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Published in: Journal of General Internal Medicine 8/2012

01-08-2012 | Original Research

Use of an Electronic Problem List by Primary Care Providers and Specialists

Authors: Adam Wright, PhD, Joshua Feblowitz, MS, Francine L. Maloney, BA, Stanislav Henkin, BA, David W. Bates, MD, MSc

Published in: Journal of General Internal Medicine | Issue 8/2012

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ABSTRACT

BACKGROUND

Accurate patient problem lists are valuable tools for improving the quality of care, enabling clinical decision support, and facilitating research and quality measurement. However, problem lists are frequently inaccurate and out-of-date and use varies widely across providers.

OBJECTIVE

Our goal was to assess provider use of an electronic problem list and identify differences in usage between medical specialties.

DESIGN

Chart review of a random sample of 100,000 patients who had received care in the past two years at a Boston-based academic medical center.

PARTICIPANTS

Counts were collected of all notes and problems added for each patient from 1/1/2002 to 4/30/2010. For each entry, the recording provider and the clinic in which the entry was recorded was collected. We used the Healthcare Provider Taxonomy Code Set to categorize each clinic by specialty.

MAIN MEASURES

We analyzed the problem list use across specialties, controlling for note volume as a proxy for visits.

KEY RESULTS

A total of 2,264,051 notes and 158,105 problems were recorded in the electronic medical record for this population during the study period. Primary care providers added 82.3% of all problems, despite writing only 40.4% of all notes. Of all patients, 49.1% had an assigned primary care provider (PCP) affiliated with the hospital; patients with a PCP had an average of 4.7 documented problems compared to 1.5 problems for patients without a PCP.

CONCLUSIONS

Primary care providers were responsible for the majority of problem documentation; surgical and medical specialists and subspecialists recorded a disproportionately small number of problems on the problem list.
Literature
1.
go back to reference Hartung DM, Hunt J, Siemienczuk J, Miller H, Touchette DR. Clinical implications of an accurate problem list on heart failure treatment. J Gen Intern Med. 2005;20:143–7.PubMedCrossRef Hartung DM, Hunt J, Siemienczuk J, Miller H, Touchette DR. Clinical implications of an accurate problem list on heart failure treatment. J Gen Intern Med. 2005;20:143–7.PubMedCrossRef
2.
go back to reference Wright A, Goldberg H, Hongsermeier T, Middleton B. A description and functional taxonomy of rule-based decision support content at a large integrated delivery network. J Am Med Inform Assoc. 2007;14:489–96.PubMedCrossRef Wright A, Goldberg H, Hongsermeier T, Middleton B. A description and functional taxonomy of rule-based decision support content at a large integrated delivery network. J Am Med Inform Assoc. 2007;14:489–96.PubMedCrossRef
3.
go back to reference Wright A, McGlinchey EA, Poon EG, Jenter CA, Bates DW, Simon SR. Ability to generate patient registries among practices with and without electronic health records. J Med Internet Res. 2009;11:e31.PubMedCrossRef Wright A, McGlinchey EA, Poon EG, Jenter CA, Bates DW, Simon SR. Ability to generate patient registries among practices with and without electronic health records. J Med Internet Res. 2009;11:e31.PubMedCrossRef
4.
go back to reference Poon EG, Wright A, Simon SR, et al. Relationship between use of electronic health record features and health care quality: results of a statewide survey. Med Care. 2010;48:203–9.PubMedCrossRef Poon EG, Wright A, Simon SR, et al. Relationship between use of electronic health record features and health care quality: results of a statewide survey. Med Care. 2010;48:203–9.PubMedCrossRef
6.
go back to reference Kaplan DM. Clear writing, clear thinking and the disappearing art of the problem list. J Hosp Med. 2007;2:199–202.PubMedCrossRef Kaplan DM. Clear writing, clear thinking and the disappearing art of the problem list. J Hosp Med. 2007;2:199–202.PubMedCrossRef
7.
go back to reference Szeto HC, Coleman RK, Gholami P, Hoffman BB, Goldstein MK. Accuracy of computerized outpatient diagnoses in a Veterans Affairs general medicine clinic. Am J Manage Care. 2002;8:37–43. Szeto HC, Coleman RK, Gholami P, Hoffman BB, Goldstein MK. Accuracy of computerized outpatient diagnoses in a Veterans Affairs general medicine clinic. Am J Manage Care. 2002;8:37–43.
8.
go back to reference Tang PC, LaRosa MP, Gorden SM. Use of computer-based records, completeness of documentation, and appropriateness of documented clinical decisions. J Am Med Inform Assoc. 1999;6:245–51.PubMedCrossRef Tang PC, LaRosa MP, Gorden SM. Use of computer-based records, completeness of documentation, and appropriateness of documented clinical decisions. J Am Med Inform Assoc. 1999;6:245–51.PubMedCrossRef
9.
go back to reference Feblowitz J, Wright A. The Patient Problem List: An Ethnographic Study of Primary Care Provider Use and Attitudes. AMIA 2011 Annual Symposium. Washington, D.C.; 2011 (under review). Feblowitz J, Wright A. The Patient Problem List: An Ethnographic Study of Primary Care Provider Use and Attitudes. AMIA 2011 Annual Symposium. Washington, D.C.; 2011 (under review).
10.
go back to reference Wright A, Maloney F, Feblowitz J. Clinician attitudes toward and use of electronic problem lists: a thematic analysis. BMC Med Inform Decis Mak. 2011;11:36–45.PubMedCrossRef Wright A, Maloney F, Feblowitz J. Clinician attitudes toward and use of electronic problem lists: a thematic analysis. BMC Med Inform Decis Mak. 2011;11:36–45.PubMedCrossRef
11.
go back to reference Wright A, Pang J, Feblowitz J, et al. A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record. J Am Med Inform Assoc. 2011;18:859–67.PubMedCrossRef Wright A, Pang J, Feblowitz J, et al. A method and knowledge base for automated inference of patient problems from structured data in an electronic medical record. J Am Med Inform Assoc. 2011;18:859–67.PubMedCrossRef
12.
go back to reference Information Management Processes (Standard IM 6.40): 2008 Comprehensive Accreditation Manual for Hospitals: The Official Handbook. Oakbrook Terrace, Illinois: Joint Commission Resources: 2008. Information Management Processes (Standard IM 6.40): 2008 Comprehensive Accreditation Manual for Hospitals: The Official Handbook. Oakbrook Terrace, Illinois: Joint Commission Resources: 2008.
13.
go back to reference McMullen CK, Ash JS, Sittig DF, et al. Rapid assessment of clinical information systems in the healthcare setting. An efficient method for time-pressed evaluation. Methods Inf Med. 2010;50:299–307. McMullen CK, Ash JS, Sittig DF, et al. Rapid assessment of clinical information systems in the healthcare setting. An efficient method for time-pressed evaluation. Methods Inf Med. 2010;50:299–307.
14.
go back to reference Bonetti R, Castelli J, Childress JL, et al. Best practices for problem lists in an EHR. J AHIMA / Am Health Inf Manag Assoc. 2008;79:73–7. Bonetti R, Castelli J, Childress JL, et al. Best practices for problem lists in an EHR. J AHIMA / Am Health Inf Manag Assoc. 2008;79:73–7.
Metadata
Title
Use of an Electronic Problem List by Primary Care Providers and Specialists
Authors
Adam Wright, PhD
Joshua Feblowitz, MS
Francine L. Maloney, BA
Stanislav Henkin, BA
David W. Bates, MD, MSc
Publication date
01-08-2012
Publisher
Springer-Verlag
Published in
Journal of General Internal Medicine / Issue 8/2012
Print ISSN: 0884-8734
Electronic ISSN: 1525-1497
DOI
https://doi.org/10.1007/s11606-012-2033-5

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