ArticleJournal of the American Medical Informatics Association : JAMIA
The use of count data models in biomedical informatics evaluation research.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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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.
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Who cites it
18 citing papers in PubMed.
- Trial
- Robustness of zero truncated negative binomial models over traditional models with application to analysing factor association to length of ICU stay in a middle-income country.BMC research notes · 2026Article
- Poisson Beta Regression for Count Data With an Application to Hospital Length of Stay Data.Statistics in medicine · 2025Article
- Investigator-initiated versus industry-sponsored trials - visibility and relevance of randomized controlled trials in clinical practice guidelines (IMPACT).BMC medical research methodology · 2025Article
- Association of strong opioids and antibiotics prescribing with GP burnout: a retrospective cross-sectional study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2023Article
- Building on a novel bootstrapping modelling technique to predict region-wide critical care capacity requirements over the next decade.Future healthcare journal · 2023Article
- One and done? Exploring linkages between households' intended adaptations to climate-induced floods.Risk analysis : an official publication of the Society for Risk Analysis · 2022Article
- Count data models for outpatient health services utilisation.BMC medical research methodology · 2022Article
- Consumer demand for healthy beverages in the hospitality industry: Examining willingness to pay a premium, and barriers to purchase.PloS one · 2022Article
- Application of a Poisson deep neural network model for the prediction of count data in genome-based prediction.The plant genome · 2021Article
- Link between redemption of a medical food pantry voucher and reduced hospital readmissions.Preventive medicine reports · 2021Article
- Risk of Mortality and Readmission among Patients with Pelvic Fracture and Urinary Tract Infection: A Population-Based Cohort Study.International journal of environmental research and public health · 2021Article
- Q-DEPICT: Qatar Determining Emergency Physician Incidence of COVID-Positive Testing.Qatar medical journal · 2021Article
- A Multivariate Poisson Deep Learning Model for Genomic Prediction of Count Data.G3 (Bethesda, Md.) · 2020Article
- Article
- The impact of electronic health records on people with diabetes in three different emergency departments.Journal of the American Medical Informatics Association : JAMIA · 2014Article
- Community Health Center Use After Oregon's Randomized Medicaid Experiment.Annals of family medicineObservational
- The impact of electronic health records on care of heart failure patients in the emergency room.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectivesStudies on the impact and value of health information technology (HIT) have often focused on outcome measures that are counts of such things as hospital admissions or the number of laboratory tests per patient. These measures with their highly skewed distributions (high frequency of 0s and 1s) are more appropriately analyzed with count data models than the much more frequently used variations of ordinary least squares (OLS). Use of a statistical procedure that does not properly fit the distribution of the data can result in significant findings being overlooked. The objective of this paper is to encourage greater use of count data models by demonstrating their utility with an example based on the authors' current work. TARGET AUDIENCE: Researchers conducting impact and outcome studies related to HIT. SCOPE: We review and discuss count data models and illustrate their value in comparison to OLS using an example from a study of the impact of an electronic health record (EHR) on laboratory test orders. The best count data model reveals significant relationships that OLS does not detect. We conclude that comprehensive model checking is highly recommended to identify the most appropriate analytic model when the dependent variable being examined contains count data. This strategy can lead to more valid and precise findings in HIT evaluation studies.
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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.