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Influences of hospital information systems, indicator data collection and computation on reported Dutch hospital performance indicator scores.

ABSTRACT: BACKGROUND: For health care performance indicators (PIs) to be reliable, data underlying the PIs are required to be complete, accurate, consistent and reproducible. Given the lack of regulation of the data-systems used in the Netherlands, and the self-report based indicator scores, one would expect heterogeneity with respect to the data collection and the ways indicators are computed. This might affect the reliability and plausibility of the nationally reported scores. METHODS: We aimed to investigate the extent to which local hospital data collection and indicator computation strategies differ and how this affects the plausibility of self-reported indicator scores, using survey results of 42 hospitals and data of the Dutch national quality database. RESULTS: The data collection and indicator computation strategies of the hospitals were substantially heterogenic. Moreover, the Hip and Knee replacement PI scores can be regarded as largely implausible, which was, to a great extent, related to a limited (computerized) data registry. In contrast, Breast Cancer PI scores were more plausible, despite the incomplete data registry and limited data access. This might be explained by the role of the regional cancer centers that collect most of the indicator data for the national cancer registry, in a standardized manner. Hospitals can use cancer registry indicator scores to report to the government, instead of their own locally collected indicator scores. CONCLUSIONS: Indicator developers, users and the scientific field need to focus more on the underlying (heterogenic) ways of data collection and conditional data infrastructures. Countries that have a liberal software market and are aiming to implement a self-report based performance indicator system to obtain health care transparency, should secure the accuracy and precision of the heath care data from which the PIs are calculated. Moreover, ongoing research and development of PIs and profound insight in the clinical practice of data registration is warranted.

SUBMITTER: Anema HA

PROVIDER: S-EPMC3698115 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Influences of hospital information systems, indicator data collection and computation on reported Dutch hospital performance indicator scores.

Anema Helen A HA Kievit Job J Fischer Claudia C Steyerberg Ewout W EW Klazinga Niek S NS

BMC health services research 20130612

<h4>Background</h4>For health care performance indicators (PIs) to be reliable, data underlying the PIs are required to be complete, accurate, consistent and reproducible. Given the lack of regulation of the data-systems used in the Netherlands, and the self-report based indicator scores, one would expect heterogeneity with respect to the data collection and the ways indicators are computed. This might affect the reliability and plausibility of the nationally reported scores.<h4>Methods</h4>We a ...[more]

PMID: 23758921

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Project description:ContextThe Leapfrog Hospital Survey allows hospitals to self-report the steps they have taken toward implementing the Safe Practices for Better Healthcare endorsed by the National Quality Forum. The Leapfrog Group currently ranks hospital performance on the safe practices initiative by quartiles and presents this information to the public on its Web site. It is unknown how well a hospital's resulting Safe Practices Score (SPS) correlates with outcomes such as inpatient mortality.ObjectiveTo determine the relationship between hospitals' SPSs and risk-adjusted inpatient mortality rates.Design, setting, and participantsObservational analysis of discharge data for all urban US hospitals completing the 2006 safe practices initiative and identifiable in the Nationwide Inpatient Sample. Leapfrog provided an SPS for each hospital as well as 3 alternative scores based on shorter versions of the original survey. Hierarchical logistic regression was used to determine the relationship between quartiles of SPS and risk-adjusted inpatient mortality, after adjusting for hospital discharge volume and teaching status. Subgroup analyses were performed using data from patients older than 65 years and patients with 5% or greater expected mortality risk.Main outcome measuresInpatient risk-adjusted mortality by quartiles of survey score.ResultsOf 1075 hospitals completing the 2006 Safe Practices Survey, 155 (14%) were identifiable in the National Inpatient Sample (1,772,064 discharges). Raw observed mortality in the primary sample was 2.09%. Fully adjusted mortality rates by quartile of SPS, from lowest to highest, were 1.97% (95% confidence interval [CI], 1.78%-2.18%), 2.04% (95% CI, 1.84%-2.25%), 1.96% (95% CI, 1.77%-2.16%), and 2.00% (95% CI, 1.80%-2.22%) (P = .99 for linear trend). Results were similar in the subgroup analyses. None of the 3 alternative survey scores was associated with risk-adjusted inpatient mortality, although P values for linear trends were lower (.80, .20, and .11).ConclusionIn this sample of hospitals that completed the 2006 Safe Practices Survey, survey scores were not significantly associated with risk-adjusted inpatient mortality.

Project description:Patient-reported outcomes (PRO) have been increasingly emphasized, however, determining clinically valuable PRO has been problematic and investigation limited. This study examines the association of readiness for discharge, which has been described previously, with patient satisfaction and readmission.Data from adult patients admitted to our institution from 2009 to 2012 who completed both the Hospital Consumer Assessment of Healthcare Providers and Systems and the Press Ganey surveys post discharge were extracted from an existing database of patients (composed of 220 patients admitted for small bowel obstruction and 98 patients with hospital stays ? 21 days). Using the survey question, "Did you feel ready for discharge?" (RFD), 2 groups were constructed, those RFD and those with lesser degrees of readiness (ie, less ready for discharge [LRFD]) using topbox methodology. Outcomes, readmission rates, and satisfaction were compared between RFD and LRFD groups.Three hundred and eighteen patients met the inclusion criteria; 45% were female and 94% were Caucasian. Median age was 62.3 years (interquartile range 52.5 to 70.8 year). Median length of stay was 10 days (interquartile range 6.0 to 24.0 days) and 69.2% were admitted with small bowel obstruction. The 30-day readmission rate was 14.3% and 55% indicated they were RFD. Those RFD and LRFD had similar demographics, comorbidity scores, and rates of surgery. Those RFD had higher overall hospital satisfaction (87.3% RFD vs 62.4% LRFD; p < 0.001), higher physician communication scores (median 3.0 RFD vs 2.0 LRFD; p < 0.001), and higher nursing communication scores (median 3.0 RFD vs 2.0 LRFD, p < 0.001). Readmission rates were similar between the groups (11.4% RFD vs 18.2% LRFD; p = 0.09).Readiness for discharge appears to be a clinically useful patient-reported metric, as those RFD have higher satisfaction with the hospital and physicians. Prospective investigation into variables affecting patient satisfaction in those LRFD is needed.

Dataset Information

Influences of hospital information systems, indicator data collection and computation on reported Dutch hospital performance indicator scores.

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Influences of hospital information systems, indicator data collection and computation on reported Dutch hospital performance indicator scores.

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