescribing profile variation with unsupervised clustering and t-distributed stochastic neighbor embedding (t-SNE) dimensional reduction techniques. Additionally, we examined differences between ...[more]

PMID: 30454029

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Project description:ImportanceIn response to the opioid epidemic, policies aiming to reduce opioid prescribing, misuse, and abuse may have the unintended consequence of restricting access to necessary opioid therapy for cancer-related pain. It is unknown how opioid prescribing patterns have changed among generalists and oncologists during this era.ObjectiveTo examine trends in opioid prescription rates for Medicare Part D beneficiaries from 2013 to 2017 among oncologists and generalists.Design, setting, and participantsThis repeated cross-sectional study of generalist physicians (internal medicine, family medicine, geriatric medicine, general practice) and oncology specialists (medical oncology, hematology-oncology, and radiation oncology) analyzed the Medicare Provider Utilization and Payment Data: Part D prescriber files from 2013 to 2017.ExposuresGeneralist vs oncology specialty.Main outcomes and measuresOutcomes included physician-level rates of both opioid and long-acting opioid prescriptions per 100 Medicare Part D beneficiaries. Poisson regression was used to estimate annual predicted outcome rates and incidence rate ratios, adjusting for prescriber characteristics and state fixed effects.ResultsWe analyzed the prescribing patterns of 251 820 generalists and 14 210 oncologists. From 2013 to 2017, the annual adjusted predicted mean rate of opioid prescriptions per 100 Medicare beneficiaries decreased from 68.2 to 49.7 among generalists (adjusted incidence rate ratio [aIRR] = 0.73; 95% CI, 0.73-0.73) and from 77.8 to 58.8 among oncologists (aIRR = 0.76; 95% CI, 0.74-0.77). The rate of long-acting opioid prescriptions per 100 Medicare beneficiaries also decreased from 8.0 to 5.4 for generalists (aIRR = 0.67; 95% CI, 0.66-0.68) and from 18.6 to 13.3 for oncologists (aIRR = 0.72; 95% CI, 0.69-0.74).Conclusions and relevanceWe found large declines in opioid prescription rates for Medicare beneficiaries by generalists and oncologists from 2013 to 2017. Opioid policy and advocacy appear to have been effective in reducing the extent of opioid prescribing in the Medicare population. Similar declines between generalists and oncologists raise concern that access to cancer pain management may have been inadvertently restricted. How much of the decrease in prescribing by oncologists is appropriate vs inappropriate deserves further investigation.

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Project description:BackgroundSources of regional variation in spending for prescription drugs under Medicare Part D are poorly understood, and such variation may reflect differences in health status, use of effective treatments, or selection of branded drugs over lower-cost generics.MethodsWe analyzed 2008 Medicare data for 4.7 million beneficiaries for prescription-drug use and expenditures overall and in three drug categories: angiotensin-converting-enzyme (ACE) inhibitors and angiotensin-receptor blockers (ARBs), 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins), and selective serotonin-reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs). Differences in per capita expenditures across hospital-referral regions (HRRs) were decomposed into annual prescription volume and cost per prescription. The ratio of prescriptions filled as branded drugs to all prescriptions filled was calculated. We adjusted all measures for demographic, socioeconomic, and health-status differences.ResultsMean adjusted per capita pharmaceutical spending ranged from $2,413 in the lowest to $3,008 in the highest quintile of HRRs. Most (75.9%) of that difference was attributable to the cost per prescription ($53 vs. $63). Regional differences in cost per prescription explained 87.5% of expenditure variation for ACE inhibitors and ARBs and 56.3% for statins but only 36.1% for SSRIs and SNRIs. The ratio of branded-drug to total prescriptions, which correlated highly with cost per prescription, ranged across HRRs from 0.24 to 0.45 overall and from 0.24 to 0.55 for ACE inhibitors and ARBs, 0.29 to 0.60 for statins, and 0.15 to 0.51 for SSRIs and SNRIs.ConclusionsRegional variation in Medicare Part D spending results largely from differences in the cost of drugs selected rather than prescription volume. A reduction in branded-drug use in some regions through modification of Part D plan benefits might lower costs without reducing quality of care. (Funded by the National Institute on Aging and others.).

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Dataset Information

Visualizing nationwide variation in medicare Part D prescribing patterns.

Background

Methods

Results

Conclusions

Publications

Visualizing nationwide variation in medicare Part D prescribing patterns.

Similar Datasets

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