ArticleBMC health services research2017
Barriers to data quality resulting from the process of coding health information to administrative data: a qualitative study.
Article in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 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
59 citing papers in PubMed.
- Inpatient non-communicable disease patterns and influencing factors at two tertiary hospitals in New Zealand and China: a mixed-methods study protocol.Global health action · 2026Article
- Applying the hospital administrative data quality scoring tool in 15 countries.Health information management : journal of the Health Information Management Association of Australia · 2026Article
- Why is the data quality of hospital morbidity so heterogeneous? A nationwide survey of Portuguese clinical coders.Archives of public health = Archives belges de sante publique · 2026Article
- Association between hospital volume and mortality after elective oesophageal cancer resection in Switzerland: a retrospective national registry study from 2013 to 2022.Langenbeck's archives of surgery · 2026Observational
- Accuracy of administrative data in ascertaining health conditions: a systematic review.JAMIA open · 2026Review
- Time and patient journey to axial spondyloarthritis diagnosis: a retrospective study in French primary care.Rheumatology (Oxford, England) · 2026Article
- Indonesian National Health Insurance scheme longitudinal sample data 2015-2020: overview and potential uses for health policy analysis.BMC health services research · 2025Article
- How does the mapped ICD data in an EHR system compare to the hospital DAD data in Alberta, Canada?BMC health services research · 2025Article
- Development of a case definition for polycystic ovary syndrome using administrative health data: a validation study.BMJ open · 2025Article
- Validating adverse events in administrative healthcare data in ireland: a retrospective chart review study.BMC health services research · 2025Article
- Designing a Minimum Dataset for the Cow's Milk Protein Allergy in Children: Identifying and Evaluating the Key Factors in Managing, Controlling and Monitoring the Cow's Milk Protein Allergy in Children: A Cross-Sectional Study.Health science reports · 2025Article
- Assessing the validity of ICD-10 administrative data in coding comorbidities.BMJ health & care informatics · 2025Article
- Exploring unregulated substance use health data in Ontario, Canada: Identifying gaps, addressing challenges, and uncovering opportunities.Frontiers in public health · 2025Article
- Considerations for selecting and implementing comorbidity indices when using secondary data sources: a guide for health researchers.International journal of population data science · 2025Review
- Building a Foundation for High-Quality Health Data: Multihospital Case Study in Belgium.JMIR medical informatics · 2024Article
- Targeting Machine Learning and Artificial Intelligence Algorithms in Health Care to Reduce Bias and Improve Population Health.The Milbank quarterly · 2024Article
- Undercounting diagnoses in Australian general practice: a data quality study with implications for population health reporting.BMC medical informatics and decision making · 2024Article
- International Classification of Diseases clinical coding training: An international survey.Health information management : journal of the Health Information Management Association of Australia · 2024Article
- Evaluating the coding accuracy of type 2 diabetes mellitus among patients with non-alcoholic fatty liver disease.BMC health services research · 2024Article
- Factors Affecting the Medical Coding Errors of COVID-19 Hospital Records: A Cross-Sectional Study in East Iran.Tanaffos · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdministrative health data are increasingly used for research and surveillance to inform decision-making because of its large sample sizes, geographic coverage, comprehensivity, and possibility for longitudinal follow-up. Within Canadian provinces, individuals are assigned unique personal health numbers that allow for linkage of administrative health records in that jurisdiction. It is therefore necessary to ensure that these data are of high quality, and that chart information is accurately coded to meet this end. Our objective is to explore the potential barriers that exist for high quality data coding through qualitative inquiry into the roles and responsibilities of medical chart coders.
methodsWe conducted semi-structured interviews with 28 medical chart coders from Alberta, Canada. We used thematic analysis and open-coded each transcript to understand the process of administrative health data generation and identify barriers to its quality.
resultsThe process of generating administrative health data is highly complex and involves a diverse workforce. As such, there are multiple points in this process that introduce challenges for high quality data. For coders, the main barriers to data quality occurred around chart documentation, variability in the interpretation of chart information, and high quota expectations.
conclusionsThis study illustrates the complex nature of barriers to high quality coding, in the context of administrative data generation. The findings from this study may be of use to data users, researchers, and decision-makers who wish to better understand the limitations of their data or pursue interventions to improve data quality.
Indexed as
Identifiers
What 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.