Dataset Information

Assessing the Representativeness of Medical Expenditure Panel Survey Inpatient Utilization Data for Individuals With Psychiatric and Nonpsychiatric Conditions.

ABSTRACT: Sampling and reporting biases in the Medical Expenditure Panel Survey (MEPS) survey could render data on inpatient utilization that are not representative for individuals with severe psychiatric conditions. The authors assessed the representativeness of MEPS data on psychiatric inpatient utilization, by comparing MEPS estimates of total annual psychiatric and nonpsychiatric inpatient admissions and bed days, and mean length of stay, for nonelderly U.S. adults in calendar years 2005 to 2010 (N = 9,288) to estimates from the Nationwide Inpatient Sample (NIS), a nationally representative inpatient care database derived from hospitals' administrative records (N = 21,934,378). Compared with the NIS, the MEPS indicated 34% as many psychiatric admissions and 86% as many nonpsychiatric admissions, while mean psychiatric length of stay was greater in MEPS than in NIS. In MEPS data, underrepresentation of psychiatric inpatient utilization at community hospitals may result in measurement distortions for commonly used statistics on psychiatric inpatient utilization and costs.

SUBMITTER: Slade EP

PROVIDER: S-EPMC4861401 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Assessing the Representativeness of Medical Expenditure Panel Survey Inpatient Utilization Data for Individuals With Psychiatric and Nonpsychiatric Conditions.

Slade Eric P EP Goldman Howard H HH Dixon Lisa B LB Gibbons Brent B Stuart Elizabeth A EA

Medical care research and review : MCRR 20150706 6

Sampling and reporting biases in the Medical Expenditure Panel Survey (MEPS) survey could render data on inpatient utilization that are not representative for individuals with severe psychiatric conditions. The authors assessed the representativeness of MEPS data on psychiatric inpatient utilization, by comparing MEPS estimates of total annual psychiatric and nonpsychiatric inpatient admissions and bed days, and mean length of stay, for nonelderly U.S. adults in calendar years 2005 to 2010 (N = ...[more]

PMID: 26149973

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Project description:BACKGROUND:Although antipsychotics are used for treatment of delirium/agitation in hospitalized patients, their scope of use has not been investigated in a large, multicenter cohort. OBJECTIVE:To determine rates of use and hospital variation in use of antipsychotics in nonpsychiatric admissions. DESIGN, SETTING, PATIENTS:Cohort study of adult, nonpsychiatric admissions to 300 US hospitals contributing data to the Premier database, from July 1, 2009 to June 30, 2010. MEASUREMENTS:Antipsychotic exposure defined using pharmacy charges. Potentially excessive dosing defined using guidelines for long-term care facilities. RESULTS:Our cohort included 2,695,081 admissions (median age, 63 years; 56% female). Antipsychotic exposure occurred in 160,773 (6%) admissions; 102,148 (64%) received atypical antipsychotics, 76,979 (48%) received typical, and 18,354 (11%) received both. Among exposed admissions, 47% received ?1 potentially excessive daily dose. Among the variables we analyzed, the strongest predictors of antipsychotic receipt were delirium (relative risk [RR]: 2.93, 95% CI: 2.88-2.98) and dementia (RR: 2.78, 95% CI: 2.72-2.83). After adjustment for patient characteristics, patients admitted to hospitals in the highest antipsychotic prescribing quintile were more than twice as likely to be exposed compared to patients admitted to hospitals in the lowest prescribing quintile (RR: 2.56, 95% CI: 2.50-2.61). This relationship was similar across subgroups of admissions with delirium and dementia. CONCLUSIONS:Antipsychotic medication exposure is common in nonpsychiatric admissions to US hospitals. The observed variation in antipsychotic prescribing was not fully explained by measured patient characteristics, suggesting the possibility of differing hospital prescribing cultures. Additional research and guidelines are necessary to define appropriate use of these potentially harmful medications in the hospital setting. Journal of Hospital Medicine 2016;11:543-549. © 2016 Society of Hospital Medicine.

Project description:Background: The link between body weight status and spinal diseases has been suggested by a number of cross-sectional and cohort studies with a limited range of patient populations. No population-representative samples have been used to examine the link between obesity and spinal diseases. The present study is based on a nationally representative sample drawn from the Medical Expenditure Panel Survey. Methods: Using the cross-sectional sample of the 2014 Medical Expenditure Panel Study, we built four weighted logistic regression analyses of the associations between body weight status and the following four spinal diseases: low back pain, spondylosis, other cervical disorders and intervertebral disc disorder (IDD). Each respondent's body weight status was used as the key independent variable with three categories: normal/underweight, overweight, and obese. We controlled for marital status, gender, age, smoking status, household income, health insurance coverage, educational attainment and the use of health services for other major categories of diseases. Results: A total sample of 23,048 respondents was used in our analysis. Overweight and obese respondents, as compared to normal/underweight respondents, were more likely to develop lower back problems (Overweight: logged odds = 0.218, p < 0.01; Obese: logged odds = 0.395, p < 0.001) and IDD (Overweight: logged odds = 0.441, p < 0.05; Obese: logged odds = 0.528, p < 0.001). The associations between bodyweight status and spondylitis were statistically insignificant (Overweight: logged odds = 0.281, p = 0.442; Obese: logged odds = 0.680, p = 0.104). The associations between body weight status and other cervical disorders (Overweight: logged odds = -0.116, p = 0.304; Obese: logged odds = -0.160, p = 0.865) were statistically insignificant. Conclusions: As the first study using a national sample to study bodyweight and spinal diseases, our paper supports the hypothesis that obesity adds to the burden of low back pain and IDD. Longitudinal and interventional studies are needed to understand the specific mechanisms behind these positive associations.

Project description:BackgroundA comprehensive picture of how the US population engages in specialty care use is lacking, even though redesign models focused on specialty care are becoming more popular.ObjectiveTo describe the type of provider, primary care or specialist, most often seen by individuals, to test associations between type of provider most often seen and insurance coverage, and to test associations between the number of generalist and specialist visits and insurance coverage.DesignCross-sectional analysis of 2013-2016 Medicaid Expenditure Panel Survey. Logistic and negative binomial models were used in multivariate regression modeling.ParticipantsDepending on the analysis, the study samples include between 71,402 and 79,518 US residents.Main measuresIndividuals' provider type most often seen, primary care visits, and specialist visits were reported.Key resultsMore than half of the sample (55%) predominantly visited primary care providers (or generalists), and 36% predominantly visited specialists. Among individuals primarily visiting generalists, 80% visited only one type of primary care provider, and 24% also visited one or more specialists. Among individuals primarily visiting specialists, 48% visited only one type of specialist, and 47% did not visit any generalists in the year. Among Medicare enrollees, 50% predominantly visited specialists, and 40% predominantly visited generalists. Medicare enrollment was associated with greater odds of predominantly visiting specialists (p < 0.05), and Medicare-Medicaid enrollment and having no insurance were associated with lower odds of predominantly visiting specialists (p < 0.05). Medicare enrollment was associated with 13% more generalist visits and 35% more specialist visits, and Medicare-Medicaid enrollment was associated with 38% more generalist visits and 15% more specialist visits (all p < 0.05).ConclusionsGiven the overall frequency of specialty care use and the reliance on multiple specialists in any given year, particularly among Medicare enrollees, public payers are uniquely positioned to promote specialty care redesign and champion improved coordination between specialists.

Dataset Information

Assessing the Representativeness of Medical Expenditure Panel Survey Inpatient Utilization Data for Individuals With Psychiatric and Nonpsychiatric Conditions.

Publications

Assessing the Representativeness of Medical Expenditure Panel Survey Inpatient Utilization Data for Individuals With Psychiatric and Nonpsychiatric Conditions.

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