Dataset Information

Risk adjustment for cesarean delivery rates: how many variables do we need? An observational study using administrative databases.

ABSTRACT:

Background

Various studies indicate that inter-hospital comparisons have to take case mix into account and that risk adjustment procedures are necessary to control for potential predictors of cesarean delivery (CD). Different data sources have been used to retrieve information on potential predictors of CD. The aim of this study was to compare the discrimination capacity and fit of predictive models of CD created using different sources and to assess whether more complex models improve inter-hospital comparisons.

Methods

We created 4 predictive models of CD. One model included only variables from Hospital Discharge Records of the index hospitalization, one included also information from previous hospitalizations, one also clinical variables from birth certificates (BC) and one also socio-demographic variables. We compared the four models using the Receiver Operator Curve and the Akaike and Bayesian Information Criteria.

Results

Information from Birth Certificates improved the discrimination and model fit. Adding socio-demographic variables or past comorbidities did not improve the discrimination capacity or the model fit. Hospital-specific CD resulting from the models were highly correlated.

Conclusions

Record linkage improves the performance of the models but does not affect inter-hospital comparisons.

SUBMITTER: Stivanello E

PROVIDER: S-EPMC3554564 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Risk adjustment for cesarean delivery rates: how many variables do we need? An observational study using administrative databases.

Stivanello Elisa E Rucci Paola P Carretta Elisa E Pieri Giulia G Fantini Maria P MP

BMC health services research 20130110

<h4>Background</h4>Various studies indicate that inter-hospital comparisons have to take case mix into account and that risk adjustment procedures are necessary to control for potential predictors of cesarean delivery (CD). Different data sources have been used to retrieve information on potential predictors of CD. The aim of this study was to compare the discrimination capacity and fit of predictive models of CD created using different sources and to assess whether more complex models improve i ...[more]

PMID: 23305225

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Project description:BackgroundCesarean section rates is often used as an indicator of quality of care in maternity hospitals. The assumption is that lower rates reflect in developed countries more appropriate clinical practice and general better performances. Hospitals are thus often ranked on the basis of caesarean section rates. The aim of this study is to assess whether the adjustment for clinical and sociodemographic variables of the mother and the fetus is necessary for inter-hospital comparisons of cesarean section (c-section) rates and to assess whether a risk adjustment model based on a limited number of variables could be identified and used.MethodsDischarge abstracts of labouring women without prior cesarean were linked with abstracts of newborns discharged from 29 hospitals of the Emilia-Romagna Region (Italy) from 2003 to 2004. Adjusted ORs of cesarean by hospital were estimated by using two logistic regression models: 1) a full model including the potential confounders selected by a backward procedure; 2) a parsimonious model including only actual confounders identified by the "change-in-estimate" procedure. Hospital rankings, based on ORs were examined.Results24 risk factors for c-section were included in the full model and 7 (marital status, maternal age, infant weight, fetopelvic disproportion, eclampsia or pre-eclampsia, placenta previa/abruptio placentae, malposition/malpresentation) in the parsimonious model. Hospital ranking using the adjusted ORs from both models was different from that obtained using the crude ORs. The correlation between the rankings of the two models was 0.92. The crude ORs were smaller than ORs adjusted by both models, with the parsimonious ones producing more precise estimates.ConclusionRisk adjustment is necessary to compare hospital c-section rates, it shows differences in rankings and highlights inappropriateness of some hospitals. By adjusting for only actual confounders valid and more precise estimates could be obtained.

Project description:BackgroundMajor adverse cardiovascular events (MACE) are increasingly used as composite outcomes in randomized controlled trials (RCTs) and observational studies. However, it is unclear how observational studies most commonly define MACE in the literature when using administrative data.MethodsWe identified peer-reviewed articles published in MEDLINE and EMBASE between January 1, 2010 to October 9, 2020. Studies utilizing administrative data to assess the MACE composite outcome using International Classification of Diseases 9th or 10th Revision diagnosis codes were included. Reviews, abstracts, and studies not providing outcome code definitions were excluded. Data extracted included data source, timeframe, MACE components, code definitions, code positions, and outcome validation.ResultsA total of 920 articles were screened, 412 were retained for full-text review, and 58 were included. Only 8.6% (n = 5/58) matched the traditional three-point MACE RCT definition of acute myocardial infarction (AMI), stroke, or cardiovascular death. None matched four-point (+unstable angina) or five-point MACE (+unstable angina and heart failure). The most common MACE components were: AMI and stroke, 15.5% (n = 9/58); AMI, stroke, and all-cause death, 13.8% (n = 8/58); and AMI, stroke and cardiovascular death 8.6% (n = 5/58). Further, 67% (n = 39/58) did not validate outcomes or cite validation studies. Additionally, 70.7% (n = 41/58) did not report code positions of endpoints, 20.7% (n = 12/58) used the primary position, and 8.6% (n = 5/58) used any position.ConclusionsComponents of MACE endpoints and diagnostic codes used varied widely across observational studies. Variability in the MACE definitions used and information reported across observational studies prohibit the comparison, replication, and aggregation of findings. Studies should transparently report the administrative codes used and code positions, as well as utilize validated outcome definitions when possible.

Project description:ImportanceA high cesarean delivery rate in US hospitals indicates the potential overuse of this procedure; however, underlying causes of the excessive use of cesarean procedures in the US have not been fully understood.ObjectiveTo investigate the association between the probability of cesarean delivery at the patient-level and profit per procedure from cesarean deliveries.Design, setting, and participantsThis observational, cross-sectional study used a nationally representative sample of hospital discharge data from women at low risk for cesarean birth who delivered newborns between 2010 and 2014 in the US. Data were gathered from the Nationwide Readmissions Database from the Healthcare Cost and Utilization Project, compiled by the Agency for Healthcare Research and Quality. Data cleaning and analyses were conducted between August 2019 and May 2020.ExposuresHospital-level median value of profits from cesarean deliveries, defined as the difference between the charge and the cost for cesarean delivery calculated for each hospital.Main outcomes and measuresOur primary outcome was the individual-level probability of undergoing a cesarean delivery. We examined the association with the hospital-level median value of profits per procedure for cesarean delivery (defined as the difference between the charge and the cost for cesarean delivery) using hierarchical regression models adjusted for patient and hospital characteristics and year-fixed effects.ResultsA total of 13 215 853 deliveries were included in our analyses (mean [SE] age, 27.4 [0] years), of which 2 202 632 (16.7%) were cesarean deliveries. After adjusting for potential confounders, pregnant women were more likely to have a cesarean birth when they delivered at hospitals with higher profits per procedure from cesarean deliveries. Women cared for at hospitals with the highest (adjusted odds ratio, 1.08; 95% CI, 1.02-1.14; P = .005) and second-highest profit quartiles (adjusted odds ratio, 1.07; 95% CI, 1.02-1.13; P = .007) had higher probabilities of a cesarean delivery compared with those cared for at hospitals in the lowest profit quartile.Conclusions and relevanceIn this cross-sectional study of US nationally representative hospital discharge data, hospitals with higher profits per cesarean procedure were associated with an increased probability of delivering newborns through cesarean birth. These findings highlight the potential influence financial incentives play in determining a high cesarean delivery rate in the US.

Project description:BACKGROUND:To systematically review the literature on clinical interventions that influence vaginal birth after cesarean (VBAC) rates. METHODS:We searched Ovid Medline, Ovid Embase, Wiley Cochrane Library, CINAHL via EBSCOhost; and Ovid PsycINFO. Additional studies were identified by searching for clinical trial records, conference proceedings and dissertations. Limits were applied for language (English and French) and year of publication (1985 to present). Two reviewers independently screened comparative studies (randomized or non-randomized controlled trials, and observational designs) according to a priori eligibility criteria: women with prior cesarean sections; any clinical intervention or exposure intended to increase the VBAC rate; any comparator; and, outcomes reporting VBAC, uterine rupture and uterine dehiscence rates. One reviewer extracted data and a second reviewer verified for accuracy. Meta-analysis was conducted using Mantel-Haenszel (random effects model) relative risks (VBAC rate) and risk differences (uterine rupture and dehiscence). Two reviewers independently conducted methodological quality assessments using the Mixed Methods Appraisal Tool (MMAT). RESULTS:Twenty-nine studies (six trials and 23 cohorts) examined different clinical interventions affecting rates of vaginal deliveries among women with a prior cesarean delivery (CD). Methodological quality was good overall for the trials; however, concerns among the cohort studies regarding selection bias, comparability of groups and outcome measurement resulted in higher risk of bias. Interventions for labor induction, with or without cervical ripening, included pharmacologic (oxytocin, prostaglandins, misoprostol, mifepristone, epidural analgesia), non-pharmacologic (membrane sweep, amniotomy, balloon devices), and combined (pharmacologic and non-pharmacologic). Single studies with small sample sizes and event rates contributed to most comparisons, with no clear differences between groups on rates of VBAC, uterine rupture and uterine dehiscence. CONCLUSIONS:This systematic review evaluated clinical interventions directed at increasing the rate of vaginal delivery among women with a prior CD and found low to very low certainty in the body of evidence for cervical ripening and/or labor induction techniques. There is insufficient high-quality evidence to inform optimal clinical interventions among women attempting a trial of labor after a prior CD.

Dataset Information

Risk adjustment for cesarean delivery rates: how many variables do we need? An observational study using administrative databases.

Background

Methods

Results

Conclusions

Publications

Risk adjustment for cesarean delivery rates: how many variables do we need? An observational study using administrative databases.

Similar Datasets

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