ArticleInternational journal of medical informatics2023
Assessing the effect of electronic health information exchange on the completeness and validity of data for measuring viral load testing turnaround time in Nigeria.
Article in International journal of medical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.
- Health Information Exchange: Contributions from 2023.Yearbook of medical informatics · 2024Pooled it
- Feasibility of AI-Enabled Chatbots for Pre-consultation in HIV Care in Northern Nigeria.International journal of behavioral medicine · 2026Article
- Impact of electronic medical records on healthcare delivery in Nigeria: A review.PLOS digital health · 2024Article
- Modernizing Public Health Data Systems and Workforce Capacity: The Centers for Disease Control and Prevention's Public Health Informatics Fellowship Program.Journal of public health management and practice : JPHMPArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 5 institutions in 3 countries.
Funding
Abstract
introductionImplementation of health information exchange has been shown to result in several benefits which includes the improvement in the completeness and timeliness of data for public health program monitoring and surveillance.
objectiveThe objective of this study was to assess the effect of implementing an electronic health information exchange (HIE) on the quality of data available to measure HIV viral load testing turnaround time (TAT) in Nigeria.
methodsWe measured viral load data validity and completeness before the implementation of electronic health information exchange, and 6 months after implementation. Records of specimens collected at 30 healthcare facilities and tested in 3 Polymerase Chain Reaction (PCR) labs were analyzed. We define data completeness as the percentage of non-missing values and measured this value by specimens and by data elements in the dataset for calculating TAT. To examine data validity, we classified TAT segments with negative values and date fields that were not in International Organization for Standardization(ISO) standard date format as invalid. Validity was measured by specimens and by each TAT segment. Pearson's chi square was used to assess for improvements in validity and completeness post implementation of HIE.
results15,226 records of specimens were analyzed at baseline and 18,022 records of specimens analyzed at endline. Data completeness for all specimens recorded increased significantly from 47% before HIE implementation to 67% six months after implementation (p < 0.01). Data validity also increased from 90% before implementation to 91% after implementation (p < 0.01)
conclusionOur study demonstrated evidence of significant improvement in the quality of data available to measure viral load turnaround time with the implementation of HIE.
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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.