Role of computerized physician order entry systems in facilitating medication errors

Department of Sociology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia 19104 USA.
JAMA The Journal of the American Medical Association (Impact Factor: 30.39). 04/2005; 293(10):1197-203. DOI: 10.1001/jama.293.10.1197
Source: PubMed

ABSTRACT Hospital computerized physician order entry (CPOE) systems are widely regarded as the technical solution to medication ordering errors, the largest identified source of preventable hospital medical error. Published studies report that CPOE reduces medication errors up to 81%. Few researchers, however, have focused on the existence or types of medication errors facilitated by CPOE.
To identify and quantify the role of CPOE in facilitating prescription error risks.
We performed a qualitative and quantitative study of house staff interaction with a CPOE system at a tertiary-care teaching hospital (2002-2004). We surveyed house staff (N = 261; 88% of CPOE users); conducted 5 focus groups and 32 intensive one-on-one interviews with house staff, information technology leaders, pharmacy leaders, attending physicians, and nurses; shadowed house staff and nurses; and observed them using CPOE. Participants included house staff, nurses, and hospital leaders.
Examples of medication errors caused or exacerbated by the CPOE system.
We found that a widely used CPOE system facilitated 22 types of medication error risks. Examples include fragmented CPOE displays that prevent a coherent view of patients' medications, pharmacy inventory displays mistaken for dosage guidelines, ignored antibiotic renewal notices placed on paper charts rather than in the CPOE system, separation of functions that facilitate double dosing and incompatible orders, and inflexible ordering formats generating wrong orders. Three quarters of the house staff reported observing each of these error risks, indicating that they occur weekly or more often. Use of multiple qualitative and survey methods identified and quantified error risks not previously considered, offering many opportunities for error reduction.
In this study, we found that a leading CPOE system often facilitated medication error risks, with many reported to occur frequently. As CPOE systems are implemented, clinicians and hospitals must attend to errors that these systems cause in addition to errors that they prevent.

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    ABSTRACT: Assess (1) if patients can improve their medical records' accuracy if effectively engaged using a networked Personal Health Record; (2) workflow efficiency and reliability for receiving and processing patient feedback; and (3) patient feedback's impact on medical record accuracy. Improving medical record' accuracy and associated challenges have been documented extensively. Providing patients with useful access to their records through information technology gives them new opportunities to improve their records' accuracy and completeness. A new approach supporting online contributions to their medication lists by patients of Geisinger Health Systems, an online patient-engagement advocate, revealed this can be done successfully. In late 2011, Geisinger launched an online process for patients to provide electronic feedback on their medication lists' accuracy before a doctor visit. Patient feedback was routed to a Geisinger pharmacist, who reviewed it and followed up with the patient before changing the medication list shared by the patient and the clinicians. The evaluation employed mixed methods and consisted of patient focus groups (users, nonusers, and partial users of the feedback form), semi structured interviews with providers and pharmacists, user observations with patients, and quantitative analysis of patient feedback data and pharmacists' medication reconciliation logs. (1) Patients were eager to provide feedback on their medications and saw numerous advantages. Thirty percent of patient feedback forms (457 of 1,500) were completed and submitted to Geisinger. Patients requested changes to the shared medication lists in 89 percent of cases (369 of 414 forms). These included frequency-or dosage changes to existing prescriptions and requests for new medications (prescriptions and over-the counter). (2) Patients provided useful and accurate online feedback. In a subsample of 107 forms, pharmacists responded positively to 68 percent of patient requests for medication list changes. (3) Processing patient feedback will requires both software algorithms and human interpretation. For the 107 forms subsample, pharmacists accepted patient input in 51 percent of cases where they could not contact the patient. Where the patient was contacted, they accepted feedback from 68 percent. This suggests there may be opportunities to automate feedback filtering and processing for more efficient (and larger scale) medication-list optimization. (4) A supportive overall e-health environment makes acceptance of an online patient feedback system more likely. Review of Geisinger usage data showed patients who completed the medication feedback form had previously accessed MyGeisinger 2.3 times as often as the average patient and initiated secure messages with a clinician 1.35 times as often as patients not involved in the pilot. Patient feedback, placed in a useful workflow, can improve medical record accuracy. Electronic health record (EHR) vendors and developers need to build appropriate capabilities into applications. Continued research and development is needed for enabling health care organizations to elicit and process patient information most effectively.
    01/2014; 2(3):1080. DOI:10.13063/2327-9214.1080

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