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Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases.

ABSTRACT: BACKGROUND:To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional variation in healthcare spending by studying prevalent chronic diseases. METHODS:We used 2012 secondary health survey data linked with claims data, healthcare supply data and demographics at the individual level for 18 Dutch regions. We studied patients with diabetes (n =?10,767) and depression (n =?3,735), in addition to the general population (n =?44,694). For all samples, we estimated the cross-sectional relationship between spending, supply and demand variables and region effects using linear mixed models. RESULTS:Regions with above (below) average spending for the general population mostly showed above (below) average spending for diabetes and depression as well. Less than 1% of the a-priori total variation in spending was attributed to the regions. For all samples, we found that individual-level demand variables explained 62-63% of the total variance. Self-reported health status was the most prominent predictor (28%) of healthcare spending. Supply variables also explained, although a small part, of regional variation in spending in the general population and depression. Demand variables explained nearly 100% of regional variation in spending for depression and 88% for diabetes, leaving 12% of the regional variation left unexplained indicating differences between regions due to inefficiencies. CONCLUSIONS:The extent to which regional variation in healthcare spending can be considered as inefficiency may differ between regions and disease-groups. Therefore, analyzing chronic diseases, in addition to the traditional approach where the general population is studied, provides more insight into the causes of regional variation in healthcare spending, and identifies potential areas for efficiency improvement and budget allocation decisions.

SUBMITTER: de Vries EF

PROVIDER: S-EPMC5934839 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases.

de Vries Eline F EF Heijink Richard R Struijs Jeroen N JN Baan Caroline A CA

BMC health services research 20180503 1

<h4>Background</h4>To indicate inefficiencies in health systems, previous studies examined regional variation in healthcare spending by analyzing the entire population. As a result, population heterogeneity is taken into account to a limited extent only. Furthermore, it clouds a detailed interpretation which could be used to inform regional budget allocation decisions to improve quality of care of one chronic disease over another. Therefore, we aimed to gain insight into the drivers of regional ...[more]

PMID: 29724215

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Project description:BackgroundSenior high cost health care users (HCU) are a priority for many governments. Little research has addressed regional variation of HCU incidence and outcomes, especially among incident HCU. This study describes the regional variation in healthcare costs and mortality across Ontario's health planning districts [Local Health Integration Networks (LHIN)] among senior incident HCU and non-HCU and explores the relationship between healthcare spending and mortality.MethodsWe conducted a retrospective population-based matched cohort study of incident senior HCU defined as Ontarians aged ?66 years in the top 5% most costly healthcare users in fiscal year (FY) 2013. We matched HCU to non-HCU (1:3) based on age, sex and LHIN. Primary outcomes were LHIN-based variation in costs (total and 12 cost components) and mortality during FY2013 as measured by variance estimates derived from multi-level models. Outcomes were risk-adjusted for age, sex, ADGs, and low-income status. In a cost-mortality analysis by LHIN, risk-adjusted random effects for total costs and mortality were graphically presented together in a cost-mortality plane to identify low and high performers.ResultsWe studied 175,847 incident HCU and 527,541 matched non-HCU. On average, 94 out of 1000 seniors per LHIN were HCU (CV?=?4.6%). The mean total costs for HCU in FY2013 were 12 times higher that of non-HCU ($29,779 vs. $2472 respectively), whereas all-cause mortality was 13.6 times greater (103.9 vs. 7.5 per 1000 seniors). Regional variation in costs and mortality was lower in senior HCU compared with non-HCU. We identified greater variability in accessing the healthcare system, but, once the patient entered the system, variation in costs was low. The traditional drivers of costs and mortality that we adjusted for played little role in driving the observed variation in HCUs' outcomes. We identified LHINs that had high mortality rates despite elevated healthcare expenditures and those that achieved lower mortality at lower costs. Some LHINs achieved low mortality at excessively high costs.ConclusionsRisk-adjusted allocation of healthcare resources to seniors in Ontario is overall similar across health districts, more so for HCU than non-HCU. Identified important variation in the cost-mortality relationship across LHINs needs to be further explored.

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.).

Project description:BackgroundThe association between nonadherence to chronic medications and potentially preventable healthcare utilization and spending is largely unknown.ObjectivesTo examine the associations of chronic medication nonadherence with potentially preventable utilization and spending among patients who were prescribed diabetic medications, renin-angiotensin system antagonists (RASA) for hypertension, or statins for high cholesterol, and compare the associations by patient race/ethnicity and socioeconomic status.DesignRetrospective cohort study. Medicare fee-for-service claims data from 2013 to 2016 for 177,881 patients.MeasuresMedication nonadherence was defined as having a below 80% proportion of days covered in each 6-month interval after the index prescription. Potentially preventable utilization was measured by preventable emergency department visits and preventable hospitalizations. Potentially preventable spending was calculated as the geographically adjusted spending associated with preventable encounters.ResultsAfter adjustment for other patient characteristics, medication nonadherence was associated with a 1.7-percentage-point increase (95% confidence interval [CI]: 1.4 to 2.0 percentage points, p < 0.001) in the probability of preventable utilization among the diabetic medication cohort, a 1.7-percentage-point increase (95% CI: 1.5 to 1.9 percentage points, p < 0.001) among the RASA cohort, and a 1.0-percentage-point increase (95% CI: 0.8 to 1.1 percentage points, p < 0.001) among the statin cohort. Among patients with at least one preventable encounter, medication nonadherence was associated with $679-$898 increased preventable spending. The incremental probability of preventable utilization and incremental spending associated with nonadherence were higher among racial/ethnic minority and low socioeconomic groups.ConclusionsImproving medication adherence is a potential avenue to reducing preventable utilization and spending. Interventions are needed to address racial/ethnic and socioeconomic disparities.

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Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases.

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Unraveling the drivers of regional variation in healthcare spending by analyzing prevalent chronic diseases.

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