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K Alagiakrishnan,1 M Ballermann,2 D Rolfson,1 K Mohindra,3 CA Sadowski,4 A Ausford,5 J Romney,6 RS Hayward71Division of Geriatric Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada; 2Chief Medical Information Office, Alberta Health Services, Division of Critical Care Medicine, University of Alberta, Edmonton, Alberta, Canada; 3OpTime OR and Anesthesia, Connect Care, Information Systems, Alberta Health Services, Edmonton, Alberta, Canada; 4Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada; 5Department of Family Medicine, University of Alberta, Edmonton, Alberta, Canada; 6Division of Endocrinology, Department of Medicine, University of Alberta, Edmonton, Alberta, Canada; 7Division of Internal Medicine, Department of Medicine, University of Alberta, Edmonton, Alberta, CanadaBackground: 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.Keywords: polypharmacy, Beers Criteria, deprescribing, best practice advisory, alert fatigue, e-prescribing, prescribing

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.

Kannayiram Alagiakrishnan,1 Patricia Wilson,2 Cheryl A Sadowski,3 Darryl Rolfson,1 Mark Ballermann,4,5 Allen Ausford,6,7 Karla Vermeer,7 Kunal Mohindra,8 Jacques Romney,9 Robert S Hayward10 1Department of Medicine, Division of Geriatric Medicine, 2Department of Medicine, 3Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, 4Chief Medical Information Office, Alberta Health Services, 5Division of Critical Care, Department of Medicine, University of Alberta, 6Department of Family Medicine, University of Alberta, 7Lynwood Family Physician, 8eClinician EMR, Alberta Health Services-Information Systems, 9Department of Medicine, Division of Endocrinology, 10Division of General Internal Medicine, University of Alberta, Edmonton, AB, Canada Background: Elderly people (aged 65 years or more) are at increased risk of polypharmacy (five or more medications), inappropriate medication use, and associated increased health care costs. The use of clinical decision support (CDS) within an electronic medical record (EMR) could improve medication safety.Methods: Participatory action research methods were applied to preproduction design and development and postproduction optimization of an EMR-embedded CDS implementation of the Beers’ Criteria for medication management and the Cockcroft–Gault formula for estimating glomerular filtration rates (GFR). The “Seniors Medication Alert and Review Technologies” (SMART) intervention was used in primary care and geriatrics specialty clinics. Passive (chart messages) and active (order-entry alerts) prompts exposed potentially inappropriate medications, decreased GFR, and the possible need for medication adjustments. Physician reactions wereassessed using surveys, EMR simulations, focus groups, and semi-structured interviews. EMR audit data were used to identify eligible patient encounters, the frequency of CDS events, how alerts were managed, and when evidence links were followed.Results: Analysis of subjective data revealed that most clinicians agreed that CDS appeared at appropriate times during patient care. Although managing alerts incurred a modest time burden, most also agreed that workflow was not disrupted. Prevalent concerns related to clinician accountability and potential liability. Approximately 36% of eligible encounters triggered at least one SMART alert, with GFR alert, and most frequent medication warnings were with hypnotics and anticholinergics. Approximately 25% of alerts were overridden and ~15% elicited an evidence check.Conclusion: While most SMART alerts validated clinician choices, they were received as valuable reminders for evidence-informed care and education. Data from this study may aid other attempts to implement Beers’ Criteria in ambulatory care EMRs. Keywords: Beers’ Criteria, medication management, polypharmacy, Cockcroft–Gault formula, clinical decision support

Kannayiram Alagiakrishnan,1 Patricia Wilson,2 Cheryl A Sadowski,3 Darryl Rolfson,1 Mark Ballermann,4,5 Allen Ausford,6,7 Karla Vermeer,7 Kunal Mohindra,8 Jacques Romney,9 Robert S Hayward10 1Department of Medicine, Division of Geriatric Medicine, 2Department of Medicine, 3Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, 4Chief Medical Information Office, Alberta Health Services, 5Division of Critical Care, Department of Medicine, University of Alberta, 6Department of Family Medicine, University of Alberta, 7Lynwood Family Physician, 8eClinician EMR, Alberta Health Services-Information Systems, 9Department of Medicine, Division of Endocrinology, 10Division of General Internal Medicine, University of Alberta, Edmonton, AB, Canada Background: Elderly people (aged 65 years or more) are at increased risk of polypharmacy (five or more medications), inappropriate medication use, and associated increased health care costs. The use of clinical decision support (CDS) within an electronic medical record (EMR) could improve medication safety.Methods: Participatory action research methods were applied to preproduction design and development and postproduction optimization of an EMR-embedded CDS implementation of the Beers’ Criteria for medication management and the Cockcroft–Gault formula for estimating glomerular filtration rates (GFR). The “Seniors Medication Alert and Review Technologies” (SMART) intervention was used in primary care and geriatrics specialty clinics. Passive (chart messages) and active (order-entry alerts) prompts exposed potentially inappropriate medications, decreased GFR, and the possible need for medication adjustments. Physician reactions wereassessed using surveys, EMR simulations, focus groups, and semi-structured interviews. EMR audit data were used to identify eligible patient encounters, the frequency of CDS events, how alerts were managed, and when evidence links were followed.Results: Analysis of subjective data revealed that most clinicians agreed that CDS appeared at appropriate times during patient care. Although managing alerts incurred a modest time burden, most also agreed that workflow was not disrupted. Prevalent concerns related to clinician accountability and potential liability. Approximately 36% of eligible encounters triggered at least one SMART alert, with GFR alert, and most frequent medication warnings were with hypnotics and anticholinergics. Approximately 25% of alerts were overridden and ~15% elicited an evidence check.Conclusion: While most SMART alerts validated clinician choices, they were received as valuable reminders for evidence-informed care and education. Data from this study may aid other attempts to implement Beers’ Criteria in ambulatory care EMRs. Keywords: Beers’ Criteria, medication management, polypharmacy, Cockcroft–Gault formula, clinical decision support

To identify and describe the important rewards and challenges that affect family physicians in Alberta.Web-based qualitative study using the Delphi method.Province of Alberta.Twenty-eight family physicians practising in Alberta.The study website presented a description of the project, ethical information, a calendar of events, and contact information. Delphi surveys and demographic questionnaires were password protected. Five rounds of surveys were conducted between May 2004 and January 2005. Participants were notified of each round of surveys and prompted by e-mail if they did not respond. FINDINGS Participants identified 8 key rewards and 9 key challenges. The research team identified 2 additional challenges that were validated by participants. In order of perceived importance, key rewards were providing diverse and comprehensive care; providing preventive care; having relationships with patients and their families; being an immersed witness to the human condition; providing continuity of care and receiving ongoing feedback; having flexibility and control of practice and job security; maintaining and acquiring skills and knowledge; teaching and sharing knowledge and gaining experience and mentoring. The challenges, in order of perceived need to be addressed, were workload and time pressures and meeting demands; the need to promote the rewards of family practice to those considering joining the profession; overhead and income inequities; getting respect from specialists; the need to ensure that the rewards identified are not adversely affected by primary care reform; lack of availability of specialists, procedures, tests, and other resources; running a practice as a small business; paperwork, telephone calls, and forms; maintaining and acquiring skills and knowledge; patients' expectations; and medicolegal issues, insurance paperwork, and dealing with medical claims related to motor vehicle accidents.The rewards and challenges reported by participants outline the positive and negative factors in family practice. The challenges provide a focus for further work.