Does hospital performance on process measures directly measure high quality care or is it a marker of unmeasured care?
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ABSTRACT: Objective
Quality measures may be associated with improved outcomes for two reasons. First, measured activities may directly improve care. Second, success on these measures may be a marker for other unmeasured aspects of high quality care. Our objective is to test the contribution of both possible effects.Data sources
2004 Medicare data on hospital performance from Hospital Compare and risk-adjusted mortality rates from Medicare Part A claims.Study design
We studied 3,657 acute care U.S. hospitals and compared observed differences in condition-specific hospital mortality rates based on hospital performance with expected differences in mortality from the clinical studies underlying the measures.Principal findings
Differences in observed mortality rates across U.S. hospitals are larger than what would be expected if these differences were due only to the direct effects of delivering measured care.Conclusions
Performance measures reflect care processes that both improve care directly and are also markers of elements of health care quality that are otherwise unmeasured. This finding suggests that process measures capture important information about care that is not directly measured, and that these unmeasured effects are in general larger than the measured effects.
SUBMITTER: Werner RM
PROVIDER: S-EPMC2653884 | biostudies-literature | 2008 Oct
REPOSITORIES: biostudies-literature
Publications
Does hospital performance on process measures directly measure high quality care or is it a marker of unmeasured care?
Werner Rachel M RM Bradlow Eric T ET Asch David A DA
Health services research 20071220 5 Pt 1
<h4>Objective</h4>Quality measures may be associated with improved outcomes for two reasons. First, measured activities may directly improve care. Second, success on these measures may be a marker for other unmeasured aspects of high quality care. Our objective is to test the contribution of both possible effects.<h4>Data sources</h4>2004 Medicare data on hospital performance from Hospital Compare and risk-adjusted mortality rates from Medicare Part A claims.<h4>Study design</h4>We studied 3,657 ...[more]
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Project description:BackgroundResults of associations between process and mortality indicators, both used for the external assessment of hospital care quality or public reporting, differ strongly across studies. However, most of those studies were conducted in North America or United Kingdom. Providing new evidence based on French data could fuel the international debate on quality of care indicators and help inform French policy-makers. The objective of our study was to explore whether optimal care delivery in French hospitals as assessed by their Hospital Process Indicators (HPIs) is associated with low Hospital Standardized Mortality Ratios (HSMRs).MethodsThe French National Authority for Health (HAS) routinely collects for each hospital located in France, a set of mandatory HPIs. Five HPIs were selected among the process indicators collected by the HAS in 2009. They were measured using random samples of 60 to 80 medical records from inpatients admitted between January 1st, 2009 and December 31, 2009 in respect with some selection criteria. HSMRs were estimated at 30, 60 and 90 days post-admission (dpa) using administrative health data extracted from the national health insurance information system (SNIIR-AM) which covers 77% of the French population. Associations between HPIs and HSMRs were assessed by Poisson regression models corrected for measurement errors with a simulation-extrapolation (SIMEX) method.ResultsMost associations studied were not statistically significant. Only two process indicators were found associated with HSMRs. Completeness and quality of anesthetic records was negatively associated with 30 dpa HSMR (0.72 [0.52-0.99]). Early detection of nutritional disorders was negatively associated with all HSMRs: 30 dpa HSMR (0.71 [0.54-0.95]), 60 dpa HSMR (0.51 [0.39-0.67]) and 90 dpa HSMR (0.52 [0.40-0.68]).ConclusionIn absence of gold standard of quality of care measurement, the limited number of associations suggested to drive in-depth improvements in order to better determine associations between process and mortality indicators. A smart utilization of both process and outcomes indicators is mandatory to capture aspects of the hospital quality of care complexity.
| S-EPMC5568353 | biostudies-literature
Project description:Reporting the results of quality indicators can narrow the gap in the quality of care between hospitals. While most studies rely on outcome indicators, they may not accurately measure the quality of care. Process indicators are not only strongly associated with treatment outcomes, but are also more sensitive to whether patients are treated accurately, enabling timely intervention. Our study aims to investigate whether process indicators provide a more reasonable assessment of hospital quality of care compared to outcome indicators. Data were sourced from the Specific Disease Medical Service Quality Management and Control System in China. A total of 113,942 patients with breast cancer treated in 298 hospitals between January 2019 and April 2023 were included in this retrospective study. The rankability of 11 process indicators was calculated and used as a weight to create a new composite indicator. The composite indicators and outcome measures were compared using the O/E ratio categories. Finally, in order to determine the impact of different years on the results, a sensitivity analysis was conducted using bootstrap sampling. The rankability ( ρ ) values of the eleven process indicators showed significant differences, with the highest ρ value for preoperative cytological or histological examination before surgery (0.919). The ρ value for the outcome indicator was 0.011. The rankability-weighting method yielded a comprehensive score ( ρ = 0.883). The comparison with categorical results of the outcome indicator has different performance classifications for 113 hospitals (37.92%) for composite scores and 140 (46.98%) for preoperative cytological or histological examinationbefore surgery. Process indicators are more suitable than outcome indicators for assessing the quality of breast cancer care in hospitals. Healthcare providers can use process indicators to identify specific areas for improvement, thereby driving continuous quality improvement efforts.
| S-EPMC11333708 | biostudies-literature
Project description:ImportanceHealth care systems, payers, and hospitals use hospital readmission rates as a measure of quality. Although hospitals can track readmissions back to themselves (hospital A to hospital A), they lack information when their patients are readmitted to different hospitals (hospital A to hospital B). Because hospitals lack different-hospital readmission (DHR) data, they may underestimate all-hospital readmission (AHR) rates (hospital A to hospital A or B).ObjectivesTo determine the prevalence of 30-day pediatric DHRs; to assess the effect of DHR on readmission performance; and to identify patient and hospital characteristics associated with DHR.Design, setting, and participantsWe analyzed all-payer inpatient claims for 701,263 pediatric discharges (patients aged 0-17 years) from 177 acute care hospitals in New York State from January 1, 2005, through November 30, 2009, to identify 30-day same-hospital readmissions (SHRs), DHRs, and AHRs. Data analysis was performed from March 12, 2013, through April 6, 2015. We compared excess readmission ratios (calculated per the Medicare formula) using SHRs and AHRs to determine what might happen if the federal formula were applied to a specific state and to evaluate how often hospitals might accurately anticipate-using data available to them--whether they would incur penalties (excess readmission ratio >1) for readmissions. Using multivariate logistic regression, we identified patient- and hospital-level predictors of DHR vs SHR.Main outcomes and measuresThe proportion of DHRs vs SHRs, AHR and SHR rates, and excess readmissions.ResultsDifferent-hospital readmissions constituted 13.9% of 31,325 AHRs. At the individual hospital level, the median (interquartile range) percentage of DHRs was 21.6% (12.8%-39.1%). The median (interquartile range) adjusted AHR rate was 3.4% (3.0%-4.1%), 38.9% higher than the median adjusted SHR rate of 2.5% (2.0%-3.4%) (P < .001). Excess readmission ratios using SHRs inaccurately anticipated penalties (changed from >1 to ≤ 1 or vice versa) for 20 of the 177 hospitals (11.3%); all were nonchildren's hospitals and 18 of 20 (90.0%) were nonteaching hospitals. Characteristics associated with higher odds ratios (ORs) (reported with 95% CIs) of DHR in multivariate analyses included being younger (compared with age <1 year, ORs [95% CIs] for the other age categories ranged from 0.76 [0.66-0.88] to 0.85 [0.73-0.99]); being white (ORs [95% CIs] for nonwhite race/ethnicity ranged from 0.74 [0.65-0.84] to 0.88 [0.79-0.99]); having private insurance (1.14 [1.04-1.24]); having a chronic condition indicator for a mental disorder (1.33 [1.13-1.56]) or a disease of the nervous system (1.37 [1.20-1.57]) or circulatory system (1.20 [1.00-1.43]); and admission to a nonchildren's (1.62 [1.01-2.60]), urban (ORs for nonurban hospitals ranged from 0.35 [0.24-0.52] to 0.36 [0.21-0.64]), or lower-volume (0.73 [0.64-0.84]) hospital (P < .05 for each).Conclusions and relevanceDifferent-hospital readmissions differentially affect hospitals' pediatric readmission rates and anticipated performance, making SHRs an incomplete surrogate for AHRs-particularly for certain hospital types. Failing to incorporate DHRs into readmission measurement may impede quality assessment, anticipation of penalties, and quality improvement.
| S-EPMC5336323 | biostudies-literature
Project description:ObjectiveLittle is known regarding variation among electronic health record (EHR) vendors in quality performance. This issue is compounded by selection effects in which high-quality hospitals coalesce to a subset of market leading vendors. We measured hospital performance, stratified by EHR vendor, across 4 quality metrics.Materials and methodsWe used data on 1272 hospitals in 2018 across 4 quality measures: Leapfrog Computerized Provider Order Entry/EHR Evaluation, Centers for Medicare and Medicaid Services Hospital Compare Star Ratings, Hospital-Acquired Condition (HAC) score, and Hospital Readmission Reduction Program (HRRP) ratio. We examined score distributions and used multivariable regression to evaluate the association between vendor and score, recovering partial R2 to assess the proportion of quality variation explained by vendor.ResultsWe found significant variation across and within EHR vendors. The largest vendor, vendor A, had the highest mean score on the Leapfrog Computerized Provider Order Entry/EHR Evaluation and HRRP ratio, vendor G had the highest Hospital Compare score, and vendor F had the highest HAC score. In adjusted models, no vendor was significantly associated with higher performance on more than 2 measures. EHR vendor explained between 1.2% (HAC) and 7.6 (HRRP) of the variation in quality performance.DiscussionNo EHR vendor was associated with higher quality across all measures, and the 2 largest vendors were not associated with the highest scores. Only a small fraction of quality variation was explained by EHR vendor choice.ConclusionsTop performance on quality measures can be achieved with any EHR vendor; much of quality performance is driven by the hospital and how it uses the EHR.
| S-EPMC8449606 | biostudies-literature
Project description:ObjectiveThe ability to assess quality of care is a necessary component of continuous quality improvement. The assessment typically is accomplished by determination of compliance with a defined set of quality measures (QMs). The objective of this effort was to establish a set of QMs for the assessment of the process of care in juvenile idiopathic arthritis (JIA).MethodsA 12-member working group composed of representatives from the American College of Rheumatology, American Academy of Pediatrics, American Board of Pediatrics, and Association of Rheumatology Health Professionals was assembled to guide the project. Delphi questionnaires were sent to 237 health professionals involved in the care of children with JIA. A total of 471 items in 23 domains were identified. The working group met via 4 live e-meetings during which results from the Delphi questionnaires were distilled to a reduced draft set. Each working group member selected a proposed QM to investigate and present evidence from the literature as to its attributes and appropriateness for inclusion into the set. Nominal group technique was used to come to consensus on a proposed set of QMs.ResultsThe proposed set contains 12 QMs within 4 health care domains. Each QM consists of a statement of 1) the assessment to be completed, 2) when the first assessment should be completed and a suggested frequency of assessment during followup, 3) recommendations of appropriate tools or methods of assessment, and 4) initial performance goals.ConclusionImplementation of the proposed QM set will improve the process of care, facilitate continuous quality improvement, and eventuate in improved health outcomes of children with JIA.
| S-EPMC3016458 | biostudies-literature
Project description:ImportanceSurvival rates after in-hospital cardiac arrest (IHCA) vary significantly among US centers; whether this variation is owing to differences in IHCA care quality is unknown.ObjectiveTo evaluate hospital-level variation to determine whether hospital process composite performance measures of IHCA care quality are associated with patient outcomes.Design, setting, and participantsUsing data from the American Heart Association's Get With the Guidelines-Resuscitation (GWTG-R) program, we analyzed 35 283 patients 18 years or older with IHCA treated at 261 US hospitals from January 1, 2010, through December 31, 2012. We calculated the hospital process composite performance score for IHCA using 5 guideline-recommended process measures. Opportunity-based scores were calculated for all patients, aggregated at the hospital level, divided into quartiles, and then associated with risk-standardized survival and neurologic status by a test for trend. The scores were then evaluated through hierarchical logistic regression and reported as odds ratios per 10% increment in hospital process composite performance.InterventionsAcute care treatments for IHCA.Main outcomes and measuresThe primary outcome was survival to discharge measured as risk standard survival rates, and the secondary outcome was favorable neurologic status at hospital discharge.ResultsOf the 35 283 adults included in this study, the median age was 67 years (interquartile range [IQR] 56-78 years), and 57.9% were male. The median IHCA hospital process composite performance was 89.7% (interquartile range, 85.4%-93.1%) and varied among hospital quartiles from 82.6% (lowest) to 94.8% (highest). The IHCA hospital process composite performance was linearly associated with risk-standardized hospital survival to discharge rates: 21.1%, 21.4%, 22.8%, and 23.4% from lowest to highest performance quartiles, respectively (P < .001). After adjustment, each 10% increase in a hospital's process composite performance was associated with a 22% higher odds of survival (adjusted odds ratio, 1.22; 95% CI, 1.08-1.37; P = .01). Hospital process composite quality performance was also associated with favorable neurologic status at discharge (P = .004).Conclusions and relevanceThe quality of guideline-based care for IHCA varies significantly among US hospitals and is associated with patient survival and neurologic outcomes.
| S-EPMC6545891 | biostudies-literature
Project description:ObjectivesThe main objective of the present study was to estimate the uptake to quality indicators that reflect the current evidence-based recommendations and guidelines.MethodsA retrospective review of medical records of patients admitted to two hospitals in the South of Italy was conducted. For the purposes of the analysis, a sets of quality indicators has been used from the Joint Commission on Accreditation of Hospital Organizations and Centers for Medicare & Medicaid Services. Four areas of care were selected: acute myocardial infarction (AMI), heart failure (HF), pneumonia (PN), and surgical care improvement project (SCIP). Frequency or median was calculated, as appropriate, for each indicator. A composite score was calculated to estimate the overall performance for each area of care.ResultsA total of 1772 medical records were reviewed. The adherence rates showed a wide-ranging variability among the selected indicators. The use of aspirin and angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) for AMI, the use of ACEI or ARB for HF, the use of appropriate thromboembolism prophylaxis and appropriate hair removal for surgical patients almost approached optimal adherence. At the other extreme, rates regarding adherence to smoking-cessation counseling in AMI and HF patients, discharge instructions in HF patients, and influenza and pneumococcal vaccination in pneumonia patients were noticeably intangible. Overall, the recommended processes of care among eligible patients were provided in 70% for AMI, in 32.4% for HF, in 46.4% for PN, and in 46% for SCIP.ConclusionsThe results show that there is still substantial work that lies ahead on the way to improve the uptake to evidence-based processes of care. Improvement initiatives should be focused more on domains of healthcare than on specific conditions, especially on the area of preventive care.
| S-EPMC3492134 | biostudies-literature
Project description:ImportancePublic reporting of quality is considered a key strategy for stimulating improvement efforts at US hospitals; however, little is known about the attitudes of hospital leaders toward existing quality measures.ObjectivesTo describe US hospital leaders' attitudes toward hospital quality measures found on the Centers for Medicare & Medicaid Services' Hospital Compare website, assess use of these measures for quality improvement, and examine the association between leaders' attitudes and hospital quality performance.Design, setting, and participantsWe mailed a 21-item questionnaire from January 1 through September 31, 2012, to senior hospital leaders from a stratified random sample of 630 US hospitals, including equal numbers with better-than-expected, as-expected, and worse-than-expected performance on mortality and readmission measures.Main outcomes and measuresWe assessed levels of agreement with statements concerning quality measures, examined use of measures for improvement activities, and analyzed the association between leaders' attitudes and hospital performance.ResultsOf 630 hospitals surveyed, 380 (60.3%) responded. For each of the mortality, readmission, process, and patient experience measures, more than 70% of hospitals agreed with the statement that "public reporting stimulates quality improvement activity at my institution"; agreement for measures of cost and volume was 65.2% and 53.3%, respectively. A similar pattern was observed for the statement that "our hospital is able to influence performance on this measure"; agreement for processes of care and patient experience measures was 96.4% and 94.2%, respectively. A total of 89.7% of hospitals agreed that the hospital's reputation was influenced by patient experience measures; agreement was 77.4% for mortality, 69.9% for readmission, 76.3% for process measures, 66.1% for cost measures, and 54.0% for volume measures. A total of 87.1% of hospitals reported incorporating performance on publicly reported measures into their hospital's annual goals, whereas 90.2% reported regularly reviewing the results with the hospital's board of trustees and 94.3% with senior clinical and administrative leaders. When compared with chief executive officers and chief medical officers, respondents who identified themselves as chief quality officers or vice presidents of quality were less likely to agree that public reporting stimulates quality improvement and that measured differences are large enough to differentiate among hospitals.Conclusions and relevanceHospital leaders indicated that the measures reported on the Hospital Compare website exert strong influence over local planning and improvement efforts. However, they expressed concerns about the clinical meaningfulness, unintended consequences, and methods of public reporting.
| S-EPMC4250277 | biostudies-literature
Project description:ObjectiveTo explore factors that may influence use of comparative public reports for hospital maternity care.Data sourcesFour focus groups conducted in 2013 with 41 women and preintervention survey data collected in 2014 to 2015 from 245 pregnant women in North Carolina.Study designAs part of a larger randomized controlled trial, we conducted qualitative formative research to develop an intervention that will be evaluated through pre- and postintervention surveys.Data extraction methodsAnalysis of focus group transcripts examined participants' perceptions of high-quality maternity care and the importance of different quality measures. Quantitative analysis included descriptive results of the preintervention survey and subgroup analyses to examine the impact of race, education, and being a first-time mom on outcomes.Principal findingsWhen describing high-quality maternity care, participants focused on interactions with providers, including respect for preferences and communication. The importance of quality measures was influenced by the extent to which they focused on babies' health, were perceived as the hospital's responsibility, and were perceived as representing "standard care." At baseline, 28 percent of survey respondents had used quality information to choose a hospital. Survey respondents were more aware of some quality measures (e.g., breastfeeding support) than others (e.g., episiotomy rates).ConclusionsPublic reporting efforts could help increase relevance of maternity care quality measures by creating measures that reflect women's concerns, clearly explaining the hospital's role in supporting quality care, and showing how available quality measures can inform decisions about childbirth.
| S-EPMC4874945 | biostudies-literature
Project description:To examine whether high performance on one measure of quality is associated with high performance on others and to develop a data-driven explanatory model of neonatal intensive care unit (NICU) performance.We conducted a cross-sectional data analysis of a statewide perinatal care database. Risk-adjusted NICU ranks were computed for each of 8 measures of quality selected based on expert input. Correlations across measures were tested using the Pearson correlation coefficient. Exploratory factor analysis was used to determine whether underlying factors were driving the correlations.Twenty-two regional NICUs in California.In total, 5445 very low-birth-weight infants cared for between January 1, 2004, and December 31, 2007.Pneumothorax, growth velocity, health care-associated infection, antenatal corticosteroid use, hypothermia during the first hour of life, chronic lung disease, mortality in the NICU, and discharge on any human breast milk.The NICUs varied substantially in their clinical performance across measures of quality. Of 28 unit-level correlations, 6 were significant (? < .05). Correlations between pairs of measures of quality of care were strong (? ? .5) for 1 pair, moderate (range, ? ? .3 to ? < .5) for 8 pairs, weak (range, ? ? .1 to ? < .3) for 5 pairs, and negligible (? < .1) for 14 pairs. Exploratory factor analysis revealed 4 underlying factors of quality in this sample. Pneumothorax, mortality in the NICU, and antenatal corticosteroid use loaded on factor 1; growth velocity and health care-associated infection loaded on factor 2; chronic lung disease loaded on factor 3; and discharge on any human breast milk loaded on factor 4.In this sample, the ability of individual measures of quality to explain overall quality of neonatal intensive care was modest.
| S-EPMC4028032 | biostudies-literature