Dataset Information

Effects of survey mode, patient mix, and nonresponse on CAHPS hospital survey scores.

ABSTRACT:

Objective

To evaluate the need for survey mode adjustments to hospital care evaluations by discharged inpatients and develop the appropriate adjustments.

Data source

A total of 7,555 respondents from a 2006 national random sample of 45 hospitals who completed the CAHPS Hospital (HCAHPS [Hospital Consumer Assessments of Healthcare Providers and Systems]) Survey.

Study design/data collection/extraction methods

We estimated mode effects in linear models that predicted each HCAHPS outcome from hospital-fixed effects and patient-mix adjustors.

Principal findings

Patients randomized to the telephone and active interactive voice response (IVR) modes provided more positive evaluations than patients randomized to mail and mixed (mail with telephone follow-up) modes, with some effects equivalent to more than 30 percentile points in hospital rankings. Mode effects are consistent across hospitals and are generally larger than total patient-mix effects. Patient-mix adjustment accounts for any nonresponse bias that could have been addressed through weighting.

Conclusions

Valid comparisons of hospital performance require that reported hospital scores be adjusted for survey mode and patient mix.

SUBMITTER: Elliott MN

PROVIDER: S-EPMC2677051 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

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Publications

Effects of survey mode, patient mix, and nonresponse on CAHPS hospital survey scores.

Elliott Marc N MN Zaslavsky Alan M AM Goldstein Elizabeth E Lehrman William W Hambarsoomians Katrin K Beckett Megan K MK Giordano Laura L

Health services research 20090401 2 Pt 1

<h4>Objective</h4>To evaluate the need for survey mode adjustments to hospital care evaluations by discharged inpatients and develop the appropriate adjustments.<h4>Data source</h4>A total of 7,555 respondents from a 2006 national random sample of 45 hospitals who completed the CAHPS Hospital (HCAHPS [Hospital Consumer Assessments of Healthcare Providers and Systems]) Survey.<h4>Study design/data collection/extraction methods</h4>We estimated mode effects in linear models that predicted each HCA ...[more]

PMID: 19317857

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Project description:To isolate hospital effects on risk-standardized hospital-readmission rates, we examined readmission outcomes among patients who had multiple admissions for a similar diagnosis at more than one hospital within a given year.We divided the Centers for Medicare and Medicaid Services hospital-wide readmission measure cohort from July 2014 through June 2015 into two random samples. All the patients in the cohort were Medicare recipients who were at least 65 years of age. We used the first sample to calculate the risk-standardized readmission rate within 30 days for each hospital, and we classified hospitals into performance quartiles, with a lower readmission rate indicating better performance (performance-classification sample). The study sample (identified from the second sample) included patients who had two admissions for similar diagnoses at different hospitals that occurred more than 1 month and less than 1 year apart, and we compared the observed readmission rates among patients who had been admitted to hospitals in different performance quartiles.In the performance-classification sample, the median risk-standardized readmission rate was 15.5% (interquartile range, 15.3 to 15.8). The study sample included 37,508 patients who had two admissions for similar diagnoses at a total of 4272 different hospitals. The observed readmission rate was consistently higher among patients admitted to hospitals in a worse-performing quartile than among those admitted to hospitals in a better-performing quartile, but the only significant difference was observed when the patients were admitted to hospitals in which one was in the best-performing quartile and the other was in the worst-performing quartile (absolute difference in readmission rate, 2.0 percentage points; 95% confidence interval, 0.4 to 3.5; P=0.001).When the same patients were admitted with similar diagnoses to hospitals in the best-performing quartile as compared with the worst-performing quartile of hospital readmission performance, there was a significant difference in rates of readmission within 30 days. The findings suggest that hospital quality contributes in part to readmission rates independent of factors involving patients. (Funded by Yale-New Haven Hospital Center for Outcomes Research and Evaluation and others.).

Dataset Information

Effects of survey mode, patient mix, and nonresponse on CAHPS hospital survey scores.

Objective

Data source

Study design/data collection/extraction methods

Principal findings

Conclusions

Publications

Effects of survey mode, patient mix, and nonresponse on CAHPS hospital survey scores.

Similar Datasets

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