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Order Entry (order + entry)
Kinds of Order Entry Selected AbstractsComputerized Physician Order Entry with Clinical Decision Support in the Long-Term Care Setting: Insights from the Baycrest Centre for Geriatric CareJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 10 2005Paula A. Rochon MD Although computerized physician order entry (CPOE) has been successfully implemented in many acute care hospitals, few descriptions of its use in the long-term care (LTC) setting are available. This report describes the experiences of one LTC facility in developing and implementing a CPOE system with clinical decision support (CDS). Even when a facility has the necessary resources and "institutional will," many challenges are associated with the implementation of this application. The system was designed to meet the needs of healthcare providers in the LTC setting, in particular by informing prescribing decisions, reducing the frequency of prescribing and monitoring errors, and reducing adverse drug event rates. Based on experience adopting this technology early, 10 insights are offered that it is hoped will assist others who are considering the implementation of CPOE systems with CDS in the LTC setting. [source] Effects of Computerized Provider Order Entry and Nursing Documentation on WorkflowACADEMIC EMERGENCY MEDICINE, Issue 10 2008Phillip V. Asaro MD Abstract Objectives:, The objective was to measure the effects of the implementation of computerized provider order entry (CPOE) and electronic nursing documentation on provider workflow in the emergency department (ED). Methods:, The authors performed a before-and-after time-motion study of the activities of physicians and nurses. The percentages of time spent in task categories were calculated by provider session and averaged across provider sessions. Results:, There was a shift in physician time from working with paper alone, 13.1% to 9.6% (p = 0.05), to working with paper while using a computer, 1.6% to 4.3% (p = 0.02), and an increase in time spent working on computer and/or paper from 30.0% to 38.9% (p = 0.02). For nurses, the increase in time spent on computer from 9.5% to 25.7% (p < 0.01) was offset by a decrease in time spent working with paper from 16.5% to 1.8% (p < 0.01). Direct care decreased minimally for nurses from 56.9% to 55.3% (p = 0.69), but from 36.8% to 29.1% (p = 0.07) for physicians, approaching statistical significance. Care planning decreased for nurses from 9.4% to 6.4% (p = 0.04) and from 21.7% to 19.5% (p = 0.60) for physicians. Conclusions:, The net effects of an implementation on provider workflow depend not only on changes in tasks directly related to the provider,computer interface, but also on changes in underlying patient care processes and information flows. The authors observed an unanticipated shift in physician time from interacting with nurses and patients toward retrieving information from the electronic patient record. Implementers should carefully consider how implementations will affect information flow and then expect the unexpected. [source] Providers Do Not Verify Patient Identity during Computer Order EntryACADEMIC EMERGENCY MEDICINE, Issue 7 2008Philip L. Henneman MD Abstract Introduction:, Improving patient identification (ID), by using two identifiers, is a Joint Commission safety goal. Appropriate identifiers include name, date of birth (DOB), or medical record number (MRN). Objectives:, The objectives were to determine the frequency of verifying patient ID during computerized provider order entry (CPOE). Methods:, This was a prospective study using simulated scenarios with an eye-tracking device. Medical providers were asked to review 10 charts (scenarios), select the patient from a computer alphabetical list, and order tests. Two scenarios had embedded ID errors compared to the computer (incorrect DOB or misspelled last name), and a third had a potential error (second patient on alphabetical list with same last name). Providers were not aware the focus was patient ID. Verifying patient ID was defined as looking at name and either DOB or MRN on the computer. Results:, Twenty-five of 25 providers (100%; 95% confidence interval [CI] = 86% to 100%) selected the correct patient when there was a second patient with the same last name. Two of 25 (8%; 95% CI = 1% to 26%) noted the DOB error; the remaining 23 ordered tests on an incorrect patient. One of 25 (4%, 95% CI = 0% to 20%) noted the last name error; 12 ordered tests on an incorrect patient. No participant (0%, 0/107; 95% CI = 0% to 3%) verified patient ID by looking at MRN prior to selecting a patient from the alphabetical list. Twenty-three percent (45/200; 95% CI = 17% to 29%) verified patient ID prior to ordering tests. Conclusions:, Medical providers often miss ID errors and infrequently verify patient ID with two identifiers during CPOE. [source] Computerized Physician Order Entry with Clinical Decision Support in the Long-Term Care Setting: Insights from the Baycrest Centre for Geriatric CareJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 10 2005Paula A. Rochon MD Although computerized physician order entry (CPOE) has been successfully implemented in many acute care hospitals, few descriptions of its use in the long-term care (LTC) setting are available. This report describes the experiences of one LTC facility in developing and implementing a CPOE system with clinical decision support (CDS). Even when a facility has the necessary resources and "institutional will," many challenges are associated with the implementation of this application. The system was designed to meet the needs of healthcare providers in the LTC setting, in particular by informing prescribing decisions, reducing the frequency of prescribing and monitoring errors, and reducing adverse drug event rates. Based on experience adopting this technology early, 10 insights are offered that it is hoped will assist others who are considering the implementation of CPOE systems with CDS in the LTC setting. [source] A 3-year study of medication incidents in an acute general hospitalJOURNAL OF CLINICAL PHARMACY & THERAPEUTICS, Issue 2 2008L. Song MPhil Summary Background and objective:, Inappropriate medication use may harm patients. We analysed medication incident reports (MIRs) as part of the feedback loop for quality assurance. Methods:, From all MIRs in a university-affiliated acute general hospital in Hong Kong in the period January 2004,December 2006, we analysed the time, nature, source and severity of medication errors. Results:, There were 1278 MIRs with 36 (range 15,107) MIRs per month on average. The number of MIRs fell from 649 in 2004, to 353 in 2005, and to 276 in 2006. The most common type was wrong strength/dosage (36·5%), followed by wrong drug (16·7%), wrong frequency (7·7%), wrong formulation (7·0%), wrong patient (6·9%) and wrong instruction (3·1%). 60·9%, 53·7% and 84·0% of MIRs arose from handwritten prescription (HP) rather than the computerized medication order entry in 2004, 2005 and 2006 respectively. In 43·1% of MIRs, preregistration house officers were involved. Most errors (80·2%) were detected before any drug was wrongly administered. The medications were administered in 212 cases (19·7%), which resulted in an untoward effect in nine cases (0·8%). Conclusions:, The most common errors were wrong dosage and wrong drug. Many incidents involved preregistration house officers and HPs. Our computerized systems appeared to reduce medication incidents. [source] Computerized physician order entry (CPOE) system: expectations and experiences of usersJOURNAL OF EVALUATION IN CLINICAL PRACTICE, Issue 4 2010Jasperien E. Van Doormaal PharmD Abstract Objectives, To explore physicians' and nurses' expectations before and experiences after the implementation of a computerized physician order entry (CPOE) system in order to give suggestions for future optimization of the system as well as the implementation process. Method, On four internal medicine wards of two Dutch hospitals, 18 physicians and 42 nurses were interviewed to measure expectations and experiences with the CPOE system. Using semi-structured questionnaires, expectations and experiences of physicians and nurses with the CPOE system were measured with statements on a 5-point Likert scale (1 = completely disagree, 5 = completely agree). The percentage respondents agreeing (score of 4 or 5) was calculated. Chi-squared tests were used to compare the expectations versus experiences of physicians and nurses and to assess the differences between physicians and nurses. Results, In general, both physicians and nurses were positive about CPOE before and after the implementation of this system. Physicians and nurses did not differ in their views towards CPOE except for the overview of patients' medication use that was not clear according to the nurses. Both professions were satisfied with the implementation process. CPOE could be improved especially with respect to technical aspects (including the medication overview) and decision support on drug,drug interactions. Conclusion, Overall we conclude that physicians and nurses are positive about CPOE and the process of its implementation and do accept these systems. However, these systems should be further improved to fit into clinical practice. [source] Methodology for evaluating physician order entry (POE) implementationsJOURNAL OF EVALUATION IN CLINICAL PRACTICE, Issue 4 2003Glen Geiger MD CM MASc BASc FRCPC Abstract The body of physician order entry (POE) implementations literature uses statistical evaluation methods to demonstrate changes in specified variables after POE implementation. To understand and manage the holistic impact of POE on the health care institution, a methodology that utilizes feedback to guide the POE implementation towards the satisfaction of stakeholder objectives is presented. Stakeholders jointly define quantitative and qualitative metrics for their objectives, establish target value vectors for the metrics that represent acceptable implementation outcomes and specify evaluation milestones. These are used to compare pre- and post-POE implementation clinical performance, enabling a socio-technical feedback,improvement cycle. A case study is provided to illustrate how the methodology is being used at Sunnybrook and Women's College Health Science Centre in Toronto, Canada. [source] Universal acceptance of computerized physician order entry: What would it take?JOURNAL OF HOSPITAL MEDICINE, Issue 4 2006Eric G. Poon MD [source] The relationship between computerized physician order entry and pediatric adverse drug events: a nested matched case-control study,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 8 2009Feliciano Yu MD, MSPH Abstract This study assesses the impact of computerized physician order entry (CPOE) implementation in pediatric hospitals on reported adverse drug events. Using a nested matched case-control design; we linked CPOE implementation information from the health information management systems society analytics database with reported adverse drug event (ADE) from the national association of children's hospitals and related institutions case mix comparative data program. Differences were examined using univariate and multivariate conditional logistic regression analyses. Patients from CPOE hospitals were more frequently seen in larger hospitals have more co-morbidities than those from non-CPOE hospitals. When matched by admitting diagnosis, age, gender and race, ADE cases were associated with more reported co-morbidities, and were reported less frequently in hospitals with CPOE. Patients from hospitals without CPOE were 42% more likely to experience reportable ADE after adjusting for the presence of co-morbidities. In conclusion, we found significant beneficial associations between reportable ADE and CPOE adoption in a representative sample of pediatric hospitals. Copyright © 2009 John Wiley & Sons, Ltd. [source] Rural Hospital Patient Safety Systems Implementation in Two StatesTHE JOURNAL OF RURAL HEALTH, Issue 3 2007Daniel R. Longo ScD ABSTRACT:,Context and Purpose:With heightened attention to medical errors and patient safety, we surveyed Utah and Missouri hospitals to assess the "state of the art" in patient safety systems and identify changes over time. This study examines differences between urban and rural hospitals.Methods:Survey of all acute care hospitals in Utah and Missouri at 2 points in time (2002 and 2004). Factor analysis was used to develop 7 latent variables to summarize the data, comparing rural and urban hospitals at each point in time and on change between the 2 survey times.Findings:On 3 of the 7 latent variables, there was a statistically significant difference between rural and urban hospitals at the first survey, with rural hospitals indicating lower levels of implementation. The differences remained present on 2 of those latent variables at the second survey. In both cases, 1 of those variables was computerized physician order entry (CPOE) systems. Rural hospitals reported more improvement in systems implementation between the 2 survey times, with the difference statistically significant on 1 of the 7 latent variables; the greatest improvement was in implementation of "root cause analysis."Conclusions:Adoption of patient safety systems overall is low. Although rates of adoption among rural versus urban hospitals appear lower, most differences are not statistically significant; the gap between rural and urban hospitals relative to quality measures is narrowing. Change in rural and urban hospitals is in the right direction, with the rate of change higher in rural hospitals for many systems. [source] The impact of computerised physician order entry on prescribing practices in a cardiothoracic intensive care unit,ANAESTHESIA, Issue 2 2010J. Ali Summary This prospective, time series, cross-sectional study was designed to compare the quality of handwritten vs computerised prescriptions in a tertiary 25-bedded cardiothoracic intensive care unit. A total of 14 721 prescriptions for 613 patients were analysed over three periods of investigation: 7 months before; and 5 and 12 months after implementation of a clinical information system with computerised physician order entry capability. Errors in prescribing were common. Only (53%) of handwritten charts analysed had all immediate administration drugs prescribed correctly. Errors included omission of route 81 (8.0%), date of prescription 78 (7.7%), and time to be given 255 (25.2%), and 119 (11.7%) had no dose or an incorrect dose prescribed. All errors of completeness were abolished following implementation. The computerised system led to a significant improvement in prescribing safety, in a clinical area previously highlighted as having a high rate of adverse drug errors. Legibility, completeness and traceability are no longer possible sources of medication errors. [source] Effects of Computerized Provider Order Entry and Nursing Documentation on WorkflowACADEMIC EMERGENCY MEDICINE, Issue 10 2008Phillip V. Asaro MD Abstract Objectives:, The objective was to measure the effects of the implementation of computerized provider order entry (CPOE) and electronic nursing documentation on provider workflow in the emergency department (ED). Methods:, The authors performed a before-and-after time-motion study of the activities of physicians and nurses. The percentages of time spent in task categories were calculated by provider session and averaged across provider sessions. Results:, There was a shift in physician time from working with paper alone, 13.1% to 9.6% (p = 0.05), to working with paper while using a computer, 1.6% to 4.3% (p = 0.02), and an increase in time spent working on computer and/or paper from 30.0% to 38.9% (p = 0.02). For nurses, the increase in time spent on computer from 9.5% to 25.7% (p < 0.01) was offset by a decrease in time spent working with paper from 16.5% to 1.8% (p < 0.01). Direct care decreased minimally for nurses from 56.9% to 55.3% (p = 0.69), but from 36.8% to 29.1% (p = 0.07) for physicians, approaching statistical significance. Care planning decreased for nurses from 9.4% to 6.4% (p = 0.04) and from 21.7% to 19.5% (p = 0.60) for physicians. Conclusions:, The net effects of an implementation on provider workflow depend not only on changes in tasks directly related to the provider,computer interface, but also on changes in underlying patient care processes and information flows. The authors observed an unanticipated shift in physician time from interacting with nurses and patients toward retrieving information from the electronic patient record. Implementers should carefully consider how implementations will affect information flow and then expect the unexpected. [source] Providers Do Not Verify Patient Identity during Computer Order EntryACADEMIC EMERGENCY MEDICINE, Issue 7 2008Philip L. Henneman MD Abstract Introduction:, Improving patient identification (ID), by using two identifiers, is a Joint Commission safety goal. Appropriate identifiers include name, date of birth (DOB), or medical record number (MRN). Objectives:, The objectives were to determine the frequency of verifying patient ID during computerized provider order entry (CPOE). Methods:, This was a prospective study using simulated scenarios with an eye-tracking device. Medical providers were asked to review 10 charts (scenarios), select the patient from a computer alphabetical list, and order tests. Two scenarios had embedded ID errors compared to the computer (incorrect DOB or misspelled last name), and a third had a potential error (second patient on alphabetical list with same last name). Providers were not aware the focus was patient ID. Verifying patient ID was defined as looking at name and either DOB or MRN on the computer. Results:, Twenty-five of 25 providers (100%; 95% confidence interval [CI] = 86% to 100%) selected the correct patient when there was a second patient with the same last name. Two of 25 (8%; 95% CI = 1% to 26%) noted the DOB error; the remaining 23 ordered tests on an incorrect patient. One of 25 (4%, 95% CI = 0% to 20%) noted the last name error; 12 ordered tests on an incorrect patient. No participant (0%, 0/107; 95% CI = 0% to 3%) verified patient ID by looking at MRN prior to selecting a patient from the alphabetical list. Twenty-three percent (45/200; 95% CI = 17% to 29%) verified patient ID prior to ordering tests. Conclusions:, Medical providers often miss ID errors and infrequently verify patient ID with two identifiers during CPOE. [source] | ||||||||||||||||||||||