Contrasting views of physicians and nurses about an inpatient computer-based provider order-entry system.
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OBJECTIVE: Many hospitals are investing in computer-based provider order-entry (POE) systems, and providers' evaluations have proved important for the success of the systems. The authors assessed how physicians and nurses viewed the effects of one modified commercial POE system on time spent patients, resource utilization, errors with orders, and overall quality of care. DESIGN: Survey. MEASUREMENTS: Opinions of 271 POE users on medicine wards of an urban teaching hospital: 96 medical house officers, 49 attending physicians, 19 clinical fellows with heavy inpatient loads, and 107 nurses. RESULTS: Responses were received from 85 percent of the sample. Most physicians and nurses agreed that orders were executed faster under POE. About 30 percent of house officers and attendings or fellows, compared with 56 percent of nurses, reported improvement in overall quality of care with POE. Forty-four percent of house officers and 34 percent of attendings/fellows reported that their time with patients decreased, whereas 56 percent of nurses indicated that their time with patients increased (P < 0.001). Sixty percent of house officers and 41 percent of attendings/fellows indicated that order errors increased, whereas 69 percent of nurses indicated a decrease or no change in errors. Although most nurses reported no change in the frequency of ordering tests and medications with POE, 61 percent of house officers reported an increased frequency. CONCLUSION: Physicians and nurses had markedly different views about effects of a POE system on patient care, highlighting the need to consider both perspectives when assessing the impact of POE. With this POE system, most nurses saw beneficial effects, whereas many physicians saw negative effects. (+info)
The impact of computerized physician order entry on medication error prevention.
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BACKGROUND: Medication errors are common, and while most such errors have little potential for harm they cause substantial extra work in hospitals. A small proportion do have the potential to cause injury, and some cause preventable adverse drug events. OBJECTIVE: To evaluate the impact of computerized physician order entry (POE) with decision support in reducing the number of medication errors. DESIGN: Prospective time series analysis, with four periods. SETTING AND PARTICIPANTS: All patients admitted to three medical units were studied for seven to ten-week periods in four different years. The baseline period was before implementation of POE, and the remaining three were after. Sophistication of POE increased with each successive period. INTERVENTION: Physician order entry with decision support features such as drug allergy and drug-drug interaction warnings. MAIN OUTCOME MEASURE: Medication errors, excluding missed dose errors. RESULTS: During the study, the non-missed-dose medication error rate fell 81 percent, from 142 per 1,000 patient-days in the baseline period to 26.6 per 1,000 patient-days in the final period (P < 0.0001). Non-intercepted serious medication errors (those with the potential to cause injury) fell 86 percent from baseline to period 3, the final period (P = 0.0003). Large differences were seen for all main types of medication errors: dose errors, frequency errors, route errors, substitution errors, and allergies. For example, in the baseline period there were ten allergy errors, but only two in the following three periods combined (P < 0.0001). CONCLUSIONS: Computerized POE substantially decreased the rate of non-missed-dose medication errors. A major reduction in errors was achieved with the initial version of the system, and further reductions were found with addition of decision support features. (+info)
The transition to automated practitioner order entry in a teaching hospital: the VA Puget Sound experience.
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We recently installed an automated practitioner order entry system on our busiest inpatient wards and critical care units. The installation followed 20 months preparation in which we created the workstation, network, and host infrastructure, developed requisite policies, recruited personnel to support the system, and installed the software in areas where the pace of order entry was less intense. Since implementing automated order entry, we have experienced problems such as an increase in time required for practitioners to enter orders, workflow changes on inpatient units, difficulties with patient transfers, and others. Our user support system has been heavily used during the transition period. Software tailoring and enhancements designed to address these problems are planned, as is installation of the order entry system in remaining clinical units in our medical centers. (+info)
Comparison of two knowledge bases on the detection of drug-drug interactions.
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This paper describes a drug ordering decision support system that helps with the prevention of adverse drug events by detecting drug-drug interactions in drug orders. The architecture of the system was devised in order to facilitate its use attached to physician order entry systems. The described model focuses in issues related to knowledge base maintenance and integration with external systems. Finally, a retrospective study was performed. Two knowledge bases, developed by different academic centers, were used to detect drug-drug interactions in a dataset with 37,237 drug prescriptions. The study concludes that the proposed knowledge base architecture enables content from other knowledge sources to be easily transferred and adapted to its structure. The study also suggests a method that can be used on the evaluation and refinement of the content of drug knowledge bases. (+info)
Improving allergy alerting in a computerized physician order entry system.
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Computerized physician order entry has been shown to reduce the frequency of serious medication errors. Decision support tools such as alerting functions for patient medication allergy are a key part of these applications. However, optimal performance requires iterative refinement. As systems become increasingly complex, mechanisms to monitor their performance become increasingly critical. We analyzed trend data obtained over a five-year period that showed decreasing compliance to allergy alert functions within computerized order entry. Many medication-allergy pairs were being consistently overridden. Renewal policies affecting reordering narcotics also contributed heavily to this trend. Each factor revealed a system-wide trend that could result in suggestions for policy or software change. Monitoring trends such as these is very important to maintain software correctness and ensure user trust in alerting systems, so users remain responsive to computerized alerts. (+info)
Reducing medication regimen complexity: a controlled trial.
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OBJECTIVE: To determine if a visual intervention (medication grid) delivered to physicians can reduce medication regimen complexity. DESIGN: Nonrandomized, controlled trial. SETTING: Veterans Affairs medical center. PATIENTS/PARTICIPANTS: Eight hundred thirty-six patients taking at least 5 medications at the time of admission and the 48 teams of physicians and students on the general medicine inpatient service. INTERVENTION: For intervention patients, a medication grid was created that displayed all of the patients' medicines and the times of administration for 1 week. This grid was delivered to the admitting resident soon after admission. MEASUREMENTS AND MAIN RESULTS: For the patients of each team of physicians, we calculated the change in the average number of medications and doses from admission to discharge. The number of medications in the intervention group decreased by 0.92 per patient, and increased by 1.65 in the control group (P <.001). The mean number of doses per day in the intervention group decreased by 2.47 per patient and increased by 3.83 in the control group (P <.001). CONCLUSIONS: This simple intervention had a significant impact on medication regimen complexity in this population. Apparently, physicians were able to address polypharmacy when the issue was brought to their attention. (+info)
What's so special about medications: a pharmacist's observations from the POE study.
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Observations from a multi-site observational study of physician order entry (POE) confirm that implementing POE is problematic, and suggest that implementing medication order entry is particularly difficult. A pharmacist participating in the study group sought to answer the question: What makes medications different? Analysis of themes specific to medication POE in this study's large data set was undertaken using a grounded theory approach. Emerging themes in the data are explored and include: (1) order complexity and the consequences of error; (2) impacts on professional roles; (3) prescribing needs in different settings; and (4) technology impact on medication administration. Awareness of potential roadblocks and lessons learned from previous implementation attempts should help organizations considering medication POE to optimize their own strategies. (+info)
Physician Order Entry impact on drug turn-around times.
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This paper describes a study of the impact of Physician Order Entry (POE) on pharmacy order turn-around times. The study looked at two surgical services, Neurosurgery and Transplant, of a large Midwestern academic medical center. Pharmacy orders were followed in these units from the time a physician wrote an order to the time the patient received the medication. The first part of the study tracked pharmacy orders for a two-month period before the implementation of POE and the second part of the study tracked pharmacy orders for a two-month period after POE had been implemented. The pre- and post-POE pharmacy turn-around times were compared. It was expected that the data would show a substantial decrease in pharmacy order turn-around times. Our study did, in fact, show a significant reduction in this turn-around-time. (+info)