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Demographic factors and hospital size predict patient satisfaction variance--implications for hospital value-based purchasing.

ABSTRACT: Hospital Value-Based Purchasing (HVBP) incentivizes quality performance-based healthcare by linking payments directly to patient satisfaction scores obtained from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys. Lower HCAHPS scores appear to cluster in heterogeneous population-dense areas and could bias Centers for Medicare & Medicaid Services (CMS) reimbursement.Assess nonrandom variation in patient satisfaction as determined by HCAHPS.Multivariate regression modeling was performed for individual dimensions of HCAHPS and aggregate scores. Standardized partial regression coefficients assessed strengths of predictors. Weighted Individual (hospital) Patient Satisfaction Adjusted Score (WIPSAS) utilized 4 highly predictive variables, and hospitals were reranked accordingly.A total of 3907 HVBP-participating hospitals.There were 934,800 patient surveys by the most conservative estimate.A total of 3144 county demographics (US Census) and HCAHPS surveys.Hospital size and primary language (non-English speaking) most strongly predicted unfavorable HCAHPS scores, whereas education and white ethnicity most strongly predicted favorable HCAHPS scores. The average adjusted patient satisfaction scores calculated by WIPSAS approximated the national average of HCAHPS scores. However, WIPSAS changed hospital rankings by variable amounts depending on the strength of the predictive variables in the hospitals' locations. Structural and demographic characteristics that predict lower scores were accounted for by WIPSAS that also improved rankings of many safety-net hospitals and academic medical centers in diverse areas.Demographic and structural factors (eg, hospital beds) predict patient satisfaction scores even after CMS adjustments. CMS should consider WIPSAS or a similar adjustment to account for the severity of patient satisfaction inequities that hospitals could strive to correct.

SUBMITTER: McFarland DC

PROVIDER: S-EPMC4790720 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Demographic factors and hospital size predict patient satisfaction variance--implications for hospital value-based purchasing.

McFarland Daniel C DC Ornstein Katherine A KA Holcombe Randall F RF

Journal of hospital medicine 20150504 8

<h4>Background</h4>Hospital Value-Based Purchasing (HVBP) incentivizes quality performance-based healthcare by linking payments directly to patient satisfaction scores obtained from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys. Lower HCAHPS scores appear to cluster in heterogeneous population-dense areas and could bias Centers for Medicare & Medicaid Services (CMS) reimbursement.<h4>Objective</h4>Assess nonrandom variation in patient satisfaction as determine ...[more]

PMID: 25940305

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Project description:BACKGROUND:Starting in fiscal year 2013, the Hospital Value-Based Purchasing (HVBP) program introduced quality performance-based adjustments of up to 1% to Medicare reimbursements for acute care hospitals. METHODS:We evaluated whether quality improved more in acute care hospitals that were exposed to HVBP than in control hospitals (Critical Access Hospitals, which were not exposed to HVBP). The measures of quality were composite measures of clinical process and patient experience (measured in units of standard deviations, with a value of 1 indicating performance that was 1 standard deviation [SD] above the hospital mean) and 30-day risk-standardized mortality among patients who were admitted to the hospital for acute myocardial infarction, heart failure, or pneumonia. The changes in quality measures after the introduction of HVBP were assessed for matched samples of acute care hospitals (the number of hospitals included in the analyses ranged from 1364 for mortality among patients admitted for acute myocardial infarction to 2615 for mortality among patients admitted for pneumonia) and control hospitals (number of hospitals ranged from 31 to 617). Matching was based on preintervention performance with regard to the quality measures. We evaluated performance over the first 4 years of HVBP. RESULTS:Improvements in clinical-process and patient-experience measures were not significantly greater among hospitals exposed to HVBP than among control hospitals, with difference-in-differences estimates of 0.079 SD (95% confidence interval [CI], -0.140 to 0.299) for clinical process and -0.092 SD (95% CI, -0.307 to 0.122) for patient experience. HVBP was not associated with significant reductions in mortality among patients who were admitted for acute myocardial infarction (difference-in-differences estimate, -0.282 percentage points [95% CI, -1.715 to 1.152]) or heart failure (-0.212 percentage points [95% CI, -0.532 to 0.108]), but it was associated with a significant reduction in mortality among patients who were admitted for pneumonia (-0.431 percentage points [95% CI, -0.714 to -0.148]). CONCLUSIONS:In our study, HVBP was not associated with improvements in measures of clinical process or patient experience and was not associated with significant reductions in two of three mortality measures. (Funded by the National Institute on Aging.).

Project description:BackgroundMedicare hospital Value-based purchasing (VBP) program that links Medicare payments to quality of care will become effective from 2013. It is unclear whether specific hospital characteristics are associated with a hospital's VBP score, and consequently incentive payments.The objective of the study was to assess the association of hospital characteristics with (i) the mean VBP score, and (ii) specific percentiles of the VBP score distribution. The secondary objective was to quantify the associations of hospital characteristics with the VBP score components: clinical process of care (CPC) score and patient satisfaction score.MethodsObservational analysis that used data from three sources: Medicare Hospital Compare Database, American Hospital Association 2010 Annual Survey and Medicare Impact File. The final study sample included 2,491 U.S. acute care hospitals eligible for the VBP program. The association of hospital characteristics with the mean VBP score and specific VBP score percentiles were assessed by ordinary least square (OLS) regression and quantile regression (QR), respectively.ResultsVBP score had substantial variations, with mean score of 30 and 60 in the first and fourth quartiles of the VBP score distribution. For-profit status (vs. non-profit), smaller bed size (vs. 100-199 beds), East South Central region (vs. New England region) and the report of specific CPC measures (discharge instructions, timely provision of antibiotics and beta blockers, and serum glucose controls in cardiac surgery patients) were positively associated with mean VBP scores (p<0.01 in all). Total number of CPC measures reported, bed size of 400-499 (vs. 100-199 beds), a few geographic regions (Mid-Atlantic, West North Central, Mountain and Pacific) compared to the New England region were negatively associated with mean VBP score (p<0.01 in all). Disproportionate share index, proportion of Medicare and Medicaid days to total inpatient days had significant (p<0.01) but small effects. QR results indicate evidence of differential effects of some of the hospital characteristics across low-, medium- and high-quality providers.ConclusionsAlthough hospitals serving the poor and the elderly are more likely to score lower under the VBP program, the correlation appears small. Profit status, geographic regions, number and type of CPC measures reported explain the most variation among scores.

Project description:BackgroundPatient satisfaction is one proxy indicator of the health care quality; however, enhancing patient satisfaction in low-income settings is very challenging due to the inadequacy of resources as well as low health literacy among patients. In this study, we assess patient satisfaction and its correlates in a tertiary public hospital in Nepal.MethodsWe conducted a cross sectional study at outpatient department of Bhaktapur Hospital of Nepal. To recruit participants for the study, we applied a systematic random sampling method. Our study used a validated Patient Satisfaction Questionnaire III (PSQ-III) developed by RAND Corporation including various contextual socio-demographic characteristics. We calculated mean score and percentages of satisfaction across seven dimensions of patient satisfaction. To determine the association between various dimensions of patient satisfaction and socio-demographic characteristics of the patient, we used a multi-ordinal logistic regression.ResultsAmong 204 patients, we observed a wide variation in patient satisfaction across seven dimensions. About 39% of patients were satisfied in the dimension of general satisfaction, 92% in interpersonal manner, and 45% in accessibility and convenience. Sociodemographic factors such as age (AOR: 6.42; CI: 1.30-35.05), gender (AOR: 2.81; CI: 1.41-5.74), and ethnicity (AOR: 0.26; CI: 0.08-0.77) were associated with general satisfaction of the patients. Other sociodemographic variables such as education, occupation, and religion were associated with a majority of the dimensions of patient satisfaction (p < 0.05). Age was found to be the strongest predictor of patient satisfaction in five out of seven dimensions.ConclusionsWe concluded that patient satisfaction varies across different dimensions. Therefore, targeted interventions that direct to improve the dimensions of patient satisfaction where the proportion of satisfaction is low are needed. Similar studies should be conducted regularly at different levels of health facilities across the country to capture a wider picture of patient satisfaction at various levels.

Project description:BackgroundWe used a validated inpatient satisfaction questionnaire to evaluate the health care received by patients admitted to several hospitals. This questionnaire was factored into distinct domains, creating a score for each to assist in the analysis. We evaluated possible predictors of patient satisfaction in relation to socio-demographic variables, history of admission, and survey logistics.MethodsCross-sectional study of patients discharged from four acute care general hospitals. Random sample of 650 discharged patients from the medical and surgical wards of each hospital during February and March 2002. A total of 1,910 patients responded to the questionnaire (73.5%). Patient satisfaction was measured by a validated questionnaire with six domains: information, human care, comfort, visiting, intimacy, and cleanliness. Each domain was scored from 0 to 100, with higher scores indicating higher levels of patient satisfaction.ResultsIn the univariate analysis, age was related to all domains except visiting; gender to comfort, visiting, and intimacy; level of education to comfort and cleanliness; marital status to information, human care, intimacy, and cleanliness; length of hospital stay to visiting and cleanliness, and previous admissions to human care, comfort, and cleanliness. The timing of the response to the mailing and who completed the questionnaire were related to all variables except visiting and cleanliness. Multivariate analysis confirmed in most cases the previous findings and added additional correlations for level of education (visiting and intimacy) and marital status (comfort and visiting).ConclusionThese results confirm the varying importance of some socio-demographic variables and length of stay, previous admission, the timing of response to the questionnaire, and who completed the questionnaire on some aspects of patient satisfaction after hospitalization. All these variables should be considered when evaluating patient satisfaction.

Project description:ObjectiveTo determine the impact of the Hospital Value-Based Purchasing (HVBP) program-the US pay for performance program introduced by Medicare to incentivize higher quality care-on 30 day mortality for three incentivized conditions: acute myocardial infarction, heart failure, and pneumonia.DesignObservational study.Setting4267 acute care hospitals in the United States: 2919 participated in the HVBP program and 1348 were ineligible and used as controls (44 in general hospitals in Maryland and 1304 critical access hospitals across the United States).Participants2 430 618 patients admitted to US hospitals from 2008 through 2013.Main outcome measures30 day risk adjusted mortality for acute myocardial infarction, heart failure, and pneumonia using a patient level linear spline analysis to examine the association between the introduction of the HVBP program and 30 day mortality. Non-incentivized, medical conditions were the comparators. A secondary outcome measure was to determine whether the introduction of the HVBP program was particularly beneficial for a subgroup of hospital-poor performers at baseline-that may benefit the most.ResultsMortality rates of incentivized conditions in hospitals participating in the HVBP program declined at -0.13% for each quarter during the preintervention period and -0.03% point difference for each quarter during the post-intervention period. For non-HVBP hospitals, mortality rates declined at -0.14% point difference for each quarter during the preintervention period and -0.01% point difference for each quarter during the post-intervention period. The difference in the mortality trends between the two groups was small and non-significant (difference in difference in trends -0.03% point difference for each quarter, 95% confidence interval -0.08% to 0.13% point difference, P=0.35). In no subgroups of hospitals was HVBP associated with better outcomes, including poor performers at baseline.ConclusionsEvidence that HVBP has led to lower mortality rates is lacking. Nations considering similar pay for performance programs may want to consider alternative models to achieve improved patient outcomes.

Project description:ImportanceThe Centers for Medicare and Medicaid Services (CMS) use point estimates of 30-day risk-standardized readmission rates (RSRRs) to compare hospitals under the Hospital Readmissions Reduction Program (HRRP). An important characteristic of this measure is that it is a point estimate with a margin of error, which may affect the CMS's ability to accurately evaluate and distinguish hospital performance in the program.ObjectiveTo determine the number and percentage of hospitals with a penalty status misclassified under the HRRP.Design, setting, and participantsThis cross-sectional study used the bayesian deconvolution method to estimate the rate of penalty status misclassification for hospitals participating in the HRRP in fiscal year 2019, using data from the CMS Hospital Compare website that were collected between July 1, 2014, and June 30, 2017. Beneficiaries of Medicare fee-for-service coverage who were 65 years or older and hospitalized with acute myocardial infarction, heart failure, or pneumonia in hospitals with 25 or more discharges per condition were included in the data set. Data analysis occurred from November 2019 to July 2020.ExposuresNone.Main outcomes and measuresThe rate of penalty status misclassification for acute myocardial infarction, heart failure, or pneumonia under the HRRP.ResultsThe study included 1633, 2626, and 2705 hospitals for acute myocardial infarction, heart failure, and pneumonia, respectively, that participated in the HRRP in fiscal year 2019. The percentages of hospitals that should have been penalized, but were not, were 20.9% (95% CI, 16.0%-25.8%) for acute myocardial infarction, 13.5% (95% CI, 9.8%-17.2%) for heart failure, and 13.2% (95% CI, 10.3%-16.1%) for pneumonia. In contrast, the percentages of hospitals that were incorrectly penalized by the HRRP were 10.1% (95% CI, 5.8%-14.4%) for acute myocardial infarction, 10.9% (95% CI, 7.2%-14.6%) for heart failure, and 12.3% (95% CI, 9.9%-14.6%) for pneumonia.Conclusions and relevanceThe margin of error associated with the 30-day RSRRs resulted in the misclassification of condition-specific penalty status for up to 31% of hospitals. These findings suggest that the hospital-level 30-day RSRR measure may not reliably distinguish hospital performance in the HRRP. This has important implications for CMS value-based programs that use risk-standardized outcomes to evaluate and compare hospital performance.

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Demographic factors and hospital size predict patient satisfaction variance--implications for hospital value-based purchasing.

Publications

Demographic factors and hospital size predict patient satisfaction variance--implications for hospital value-based purchasing.

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