Medication safety messages for patients via the web portal: The MedCheck intervention (original) (raw)
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Contemporary clinical trials, 2016
Adverse drug events (ADEs) affect millions of patients annually and place a significant burden on the healthcare system. The Food and Drug Administration (FDA) has developed patient safety information for high-risk medications that pose serious public health concerns. However, there are currently few assurances that patients receive this information or are able to identify or respond correctly to ADEs. To compare the effectiveness of the Electronic Medication Complete Communication (EMC(2)) Strategy to promote safe medication use and reporting of ADEs in comparison to usual care. The automated EMC(2) Strategy consists of: 1) provider alerts to counsel patients on medication risks, 2) the delivery of patient-friendly medication information via the electronic health record, and 3) an automated telephone assessment to identify potential medication concerns or ADEs. The study will take place in two community health centers in Chicago, IL. Adult, English or Spanish-speaking patients (N=1...
Physicians’ responses to computerized drug–drug interaction alerts for outpatients
Computer Methods and Programs in Biomedicine, 2013
Introduction: Adverse drug reactions (ADR) increase morbidity and mortality; potential drug-drug interactions (DDI) increase the probability of ADR. Studies have proven that computerized drug-interaction alert systems (DIAS) might reduce medication errors and potential adverse events. However, the relatively high override rates obscure the benefits of alert systems, which result in barriers for availability. It is important to understand the frequency at which physicians override DIAS and the reasons for overriding reminders. Method: All the DDI records of outpatient prescriptions from a tertiary university hospital from 2005 and 2006 detections by the DIAS are included in the study. The DIAS is a JAVA language software that was integrated into the computerized physician order entry system. The alert window is displayed when DDIs occur during order entries, and physicians choose the appropriate action according to the DDI alerts. There are seven response choices are obligated in representing overriding and acceptance: (1) necessary order and override; (2) expected DDI and override; (3) expected DDI with modified dosage and override; (4) no DDI and override; (5) too busy to respond and override; (6) unaware of the DDI and accept; and (7) unexpected DDI and accept. The responses were collected for analysis. Results: A total of 11,084 DDI alerts of 1,243,464 outpatient prescriptions were present, 0.89% of all computerized prescriptions. The overall rate for accepting was 8.5%, but most of the alerts were overridden (91.5%). Physicians of family medicine and gynecology-obstetrics were more willing to accept the alerts with acceptance rates of 20.8% and 20.0% respectively (p < 0.001). Information regarding the recognition of DDIs indicated that 82.0% of the DDIs were aware by physicians, 15.9% of DDIs were unaware by physicians, and 2.1% of alerts were ignored. The percentage of total alerts declined from 1.12% to 0.79% during 24 months' study period, and total overridden alerts also declined (from 1.04% to 0.73%). Conclusion: We explored the physicians' behavior by analyzing responses to the DDI alerts. Although the override rate is still high, the reasons why physicians may override DDI alerts were well analyzed and most DDI were recognized by physicians. Nonetheless, the trend of
A Mixed Method Study of the Merits of E-Prescribing Drug Alerts in Primary Care
Journal of General Internal Medicine, 2008
Objectives The objective of this paper was to describe primary care prescribers’ perspectives on electronic prescribing drug alerts at the point of prescribing. Design We used a mixed-method study which included clinician surveys (web-based and paper) and focus groups with prescribers and staff. Participants Prescribers (n = 157) working in one of 64 practices using 1 of 6 e-prescribing technologies in 6 US states completed the quantitative survey and 276 prescribers and staff participated in focus groups. Measurements The study measures self-reported frequency of overriding of drug alerts; open-ended responses to: “What do you think of the drug alerts your software generates for you?” Results More than 40% of prescribers indicated they override drug–drug interactions most of the time or always (range by e-prescribing system, 25% to 50%). Participants indicated that the software and the interaction alerts were beneficial to patient safety and valued seeing drug–drug interactions for medications prescribed by others. However, they noted that alerts are too sensitive and often unnecessary. Participant suggestions included: (1) run drug alerts on an active medication list and (2) allow prescribers to set the threshold for severity of alerts. Conclusions Primary care prescribers recognize the patient safety value of drug prescribing alerts embedded within electronic prescribing software. Improvements to increase specificity and reduce alert overload are needed.
Journal of the American Medical Informatics Association, 2011
Objective Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems. Design A randomized study of 24 junior doctors each performing 30 simulated prescribing tasks in random order with a prototype e-prescribing system. Using a within-participant design, doctors were randomized to be shown one of three types of e-prescribing alert (modal, non-modal, no alert) during each prescribing task. Measurements The main outcome measure was prescribing error rate. Structured interviews were performed to elicit participants' preferences for the prescribing alerts and their views on clinical decision support systems. Results Participants exposed to modal alerts were 11.6 times less likely to make a prescribing error than those not shown an alert (OR 11.56, 95% CI 6.00 to 22.26). Those shown a non-modal alert were 3.2 times less likely to make a prescribing error (OR 3.18, 95% CI 1.91 to 5.30) than those not shown an alert. The error rate with non-modal alerts was 3.6 times higher than with modal alerts (95% CI 1.88 to 7.04). Conclusions Both kinds of e-prescribing alerts significantly reduced prescribing error rates, but modal alerts were over three times more effective than nonmodal alerts. This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes. < Additional appendices are published online only. To view these files please visit the journal online (www.jamia.org).
Utilization of computerized clinical decision support for potentially inappropriate medications
Clinical Interventions in Aging, 2019
Background: Electronic medical record (EMR) alerts may inform point of care decisions, including the decision to prescribe potentially inappropriate medications (PIM) identified in the Beers criteria. EMR alerts may not be considered relevant or informative in the clinician context, leading to a phenomenon colloquially known as "alert fatigue." Objective: To assess the frequency of clinical interaction with EMR alerts and associated deprescribing behaviors in ambulatory settings. Methods: This is a retrospective observational study in two ambulatory clinics (the Kaye Edmonton Clinic Senior's Clinic and the Lynnwood Family Practice Clinic) in Edmonton over an observational period of 30 months. Statistical analysis was done using descriptive statistics, chi-square and regression analysis. Results: The reminder performance for interactions with the alert was 17.2% across the two clinics. The Number Needed to Remind (NNR) or mean number of alerts shown on clinician screens prior to a single interaction of any kind with the alert was 5.8. When actions were defined as a deprescribing (ie discontinuation) event that was related to the alert and that particular interaction in the EMR, the reminder performance was 1.2%, for an NNR of 82.8. Conclusion: The configuration of alerts in the EMR was not associated with a clinically detectable increase in the uptake of the Beers criteria for high hazard medications.
How to design computerized alerts to ensure safe prescribing practices
2004
Background: Medication errors and preventable adverse drug events are common, and about half of medication errors occur during medication ordering. This study was designed to develop and evaluate medication safety alerts and processes for educating prescribers about the alerts. Methods: At Kaiser Permanente Northwest, a group-model health maintenance organization where prescribers have used computerized order entry since 1996, qualitative interviews were conducted with 20 primary care prescribers.
Acta Informatica Medica, 2021
Background: Clinical decision support systems (CDSS) can enhance patient safety and reduce medication errors by giving physicians alerts while dispensing medications. Physicians inappropriately override these alerts for various reasons, which can possibly lead to medication errors and impact patient safety. Objective: To assess the appropriateness of overridden major medication-related alerts, to investigate the reasons behind inappropriate overriding, and to evaluate if medication errors occur in inappropriately overridden alerts. Methods: A mixed-methods study was conducted.. Quantitative: Retrospective observation to evaluate the appropriateness of major drug-dose related alert overrides. A simple random sample was taken from appropriate and inappropriate overrides and reviewed for medication errors. Qualitative: Semi-Structured Interviews were conducted with ten consultant physicians from various specialties. Interviews were transcribed and coded inductively then analyzed using ...
Research in Social and Administrative Pharmacy, 2014
Background: As a result of the US Omnibus Reconciliation Act of 1990 (OBRA '90), pharmacists have the obligation to ensure that prescription orders are appropriate and are not likely to cause adverse events. However, patient diagnosis information is not a requirement for a legal prescription order in any state in the US. Objective: To compare a pharmacist's interventions before and after patient diagnosis is added by prescribers to their electronic prescription orders. Methods: This prospective, pre-post study was conducted during two consecutive 4-week periods in a community health center pharmacy. During the first data collection period, the clinical pharmacist prospectively evaluated e-prescriptions using a standard DUR protocol. All problematic prescriptions were documented using a medication intervention form. During the second data collection period, providers included the patient's diagnosis on each e-prescription and the same clinical pharmacist again evaluated prescribed therapy and documented interventions.