Cited by 301Clinical Laboratory Practices and Quality ControlElectronic Health Records SystemsPatient Safety and Medication Errors

“I Wish I Had Seen This Test Result Earlier!”: Dissatisfaction With Test Result Management Systems in Primary Care

Open access
Poon, Eric G., Gandhi, Tejal K., Sequist, Thomas D., Murff, Harvey J., Karson, Andrew S., Bates, David W.·2004·Archives of Internal Medicine

Abstract

BACKGROUND: Failure to review and follow up on outpatient test results in a timely manner represents a patient safety and malpractice concern. Therefore, we sought to identify problems in current test result management systems and possible ways to improve these systems. METHODS: We surveyed 262 physicians working in 15 internal medicine practices affiliated with 2 large urban teaching hospitals (response rate, 64%). We asked physicians about systems they used and the amount of time they spent managing test results. We asked them to report delays in reviewing test results and their overall satisfaction with their management of test results. We also asked physicians to rate features they would find useful in a new test result management system. RESULTS: Overall, 83% of respondents reported at least 1 delay in reviewing test results during the previous 2 months. Despite reporting that they spent on average 74 minutes per clinical day managing test results, only 41% of physicians reported being satisfied with how they managed test results. Satisfaction was associated with fewer self-reported delays in reviewing test results. Physicians who actively tracked their test orders to completion were also more likely to be satisfied. The most highly desired features of a test result management system were tools to help physicians generate result letters to patients, prioritize their workflow, and track test orders to completion. CONCLUSIONS: Delays in test result review are common, and many physicians are not satisfied with how they manage test results. Tools to improve test result management in office practices need to improve workflow efficiency and track test orders to completion.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1001/archinte.164.20.2223

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

  • 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 [13]

    The COMMENT section reports frequent delays in reviewing test results and significant deficiencies in ambulatory test-result management. But the paper does not establish that these problems persisted despite EHR alerts and reminders: TEST RESULT MANAGEMENT SYSTEMS IN PLACE describes an electronic-medical-record to-do list used by some physicians, while COMMENT proposes automated warnings as a desired feature. Page numbers are unavailable in our copy. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • 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 [13]

    The citation is attached to the anticipated rate of appropriately identified abnormal test results, not to the citing authors’ sample-size calculation. The source’s “Test Result Management Systems in Place” section reports physicians’ follow-up systems, but our copy gives no rate of appropriately identified abnormal results. Its “Data Analysis” section also contains no 30-participant, 35-result, or 80%-power calculation. (LLM, conf=0.75)

    Experimental — accuracy not yet measured
  • Outpatient care is often busy and fragmented, making follow-up of abnormal laboratory test results prone to error.

    “Outpatient care is often busy and fragmented, and therefore follow-up of abnormal laboratory test results is prone to error.”
  • Missed laboratory results or delayed recognition of results creates a significant potential for outpatient diagnostic errors, adverse events, and liability claims.

    “missed laboratory results or delayed recognition of results leads to a significant potential for outpatient diagnostic errors, adverse events and liability claims.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 19 · Cited by 301

Research works printed but not linked: 3

  1. Risk Management Foundation. Reducing office practice risks. Forum. 2000;20:2.
  2. Reason J. Human Error. Cambridge, England: Cambridge University Press; 1990.
  3. Harbrecht MG. Using a comprehensive breast program to illustrate ways to improve patient safety. Paper presented at: National Ambulatory Primary Care Research and Education Conference on Patient Safety; September 18, 2003; Chicago, Ill.

Authors
Poon, E. G., Gandhi, T. K., Sequist, T. D., Murff, H. J., Karson, A. S., & Bates, D. W.
Affiliations
Brigham and Women's Hospital (US)
Venue
Archives of Internal Medicine
Published
2004-11-08
Volume
164
Issue
20
Pages
2223
ISSN
0003-9926 (ISSN-L)
OpenAlex
W2127579435
Cited by
301
References
19
Citations by year
2026: 4 · 2024: 5 · 2023: 7 · 2022: 5 · 2021: 13 · 2020: 8 · 2019: 19 · 2018: 12 · 2017: 19 · 2016: 10 · 2015: 29 · 2014: 26 · 2013: 18 · 2012: 11
FWCI
9.46
Type
journal article
Language
en
Open access
Locations
  • Archives of Internal Medicine (publishedVersion)
  • PubMed (publishedVersion)
Funders
Agency for Healthcare Research and Quality (R01 1U18 HS 11046-03)
Topics
  • Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
Keywords
test result management, physician satisfaction, patient safety, medical malpractice, internal medicine practice, workflow efficiency, physician time use
MeSH terms
Adult, Attitude of Health Personnel, Clinical Competence, Continuity of Patient Care, Female, Hospitals, Teaching, Humans, Internal Medicine, Job Satisfaction, Male, Middle Aged, Office Management, Probability, Time Factors, Multicenter Studies as Topic, Logistic Models, Medical Records Systems, Computerized, Outcome Assessment, Health Care, Clinical Laboratory Techniques, Health Care Surveys

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