Cited by 324Electronic Health Records SystemsHealthcare Technology and Patient MonitoringAcute Kidney Injury Research

Effect of Computer-Based Alerts on the Treatment and Outcomes of Hospitalized Patients

Rind, David M.·1994·Archives of Internal Medicine

Abstract

BACKGROUND: Hospital computing systems play an important part in the communication of clinical information to physicians. We sought to determine whether computer-based alerts for hospitalized patients can affect physicians' behavior and improve patients' outcomes. METHODS: We performed a prospective time-series study to determine whether computerized alerts to physicians about rising creatinine levels in hospitalized patients receiving nephrotoxic or renally excreted medications led to more rapid adjustment or discontinuation of those medications, and to determine whether such alerts protected renal function. RESULTS: Laboratory data were observed for 20,228 hospitalizations, with documentation of 1573 events (instances of rising creatinine levels during treatment with a nephrotoxic or renally excreted drug). During the intervention period, doses were adjusted or medications discontinued an average of 21.6 hours sooner after such an event (P < .0001). For patients receiving nephrotoxic medications during the intervention period, the relative risk of serious renal impairment was 0.45 (95% confidence interval, 0.22 to 0.94) as compared with the control period, and the mean serum creatinine level was 14.1 mumol/L (0.16 mg/dL) lower on day 3 (P < .01) and 25.6 mumol/L (0.29 mg/dL) lower on day 7 (P < .05) after an event. Forty-four percent of physicians who responded to a questionnaire said that the alerts had been helpful in the care of their patients, whereas 28% found them annoying. Sixty-five percent wished to continue receiving alerts. CONCLUSIONS: Computer-based alerts regarding patients with rising creatinine levels affect physician behavior, prevent serious renal impairment, preserve renal function, and are accepted by clinicians.

Integrity signals

Registry

Crossref · 10.1001/archinte.1994.00420130107014

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Rind, D. M.
Affiliations
Harvard University (US)
Corresponding author
Rind, David M.
Venue
Archives of Internal Medicine
Published
1994-07-11
Volume
154
Issue
13
Pages
1511
ISSN
0003-9926 (ISSN-L)
OpenAlex
W2011542177
Cited by
323
References
29
Citations by year
2026: 1 · 2025: 4 · 2024: 4 · 2023: 8 · 2022: 9 · 2021: 8 · 2020: 5 · 2019: 6 · 2018: 5 · 2017: 9 · 2016: 14 · 2015: 12 · 2014: 10 · 2013: 7 · 2012: 10
FWCI
30.14
Type
journal article
Language
en
Open access
closed
Locations
  • Archives of Internal Medicine (publishedVersion)
  • PubMed (publishedVersion)
Funders
Agency for Healthcare Research and Quality (HS06288-03)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
  • Health Sciences › Medicine › Nephrology › Acute Kidney Injury Research
Keywords
nephrotoxic drugs, renal function, serum creatinine, medication dose adjustment, physician behavior, hospitalized patients, drug-induced nephrotoxicity, electronic health records
MeSH terms
Adult, Clinical Laboratory Information Systems, Creatinine, Drug Therapy, Computer-Assisted, Hospital Information Systems, Hospitalization, Humans, Office Automation, Prospective Studies, Surveys and Questionnaires, Linear Models, Treatment Outcome, Acute Kidney Injury

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review