Background Heart failure (HF) readmission rates have been a significant concern for healthcare systems globally. Accurate predictive models are essential to identify patients at high readmission risk and implement timely interventions. Current models often lack comprehensive variables that reflect both clinical and patient and/or caregiver perspectives. We aimed to develop a consensus-driven approach to identify essential variables for inclusion in HF hospital readmission risk prediction algorithms. Methods A Delphi panel comprised of clinicians and patient and/or caregiver partners was assembled. The Delphi panelists were recruited from the province of Alberta, Canada. The panel consisted of 13 individuals, including 9 healthcare providers and 4 patients and/or caregivers. The review panel was provided with a list of variables from a previously completed systematic literature review. Three rounds were conducted. The panel also determined the directionality of the association. Results A total of 99 variables were identified through literature and physician input. Panelists reached a consensus on 61 variables, which were deemed to be associated with the risk of readmission for any cause within 30 days of discharge after HF hospitalization. Clinician ratings on consensus were consistently higher than those of nonclinicians. Conclusions This study successfully identified 61 variables associated with HF readmission risk through a modified Delphi process, incorporating both clinician and patient and/or caregiver perspectives. These findings provide a foundation for future research and the development of more comprehensive and accurate risk prediction models. Including diverse stakeholder input highlights the importance of integrating medical expertise and patient experiences in improving HF management and reducing readmission rates.

This environmental scan aims to identify and describe initiatives implemented in Alberta, one of the few Canadian provinces with a unified health delivery system, to reduce heart failure (HF)readmissions. It also acknowledges the challenges in attributing direct benefits to these interventions. Using snowball sampling, we identified and recruited 11 employees and clinicians from Alberta Health Services (AHS) who possessed significant historical institutional knowledge about HF. Academic and grey literature were reviewed related to Alberta's readmission reduction initiatives and reported outcomes. Unstructured, in-depth interviews were conducted to clarify timelines and provide detailed descriptions of these interventions. Our findings indicate substantial clinician efforts over 15 years to address all-cause readmissions post HF hospitalization in Alberta, encompassing a range of interventions from small-scale projects to large multi-city, multi-stakeholder initiatives. Assessing the impact of smaller interventions on provincial readmission rates proved challenging; however, five major initiatives collectively led to a 1.8% reduction in 30-day all-cause readmissions province-wide (from 22.2% to 20.4%, p=0.04). Key factors that appeared to support these efforts included utilization of the EMR system, stakeholder engagement in standardized care, effective communication practices, and appropriate resource allocation. Clinical teams are now integrating successful components from these initiatives into the province-wide clinical information system, Connect Care, to enhance care coordination and patient outcomes. This environmental scan highlights various comprehensive initiatives in Alberta aimed at improving patient care and reducing readmission after HF hospitalization. While an overall 1.8% reduction in readmission rates was observed over the 15 years, attributing this change directly to the interventions is challenging due to various implementation barriers and the complexity of healthcare delivery. Continued efforts towards personalized care and innovative EMR utilization hold promise for further improvement in HF readmission rates. Key Words: Heart failure, readmissions, environmental scan, clinical pathways, health outcomes, patient-centered care ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Informed consent was obtained prior to each interview. Ethics was obtained from the Conjoint Health Research Ethics Board REB20-0684 I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data cannot be shared publicly because to respect the privacy of the participants. Data are available from the University of Calgary Institutional Data Access / Ethics Committee (contact via cfreb{at}ucalgary.ca) for researchers who meet the criteria for access to confidential data.

Background Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research. Objective The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences. Methods We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results. Results We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized. Conclusions The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

Background The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders’ skills acquired during ICD training, which varies greatly across countries. Objective To characterise the current landscape of international ICD clinical coding training. Method An online questionnaire was created to survey the 194 World Health Organization (WHO) member countries. Questions focused on the training provided to clinical coding professionals. The survey was distributed to potential participants who met specific criteria, and to organisations specialised in the topic, such as WHO Collaborating Centres, to be forwarded to their representatives. Responses were analysed using descriptive statistics. Results Data from 47 respondents from 26 countries revealed disparities in all inquired topics. However, most participants reported clinical coders as the primary person assigning ICD codes. Although training was available in all countries, some did not mandate training qualifications, and those that did differed in type and duration of training, with college or university degree being most common. Clinical coding certificates most frequently entailed passing a certification exam. Most countries offered continuing training opportunities, and provided a range of support resources for clinical coders. Conclusion Variability in clinical coder training could affect data collection worldwide, thus potentially hindering international comparability of health data. Implications These findings could encourage countries to improve their resources and training programs available for clinical coders and will ultimately be valuable to the WHO for the standardisation of ICD training.

Introduction Countries use varying coding standards, which impact international coded data comparability. The `main condition' (MC) field is coded within the Discharge Abstract Database as "reason for admission" or "largest resource use". Objective We offer a preliminary analysis on the frequency of and contributing factors to MC definition agreements within an inpatient Canadian dataset. Methods Six professional coders performed a chart review between August 2016 and June 2017 on 3,000 randomly selected inpatient charts from three acute care hospitals in Calgary, Alberta. Coders classified the MC as "reason for admission", "largest resource use" or "both". Patients were admitted between 1st January and 30th June 2015 and met the inclusion criteria if they were >18 years, had an Alberta personal health care number, and had an inpatient visit for any service outside of obstetrics. Agreement between the two MC definitions was stratified by length of stay (LOS), emergency department admission, hospital of origin, discharge location, age, sex, procedures, and comorbidities. Chi-square analysis and frequency of inconsistencies were reported. Results Only 34 (1.51%) of the 2,250 patient charts had disagreeing MC definitions. Age, emergency visit on admit, LOS, hospital, and discharge location were associated with MC agreement. Chronic conditions were seen more often in MC definition agreements, and acute conditions seen within those disagreeing. Conclusion There was a small proportion of cases in which the condition bringing the patient to hospital was not also the condition occupying the largest resources. Within disagreements, further research using a larger sample size is needed to explore the presence of MC in a secondary/tertiary condition, the association between patient complexity and disagreeing MC definitions, and the nature of the conditions seen in the inconsistent MC definitions.

Insomnia and sleep apnea are associated with a variety of comorbid conditions and carry a symptom burden to patients. As the prevalence of insomnia and sleep apnea continue to rise, it is imperative that appropriate tools are implemented to accurately capture their prevalence in acute care settings. A retrospective chart review was conducted on 3,074 inpatient charts in Calgary, Alberta. The estimated prevalence of insomnia was 10.36 percent, and sleep apnea was 6.56 percent in inpatient visits between January 1, 2015, and June 30, 2015. The sensitivity of insomnia and sleep apnea were low, and the specificity was high when comparing the chart review to the ICD-10. As both insomnia and sleep apnea were associated with various comorbid conditions, it would be imperative that alternate methods are identified to capture and code them. This would enable clinicians to better identify and treat them, and ultimately improve patient care.

Background: The International Classification of Diseases (ICD) is the reference standard for reporting diseases and health conditions globally. Variations in ICD use and data collection across countries can hinder meaningful comparisons of morbidity data. Thus, we aimed to characterize ICD and hospital morbidity data collection features worldwide. Methods: An online questionnaire was created to poll the World Health Organization (WHO) member countries that were using ICD. The survey included questions focused on ICD meta-features and hospital data collection systems, and was distributed via SurveyMonkey using purposive and snowball sampling. Accordingly, senior representatives from organizations specialized in the topic, such as WHO Collaborating Centers, and other experts in ICD coding were invited to fill out the survey and forward the questionnaire to their peers. Answers were collated by country, analyzed, and presented in a narrative form with descriptive analysis. Results: Responses from 47 participants were collected, representing 26 different countries using ICD. Results indicated worldwide disparities in the ICD meta-features regarding the maximum allowable coding fields for diagnosis, the definition of main condition, and the mandatory type of data fields in the hospital morbidity database. Accordingly, the most frequently reported answers were "reason for admission" as main condition definition (n =14), having 31 or more diagnostic fields available (n =12), and "Diagnoses" (n =26) and "Patient demographics" (n =25) for mandatory data fields. Discrepancies in data collection systems occurred between but also within countries, thereby revealing a lack of standardization both at the international and national level. Additionally, some countries reported specific data collection features, including the use or misuse of ICD coding, the national standards for coding or lack thereof, and the electronic abstracting systems utilized in hospitals. Conclusions: Harmonizing ICD coding standards/guidelines should be a common goal to enhance international comparisons of health data. The current international status of ICD data collection highlights the need for the promotion of ICD and the adoption of the newest version, ICD-11. Furthermore, it will encourage further research on how to improve and standardize ICD coding.

Introduction and Objectives: Electronic medical records (EMRs), specifically the discharge summary (DS), can improve secondary use data availability and interprofessional communication. We aimed to assess the completeness of our EMRs by assessing the presence of a DS in the EMR. Additionally, we assessed for indicators of a missing DS. Methods: A chart review was conducted on 3,011 inpatient charts in Calgary, Alberta. 893 charts were missing an electronic DS. A 10% sample was drawn to assess for presence of a paper DS. A Chi-square test, Fisher’s test and logistic regression assessed for associations between electronic DS absence and i) patient and hospital characteristics, and ii) patient comorbidities Results: The univariate analyses showed that age, being a surgical patient, a Charlson Comorbidity Index (CCI) of 1, as well as patients with myocardial infarctions, congestive heart failure, cerebrovascular disease, dementia, chronic pulmonary disease, diabetes, and renal disease were associated with a missing DS. Those that were middle aged, surgical patients, or had fewer comorbidities were more likely to have a missing DS. Within the 10% sample, approximately 50% of all patients were from a surgical department, all of which were missing both electronic and paper discharge summaries. Conclusions: Our study is the first to describe indicators of missing electronic DS. The DS impacts interprofessional communication, patient outcomes, and data quality. Therefore, the implications of an incomplete DS are widespread. Our findings will caution future researchers using EMR data about the potential for incomplete data, particularly for patients who are surgical, middle aged, and have fewer comorbidities.

BackgroundThe initiatives of precision medicine and learning health systems require databases with rich and accurately captured data on patient characteristics. We introduce the Clinical Registry, AdminisTrative Data and Electronic Medical Records (CREATE) database, which includes linked data from 4 population databases: Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH; a national clinical registry), Sunrise Clinical Manager (SCM) electronic medical record (city-wide), the Discharge Abstract Database (DAD), and the National Ambulatory Care Reporting System (NACRS). The intent of this work is to introduce a cardiovascular-specific database for pursuing precision health activities using big data analytics.MethodsWe used deterministic data linkage to link SCM electronic medical record data to APPROACH clinical registry data using patient identifier variables. The APPROACH-SCM data set was subsequently linked to DAD and NACRS to obtain inpatient and outpatient cohort data. We further validated the quality of the linkage, where applicable, in these databases by comparing against the Alberta Health Insurance Care Plan registry database.ResultsWe achieved 99.96% linkage across these 4 databases. Currently, there are 30,984 patients with 35,753 catheterizations in the CREATE database. The inpatient cohort contained 65.75% (20,373/30,984) of the patient sample, whereas the outpatient cohort contained 29.78% (9226/30,984). The infrastructure and the process to update and expand the database has been established.ConclusionsCREATE is intended to serve as a database for supporting big data analytics activities surrounding cardiac precision health. The CREATE database will be managed by the Centre for Health Informatics at the University of Calgary, and housed in a secure high-performance computing environment.

BackgroundIn persons with migraine, severity of migraine is an important determinant of several health outcomes (e.g., patient quality of life and health care resource utilization). This study investigated how migraine patients rate the severity of their disease and how these ratings correlate with their socio-demographic, clinical, and psycho-social characteristics.MethodsThis is a cohort of 263 adult migraine patients consecutively enrolled in the Neurological Disease and Depression Study (NEEDs). We obtained a broad range of clinical and patient-reported measures (e.g., patients' ratings of migraine severity using the Global Assessment of Migraine Severity (GAMS), and migraine-related disability, as measured by the Migraine Disability Scale (MIDAS)). Depression was measured using the 9-item Patient Health Questionnaire (PHQ-9) and the 14-item Hospital Anxiety and Depression Scale (HADS). Median regression analysis was used to examine the predictors of patient ratings of migraine severity.ResultsThe mean age for the patients was 42.5years (SD=13.2). While 209 (79.4%) patients were females, 177 (67.4%) participants reported moderately severe to extremely severe migraine on the GAMS, and 100 (31.6%) patients had chronic migraine. Patients' report of severity on the GAMS was strongly correlated with patients' ratings of MIDAS global severity question, overall MIDAS score, migraine type, PHQ-9 score, and frequency of migraine attacks. Mediation analyses revealed that MIDAS mediated the effect of depression on patient ratings of migraine severity, accounting for about 32% of the total effect of depression. Overall, migraine subtype, frequency of migraine, employment status, depression, and migraine-related disability were statistically significant predictors of patient-ratings of migraine severity.ConclusionsThis study highlights the impact of clinical and psychosocial determinants of patient-ratings of migraine severity. GAMS is a brief and valid tool that can be used to assess migraine severity in busy clinical settings.

Objective Despite the widespread and increasing use of electronic health records (EHRs), the quality of EHRs is problematic. Efforts have been made to address reasons for poor EHR documentation quality. Previous systematic reviews have assessed intervention effectiveness within the outpatient setting or paper documentation. The purpose of this systematic review was to assess the effectiveness of interventions seeking to improve EHR documentation within an inpatient setting. Materials and Methods A search strategy was developed based on elaborated inclusion/exclusion criteria. Four databases, gray literature, and reference lists were searched. A REDCap data capture form was used for data extraction, and study quality was assessed using a customized tool. Data were analyzed and synthesized in a narrative, semiquantitative manner. Results Twenty-four studies were included in this systematic review. Owing to high heterogeneity, quantitative comparison was not possible. However, statistically significant results in interventions and affected outcomes were analyzed and discussed. Education and implementation of a new EHR reporting system were the most successful interventions, as evidenced by significantly improved EHR documentation. Discussion Heterogeneity of interventions, outcomes, document type, EHR user, and other variables led to difficulty in measuring EHR documentation quality and effectiveness of interventions. However, the use of education as a primary intervention aligned closely with existing literature in similar fields. Conclusions Interventions implemented to enhance EHR documentation are highly variable and require standardization. Emphasis should be placed on this novel area of research to improve communication between healthcare providers and facilitate data sharing between centers and countries. PROSPERO Registration Number: CRD42017083494.

Background: The International Classification of Diseases (ICD) is globally used for coding morbidity and mortality statistics, however, its use, as well as the data collection features vary greatly across countries. Objective: To characterize hospital ICD-coded data collection worldwide. Methods: After an in-depth grey and academic literature review, an online survey was created to poll the 194 World Health Organization (WHO) member countries. Questions focused on hospital data collection systems and ICD-coded data features. The survey was distributed, using different methods, to potential participants that met the specific criteria, as well as organizations specialized in the topic, such as WHO Collaborating Centers (WHO-CC) or International Federation of Health Information Management Association (IFHIMA), to be forwarded to their representatives. Answers were analyzed using descriptive statistics. Results: Data from 48 respondents from 26 different countries has been collected. Results reveal worldwide use of ICD, with variations in the maximum allowable coding fields for diagnoses and interventions. For instance, in some countries there is an unlimited number of coding fields (Netherlands, Thailand and Iran), as opposed to others with only 1-6 available (Guatemala or Mauritius). Disparities also exist in the definition of a main condition, as 60% of the countries use “reason for admission” and 40% utilize “resource use”. Additionally, the mandatory type of data fields in the hospital morbidity database (e.g. patient demographics, admission type, discharge disposition, diagnoses, …) differ among countries, with diagnosis timing and physician information being the least frequently required. Conclusion: These survey data will establish the current state of ICD use internationally, which will ultimately be valuable to the WHO for the promotion of ICD and the rollout of ICD-11. Additionally, it will improve international comparisons of health data, and encourage further research on how to improve ICD coding.

Introduction Despite increased use of electronic health records (EHRs), EHR documentation quality remains poor. Consequently, EHR data quality is also negatively affected. Many services, including disease surveillance and health services research, utilize EHR data. Accordingly, several studies have attempted to improve EHR documentation quality in the inpatient setting using various interventions. Objectives and Approach The purpose of this systematic review was to synthesize the literature, and assess the effectiveness of interventions seeking to improve inpatient EHR documentation quality. To identify relevant experimental, quasi-experimental and observational studies, a search strategy was developed based on elaborate inclusion/exclusion criteria using four main themes: EHR, documentation, interventions, and type of study. Four databases, Cochrane, Medline, EMBASE, and CINAHL, were searched. Study quality assessment and data extraction from selected studies were performed using a Downs and Black and Newcastle-Ottawa Scale hybrid tool, and a REDCap form, respectively. Data was then analyzed and synthesized in a narrative semi-quantitative manner. Results An in-depth search of the identified databases, grey literature and reference lists, revealed a final 20 studies for inclusion in this systematic review. Due to high heterogeneity in study design, population, interventions, comparators, document types and outcomes, data could not be standardized for a quantitative comparison. However, statistically significant results in interventions and affected outcomes were further presented and discussed. A higher number of studies reported significantly improved EHR documentation when using the interventions: ‘Education’ and ‘Implementing a new EHR Reporting System’. When implementing two or more interventions, more outcome measures were affected. There was no association between study quality or study design and number of interventions used. Only one of the 20 studies found EHR documentation worsened with the interventions used. Conclusion/Implications Interventions implemented to enhance EHR documentation are highly variable and require standardization. Emphasis should be placed on this novel area of research to improve communication between healthcare providers, enhance continuity of care, reduce the burden in health information management, and to facilitate data sharing between centers, provinces, and countries.

Background: Healthcare systems worldwide have adopted the electronic medical record (EMR). EMRs are an efficient method of interprofessional communication, and can improve data availability for secondary research purposes. The discharge summary (DS) is a crucial document for both interprofessional communication, and coding of data for research purposes. We aimed to assess the completeness of our EMRs by assessing the presence of a DS in the EMR. Additionally, we evaluated the presence of indicators for a missing DS. Method: A retrospective chart review was conducted on 3,011 inpatient charts from 3 hospitals in Calgary, Alberta Canada. 893 charts were missing an electronic DS. A 10% sample was drawn to assess for presence of a paper DS. A list of variables was compiled to assess for association between patient and hospital characteristics, patient comorbidities, and the absence of an electronic DS. A Chi-square test, Fisher’s test and logistic regression were conducted to assess for associations. Results: The univariate analyses showed that age, being a surgical patient, a Charlson Comorbidity Index (CCI) of </1, as well as patients with myocardial infarctions, congestive heart failure, cerebrovascular disease, dementia, chronic pulmonary disease, diabetes, and renal disease were associated with a missing DS. The multivariate logistic regression showed that those that were middle aged, surgical patients, or with fewer comorbidities were more likely to have a missing DS. Within the 10% sample, approximately 50% of all patients were from a surgical department, all of which were missing both electronic and paper discharge summaries. Conclusion: Our study is the first to describe indicators associated with missing electronic discharge summaries. There is a modern day propensity for adoption of the EMR across healthcare systems worldwide. The EMR, especially the DS, is used for the improvement of interprofessional communication, patient outcomes, and data quality. Therefore, the implications of an incomplete EMR are widespread. Our findings will caution future researchers using EMR data about the potential for incomplete data, particularly for patients who are surgical, middle aged, and have fewer comorbidities. Additionally, our study highlights the need for further investigation into the lack of discharge summaries in surgical units.

IntroductionHospital safety performance is difficult to monitor when under-coding of hospital harms is common. The beta version of ICD-11 includes a 3-part model for coding harms to enhance adverse event descriptions. This method includes code clusters to detail each condition/event (e.g. bleed), cause (e.g. anticoagulant drug), and mode (over-dose). Objectives and ApproachThe study objective was to compare the proportion of adverse events captured using different classification systems. A large field trial of inpatient charts, previously coded in ICD-10 were coded with ICD-11. Coding training for the new ICD-11 focused on new codes, code clustering, and extension codes for cause and mode of the harm. Sensitivity, Specificity, NPV and PPV were reported for ICD-10 compared to ICD-11. ResultsOf the 1,009 records reviewed and coded using ICD-11 to date, 128 cases were coded as a harm in ICD-10 using our previously published PSI work. Coders identified 88 cases with the new ICD-11. Sensitivity and specificity were as follows: 31.3% and 94.6%. ICD-11 had NPV and PPV of 45.5% and 90.5% respectively compared to ICD-10. Detailed clinical comparison of mismatched codes will be completed. Study case examples will demonstrate advanced features of ICD-11, the coding rules being collaboratively developed by our team, CIHI, and WHO representatives, and potential analytic challenges. Conclusion/ImplicationsThe new ICD-11 found 8% of hospital admission were associated with a harm. Although the sensitivity was modest, specificity is quite high and correctly Identifies those cases without a harm. Clinical review of mismatched codes will provide further detailed code comparisons.

ObjectiveThe epilepsy monitoring unit (EMU) is a valuable resource for optimizing management of persons with epilepsy, but may place patients at risk for adverse events due to withdrawal of treatment and induction of symptoms. The purpose of this study was to synthesize data on the safety and quality of care in EMUs to inform the development of quality indicators for EMUs.MethodsA systematic review was conducted according to the Preferred Reporting and Items for Systematic Review and Meta-Analysis (PRISMA) statement. The search strategy, which included broad search terms and synonyms pertaining to the EMU, was run in six medical databases and included conference proceedings. Data abstracted included patient and EMU demographics and quality and safety variables. Study quality was evaluated using a modified 15-item Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. Descriptive statistics and meta-analyses were used to describe and synthesize the evidence.ResultsThe search yielded 7,601 references, of which 604 were reviewed in full text. One-hundred thirty-five studies were included. The quality and safety data came from 181,823 patients and reported on 34 different quality and safety variables. Included studies commonly reported the number of patients (108 studies; median number patients, 171.5), age (49 studies; mean age 35.7 years old), and the reason for admission (34 studies). The most common quality and safety data reported were the utility of the EMU admission (38 studies). Thirty-three studies (24.4%) reported on adverse events, and yielded a pooled proportion of adverse events of 7% (95% confidence interval [CI] 5-9%). The mean quality score was 73.3% (standard deviation [SD] 17.2).SignificanceThis study demonstrates that there is a great deal of variation in the reporting of quality and safety measures and in the quality and safety in EMUs. Study quality also varied considerably from one study to the next. These findings highlight the need to develop evidence-based, consensus-driven quality indicators for EMUs.

Objectives: In the current study, we aim to assess potential neurologist-related barriers to epilepsy surgery among Canadian neurologists. Methods: A 29-item, pilot-tested questionnaire was mailed to all neurologists registered to practice in Canada. Survey items included the following: (1) type of medical practice, (2) perceptions of surgical risks and benefits, (3) knowledge of existing practice guidelines, and (4) barriers to surgery for patients with epilepsy. Neurologists who did not complete the questionnaire after the initial mailing were contacted a second time by e-mail, fax, or telephone. After this reminder, the survey was mailed a second time to any remaining nonresponders. Results: In total, 425 of 796 neurologists returned the questionnaire (response rate 53.5%). Respondents included 327 neurologists who followed patients with epilepsy in their practice. More than half (56.6%) of neurologists required patients to be drug-resistant and to have at least one seizure per year before considering surgery, and nearly half (48.6%) failed to correctly define drug-resistant epilepsy. More than 75% of neurologists identified inadequate health care resources as the greatest barrier to surgery for patients with epilepsy. Conclusions: A substantial proportion of Canadian neurologists are unaware of recommended standards of practice for epilepsy surgery. Access also appears to be a significant barrier to epilepsy surgery and surgical evaluation. As a result, we are concerned that patients with epilepsy are receiving inadequate care. A greater emphasis must be placed on knowledge dissemination and ensuring that the infrastructure and personnel are in place to allow patients to have timely access to this evidence-based treatment.

ObjectiveSatisfaction with epilepsy care (SEC) encompasses care delivery, expectations, attitudes, and disease course. Through a systematic review of the evidence, we explore how and where the SEC of patients is being measured, the level of SEC overall and in specific domains, and its relationship to clinical and demographic variables.MethodsWe searched Medline, PsycINFO, CINAHL, Cochrane Register of Controlled Trials, and EMBASE using medical subject headings and keywords related to satisfaction with care and epilepsy in adults and children, in all languages. Two independent reviewers screened abstracts and full-text articles. We examined the clinical context and patient characteristics, type and content of satisfaction scales, and reported outcomes. Abstracted variables were grouped for descriptive purposes and presented as medians and proportions when the data allowed it.ResultsOf 25 included studies (6,336 patients), 88% were performed in the United States or the United Kingdom. Nine studies (36%) used validated instruments and 16 studies (64%) used nonvalidated instruments. For SEC domains reported in >1 study, the median proportion (interquartile range) of patients satisfied with epilepsy care was 86% (17%) for overall satisfaction with care, 85% (24%) for interpersonal skills, 78% (3%) for access to care, 67% (32%) for communication, and 65% (15%) for knowledge/technical skills. Communication and clinicians' knowledge was important in all settings. Patients seen in specialized settings and those receiving more and better information had higher SEC ratings. There was no consistent association between SEC and quality of care indicators.SignificanceData on SEC have been reported infrequently. Patients are least satisfied with communication, perceived skills, and knowledge of care providers. Epilepsy-specific SEC tools have neither been validated nor do they contain many of the important domains identified by this review. The relationship between SEC and indicators of quality of care requires further study. Measures aimed at improving education and communication could improve SEC.