Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/45463
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Developing high-specificity anti-hypertensive alerts by therapeutic state analysis of electronic prescribing records
Author: Gadzhanova, S.
Iankov, I.
Warren, J.
Stanek, J.
Misan, G.
Baig, M.
Ponte, L.
Citation: Journal of the American Medical Informatics Association, 2007; 14(1):100-109
Publisher: Hanley & Belfus Inc
Issue Date: 2007
ISSN: 1067-5027
1527-974X
Abstract: <h4>Objective</h4>This paper presents a model for analysis of chronic disease prescribing action over time in terms of transitions in status of therapy as indicated in electronic prescribing records. The quality of alerts derived from these therapeutic state transitions is assessed in the context of antihypertensive prescribing.<h4>Design</h4>A set of alert criteria is developed based on analysis of state-transition in past antihypertensive prescribing of a rural Australian General Practice. Thirty active patients coded as hypertensive with alerts on six months of previously un-reviewed prescribing, and 30 hypertensive patients without alerts, are randomly sampled and independently reviewed by the practice's two main general practice physicians (GPs), each GP reviewing 20 alert and 20 non-alert cases (providing 10 alert and 10 non-alert cases for agreement assessment).<h4>Measurements</h4>GPs provide blind assessment of quality of hypertension management and retrospective assessment of alert relevance.<h4>Results</h4>Alerts were found on 66 of 611 cases with coded hypertension with 37 alerts on the 30 sampled alert cases. GPs assessed alerting sensitivity as 74% (CI 52% - 89%) and specificity as 61% (CI 45% - 74%) for the sample, which is estimated as 26% sensitivity and 93% specificity for the antihypertensive population. Agreement between the GPs on assessment of alert relevance was fair (kappa = 0.37).<h4>Conclusions</h4>Data-driven development of alerts from electronic prescribing records using analysis of therapeutic state transition shows promise for derivation of high-specificity alerts to improve the quality of chronic disease management activities.
Keywords: Humans
Hypertension
Antihypertensive Agents
Medical Records Systems, Computerized
Models, Theoretical
Reminder Systems
Rural Health Services
Drug Utilization Review
Disease Management
South Australia
Medical Order Entry Systems
Drug Prescriptions
Practice Patterns, Physicians'
Description: Copyright © 2007 American Medical Informatics Association
DOI: 10.1197/jamia.M2169
Appears in Collections:Aurora harvest
Public Health publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.