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Fundamental issues. Alyna T. Chien MD, MS The University of Chicago Harvard Quality Colloquium August 20, 2008. Goal. Illustrate how the first pediatric public reporting effort is facing inherent challenges to pediatric quality measurement.
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Fundamental issues Alyna T. Chien MD, MS The University of Chicago Harvard Quality Colloquium August 20, 2008
Goal • Illustrate how the first pediatric public reporting effort is facing inherent challenges to pediatric quality measurement
Inherent challenges • Perspective • What to measure • Evidence base • Sample sizes
Inherent challenges • Perspective • Consumers • Providers • Free standing children’s hospitals • Community hospitals • Purchasers
Inherent challenges • What to measure • Structure, Process, Outcome • Safety, Effectiveness, Efficiency, Equity, Patient-centeredness, Patient Safety, Timeliness
Inherent challenges • Evidence base • Proper endpoints?
Inherent challenges • Sample size • 1/5th of the adult population • Lower disease prevalence • Significant proportion of care provided in adult contexts • Significant proportion of care provided in community contexts
300M adults ~50M children (~20% of population) Max ‘volume’ ~500,000 newborns in California 271 of 442 hospitals with pediatric services ~1800 newborns per hospital ~180 non-newborn admissions per hospital
Strategy • Perspective Diverse Workgroup • What to measure Diverse portfolio • Patchier evidence base Diverse portfolio • Patchier evidence base Invest in development • Small sample size “Functional” measures? • Small sample size “Structural” measures? • Small sample size Aggregation methods? • Small sample size Invest in development
Tool Does it apply to children? prevalence cost Is it evidence based? What dimensions does it measure? Portfolio diversification
Strategy • Systematic approach • Portfolio diversification
PMD Tool Quickie • Does it apply to children? • prevalence • Which ones? • Impact? • mortality • disease burden • cost • Evidence base? • Dimension of quality? • Portfolio diversification
CHART Future Directions • Perspective • What to measure • Evidence base • Sample size
Summary • Pediatric public reporting in its infancy • Lots of room for improvement
Thanks CHART Core • R. Adams Dudley, MD MBA • Mitzi Dean, PhD • Ted Karrison, MS • James Anderson, PhD Peds Workgroup • Diana Dooley (CCHA) • Erin Givens (CSCC) • Jeff Gould (Stanford) • Greg Janos (Sutter) • Tom Klitzner (UCLA) • Paul Kurtin (UC San Diego) • Paul Sharef (UCLA)
Public reporting: adult history • Florence Nightengale • Ernest Codman • Mortality after Coronary Artery Bypass Grafts • Medicare
Public reporting: mechanisms? • Free market mechanism: Comparative info about healthcare quality payors (employers, health plans, and patients) choose higher quality providers financial rewards will flow to better performers (and away from poorer ones) • “Self-improvement” mechanism: Comparative info about healthcare quality providers (hospitals, medical groups, individual physicians) better awareness of quality issues quality regulation cost containment quality improvement
Do “consumers” act on the information? • Free market mechanism: Comparative info about healthcare quality payors (employers, health plans, and patients) choose higher quality providers financial rewards will flow to better performers (and away from poorer ones) • “Self-improvement” mechanism: Comparative info about healthcare quality providers (hospitals, medical groups, individual physicians) better awareness of quality issues quality regulation cost containment quality improvement YES and NO Marshall MN et. al, JAMA 2000
Public reporting: mechanisms for exclusive breastfeeding • Volume • Data availability • Low prevalence of conditions • Appropriate processes? • Appropriate outcomes?
Public reporting: mechanisms for exclusive breastfeeding • Prenatal information/decision-making • Family/Friends • Healthcare providers • Social agencies (e.g. WIC) • Immediate post-natal period • Family/Friends • Healthcare providers Hospital “critical period”? • Hospital-based supports • A “critical period”?
Public reporting: mechanisms for exclusive breastfeeding • Prenatal information/decision-making • Family/Friends • Healthcare providers • Social agencies (e.g. WIC) • Immediate post-natal period • Family/Friends • Healthcare providers Hospital “critical period”? • Hospital-based supports • A “critical period”?
Public reporting: mechanisms for exclusive breastfeeding • Prenatal information/decision-making • Family/Friends • Healthcare providers • Social agencies (e.g. WIC) • Immediate post-natal period • Family/Friends • Healthcare providers • Hospital-based supports • A “critical period”?
Performance – three approaches For CHART’s exclusive breastfeeding measure: Zh = Ÿh – Ýh . VAR (Ÿh – Ýh) where: • Ÿh is mean exclusive breastfeeding rate for each hospital • Ýh is mean exclusive breastfeeding rate for all newborns (statewide average) • No other individual level adjustments • Hospitals admitting <30 newborns annually are excluded
Public reporting is one strategy aimed at improving the quality of that care • “Free market” mechanism • consumers/payors • “Self-improvement” mechanisms • providers, individuals and organizations • Evidence equivocal
Public reporting’s role in eliminating (or exacerbating) racial/ethnic disparities is unknown “Free market” “Self-imprvmnt” Consumers / payors Providers Consequence: • Improve Want to go somewhere Want to be viewed as “equitable” “equitable” • Worsen Promotes segregation • Status quo
Unique opportunity to explore public reporting’s potential role in presenting racial/ethnic disparities Exclusive breastfeeding rates in California hospitals: • Enough patients • 10% of all American newborns born in California (500,000/year) • Enough hospitals • 283 are licensed to provide pediatric services • Good racial/ethnic data (as currently available) • standardized collection • complete • variation expected
This goal of this paper is to explore three approaches to incorporating information on racial/ethnic disparities into hospital public reporting: 1. Adjusting expected performance for race/ethnicity 2. Stratifying performance by race/ethnicity 3. Developing a ‘disparity’ score
Hypotheses: 1. Hospital performance/rankings will change depending on how race/ethnicity is incorporated into performance methodology 2. Each methodology will have ‘pros’ and ‘cons’
Study Design Cross-sectional Primary independent variables: - Different performance measurement methodologies: 1. Proportional 2. Stratified 3. + ‘Disparity’ score Primary dependent variables: - Changes in hospital rank
Performance – traditional method In general: Zh = Ÿh – Ýh . VAR (Ÿh – Ýh) Where: • Zh is standardized performance • Ÿh is observed mean performance including adjustments • Ýh is expected mean performance including adjustments • Each adjusted for patient characteristics Conventionally: • Hospitals with <30 observations are excluded • Performance can be estimated using standard frequentist approaches • Or using Bayesian ones
Data Source California Department of Public Health Center for Family Health Genetic Disease Screening Program Newborn Screening Data 2006 • Mandated statewide screening program • Established 1966 • Screening rate 99%
Data Collection As part of the Newborn Screen, all providers are required to answer the following questions: “All feeding since birth: (check only one box) []Breast only []Formula only []Breast & Formula []TPN/Hyperal []Other. (SPECIFY):__________________________________________________” “Race/ethnicity: (check all that apply) []White []Hispanic []Black []Chinese []Japanese []Korean []Cambodian []Laotian []Vietnamese []Filipino []Asian Indian []Middle Eastern []Native American []Samoan []Other (SPECIFY):________________________________________________________”
Data Quality - Missing 2006 Number of newborns • 492,587 in dataset – cross-checked with Vital Statistics Breastfeeding status • Indicated 97.2% • Missing 2.8% Race/ethnicity noted • Indicated 97.4% • Missing 2.6%
Data Quality - Validity 2006 Breastfeeding status GDSP ?NSLAH • Exclusive ~40% • Any ~90% Race/ethnicity noted GDSP ?Census • White • African American • Hispanic • Asian • Multi • Other