Measuring Prices in Health Care Markets Using Commercial Claims Data.
Ontology highlight
ABSTRACT:
SUBMITTER: Neprash HT
PROVIDER: S-EPMC4693848 | biostudies-literature | 2015 Dec
REPOSITORIES: biostudies-literature
Publications
Measuring Prices in Health Care Markets Using Commercial Claims Data.
Neprash Hannah T HT Wallace Jacob J Chernew Michael E ME McWilliams J Michael JM
Health services research 20150316 6
<h4>Objective</h4>To compare methods of price measurement in health care markets.<h4>Data sources</h4>Truven Health Analytics MarketScan commercial claims.<h4>Study design</h4>We constructed medical prices indices using three approaches: (1) a "sentinel" service approach based on a single common service in a specific clinical domain, (2) a market basket approach, and (3) a spending decomposition approach. We constructed indices at the Metropolitan Statistical Area level and estimated correlation ...[more]
Similar Datasets
Project description:ObjectiveTo compare different methods of indexing health care service prices for the commercially insured population across geographic markets.Data sourcesHealth Care Cost Institute commercial claims data from 2012 to 2016.Study designWe compare price indices computed using methods with differing levels of computational intensity: weighted-average versus regression-based methods. We separately compute indices of the prices paid for set of common inpatient and set of common outpatient services in different markets across the United States using each type of method. We subsequently examined the variation of and correlations between the resulting index values.Data collection/extraction methodsWe computed health care service price indices separately using samples of inpatient and outpatient facility claims from 2012 to 2016 across 112 Core-Based Statistical Areas. Within each category of services, claims were limited to members under the age of 65 with employer-sponsored insurance. Both samples were limited to a common set of services that made up nearly 80 percent of the service use in the full sample every year.Principal findingsWe found that the methods studied produced highly correlated price indices (r > .94) with similar distributions across years for both inpatient and outpatient services.ConclusionsOur findings suggest that weighted-average methods, which are much less computationally intensive, will generate results similar to regression-based methods.
| S-EPMC6980960 | biostudies-literature
Project description:With the goal of improving clinical efficiency and effectiveness, programs to enhance care coordination are a major focus of health care reform.To examine whether "care density"--a claims-based measure of patient sharing by office-based physicians--is associated with measures of quality. Care density is a proxy measure that may reflect how frequently a patient's doctors collaborate.Cohort study using administrative databases from 3 large commercial insurance plans.A total of 1.7 million adult patients; 31,675 with congestive heart failure, 78,530 with chronic obstructive pulmonary disease, and 240,378 with diabetes.Care density was assessed in 2008. Prevention Quality Indicators (PQIs), 30-day readmissions, and Healthcare Effectiveness Data and Information Set quality indicators were measured in the following year.Among all patients, we found that patients with the highest care density density--indicating high levels of patient sharing among their office-based physicians--had significantly lower rates of adverse events measured as PQIs compared with patients with low-care density (odds ratio=0.88; 95% confidence interval, 0.85-0.92). A significant association between care density and PQIs was also observed for patients with diabetes mellitus but not congestive heart failure or chronic obstructive pulmonary disease. Diabetic patients with higher care density scores had significantly lower odds of 30-day readmissions (odds ratio=0.68, 95% confidence interval, 0.48-0.97). Significant associations were observed between care density and Healthcare Effectiveness Data and Information Set measures although not always in the expected direction.In some settings, patients whose doctors share more patients had lower odds of adverse events and 30-day readmissions.
| S-EPMC4384684 | biostudies-literature
Project description:Tools to measure care coordination are needed to evaluate federal, state, and private sector efforts encouraging coordination to improve health outcomes and contain costs. Administrative data are a rich source of data for studying the use of medical services, thus allowing for measurement of patient level, provider level, and system measures of care coordination. Based on a review the literature and input from an expert panel, this article describes 4 key components-building blocks-of care coordination and corresponding measures. These building blocks should have utility across clinical conditions. They may be used to test hypotheses about the impact of coordinated care on medication utilization, adherence to medications, and clinical outcomes.
| S-EPMC4532896 | biostudies-literature
Project description:ObjectiveTo explore the relationship between commercial health care prices and Medicare spending/utilization across U.S. regions.Data sourcesClaims from large employers and Medicare Parts A/B/D over 2007-2009.Study designWe compared prices paid by commercial health plans to Medicare spending and utilization, adjusted for beneficiary health and the cost of care, across 301 hospital referral regions.Principal findingsA 10 percent lower commercial price (around the average level) is associated with 3.0 percent higher Medicare spending per member per year, and 4.3 percent more specialist visits (p < .01).ConclusionsCommercial health care prices are negatively associated with Medicare spending across regions. Providers may respond to low commercial prices by shifting service volume into Medicare. Further investigation is needed to establish causality.
| S-EPMC4450935 | biostudies-literature
Project description:OBJECTIVE:To examine the effects of hospital and insurer markets concentration on transaction prices for inpatient hospital services. DATA SOURCES:Measures of hospital and insurer markets concentration derived from American Hospital Association and HealthLeaders-InterStudy data are linked to 2005-2008 inpatient administrative data from Truven Health MarketScan Databases. STUDY DESIGN:Uses a reduced-form price equation, controlling for cost and demand shifters and accounting for possible endogeneity of market concentration using instrumental variables (IV) technique. PRINCIPAL FINDINGS:The findings suggest that greater hospital concentration raises prices, whereas greater insurer concentration depresses prices. A hypothetical merger between two of five equally sized hospitals is estimated to increase hospital prices by about 9 percent (p < .001). A similar merger of insurers would depress prices by about 15.3 percent (p < .001). Over the 2003-2008 periods, the estimates imply that hospital consolidation likely raised prices by about 2.6 percent, while insurer consolidation depressed prices by about 10.8 percent. Additional analysis using longer panel data and applying hospital fixed effects confirms the impact of hospital concentration on prices. CONCLUSION:The findings provide support for strong antitrust enforcement to curb rising hospital service prices and health care costs.
| S-EPMC5867178 | biostudies-literature
Project description:We provide a graphical illustration of how standard consumer and producer theory can be used to quantify the welfare loss associated with inefficient pricing in insurance markets with selection. We then show how this welfare loss can be estimated empirically using identifying variation in the price of insurance. Such variation, together with quantity data, allows us to estimate the demand for insurance. The same variation, together with cost data, allows us to estimate how insurer's costs vary as market participants endogenously respond to price. The slope of this estimated cost curve provides a direct test for both the existence and nature of selection, and the combination of demand and cost curves can be used to estimate welfare. We illustrate our approach by applying it to data on employer-provided health insurance from one specific company. We detect adverse selection but estimate that the quantitative welfare implications associated with inefficient pricing in our particular application are small, in both absolute and relative terms.
| S-EPMC3016055 | biostudies-literature
Project description:ObjectiveProportion of Days Covered (PDC) is a measure of medication adherence that uses prescription claims data to describe the proportion of days that the patient possessed medication. The objective of this study is to compare PDC and self-report as measures of oral contraceptive pills (OCPs) adherence and to identify individual-level predictors of adherence.Study designIn a sample of 384 OCP users, self-report was compared with PDC as measures of adherence over the past 3 months. Patient-level variables were examined for associations with adherence using multivariable logistic regression models.ResultsHigh adherence, defined as missing ≤1 pill per month, was 76%, 68% and 54% as measured by self-report, PDC and both measures, respectively. Younger women (ages 18-25 and 26-33 years) were significantly less likely to have high adherence on both measures than women in the 34-40 age group [adjusted odds ratio (OR) 0.20, 95% confidence interval (CI) 0.08-0.51 and adjusted OR 0.26, 95% CI 0.11-0.62, respectively). Other predictors of high adherence on both self-report and PDC measures included being in a relationship (adjusted OR 2.30, 95% CI 1.14-4.64, compared with unpartnered women), Protestant religion (adjusted OR 2.08, 95% CI 1.07-4.06, compared with women with no religious affiliation) and higher contraceptive self-efficacy (adjusted OR 1.63, 95% CI 1.03-2.58).ConclusionPDC derived from pharmacy claims, or a combination of PDC and self-report measures, may be an alternative to self-report alone for measuring OCP adherence.ImplicationsPDC may be a potential tool for measuring women's adherence to OCPs and should be validated in future studies.
| S-EPMC6540974 | biostudies-literature
Project description:BackgroundPatient and consumer access to eHealth information is of crucial importance because of its role in patient-centered medicine and to improve knowledge about general aspects of health and medical topics.ObjectivesThe objectives were to analyze and compare eHealth search patterns in a private (United States) and a public (United Kingdom) health care market.MethodsA new taxonomy of eHealth websites is proposed to organize the largest eHealth websites. An online measurement framework is developed that provides a precise and detailed measurement system. Online panel data are used to accurately track and analyze detailed search behavior across 100 of the largest eHealth websites in the US and UK health care markets.ResultsThe health, medical, and lifestyle categories account for approximately 90% of online activity, and e-pharmacies, social media, and professional categories account for the remaining 10% of online activity. Overall search penetration of eHealth websites is significantly higher in the private (United States) than the public market (United Kingdom). Almost twice the number of eHealth users in the private market have adopted online search in the health and lifestyle categories and also spend more time per website than those in the public market. The use of medical websites for specific conditions is almost identical in both markets. The allocation of search effort across categories is similar in both the markets. For all categories, the vast majority of eHealth users only access one website within each category. Those that conduct a search of two or more websites display very narrow search patterns. All users spend relatively little time on eHealth, that is, 3-7 minutes per website.ConclusionsThe proposed online measurement framework exploits online panel data to provide a powerful and objective method of analyzing and exploring eHealth behavior. The private health care system does appear to have an influence on eHealth search behavior in terms of search penetration and time spent per website in the health and lifestyle categories. Two explanations are offered: (1) the personal incentive of medical costs in the private market incentivizes users to conduct online search; and (2) health care information is more easily accessible through health care professionals in the United Kingdom compared with the United States. However, the use of medical websites is almost identical, suggesting that patients interested in a specific condition have a motivation to search and evaluate health information, irrespective of the health care market. The relatively low level of search in terms of the number of websites accessed and the average time per website raise important questions about the actual level of patient informedness in both the markets. Areas for future research are outlined.
| S-EPMC5408137 | biostudies-literature
Project description:BACKGROUND:Regional population management (PM) health initiatives require insight into experienced quality of care at the regional level. Unsolicited online provider ratings have shown potential for this use. This study explored the addition of comments accompanying unsolicited online ratings to regional analyses. OBJECTIVE:The goal was to create additional insight for each PM initiative as well as overall comparisons between these initiatives by attempting to determine the reasoning and rationale behind a rating. METHODS:The Dutch Zorgkaart database provided the unsolicited ratings from 2008 to 2017 for the analyses. All ratings included both quantitative ratings as well as qualitative text comments. Nine PM regions were used to aggregate ratings geographically. Sentiment analyses were performed by categorizing ratings into negative, neutral, and positive ratings. Per category, as well as per PM initiative, word frequencies (ie, unigrams and bigrams) were explored. Machine learning-naïve Bayes and random forest models-was applied to identify the most important predictors for rating overall sentiment and for identifying PM initiatives. RESULTS:A total of 449,263 unsolicited ratings were available in the Zorgkaart database: 303,930 positive ratings, 97,739 neutral ratings, and 47,592 negative ratings. Bigrams illustrated that feeling like not being "taken seriously" was the dominant bigram in negative ratings, while bigrams in positive ratings were mostly related to listening, explaining, and perceived knowledge. Comparing bigrams between PM initiatives showed a lot of overlap but several differences were identified. Machine learning was able to predict sentiments of comments but was unable to distinguish between specific PM initiatives. CONCLUSIONS:Adding information from text comments that accompany online ratings to regional evaluations provides insight for PM initiatives into the underlying reasons for ratings. Text comments provide useful overarching information for health care policy makers but due to a lot of overlap, they add little region-specific information. Specific outliers for some PM initiatives are insightful.
| S-EPMC6937541 | biostudies-literature
Project description:Introduction: Achieving equity in health care remains a challenge for health care systems worldwide and marked inequities in access and quality of care persist. Identifying health care equity indicators is an important first step in integrating the concept of equity into assessments of health care system performance, particularly in emergency care. Methods: We conducted a systematic review of administrative data-derived health care equity indicators and their association with socioeconomic determinants of health (SEDH) in emergency care settings. Following PRISMA-Equity reporting guidelines, Ovid MEDLINE, EMBASE, PubMed, and Web of Science were searched for relevant studies. The outcomes of interest were indicators of health care equity and the associated SEDH they examine. Results: Among 29 studies identified, 14 equity indicators were identified and grouped into four categories that reflect the patient emergency care pathway. Total emergency department (ED) visits and ambulatory care-sensitive condition-related ED visits were the two most frequently used equity indicators. The studies analyzed equity based on seven SEDH: social deprivation, income, education level, social class, insurance coverage, health literacy, and financial and nonfinancial barriers. Despite some conflicting results, all identified SEDH are associated with inequalities in access to and use of emergency care. Conclusion: The use of administrative data-derived indicators in combination with identified SEDH could improve the measurement of health care equity in emergency care settings across health care systems worldwide. Using a combination of indicators is likely to lead to a more comprehensive, well-rounded measurement of health care equity than using any one indicator in isolation. Although studies analyzed focused on emergency care settings, it seems possible to extrapolate these indicators to measure equity in other areas of the health care system. Further studies elucidating root causes of health inequities in and outside the health care system are needed.
| S-EPMC8742300 | biostudies-literature