Use of a computer to detect and respond to clinical events: its effect on clinician behavior
- PMID: 1252043
- DOI: 10.7326/0003-4819-84-2-162
Use of a computer to detect and respond to clinical events: its effect on clinician behavior
Abstract
A computer was used to prospectively detect and suggest responses to simple, medication-related events as reflected in a computerized record in a prospective, randomized study of a diabetes clinic with primary-care responsibility. There were two categories of event/suggestions: when the last observation of a test required for medication control was too old, the computer suggested a repeat; and when an abnormality with therapeutic implications was detected, the computer suggested a specific change in therapeutics. Clinicians responded to 36% of events in the first category with computer reminders and 11% without (P less than 0.0001); they responded to 28% of events in the second category with computer assistance and 13% without (P less than 0.026). For the most clinically significant of these second category events, the difference was even greater: 47% with and 4% without computer assistance (P less than 0.0004). I believe that computer detection and response (in the form of reminders) to simple clinical events will change clinician behavior.
Similar articles
-
Physician response to computer reminders.JAMA. 1980 Oct 3;244(14):1579-81. JAMA. 1980. PMID: 7420656 Clinical Trial.
-
[Systematic recording and computer processing of diabetic data in a metabolism outpatient department].Wien Med Wochenschr. 1976 Apr 23;126(16-17):217-9. Wien Med Wochenschr. 1976. PMID: 969534 German. No abstract available.
-
The computer in retrieving dietary history data. II. Retrieving information by summary generation.J Am Diet Assoc. 1973 Oct;63(4):402-7. J Am Diet Assoc. 1973. PMID: 4745405 No abstract available.
-
Computer-generated reminders delivered on paper to healthcare professionals; effects on professional practice and health care outcomes.Cochrane Database Syst Rev. 2012 Dec 12;12:CD001175. doi: 10.1002/14651858.CD001175.pub3. Cochrane Database Syst Rev. 2012. Update in: Cochrane Database Syst Rev. 2017 Jul 06;7:CD001175. doi: 10.1002/14651858.CD001175.pub4. PMID: 23235578 Updated. Review.
-
Repaglinide : a pharmacoeconomic review of its use in type 2 diabetes mellitus.Pharmacoeconomics. 2004;22(6):389-411. doi: 10.2165/00019053-200422060-00005. Pharmacoeconomics. 2004. PMID: 15099124 Review.
Cited by
-
Twilighted Homegrown Systems: The Experience of Six Traditional Electronic Health Record Developers in the Post-Meaningful Use Era.Appl Clin Inform. 2020 Mar;11(2):356-365. doi: 10.1055/s-0040-1710310. Epub 2020 May 20. Appl Clin Inform. 2020. PMID: 32434224 Free PMC article.
-
Effectiveness of electronic point-of-care reminders versus monthly feedback to improve adherence to 10 clinical recommendations in primary care: a cluster randomized clinical trial.BMC Med Inform Decis Mak. 2019 Nov 29;19(1):245. doi: 10.1186/s12911-019-0976-8. BMC Med Inform Decis Mak. 2019. PMID: 31783854 Free PMC article. Clinical Trial.
-
Medication stewardship using computerized clinical decision support: A case study on intravenous immunoglobulins.Pharmacol Res Perspect. 2019 Aug 29;7(5):e00508. doi: 10.1002/prp2.508. eCollection 2019 Oct. Pharmacol Res Perspect. 2019. PMID: 31485333 Free PMC article.
-
Desiderata for sharable computable biomedical knowledge for learning health systems.Learn Health Syst. 2018 Aug 3;2(4):e10065. doi: 10.1002/lrh2.10065. eCollection 2018 Oct. Learn Health Syst. 2018. PMID: 31245589 Free PMC article.
-
Computer-generated reminders delivered on paper to healthcare professionals: effects on professional practice and healthcare outcomes.Cochrane Database Syst Rev. 2017 Jul 6;7(7):CD001175. doi: 10.1002/14651858.CD001175.pub4. Cochrane Database Syst Rev. 2017. PMID: 28681432 Free PMC article. Review.
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources