Challenges of using asthma admission rates as a measure of primary care quality in children: An international comparison.
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ABSTRACT: Objectives
To demonstrate the challenges of interpreting cross-country comparisons of paediatric asthma hospital admission rates as an indicator of primary care quality.Methods
We used hospital administrative data from >10 million children aged 6-15 years, resident in Austria, England, Finland, Iceland, Ontario (Canada), Sweden or Victoria (Australia) between 2008 and 2015. Asthma hospital admission and emergency department (ED) attendance rates were compared between countries using Poisson regression models, adjusted for age and sex.Results
Hospital admission rates for asthma per 1000 child-years varied eight-fold across jurisdictions. Admission rates were 3.5 times higher when admissions with asthma recorded as any diagnosis were considered, compared with admissions with asthma as the primary diagnosis. Iceland had the lowest asthma admission rates; however, when ED attendance rates were considered, Sweden had the lowest rate of asthma hospital contacts.Conclusions
The large variations in childhood hospital admission rates for asthma based on the whole child population reflect differing definitions, admission thresholds and underlying disease prevalence rather than primary care quality. Asthma hospital admissions among children diagnosed with asthma is a more meaningful indicator for inter-country comparisons of primary care quality.
SUBMITTER: Lut I
PROVIDER: S-EPMC8564239 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objective:To identify physician and practice characteristics associated with high clinical and technical performance on the electronic clinical quality measure (eCQM) that calculates the proportion of patients with hypertension who have controlled blood pressure. Materials and Methods:The study included 268 602 physicians participating in the Medicare Electronic Health Record Incentive Program between 2011 and 2014. Independent variables included delivery reform participation and physician, practice level, and area characteristics. Successful technical performance was a reported eCQM with non-zero values in both the numerator and denominator. Successful clinical performance was a reported eCQM value of ≥70% hypertension control. Results:Physicians with longer experience using certified health information technology, participants in delivery reform programs, and specialists that traditionally manage hypertension were 5%-15% more likely to achieve 70% control. Physicians in smaller and rural practices and a subset of physicians unlikely to primarily manage hypertension were more likely to submit measures with a zero value in either the numerator or denominator. Discussion:More physicians are using eCQMs to track and report their quality improvement efforts. This research presents the first examination of national eCQM data to identify physician and practice-level characteristics associated with performance. Conclusion:With careful selection of measures relevant to the clinician's specialty, complete data entry, and support for continuous quality improvement, health care professionals can excel technically and clinically. As care delivery transitions from fee-for-service to quality- and value-based models, high performers may realize financial gains and better patient outcomes. These analyses suggest patterns that may inform steps to improve performance.
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Project description:ImportancePresent-on-admission (POA) indicators in administrative claims data allow researchers to distinguish between preexisting conditions and those acquired during a hospital stay. The impact of adding POA information to claims-based measures of hospital quality has not yet been investigated to better understand patient underlying risk factors in the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision setting.ObjectiveTo assess POA indicator use on Medicare claims and to assess the hospital- and patient-level outcomes associated with incorporating POA indicators in identifying risk factors for publicly reported outcome measures used by the Centers for Medicare & Medicaid Services (CMS).Design, setting, and participantsThis comparative effectiveness study used national CMS claims data between July 1, 2015, and June 30, 2018. Six hospital quality measures assessing readmission and mortality outcomes were modified to include POA indicators in risk adjustment models. The models using POA were then compared with models using the existing complications-of-care algorithm to evaluate changes in risk model performance. Patient claims data were included for all Medicare fee-for-service and Veterans Administration beneficiaries aged 65 years or older with inpatient hospitalizations for acute myocardial infarction, heart failure, or pneumonia within the measurement period. Data were analyzed between September 2019 and March 2020.Main outcomes and measuresChanges in patient-level (C statistics) and hospital-level (quintile shifts in risk-standardized outcome rates) model performance after including POA indicators in risk adjustment.ResultsData from a total of 6 027 988 index admissions were included for analysis, ranging from 491 366 admissions (269 209 [54.8%] men; mean [SD] age, 78.2 [8.3] years) for the acute myocardial infarction mortality outcome measure to 1 395 870 admissions (677 158 [48.5%] men; mean [SD] age, 80.3 [8.7] years) for the pneumonia readmission measure. Use of POA indicators was associated with improvements in risk adjustment model performance, particularly for mortality measures (eg, the C statistic increased from 0.728 [95% CI, 0.726-0.730] to 0.774 [95% CI, 0.773-0.776] when incorporating POA indicators into the acute myocardial infarction mortality measure).Conclusions and relevanceThe findings of this quality improvement study suggest that leveraging POA indicators in the risk adjustment methodology for hospital quality outcome measures may help to more fully capture patients' risk factors and improve overall model performance. Incorporating POA indicators does not require extra effort on the part of hospitals and would be easy to implement in publicly reported quality outcome measures.
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Project description:ObjectiveTo examine changes in facility-level risk-standardized rehospitalization rankings for postacute inpatient rehabilitation facilities after modifying two model parameters.Data sourcesWe used national Medicare enrollment, claims, and assessment data to study 522,260 patients discharged from inpatient rehabilitation in fiscal years 2010-2011.Study designWe calculated risk-standardized 30-day unplanned rehospitalization rates for 1,135 inpatient rehabilitation facilities using four approaches. The first model replicated the current postacute risk-standardization methodology and included patients discharged from acute hospitals up to 30 days prior to postacute admission and excluded patients transferred directly back to acute hospitals following rehabilitation. Our alternative models excluded patients with delayed admissions (>1 day between acute discharge and postacute admission) and counted direct transfers back to acute as rehospitalizations.Principal findingsExcluding patients with delayed admissions and counting direct transfers back to acute care as rehospitalizations substantially impacted rankings of more than half the postacute providers: 29 percent had better and 27 percent had worse quintile rankings.ConclusionsChanging the timeframes for duration to admission and rehospitalization will have profound effects on postacute provider quality performance ratings. Reporting rehospitalization rates is an important issue with the explicit goal of improving the quality of postacute care. Research is needed to understand and minimize potential unintended consequences of this quality metric.
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