Evaluating the Usability and Perceived Impact of an Electronic Medical Record Toolkit for Atrial Fibrillation Management in Primary Care: A Mixed-Methods Study Incorporating Human Factors Design.

BACKGROUND: Atrial fibrillation (AF) is a common and preventable cause of stroke. Barriers to reducing stroke risk through appropriate prescribing have been identified at the system, provider, and patient levels. To ensure a multifaceted initiative to address these barriers is effective, it is essential to incorporate user-centered design to ensure all intervention components are optimized for users. OBJECTIVE: To test the usability of an electronic medical record (EMR) toolkit for AF in primary care with the goal of further refining the intervention to meet the needs of primary care clinicians. METHODS: An EMR-based toolkit for AF was created and optimized through usability testing and iterative redesign incorporating a human factors approach. A mixed-methods pilot study consisting of observations, semi-structured interviews, and surveys was conducted to examine usability and perceived impact on patient care and workflow. RESULTS: A total of 14 clinicians (13 family physicians and 1 nurse practitioner) participated in the study. Nine iterations of the toolkit were created in response to feedback from clinicians and the research team; interface-related changes were made, additional AF-related resources were added, and functionality issues were fixed to make the toolkit more effective. After improvements were made, clinicians expressed that the toolkit improved accessibility to AF-related information and resources, served as a reminder for guideline-concordant AF management, and was easy to use. Most clinicians intended to continue using the toolkit for patient care. With respect to impact on care, clinicians believed the toolkit increased the thoroughness of their assessments for patients with AF and improved the quality of AF-related care received by their patients. CONCLUSIONS: The positive feedback surrounding the EMR toolkit for AF and its perceived impact on patient care can be attributed to the adoption of a user-centered design that merged clinically important information about AF management with user needs. This study demonstrates the utility of a human factors approach to piloting and refining an intervention prior to wide-scale implementation.

Evaluation of Electronic Medical Record Administrative data Linked Database (EMRALD).

BACKGROUND: Primary care electronic medical records (EMRs) represent a potentially rich source of information for research and evaluation. OBJECTIVE: To assess the completeness of primary care EMR data compared with administrative data. STUDY DESIGN: Retrospective comparison of provincial health-related administrative databases and patient records for more than 50,000 patients of 54 physicians in 15 geographically distinct clinics in Ontario, Canada, contained in the Electronic Medical Record Administrative data Linked Database (EMRALD). METHODS: Physician billings, laboratory tests, medications, specialist consultation letters, and hospital discharges captured in EMRALD were compared with health-related administrative data in a universal access healthcare system. RESULTS: The mean (standard deviation [SD]) percentage of clinic primary care outpatient visits captured in EMRALD compared with administrative data was 94.4% (4.88%). Consultation letters from specialists for first consultations and for hospital discharges were captured at a mean (SD) rate of 72.7% (7.98%) and 58.5% (15.24%), respectively, within 30 days of the occurrence. The mean (SD) capture within EMRALD of the most common laboratory tests billed and the most common drugs dispensed was 67.3% (21.46%) and 68.2% (8.32%), respectively, for all clinics. CONCLUSIONS: We found reasonable capture of information within the EMR compared with administrative data, with the advantage in the EMR of having actual laboratory results, prescriptions for patients of all ages, and detailed clinical information. However, the combination of complete EMR records and administrative data is needed to provide a full comprehensive picture of patient health histories and processes, and outcomes of care.

Transient insight induction with electroconvulsive therapy in a patient with refractory schizophrenia: a case report and systematic literature review.

Anosognosia or lack of illness awareness is a clinical manifestation of both schizophrenia and right hemispheric lesions associated with stroke, neurodegeneration, or traumatic brain injury. It is thought to result from right hemispheric dysfunction or interhemispheric disequilibrium, which provides a neuroanatomical model for illness unawareness in schizophrenia. Lack of insight contributes to medication nonadherence and poor treatment outcomes and is often refractory to pharmacological and psychological interventions. We present the first report of transient illness awareness (<8 hours) after individual bilateral electroconvulsive therapy treatments in the case of a 39-year-old man with antipsychotic refractory schizophrenia. Electroencephalography demonstrated frontal slow wave activity with shifting frontotemporal predominance, which was concurrent with the patient's transient level of insight. A systematic review of the literature on electroconvulsive therapy-induced illness awareness in schizophrenia and psychotic disorders produced zero relevant results. Future research should focus on the prospective role of focal interventions, such as transcranial magnetic stimulation, in the development of a neurophysiological model for anosognosia reversal in schizophrenia that may, in turn, contribute to novel therapeutic developments targeting lack of illness awareness.

Diabetics can be identified in an electronic medical record using laboratory tests and prescriptions.

OBJECTIVE: With the increasing use of electronic medical records (EMRs) comes the potential to efficiently evaluate and improve quality of care. We set out to determine if diabetics could be accurately identified using structured data contained within an EMR. STUDY DESIGN AND SETTING: We used a 5% random sample of adult patients (969 patients) within a convenience sample of 17 primary care physicians using Practices Solutions EMR in Ontario. A reference standard of diabetes status was manually confirmed by reviewing each patient's record. Accuracy for identifying people with diabetes was assessed using various combinations of laboratory tests and prescriptions. EMR data was also compared with administrative data. RESULTS: A rule of one elevated blood sugar or a prescription for an antidiabetic medication had a 83.1% sensitivity, 98.2% specificity, 80.0% positive predictive value (PPV) and 98.5% negative predictive value (NPV) compared with the reference standard of diabetes status. CONCLUSION: We found that the use of structured data within an EMR could be used to identify patients with diabetes. Our results have positive implications for policy makers, researchers, and clinicians as they develop registries of diabetic patients to examine quality of care using EMR data.