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Analysis of hierarchical routine data with covariate missingness: effects of audit and feedback on clinicians' prescribed pediatric pneumonia care in Kenyan hospitals

Abstract:

Background: Routine clinical data are widely used in many countries to monitor quality of care. A limitation of routine data is missing information which occurs due to lack of documentation of care processes by health care providers, poor record keeping, or limited health care technology at facility level. Our objective was to address missing covariates while properly accounting for hierarchical structure in routine pediatric pneumonia care.

Methods: We analyzed routine data collected during a cluster randomized trial to investigating the effect of audit and feedback (A&F) over time on inpatient pneumonia care among children admitted in 12 Kenyan hospitals between March and November 2016. Six hospitals in the intervention arm received enhance A&F on classification and treatment of pneumonia cases in addition to a standard A&F report on general inpatient pediatric care. The remaining six in control arm received standard A&F alone. We derived and analyzed a composite outcome known as Pediatric Admission Quality of Care (PAQC) score. In our analysis, we adjusted for patients, clinician and hospital level factors. Missing data occurred in patient and clinician level variables. We did multiple imputation of missing covariates within the joint model imputation framework. We fitted proportion odds random effects model and generalized estimating equation (GEE) models to the data before and after multilevel multiple imputation.

Results: Overall, 2,299 children aged 2 to 59 months were admitted with childhood pneumonia in 12 hospitals during the trial period. 2,127 (92%) of the children (level 1) were admitted by 378 clinicians across the 12 hospitals. Enhanced A&F led to improved inpatient pediatric pneumonia care over time compared to standard A&F. Female clinicians and hospitals with low admission workload were associated with higher uptake of the new pneumonia guidelines during the trial period. In both random effects and marginal model, parameter estimates were biased and inefficient under complete case analysis.

Conclusions: Enhanced A&F improved the uptake of WHO recommended pediatric pneumonia guidelines over time compared to standard audit and feedback. When imputing missing data, it is important to account for the hierarchical structure to ensure compatibility with analysis models of interest to alleviate bias.

Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.3389/fpubh.2019.00198

Authors

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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Tropical Medicine
Role:
Author
ORCID:
0000-0002-7427-0826


More from this funder
Funding agency for:
English, M
Grant:
097170


Publisher:
Frontiers Media
Journal:
Frontiers in Public Health More from this journal
Volume:
7
Article number:
198
Publication date:
2019-07-16
Acceptance date:
2019-07-02
DOI:
EISSN:
2296-2565
Pmid:
31380338


Language:
English
Keywords:
Pubs id:
pubs:1041491
UUID:
uuid:8ee7c32d-36e0-4267-a9dc-c8eb2ac6a523
Local pid:
pubs:1041491
Source identifiers:
1041491
Deposit date:
2019-08-10
ARK identifier:

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