Cited by 252Electronic Health Records SystemsHealthcare Technology and Patient MonitoringClinical Laboratory Practices and Quality Control

The DOI matches its Crossref record; 32 of the 33 references it cites were found in a registry or an index.

Improving Response to Critical Laboratory Results with Automation: Results of a Randomized Controlled Trial

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Kuperman, G. J., Teich, J. M., Tanasijevic, M. J., Ma'Luf, N., Rittenberg, E., Jha, A., Fiskio, J., Winkelman, J., Bates, D. W.·1999·Journal of the American Medical Informatics Association

Abstract

OBJECTIVE: To evaluate the effect of an automatic alerting system on the time until treatment is ordered for patients with critical laboratory results. DESIGN: Prospective randomized controlled trial. INTERVENTION: A computer system to detect critical conditions and automatically notify the responsible physician via the hospital's paging system. PATIENTS: Medical and surgical inpatients at a large academic medical center. One two-month study period for each service. MAIN OUTCOMES: Interval from when a critical result was available for review until an appropriate treatment was ordered. Secondary outcomes were the time until the critical condition resolved and the frequency of adverse events. METHODS: The alerting system looked for 12 conditions involving laboratory results and medications. For intervention patients, the covering physician was automatically notified about the presence of the results. For control patients, no automatic notification was made. Chart review was performed to determine the outcomes. RESULTS: After exclusions, 192 alerting situations (94 interventions, 98 controls) were analyzed. The intervention group had a 38 percent shorter median time interval (1.0 hours vs. 1.6 hours, P = 0.003; mean, 4.1 vs. 4.6 hours, P = 0.003) until an appropriate treatment was ordered. The time until the alerting condition resolved was less in the intervention group (median, 8.4 hours vs. 8.9 hours, P = 0.11; mean, 14.4 hours vs. 20.2 hours, P = 0.11), although these results did not achieve statistical significance. The impact of the intervention was more pronounced for alerts that did not meet the laboratory's critical reporting criteria. There was no significant difference between the two groups in the number of adverse events. CONCLUSION: An automatic alerting system reduced the time until an appropriate treatment was ordered for patients who had critical laboratory results. Information technologies that facilitate the transmission of important patient data can potentially improve the quality of care.

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Crossref · 10.1136/jamia.1999.0060512

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Research works printed but not linked: 3

  1. Leape, 1994, JAMA, 272, 1851, 10.1001/jama.1994.03520230061039 · DOI
  2. Tate, 1990, M.D. computing : computers in medical practice, 7, 296
  3. 1995, JAMA, 274, 35, 10.1001/jama.1995.03530010049034 · DOI · Paper page

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Metadata

Authors
Kuperman, G. J., Teich, J. M., Tanasijevic, M. J., Ma'Luf, N., Rittenberg, E., Jha, A., Fiskio, J., Winkelman, J., & Bates, D. W.
Affiliations
Harvard University (US)
Corresponding author
Kuperman, G. J.
Venue
Journal of the American Medical Informatics Association
Published
1999-11-01
Volume
6
Issue
6
Pages
512-522
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
OpenAlex
W1961197524
Cited by
252
References
33
Citations by year
2026: 3 · 2025: 3 · 2024: 2 · 2023: 3 · 2022: 5 · 2021: 5 · 2020: 7 · 2019: 9 · 2018: 8 · 2017: 6 · 2016: 9 · 2015: 6 · 2014: 11 · 2013: 10 · 2012: 11
FWCI
18.24
Type
journal article
Language
en
Open access
Locations
  • Journal of the American Medical Informatics Association (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
Agency for Healthcare Research and Quality (R01-HS08927)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
  • Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
Keywords
automated alerts, physician notification, critical value reporting, adverse events, hospitalized patients, health information technology, quality of care
MeSH terms
Academic Medical Centers, Electronic Data Processing, Clinical Laboratory Information Systems, Hospital Communication Systems, Humans, Prospective Studies, Software, Therapy, Computer-Assisted, Time Factors, Point-of-Care Systems, Clinical Laboratory Techniques

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