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

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. +1 more·1999·Journal of the American Medical Informatics Association
DOI 10.1136/jamia.1999.0060512PMC PMC61393
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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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  • A sample size of 30 participants, each reviewing 35 test results, was required to achieve 80% power to detect a statistically significant difference in cognitive workload and performance.

    “On the basis of the anticipated rate of appropriately identified abnormal test results in the literature12,13,14,15,16,17,18,19,20,21 and the anticipated magnitude of the association of the enhanced EHR, we required a sample size of 30 participants, each reviewing 35 test results, to achieve 80% power to detect a statistically significant difference in cognitive workload and performance.”

    From Association of the Usability of Electronic Health Records With Cognitive Workload and Performance Levels Among Physicians (2019) · cites this paper as [12]

    The Results report rates of physician review and intended action for critical-result alerts, which can inform the cited background about responses to abnormal results. The Analysis also mentions 80% power, but for detecting reductions in time to treatment and resolution—not for a study of 30 participants reviewing 35 results or for cognitive workload and performance. Those sample-size and outcome details are not supported by this source. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Even in the EHR environment, with alerts and reminders in place, physicians continue to often inappropriately manage abnormal test results.

    “Even in the EHR environment, with alerts and reminders in place, physicians continue to often inappropriately manage abnormal test results.12,13,14,15,16,17,18,19,20,21”

    From Association of the Usability of Electronic Health Records With Cognitive Workload and Performance Levels Among Physicians (2019) · cites this paper as [12]

    The Results (page unavailable) show that even with automated alerts, treatment was ordered more than five hours later in 16% of intervention cases. This supports persistent delays for some critical laboratory results, but the paper does not establish that physicians often managed abnormal results inappropriately across EHR settings; its principal finding was that alerts shortened the time to treatment. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Electronic alerts show promise in improving the safety of outpatient test result follow-up.

    “Electronic “alerts” have been shown to improve critical lab results communication in the inpatient setting, and they show promise in improving the safety of outpatient test result follow-up.45,52,53”

    From Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology (2008) · cites this paper as [45]

  • Electronic alerts have been shown to improve critical lab results communication in the inpatient setting.

    “Electronic “alerts” have been shown to improve critical lab results communication in the inpatient setting, and they show promise in improving the safety of outpatient test result follow-up.45,52,53”

    From Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology (2008) · cites this paper as [45]

  • Achieving high standards of patient safety through the use of IT also entails system redesign to include formal policies and procedures regarding the use of IT.

    “Thus, achieving high standards of patient safety through the use of IT also entails system redesign to include formal policies and procedures regarding the use of IT.43–47”

    From Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology (2008) · cites this paper as [45]

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Cites

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1 of the 33 references couldn’t be matched to a known paper.

Research works printed but not linked: 5

  1. Tate KE, Gardner RM, Weaver LK. A computerized labo- ratory alerting system. MD Comput. 1990;7(5):296-301.
  2. McDonald CJ. Computer reminders, the quality of care, and the nonperfectability of man. N Engl J Med. 1976;295: 1351-5.
  3. Leape LL, Bates DW, Cullen DJ, et al. Systems analysis of adverse drug events. ADE Prevention Study Group. JAMA. 1995;274(1):35-43.
  4. Teich JM, Glaser JP, Beckley RF, et al. Toward cost-effective, quality care: The Brigham Integrated Computing System. In: Steen EB (ed). Proceedings of the 2nd Nicholas E. Davies CPR Recognition Symposium. Washington DC: Computer- ized Patient Record Institute, 1996:3-34.
  5. Petersen LA, Orav EJ, Teich JM, O'Neil AC, Brennan TA. Using a computerized signout to improve continuity of in- patient care and prevent adverse events. Jt Comm J Qual Improv. 1998;24(2):77-87.

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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.
ORCID
Venue
Journal of the American Medical Informatics Association
Publisher
Oxford University Press (OUP)
Published
1999-11-01
Volume
6
Issue
6
Pages
512-522
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
DOI
10.1136/jamia.1999.0060512
PMC
PMC61393
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 › Medicine › Physiology › 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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