Computerized Physician Order Entry of Medications and Clinical Decision Support Can Improve Problem List Documentation Compliance

Abstract

Objective: The Problem List is a Key and Required Element of the Electronic Medical Record (EMR). Problem Lists May Contribute Substantially to Patient Safety and Quality of Care. Physician Documentation of the Problem List is Often Lower Than Desired. Methods Are Needed to Improve Accuracy and Completeness of the Problem List. Design: An Automated Clinical Decision Support (CDS) Intervention Was Designed Utilizing a Commercially Available EMR with Computerized Physician Order Entry (CPOE) and CDS. the System Was based on Alerts Delivered during Inpatient Medication CPOE that Prompted Clinicians to Add a Diagnosis to the Problem List. Each Alert Was Studied for a 2-Month Period after Implementation. Measurements: Measures Included Alert Validity, Alert Yield, and Accuracy of Problem List Additions. Results: At a 450 Bed Teaching Hospital, the Number of Medication Orders Which Triggered Alerts during All 2-Month Study Periods Was 1011. for All the Alerts, the Likelihood of a Valid Alert (An Alert that Occurred in Patients with One of the Predefined Diagnoses) Was 96 ± 1%. the Alert Yield, Defined as Occuring When an Alert Led to Addition of a Problem to the Problem List, Was 76 ± 2%. Accurate Problem List Additions, Defined as Additions of Problems When the Problem Was Determined to Be Present by Expert Review, Was 95 ± 1%. Conclusion: The CDS Problem List Mechanism Was Integrated into the Process of Medication Order Placement and Promoted Relatively Accurate Addition of Problems to the EMR Problem List. © 2008 Elsevier Ireland Ltd. All Rights Reserved.

Department(s)

Chemistry

Comments

Agency for Healthcare Research and Quality, Grant None

Keywords and Phrases

Clinical decision support; CPOE; Medical records; Problem lists; Problem-oriented

International Standard Serial Number (ISSN)

1386-5056

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2023 Elsevier, All rights reserved.

Publication Date

01 May 2010

PubMed ID

18599342

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