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
Open accessAbstract
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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“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]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
Experimental — accuracy not yet measuredIn the citing paper
“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]
In the citing paper
“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]
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“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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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
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-11-01
- Volume
- 6
- Issue
- 6
- Pages
- 512-522
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- 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
- bronze
- doi.org
- 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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