Prediction of appointment no-shows using electronic health records.
Publication
, Journal Article
Lin, Q; Betancourt, B; Goldstein, BA; Steorts, RC
Published in: J Appl Stat
2020
Appointment no-shows have a negative impact on patient health and have caused substantial loss in resources and revenue for health care systems. Intervention strategies to reduce no-show rates can be more effective if targeted to the subpopulations of patients with higher risk of not showing to their appointments. We use electronic health records (EHR) from a large medical center to predict no-show patients based on demographic and health care features. We apply sparse Bayesian modeling approaches based on Lasso and automatic relevance determination to predict and identify the most relevant risk factors of no-show patients at a provider level.
Duke Scholars
Published In
J Appl Stat
DOI
ISSN
0266-4763
Publication Date
2020
Volume
47
Issue
7
Start / End Page
1220 / 1234
Location
England
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
Citation
APA
Chicago
ICMJE
MLA
NLM
Lin, Q., Betancourt, B., Goldstein, B. A., & Steorts, R. C. (2020). Prediction of appointment no-shows using electronic health records. J Appl Stat, 47(7), 1220–1234. https://doi.org/10.1080/02664763.2019.1672631
Lin, Qiaohui, Brenda Betancourt, Benjamin A. Goldstein, and Rebecca C. Steorts. “Prediction of appointment no-shows using electronic health records.” J Appl Stat 47, no. 7 (2020): 1220–34. https://doi.org/10.1080/02664763.2019.1672631.
Lin Q, Betancourt B, Goldstein BA, Steorts RC. Prediction of appointment no-shows using electronic health records. J Appl Stat. 2020;47(7):1220–34.
Lin, Qiaohui, et al. “Prediction of appointment no-shows using electronic health records.” J Appl Stat, vol. 47, no. 7, 2020, pp. 1220–34. Pubmed, doi:10.1080/02664763.2019.1672631.
Lin Q, Betancourt B, Goldstein BA, Steorts RC. Prediction of appointment no-shows using electronic health records. J Appl Stat. 2020;47(7):1220–1234.
Published In
J Appl Stat
DOI
ISSN
0266-4763
Publication Date
2020
Volume
47
Issue
7
Start / End Page
1220 / 1234
Location
England
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics