Quality Variation and its Impact on Costs and Satisfaction

Global Health Sciences, University of California, San Francisco, CA 94105, USA.
Medical care (Impact Factor: 3.23). 12/2009; 48(1):25-30. DOI: 10.1097/MLR.0b013e3181bd47b2
Source: PubMed


Improving the quality of inpatient hospital care is increasingly attainable in a variety of settings. However, the relationship between rising quality and costs is unclear; similarly the relationship between varying levels of quality and a patient's satisfaction remains poorly defined.
We use data from the Quality Improvement Demonstration Study (QIDS) based in 30 district hospitals in the Philippines. There were 974 children in the study; these children were cared for by 43 physicians. To measure quality of care, the physicians completed vignettes, a valid and inexpensive measure. Patient exit surveys were given to parents of children on the day of discharge, collecting information on services and hospital charges for the inpatient stay, payment sources for the hospitalization, and the Patient Satisfaction Survey (PSQ-18).
We found a nonlinear relationship between quality and hospital charges: at low levels of quality improvements are linked to lower hospital charges. However, as quality improves further, these changes lead to higher charges. Higher quality also demonstrated a similar nonlinear relationship with patient satisfaction.
The U-shaped association between quality and hospital charges suggests that targeting the lowest quality providers may decrease costs. The similar relationship between patient-reported satisfaction and quality improvement suggests that investments in quality will raise satisfaction, perhaps even when charges are increased.

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    • "Reducing variation in quality can decrease costs if the care ‘gap’ is large, but costs increase as the gap narrows until there is a net expense [52]. Evaluation of care bundle implementation in some secondary care settings has found them to be cost-effective [53]. "
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    ABSTRACT: Background A significant minority of patients do not receive all the evidence-based care recommended for their conditions. Health care quality may be improved by reducing this observed variation. Composite measures offer a different patient-centred perspective on quality and are utilized in acute hospitals via the ‘care bundle’ concept as indicators of the reliability of specific (evidence-based) care delivery tasks and improved outcomes. A care bundle consists of a number of time-specific interventions that should be delivered to every patient every time. We aimed to apply the care bundle concept to selected QOF data to measure the quality of evidence-based care provision. Methods Care bundles and components were selected from QOF indicators according to defined criteria. Five clinical conditions were suitable for care bundles: Secondary Prevention of Coronary Heart Disease (CHD), Stroke & Transient Ischaemic Attack (TIA), Chronic Kidney Disease (CKD), Chronic Obstructive Pulmonary Disease (COPD) and Diabetes Mellitus (DM). Each bundle has 3-8 components. A retrospective audit was undertaken in a convenience sample of nine general medical practices in the West of Scotland. Collected data included delivery (or not) of individual bundle components to all patients included on specific disease registers. Practice level and overall compliance with bundles and components were calculated in SPSS and expressed as a percentage. Results Nine practices (64.3%) with a combined patient population of 56,948 were able to provide data in the format requested. Overall compliance with developed QOF-based care bundles (composite measures) was as follows: CHD 64.0%, range 35.0-71.9%; Stroke/TIA 74.1%, range 51.6-82.8%; CKD 69.0%, range 64.0-81.4%; and COPD 82.0%, range 47.9-95.8%; and DM 58.4%, range 50.3-65.2%. Conclusions In this small study compliance with individual QOF-based care bundle components was high, but overall (‘all or nothing’) compliance was substantially lower. Care bundles may provide a more informed measure of care quality than existing methods. However, the acceptability, feasibility and potential impact on clinical outcomes are unknown.
    BMC Health Services Research 10/2012; 12(1):351. DOI:10.1186/1472-6963-12-351 · 1.71 Impact Factor

  • Medical care 06/2010; 48(6):570; author reply 570-1. DOI:10.1097/MLR.0b013e3181e0b277 · 3.23 Impact Factor
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    ABSTRACT: The merits of using financial incentives to improve clinical quality have much appeal, yet few studies have rigorously assessed the potential benefits. The uncertainty surrounding assessments of quality can lead to poor policy decisions, possibly resulting in increased cost with little or no quality improvement, or missed opportunities to improve care. We conducted an experiment involving physicians in thirty Philippine hospitals that overcomes many of the limitations of previous studies. We measured clinical performance and then examined whether modest bonuses equal to about 5 percent of a physician's salary, as well as system-level incentives that increased compensation to hospitals and across groups of physicians, led to improvements in the quality of care. We found that both the bonus and system-level incentives improved scores in a quality measurement system used in our study by ten percentage points. Our findings suggest that when careful measurement is combined with the types of incentives we studied, there may be a larger impact on quality than previously recognized.
    Health Affairs 04/2011; 30(4):773-81. DOI:10.1377/hlthaff.2009.0782 · 4.97 Impact Factor
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