ArticleHealth services research1998
Analysis, assessment, and presentation of risk-adjusted statewide obstetrical care data: the StORQS II study in Washington State. Statewide Obstetrics Review and Quality System.
Article in Health services research, 1998. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Early neonatal transfers after moderate and late preterm birth: a nationwide cohort study based on the French National Health Data System.Pediatric research · 2026Article
- Monitoring childbirth and immediate postpartum care quality: A scoping review of indicators in high-income countries.PloS one · 2026Article
- Method to develop health care peer groups for quality and financial comparisons across hospitals.Health services research · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop an effective, concise presentation of hospital-specific birth event and delivery-related complication rates, including significant deviations from expected rates calculated using risk-adjusted peer hospital data, for distribution to all Washington State hospitals with delivery services. DATA SOURCES: Complete data for calendar year 1993, including inpatient discharge records for mothers and newborns, birth certificates, and infant death records, for 74 hospitals from Washington state source files. STUDY
designInstitutions were classified into four peer groups based on presence of neonatal intensive care units, number of births, and rural/urban location. Twenty-three clinical indicators of procedure (e.g., cesarean section) and complication rates were analyzed and presented.
methodsFor each indicator, observed and expected rates (adjusted within peer group for categorized baseline risk factors) were calculated and presented by institution. Effective graphic and numeric techniques for presenting significant deviations from expected rates were developed. Results were calculated in terms of numbers of events as well as rates. Approaches applicable to institutions with small numbers of deliveries were selected. PRINCIPAL
findingsExact confidence intervals (C.I.s) for event rates were superior to binomial or Poisson approximations for small hospitals. For calculating expected rates, indirect adjustment was used due to small numbers within risk factor categories. For all indicators, observed and expected rates along with 95 percent C.I.s for the true rate were presented graphically by institution for each peer group. Transforming C.I.s into "statistically acceptable ranges" allowed hospital personnel to assess their performance in terms of actual numbers of events as well as rates.
conclusionsReadily available statistical methods and straightforward descriptive approaches allow accurate presentation of outcomes for both large and small institutions.
Indexed as
Identifiers
9685121PMC1070275What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.