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J Am Med Inform Assoc 19:591-596 doi:10.1136/amiajnl-2011-000375
  • Research and applications

Presence of key findings in the medical record prior to a documented high-risk diagnosis

  1. Henry Chueh1,2
  1. 1Laboratory of Computer Science, Massachusetts General Hospital, Boston, Massaschusetts, USA
  2. 2Harvard Medical School, Boston, Massachusetts, USA
  1. Correspondence to Dr Mitchell J Feldman Laboratory of Computer Science, MGH 50 Staniford Street, 7th floor Boston, Massachusetts, 02420 USA; mfeldman{at}partners.org
  • Received 13 May 2011
  • Accepted 12 February 2012
  • Published Online First 19 March 2012

Abstract

Background Failure or delay in diagnosis is a common preventable source of error. The authors sought to determine the frequency with which high-information clinical findings (HIFs) suggestive of a high-risk diagnosis (HRD) appear in the medical record before HRD documentation.

Methods A knowledge base from a diagnostic decision support system was used to identify HIFs for selected HRDs: lumbar disc disease, myocardial infarction, appendicitis, and colon, breast, lung, ovarian and bladder carcinomas. Two physicians reviewed at least 20 patient records retrieved from a research patient data registry for each of these eight HRDs and for age- and gender-compatible controls. Records were searched for HIFs in visit notes that were created before the HRD was established in the electronic record and in general medical visit notes for controls.

Results 25% of records reviewed (61/243) contained HIFs in notes before the HRD was established. The mean duration between HIFs first occurring in the record and time of diagnosis ranged from 19 days for breast cancer to 2 years for bladder cancer. In three of the eight HRDs, HIFs were much less likely in control patients without the HRD.

Conclusions In many records of patients with an HRD, HIFs were present before the HRD was established. Reasons for delay include non-compliance with recommended follow-up, unusual presentation of a disease, and system errors (eg, lack of laboratory follow-up). The presence of HIFs in clinical records suggests a potential role for the integration of diagnostic decision support into the clinical workflow to provide reminder alerts to improve the diagnostic focus.

Footnotes

  • Funding Funding for this study was provided by a grant from the Partners-Siemens Research Council. The Partners-Siemens Research Council did not participate in the design of the study, in the collection, analysis or interpretation of the data, in the writing of the report or in the decision to submit the article for publication. The researchers were independent from the Partners-Siemens Research Council. This work was conducted with support from Harvard Catalyst. The Harvard Clinical and Translational Science Center (NIH Award #UL1 RR 025758 and financial contributions from Harvard University and its affiliated academic health care centers). The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic health care centers, the National Center for Research Resources, or the National Institutes of Health.

  • Competing interests MJF, EPH, GOB, RJK, KTF and HCC are employed by the Laboratory of Computer Science at Massachusetts General Hospital, the developers of the DXplain diagnostic decision support system. During the previous 3 year period, the Laboratory of Computer Science has received licensing royalties related to the DXplain system from approximately 40 hospitals and medical schools, and from Merck & Co, Inc and Epocrates, Inc.

  • Ethics approval Partners Healthcare Human Research Committee.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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