Geographic variation in fee-for-service medicare beneficiaries' medical costs is largely explained by disease burden

Drivers of Individual and Regional Variation in CMS Hierarchical Condition Categories Among Florida Beneficiaries

Objective

To explore hierarchical condition categories (HCC) risk score variation among Florida Fee for Service (FFS) Medicare beneficiaries between 2016 and 2018.

Data Sources

This study analyzed HCC risk score variation using Medicare claims data for Florida beneficiaries enrolled in Parts A & B between 2016 and 2018.

Study Design

The CMS methodology analyzed HCC risk score variation using annual mean county- and beneficiary-level risk score changes. The association between variation and beneficiary characteristics, diagnoses, and geographic location was characterized using mixed-effects negative binomial regression models.

Data Collection

Not applicable.

Principal Findings

Counties in the Northeast [marginal effect (ME)=-0.003], Central (ME=-0.021), and Southwest (ME=-0.009) Florida have relatively lower mean risk scores. A higher number of lifetime (ME=0.246) and treatable (ME=0.288) conditions were associated with higher county-level risk scores, while more preventable conditions (ME=-0.249) were associated with lower risk scores. Counties with older beneficiaries (ME=0.015) and more Blacks (ME=0.070) have higher risk scores, while having female beneficiaries reduced risk scores (ME=-0.005). Individual risk scores did not vary by age (ME=0.000), but Blacks (ME=0.001) had higher rates of variation relative to Whites, while other races had comparatively lower variation (ME=-0.003). In addition, individuals diagnosed with more lifetime (ME=0.129), treatable (ME=0.235), and preventable (ME=0.001) conditions had higher risk score variation. Most condition-specific indicators showed small associations with risk score changes; however, metastatic cancer/acute leukemia, respirator dependence/tracheostomy, and pressure ulcers of the skin were significantly associated with both types of HCC risk score variation.

Conclusion

Results showed demographics, HCC condition classifications (ie, lifetime, preventable, and treatable), and some specific conditions were associated with higher variation in mean county-level and individual risk scores. Results suggest consistent coding and reductions in the prevalence of certain treatable or preventable conditions could reduce the county and individual HCC risk score year-to-year change.

Elucidating the association between regional variation in diagnostic frequency with risk-adjusted mortality through analysis of claims data of medicare inpatients: a cross-sectional study

OBJECTIVE

The validity of risk-adjustment methods based on administrative data has been questioned because hospital referral regions with higher diagnosis frequencies report lower case-fatality rates, implying that diagnoses do not track the underlying health risk. The objective of this study is to test the hypothesis that regional variation of diagnostic frequency in inpatient records is not associated with different coding practices but a reflection of the underlying health risks.

DESIGN

We applied two stratification methods to Medicare Analysis and Provider Review data from 2009 through 2014: (1) the number of chronic conditions; and, (2) quartiles of Risk Stratification Index (RSI)-defined risk. After sorting hospital referral regions into quintiles of diagnostic frequency, we examined all-cause mortality.

SETTING

Medicare Analysis and Provider Review administrative database.

PARTICIPANTS

18 126 301 hospitalised Medicare fee-for-service beneficiaries aged 65 or older who had at least one hospital-based procedure between 2009 and 2014.

EXPOSURE

Coding frequency and baseline regional population risk factors by hospital referral region.

PRIMARY AND SECONDARY OUTCOMES AND MEASURES

One year all-cause mortality in patients having the same number of chronic conditions or within the same RSI score quartile across US health referral regions, grouped by diagnostic frequency.

RESULTS

No consistent relationship between diagnostic frequency and mortality in the risk stratum defined by number of chronic conditions was detected. In the strata defined by RSI quartile, there was no decrease in mortality as a function of diagnostic frequency. Instead, adjusted mortality was positively correlated with socioeconomic risk factors.

CONCLUSIONS

Using present-on-admission codes only, diagnostic frequency among inpatients with at least one hospital-based procedure appears to be consequent to differences in baseline population health status, rather than diagnostic coding practices. In this population, claims-based risk-adjustment using RSI appears to be useful for assessing hospital outcomes and performance.

Social Determinants of Health and Geographic Variation in Medicare per Beneficiary Spending

IMPORTANCE

Despite substantial geographic variation in Medicare per beneficiary spending in the US, little is known about the extent to which social determinants of health (SDoH) are associated with this variation.

OBJECTIVE

To determine the associations between SDoH and county-level price-adjusted Medicare per beneficiary spending.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used county-level data on 2017 Medicare fee-for-service (FFS) spending, patient demographic characteristics (eg, age and gender) and clinical risk score, supply of health care resources (eg, number of hospital beds), and SDoH measures (eg, median income and unemployment rate) from multiple sources. Multivariable regressions were used to estimate the association of the variation in spending across quintiles with SDoH.

MAIN OUTCOMES AND MEASURES

2017 county-level price-adjusted Medicare Parts A and B spending per beneficiary. SDoH measures included socioeconomic position, race/ethnicity, social relationships, and residential and community context.

RESULTS

Among 3038 counties with 33 495 776 Medicare FFS beneficiaries (18 352 336 [54.8%] women; mean [SD] age, 72 [1.5] years), mean Medicare price-adjusted per beneficiary spending for counties in the highest spending quintile was $3785 (95% CI, $3706-$3862) higher, or 49% higher, than spending for bottom-quintile counties (mean [SD] spending per beneficiary, $11 464 [735] vs $7679 [522]; P < .001). The total contribution (including through both direct and indirect pathways) of SDoH was 37.7% ($1428 of $3785) of this variation, compared with 59.8% ($2265 of $3785) by patient clinical risk, 14.5% ($549 of $3785) by supply of health care resources, and 19.8% ($751 of $3785) by patient demographic characteristics. When all factors were included within the same model, the direct contribution of SDoH was associated with 5.8% of the variation, compared with 4.6% by supply, 4.7% by patient demographic characteristics, and 62.0% by patient clinical risk.

CONCLUSIONS AND RELEVANCE

These findings suggest social determinants of health are associated with considerable proportions of geographic variation in Medicare spending. Policies addressing SDoH for disadvantaged patients in certain regions have the potential to contain health care spending and improve the value of health care; patient SDoH may need to be accounted for in publicly reported physician performance, and in value-based purchasing incentive programs for health care professionals.

Geographic variation in inpatient costs for Acute Myocardial Infarction care: Insights from Italy

Geographic variations in healthcare expenditures have been widely reported within and between countries. Nevertheless, empirical evidence on the role of organizational factors and care systems in explaining these variations is still needed. This paper aims at assessing the regional differences in hospital spending for patients hospitalized for Acute Myocardial Infarction (AMI) in Tuscany and Lombardy regions (Italy), which rank high in terms of care quality and that have been, at least until 2016, characterized by quite different governance systems. Generalized linear models are performed to estimate index, 30-day and one-year hospitalization spending adjusted for baseline covariates. A two-part model is used to estimate 31-365 day expenditure. Adjusted hospital spending for AMI patients were significantly higher in Lombardy compared with Tuscany. In Lombardy, patients experienced higher re-hospitalizations in the 31-365 days and longer length of stays than in Tuscany. On the other hand, no significant regional differences in adjusted mortality rates at both acute and longer phases were found. Comparing two regional healthcare systems which mainly differ in both the reimbursement systems and the level of integration between hospital and community services provides insights into factors potentially contributing to regional variations in spending and, therefore, in areas for efficiency improvement.

Evolution of public hospitals expenditure by healthcare area in the Spanish National Health System: the determinants to pay attention to

BACKGROUND

In Spain, hospital expenditure represents the biggest share of overall public healthcare expenditure, the most important welfare system directly run by the Autonomous Communities (ACs). Since 2001, public healthcare expenditure has increased well above the GDP growth, and public hospital expenditure increased at an even faster rate. This paper aims at assessing the evolution of need-adjusted public hospital expenditure at healthcare area level (HCA) and its association with utilisation and 'price' factors, identifying the relative contribution of ACs, as the main locus of health policy decisions.

METHODS

Ecological study on public hospital expenditure incurred in 198 (HCAs) in 16 Spanish ACs, between 2003 and 2015. Aggregated and annual log-log multilevel models, considering ACs as a cluster, were modelled using administrative data. HCA expenditure was analysed according to differences in population need, utilization and price factors. Standardised coefficients were also estimated, as well as the variance partition coefficients.

RESULTS

Between 2003 and 2015, over 59 million hospital episodes were produced in Spain for an overall expenditure of €384,200 million. Need-adjusted public hospital expenditure, at HCA level, was mainly associated to medical and surgical hospitalizations (standardized coefficients 0.32 and 0.28, respectively). The ACs explained 42% of the variance not explained by HCA utilization and 'price' factors.

CONCLUSIONS

Utilization, rather than 'price' factors, may be explaining the difference in need-adjusted public hospital expenditure at HCA level in Spain. ACs, third-payers in the fully devolved Spanish National Health System, are responsible for a great deal of the variation in hospital expenditure.

Physician report of industry gifts and quality of care

BACKGROUND

Physician financial conflict of interest is a concern in the delivery of medicine because of its possible influence on the cost and the quality of patient care. There has been an extensive discussion of the ethical, economic, and legal aspects of this issue but little direct empirical evidence of its magnitude or effects.

METHODOLOGY

A nationally representative survey (n = 4,720) was used to empirically examine physician self-report of receipt of financial gifts from the pharmaceutical and medical devices industry and its association with their ability to provide quality care.

FINDINGS

Results indicate that the vast majority of physicians receive industry gifts in various forms, and the receipt of gifts is associated with lower perceived quality of patient care. There is also an inverse relationship between the frequency of received gifts and the perceived quality of care.

PRACTICE IMPLICATIONS

Physicians need to be aware of the widespread receipt of industry gifts in medical practice and the potential adverse impact of such receipts on the delivery of care.

Emergency Department Use across 88 Small Areas after Affordable Care Act Implementation in Illinois

Introduction

This study analyzes changes in hospital emergency department (ED) visit rates before and after the 2014 Affordable Care Act (ACA) insurance expansions in Illinois. We compare the association between population insurance status change and ED visit rate change between a 24-month (2012–2013) pre-ACA period and a 24-month post-ACA (2014–2015) period across 88 socioeconomically diverse areas of Illinois.

Methods

We used annual American Community Survey estimates for 2012–2015 to obtain insurance status changes for uninsured, private, Medicaid, and Medicare (disability) populations of 88 Illinois Public Use Micro Areas (PUMAs), areas with a mean of about 90,000 age 18–64 residents. Over 12 million ED visits to 201 non-federal Illinois hospitals were used to calculate visit rates by residents of each PUMA, using population-based mapping weights to allocate visits from zip codes to PUMAs. We then estimated n=88 correlations between population insurance-status changes and changes in ED visit rates per 1,000 residents comparing the two years before and after ACA implementation.

Results

The baseline PUMA uninsurance rate ranged from 6.7% to 41.1% and there was 4.6-fold variation in baseline PUMA ED visit rates. The top quartile of PUMAs had >21,000 reductions in uninsured residents; 16 PUMAs had at least a 15,000 person increase in Medicaid enrollment. Compared to 2012–2013, 2014–2015 average monthly ED visits by the uninsured dropped 42%, but increased 42% for Medicaid and 10% for the privately insured. Areas with the largest increases in Medicaid enrollment experienced the largest growth in ED use; change in Medicaid enrollment was the only significant correlate of area change in total ED visits and explained a third of variation across the 88 PUMAs.

Conclusion

ACA implementation in Illinois accelerated existing trends towards greater use of hospital ED care. It remains to be seen whether providing better access to primary and preventive care to the formerly uninsured will reduce ED use over time, or whether ACA insurance expansion is a part of continued, long-term growth. Monitoring ED use at the local level is critical to the success of new home- and community-based care coordination initiatives.

Regional Variation of Cost of Care in the Last 12 Months of Life in Switzerland: Small-area Analysis Using Insurance Claims Data

Supplemental Digital Content is available in the text.

Background:

Health care spending increases sharply at the end of life. Little is known about variation of cost of end of life care between regions and the drivers of such variation. We studied small-area patterns of cost of care in the last year of life in Switzerland.

Methods:

We used mandatory health insurance claims data of individuals who died between 2008 and 2010 to derive cost of care. We used multilevel regression models to estimate differences in costs across 564 regions of place of residence, nested within 71 hospital service areas. We examined to what extent variation was explained by characteristics of individuals and regions, including measures of health care supply.

Results:

The study population consisted of 113,277 individuals. The mean cost of care during last year of life was 32.5k (thousand) Swiss Francs per person (SD=33.2k). Cost differed substantially between regions after adjustment for patient age, sex, and cause of death. Variance was reduced by 52%–95% when we added individual and regional characteristics, with a strong effect of language region. Measures of supply of care did not show associations with costs. Remaining between and within hospital service area variations were most pronounced for older females and least for younger individuals.

Conclusions:

In Switzerland, small-area analysis revealed variation of cost of care during the last year of life according to linguistic regions and unexplained regional differences for older women. Cultural factors contribute to the delivery and utilization of health care during the last months of life and should be considered by policy makers.

County-Level Variation in Cardiovascular Disease Mortality in the United States in 2009-2013: Comparative Assessment of Contributing Factors

We examined factors responsible for variation in cardiovascular disease (CVD) mortality across US counties in 2009-2013. We linked county-level census, survey, administrative, and vital statistics data to examine 4 sets of features: demographic factors, social and economic factors, health-care utilization and features of the environment, and population health indicators. County-level associations of these features (standardized to a mean of 0 with a standard deviation of 1) with cardiovascular deaths per 100,000 person-years among adults aged 45-74 years was modeled using 2-level hierarchical linear regression with random intercept for state. The percentage of CVD mortality variation (intercounty disparity) modeled by each set of features was quantified. Demographic composition accounted for 36% of county CVD mortality variation, and another 32% was explained after inclusion of economic/social conditions. Health-care utilization, features of the environment, and health indicators explained an additional 6% of CVD mortality variation. The largest contributors to CVD mortality levels were median income (-23.61 deaths/100,000 person-years, 95% CI: -26.95, -20.26) and percentage without a high school education (20.71 deaths/100,000 person-years, 95% CI: 16.48, 24.94). In comparison, the largest health-related contributors were health-care utilization (19.35 deaths/100,000 person-years, 95% CI: 16.36, 22.34) and CVD risk factors (4.80 deaths/100,000 person-years, 95% CI: 2.14, 7.46). Improving health-care access and decreasing the prevalence of traditional CVD risk factors may reduce county CVD mortality levels, but improving socioeconomic circumstances of disadvantaged counties will be required in order to reduce CVD mortality disparities across counties.

Predictors of regional Medicare expenditures for otolaryngology physician services

OBJECTIVE

To describe geographic variation in spending and evaluate regional Medicare expenditures for otolaryngologist services with population- and beneficiary-related factors, physician supply, and hospital system factors.

STUDY DESIGN

Cross-sectional study.

METHODS

The average regional expenditures for otolaryngology physician services were defined as the total work relative value units (wRVUs) collected by otolaryngologists in a hospital referral region (HRR) per thousand Medicare beneficiaries in the HRR. A multivariable linear regression model tested associations with regional sociodemographics (age, sex, race, income, education), the physician and hospital bed supply, and the presence of an otolaryngology residency program.

RESULTS

In 2012, the mean Medicare expenditure for otolaryngology provider services across HRRs was 224 wRVUs per thousand Medicare beneficiaries (standard deviation [SD] 104), ranging from 31 to 604 wRVUs per thousand Medicare beneficiaries. In 2013, the average Medicare expenditures for each HRR was highly correlated with expenditures collected in 2012 (Pearson correlation coefficient .997, P = .0001). Regional Medicare expenditures were independently and positively associated with otolaryngology, medical specialist, and hospital bed supply in the region, and were negatively associated with the supply of primary care physicians and presence of an otolaryngology residency program after adjusting for other factors. The magnitude of associations with physician supply and hospital factors was stronger than any population or Medicare beneficiary factor.

CONCLUSION

Wide variations in regional Medicare expenditures for otolaryngology physician services, highly stable over 2 years, were strongly associated with regional health system factors. Changes in health policy for otolaryngology care may require coordination with other physician specialties and integrated hospital systems.

LEVEL OF EVIDENCE

NA. Laryngoscope, 127:1312-1317, 2017.

Variation in Specialty Outpatient Care Patterns in the Medicare Population

BACKGROUND

Multiple payment reform efforts are under way to improve the value of care delivered to Medicare beneficiaries, yet few directly address the interface between primary and specialty care.

OBJECTIVE

To describe regional variation in outpatient visits for individual specialties and the association between specialty physician-specific payments and patient-reported satisfaction with care and health status.

DESIGN

Retrospective cross-sectional study.

PATIENTS

A 20 % random sample of Medicare fee-for-service beneficiaries in 2012.

MAIN MEASURES

Regions were grouped into quartiles of specialist index, defined as the observed/expected regional likelihood of having an outpatient visit to a specialist, for ten common specialties, adjusting for age, sex, and race. Outcomes were per capita specialty-specific physician payments and Medicare Current Beneficiary Survey responses.

KEY RESULTS

The proportion of beneficiaries seeing a specialist varied the most for endocrinology and gastroenterology (3.7- and 3.9-fold difference between the highest and lowest quartiles, respectively) and least for orthopedics and urology (1.5- and 1.7-fold difference, respectively). Multiple analyses suggested that this variation was not explained by prevalence of disease. Average specialty-specific payments were strongly associated with the likelihood of visiting a specialist. Differences in per capita payments from lowest (Q1) to highest quartiles (Q4) were greatest for cardiology ($89, $135, $172, $251) and dermatology ($46, $64, $82, $124). Satisfaction with overall care (median [interquartile range] across specialties: Q1, 93.3 % [92.6-93.7 %]; Q4, 93.1 % [92.9-93.2 %]) and self-reported health status (Q1, 37.1 % [36.9-37.7 %]; Q4, 38.2 % [37.2-38.4 %]) was similar across quartiles. Satisfaction with access to specialty care was consistently lower in the lowest quartile of specialty index (Q1, 89.7 % [89.2-91.1 %]; Q4, 94.5 % [94.4-94.8 %]).

CONCLUSIONS

Substantial regional variability in outpatient specialist visits is associated with greater payments with limited benefits in terms of patient-reported satisfaction with care or reported health status. Reducing outpatient physician visits may represent an important opportunity to improve the efficiency of care.

Regional Growth in Medicare Spending, 1992-2010

OBJECTIVE

To determine if regions with high Medicare expenditures in a given setting remain high cost over time.

DATA SOURCES/STUDY SETTING

One hundred percent of national Medicare Parts A and B fee-for-service beneficiary claims data and enrollment for 1992-2010.

STUDY DESIGN

Patients are classified into regions. Claims are price-standardized. Risk adjustment is performed at the beneficiary level using the CMS Hierarchical Condition Categories model. Correlation analyses are conducted.

DATA COLLECTION/EXTRACTION METHODS

The data were obtained through a contract with CMS for a study performed for the Institute of Medicine.

PRINCIPAL FINDINGS

High-cost regions in 1992 are likely to remain high cost in 2010. Stability in regional spending is highest in the home health, inpatient hospital, and outpatient hospital settings over this time period. Despite the persistence of a region's relative spending over time, a region's spending levels in all settings except home health tend to regress toward the mean.

CONCLUSIONS

Relatively high-cost regions tend to remain so over long periods of time, even after controlling for patient health status and geographic price variation, suggesting that the observed effect reflects real differences in practice patterns.

Estimating True Resource Costs of Outpatient Care for Medicare Beneficiaries: Standardized Costs versus Medicare Payments and Charges

OBJECTIVE

To compare standardized estimates of the true resource costs of outpatient health care to the allowable and billed charges for that care among Medicare Fee for Service (FFS) beneficiaries.

DATA SOURCES/STUDY SETTING

Medicare Carrier and Outpatient Standard Analytic (SAF) files linked to participant data in the Study of Osteoporotic Fractures from 2004 through 2010. Participants were 3,435 female Medicare Fee for Service enrollees age 80 and older recruited in one rural and three metropolitan areas of the United States.

STUDY DESIGN

We estimated standardized costs for Carrier and OP-SAF claims using Medicare payment weights, and compared them to allowable and billed charges for those claims. We used semilog linear regression to estimate the associations of age, race, bone mineral density, prior fracture, and geriatric depression scale score with allowable charges, billed charges, and standardized costs.

RESULTS

Estimated associations of patient characteristics with standardized costs were not statistically different than the associations with allowable charges (chi-squared [χ(2)]: 8.6, p = .13) but were different from associations with billed charges (χ(2): 25.5, p < .001).

CONCLUSION

Allowable charges for outpatient utilization in the Carrier file and OP-SAF may be good surrogates for standardized costs that reflect patient medical and surgical acuity.

Factors associated with variations in hospital expenditures for acute heart failure in the United States

BACKGROUND

Relatively little contemporary data are available that describe differences in acute heart failure (AHF) hospitalization expenditures as a function of patient and hospital characteristics, especially from a population-based investigation. This study aimed to evaluate factors associated with variations in hospital expenditures for AHF in the United States.

METHODS

A cross-sectional analysis using discharge data from the 2011 Nationwide Inpatient Sample, Healthcare Cost and Utilization Project, was conducted. Discharges with primary International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes for AHF in adults were included. Costs were estimated by converting Nationwide Inpatient Sample charge data using the Healthcare Cost and Utilization Project Cost-to-Charge Ratio File. Discharges with highest (≥80th percentile) versus lowest (≤20th percentile) costs were compared for patient characteristics, hospital characteristics, utilization of procedures, and outcomes.

RESULTS

Of the estimated 1 million AHF hospital discharges, the mean cost estimates were $10,775 per episode. Younger age, higher percentage of obesity, atrial fibrillation, pulmonary disease, fluid/electrolyte disturbances, renal insufficiency, and greater number of cardiac/noncardiac procedures were observed in stays with highest versus lowest costs. Highest-cost discharges were more likely to be observed in urban and teaching hospitals. Highest-cost AHF discharges also had 5 times longer length of stay, were 9 times more costly, and had higher in-hospital mortality (5.6% vs 3.5%) compared with discharges with lowest costs (all P < .001).

CONCLUSIONS

Acute heart failure hospitalizations are costly. Expenditures vary markedly among AHF hospitalizations in the United States, with substantial differences in patient and hospital characteristics, procedures, and in-hospital outcomes among discharges with highest compared with lowest costs.

Understanding regional variation in Medicare expenditures for initial episodes of prostate cancer care

OBJECTIVES

To evaluate the contributions of patient and treatment factors to overall expenditures and regional variation for initial treatment of localized prostate cancer (CaP) in the Medicare program.

RESEARCH DESIGN

Using the Surveillance, Epidemiology, and End Results-Medicare database, we identified 47,517 beneficiaries with localized CaP during 2005-2009 and matched noncancer controls. We employed hierarchical generalized linear models to estimate risk-standardized cancer-related expenditures for each hospital referral region. To identify key contributors to the variation, we sequentially added patient characteristics, treatment intensity (the percentage of patients receiving curative treatments), ancillary procedures (biopsy, hormone therapy, and imaging), and specific treatment modalities into the model. We categorized the expenditures according to the type of services to identify their relative impact on the expenditure variations.

RESULTS

The mean expenditure on CaP-related care per CaP beneficiary was $15,900, including $1800 on surgery, $11,200 on radiotherapy, and $1900 on ancillary procedures. The expenditure difference between quintiles 5 and 1 was $6200. Patient characteristics explained 8.4% of this difference. Treatment intensity and treatment modalities accounted for an additional 21.2% and 31.2% of the variation, respectively. Between the highest and lowest expenditure quintiles, the difference in radiotherapy expenditure was $5000, whereas that in surgery or ancillary procedures was <$200.

CONCLUSIONS

There is substantial geographic variation in CaP expenditures, and the specific modality of radiotherapy is the most important contributor to this variation. Efforts to address the CaP care costs, such as bundled payment development, require targeting both treatment intensity and use of costly modalities.

Building a health care workforce for the future: more physicians, professional reforms, and technological advances

Traditionally, projections of US health care demand have been based upon a combination of existing trends in usage and idealized or expected delivery system changes. For example, 1990s health care demand projections were based upon an expectation that delivery models would move toward closed, tightly managed care networks and would greatly decrease the demand for subspecialty care. Today, however, a different equation is needed on which to base such projections. Realistic workforce planning must take into account the fact that expanded access to health care, a growing and aging population, increased comorbidity, and longer life expectancy will all increase the use of health care services per capita over the next few decades--at a time when the number of physicians per capita will begin to drop. New technologies and more aggressive screening may also change the equation. Strategies to address these increasing demands on the health system must include expanded physician training.

Variation in inpatient hospital prices and outpatient service quantities drive geographic differences in private spending in Texas

OBJECTIVE

To measure the contribution of market-level prices, utilization, and health risk to medical spending variation among the Blue Cross Blue Shield of Texas (BCBSTX) privately insured population and the Texas Medicare population.

DATA SOURCES

Claims data for all BCBSTX members and publicly available CMS data for Texas in 2011.

STUDY DESIGN

We used observational data and decomposed overall and service-specific spending into health status and health status adjusted utilization and input prices and input prices adjusted for the BCBSTX and Medicare populations.

PRINCIPAL FINDINGS

Variation in overall BCBSTX spending across HRRs appeared driven by price variation, whereas utilization variation factored more prominently in Medicare. The contribution of price to spending variation differed by service category. Price drove inpatient spending variation, while utilization drove outpatient and professional spending variation in BCBSTX. The context in which negotiations occur may help explain the patterns across services.

CONCLUSIONS

The conventional wisdom that Medicare does a better job of controlling prices and private plans do a better job of controlling volume is an oversimplification. BCBSTX does a good job of controlling outpatient and professional prices, but not at controlling inpatient prices. Strategies to manage the variation in spending may need to differ substantially depending on the service and payer.

Geographic variations in the cost of treating condition-specific episodes of care among Medicare patients

OBJECTIVES

To measure geographic variations in treatment costs for specific conditions, explore the consistency of these patterns across conditions, and examine how service mix and population health factors are associated with condition-specific and total area costs.

DATA SOURCES

Medicare claims for 1.5 million elderly beneficiaries from 60 community tracking study (CTS) sites who received services from 5,500 CTS Physician Survey respondents during 2004-2006.

STUDY DESIGN

Episodes of care for 10 costly and common conditions were formed using Episode Treatment Group grouper software. Episode and total annual costs were calculated, adjusted for price, patient demographics, and comorbidities. We correlated episode costs across sites and examined whether episode service mix and patient health were associated with condition-specific and total per-beneficiary costs.

PRINCIPAL FINDINGS

Adjusted episode costs varied from 34 to 68 percent between the most and least expensive site quintiles. Area mean costs were only weakly correlated across conditions. Hospitalization rates, surgery rates, and specialist involvement were associated with site episode costs, but local population health indicators were most related to site total per-beneficiary costs.

CONCLUSIONS

Population health appears to drive local per-beneficiary Medicare costs, whereas local practice patterns likely influence condition-specific episode costs. Reforms should be flexible to address local conditions and practice patterns.