ArticleEGEMS (Washington, DC)2019
Applying an Electronic Health Records Data Quality Framework Across Service Sectors: A Case Study of Juvenile Justice System Data.
Article in EGEMS (Washington, DC), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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, 1 synthesis or guideline pooled it.
- Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Computer System for the Capture and Preparation of Cytopathological Reports for Cervical Cancer Detection and His Utility in Training for Health Personnel.European journal of investigation in health, psychology and education · 2022Article
- The point of diminishing returns in juvenile probation: Probation requirements and risk of technical probation violations among first-time probation-involved youth.Psychology, public policy, and law : an official law review of the University of Arizona College of Law and the University of Miami School of Law · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextIntegrating electronic health records (EHR) with other sources of administrative data is key to identifying factors affecting the long-term health of traditionally underserved populations, such as individuals involved in the justice system. Linking existing administrative data from multiple sources overcomes many of the limitations of traditional prospective studies of population health, but the linking process assumes high levels of data quality and consistency within administrative data. Studies of EHR, unlike other types of administrative data, have provided guidance to evaluate the utility of big data for population health research. CASE DESCRIPTION: Here, an established EHR data quality framework was applied to identify and describe the potential shortcomings of administrative juvenile justice system data collected by one of four case management systems (CMSs) across 12 counties in a Midwest state. The CMS data were reviewed for logical inconsistencies and compared along the data quality dimensions of plausibility and completeness. MAJOR THEMES: After applying the data quality framework, several patterns of logical inconsistencies within the data were identified. To resolve these inconsistencies, recommendations regarding data entry, review, and extraction are offered.
conclusionThe recommendations related to achieving quality justice system data can be applied to future efforts to link administrative databases from multiple sources. Increasing trust in administrative data quality related to vulnerable populations ultimately improves knowledge of pressing public health concerns.
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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.