Computerized physician order entry of medications and clinical decision support can improve problem list documentation compliance

Galanter, William L.; Hier, Daniel B.; Jao, Chiang S.; Sarne, David

doi:10.1016/j.ijmedinf.2008.05.005

Cited by 61 publications

(52 citation statements)

References 17 publications

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“…This collaboration allows to identify probable gaps in the problem list [3,8,9] and to prevent possible diseases [4]. In both cases, the inpatient is the beneficiary.…”

Section: Discussionmentioning

confidence: 99%

Decision Support: Time for Collaboration

Guardia¹

2011

Yearb Med Inform

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SummaryObjectives: To summarize current outstanding research in the field of decision support. Methods: A selection of excellent research articles published in 2010 in the field of computerized clinical decision support systems. Results and Conclusions: This selection of articles shows that decision support systems (DSS) are getting better integrated into the electronic health record systems (EHR) and into the clinician's workflow. As a result, there is a better collaboration between physicians and DSS, which improves the care of patients.

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“…This collaboration allows to identify probable gaps in the problem list [3,8,9] and to prevent possible diseases [4]. In both cases, the inpatient is the beneficiary.…”

Section: Discussionmentioning

confidence: 99%

Decision Support: Time for Collaboration

Guardia¹

2011

Yearb Med Inform

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“…The final progress note incorporated several timesaving features that were presented to the medical staff by the medical staff champions. Automatic and up-todate data population of laboratory data, vital signs and parts of the histories of present illnesses were designed to pre-populate the data for subsequent notes [12]. The medical staff voted in favor of the progress note, thereby assisting buy-in.…”

Section: Methodsmentioning

confidence: 99%

Impact of Electronic Health Record Documentation and Clinical Documentation Specialists on Case Mix Index: A Retrospective Study for Quality Improvement

Stacy¹

2014

J Health Med Informat

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Background: The implementation of hospital electronic health records software is considered a significant modernization in healthcare.Objective: The objective of this study was to evaluate the impact of electronic health records and the addition of clinical documentation specialists as a clinical support group on hospitalist documentation using case mix index (CMI) as a measurement tool. Methods:A two-group pre/postimplementation retrospective research design was used to evaluate the impact of electronic health records and clinical documentation specialists on CMI in a single 125-bed full-service community hospital in the greater Los Angeles area. All hospitalist medical records were reviewed in the pre/postphases. A total of 3,536 records were reviewed over the two phases. Phase one included a review of 1,712 hospitalist medical records before implementation of electronic health records. Phase two included a review of 1,824 hospitalist medical records after implementation of electronic health records and clinical documentation specialists. Change in CMI data were analyzed over the two phases. CMI data were treated as interval data and analyzed by parametric descriptive statistics in two phases by one-way ANOVA to compare the means between the two phases. Results:The mean CMI value for phase one was 1.65 and 1.68 for phase two. One-way ANOVA yielded no difference between the mean CMI values for the two phases (p.53). Conclusion:The implementation of electronic health records and clinical documentation specialists as a clinical support group did not make any significant difference in hospitalist documentation using CMI as a measurement tool.

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“…All medication orders are placed by CPOE which is associated with a commercially available CDS system (Discern Expert; Cerner Corporation) which has been described previously for this and other types of alerts. 14 15 18 19 Orders for specified medications (table 1) triggered an alert for the clinician to update the medical record for patients whose electronic problem list did not contain an active problem indicated by that medicine. Depending on the medication, alerts displayed one or more possible problems (figure 1).…”

Section: Methodsmentioning

confidence: 99%

Indication-based prescribing prevents wrong-patient medication errors in computerized provider order entry (CPOE)

Galanter

Falck

Burns

et al. 2013

Journal of the American Medical Informatics Association

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Objective To determine whether indication-based computer order entry alerts intercept wrong-patient medication errors. Materials and methods At an academic medical center serving inpatients and outpatients, we developed and implemented a clinical decision support system to prompt clinicians for indications when certain medications were ordered without an appropriately coded indication on the problem list. Among all the alerts that fired, we identified every instance when a medication order was started but not completed and, within a fixed time interval, the same prescriber placed an order for the same medication for a different patient. We closely reviewed each of these instances to determine whether they were likely to have been intercepted errors. Results Over a 6-year period 127 320 alerts fired, which resulted in 32 intercepted wrong-patient errors, an interception rate of 0.25 per 1000 alerts. Neither the location of the prescriber nor the type of prescriber affected the interception rate. No intercepted errors were for patients with the same last name, but in 59% of the intercepted errors the prescriber had both patients' charts open when the first order was initiated. Discussion Indication alerts linked to the problem list have previously been shown to improve problem list completion. This analysis demonstrates another benefit, the interception of wrong-patient medication errors. Conclusions Indication-based alerts yielded a wrong-patient medication error interception rate of 0.25 per 1000 alerts. These alerts could be implemented independently or in combination with other strategies to decrease wrong-patient medication errors. BACKGROUND AND SIGNIFICANCE

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Computerized physician order entry of medications and clinical decision support can improve problem list documentation compliance

Cited by 61 publications

References 17 publications

Decision Support: Time for Collaboration

Decision Support: Time for Collaboration

Impact of Electronic Health Record Documentation and Clinical Documentation Specialists on Case Mix Index: A Retrospective Study for Quality Improvement

Indication-based prescribing prevents wrong-patient medication errors in computerized provider order entry (CPOE)

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