230 research outputs found

    Methods to Describe Referral Patterns in a Canadian Primary Care Electronic Medical Record Database: Modelling Multilevel Count Data

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    Background: A referral from a family physician (FP) to a specialist is an inflection point in the patient journey, with potential implications for clinical outcomes and health policy. Primary care electronic medical record (EMR) databases offer opportunities to examine referral patterns. Until recently, software techniques were not available to model these kinds of multi-level count data. Objective: To establish methodology for determining referral rates from FPs to medical specialists using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) EMR database. Method: Retrospective cohort study, mixed effects and multi-level negative binomial regression modelling with 87,258 eligible patients between 2007 and 2012. Mean referrals compared by patient sex, age, chronic conditions, FP visits, and urban/rural practice location. Proportion of variance in referral rates attributable to the patient and practice levels. Results: On average, males had 0.26, and females 0.31 referrals in a 12-month period. Referrals were significantly higher for females, increased with age, FP visits, and number of chronic conditions (p\u3c.0001). Overall, 14% of the variance in referrals could be attributed to the practice level, and 86% to patient level characteristics. Conclusions: Both patient and practice characteristics influenced referral patterns. The methodologic insights gained from this study have relevance to future studies on many research questions that utilize count data, both within primary care and broader health services research. The utility of the CPCSSN database will continue to increase in tandem with data quality improvements, providing a valuable resource to study Canadian referral patterns over time

    Family Physician Clinical Inertia in Managing Hypoglycemia

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    Aims: Clinical inertia behaviour affects family physicians managing chronic disease such as diabetes. Literature addressing clinical inertia in the management of hypoglycemia is scarce. The objectives of this study were to create a measurement for physician clinical inertia in managing hypoglycemia (ClinInert_InHypoDM), and to determine physicians’ characteristics associated with clinical inertia. Methods: The study was a secondary analysis of data provided by family physicians from the InHypo-DM Study, applying exploratory factor analysis. Principal axis factoring with an Oblimin rotation was employed to detect underlying factors associated with physician behaviors. Multiple linear regression was used to determine association between the ClinInert_InHypoDM scores and physician characteristics. Results: Factor analysis identified a statistically sound 12-item one-factor scale for clinical inertia behavior. No statistically significant differences in clinical inertia score for the studied independent variables were found. Conclusions: This study provides a scale for assessing clinical inertia in the management of hypoglycemia. Further testing this scale in other family physician populations will provide deeper understanding about the characteristics and factors that influence clinical inertia. The knowledge derived from better understanding clinical inertia in primary care has potential to improve outcomes for patients with diabetes

    The prevalence of multimorbidity in primary care: a comparison of two definitions of multimorbidity with two different lists of chronic conditions in Singapore

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    Background: The prevalence of multimorbidity varies widely due to the lack of consensus in defining multimorbidity. This study aimed to measure the prevalence of multimorbidity in a primary care setting using two definitions of multimorbidity with two different lists of chronic conditions. Methods: We conducted a cross-sectional study of 787,446 patients, aged 0 to 99 years, who consulted a family physician between July 2015 to June 2016. Multimorbidity was defined as ‘two or more’ (MM2+) or ‘three or more’ (MM3+) chronic conditions using the Fortin list and Chronic Disease Management Program (CDMP) list of chronic conditions. Crude and standardised prevalence rates were reported, and the corresponding age, sex or ethnic-stratified standardised prevalence rates were adjusted to the local population census. Results: The number of patients with multimorbidity increased with age. Age-sex-ethnicity standardised prevalence rates of multimorbidity using MM2+ and MM3+ for Fortin list (25.9, 17.2%) were higher than those for CDMP list (22.0%; 12.4%). Sex-stratified, age-ethnicity standardised prevalence rates for MM2+ and MM3+ were consistently higher in males compared to females for both lists. Chinese and Indians have the highest standardised prevalence rates among the four ethnicities using MM2+ and MM3+ respectively. Conclusions: MM3+ was better at identifying a smaller number of patients with multimorbidity requiring higher needs compared to MM2+. Using the Fortin list seemed more appropriate than the CDMP list because the chronic conditions in Fortin’s list were more commonly seen in primary care. A consistent definition of multimorbidity will help researchers and clinicians to understand the epidemiology of multimorbidity better

    Methods to Describe Referral Patterns in a Canadian Primary Care Electronic Medical Record Database: Modelling Multilevel Count Data

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    Background:  A referral from a family physician (FP) to a specialist is an inflection point in the patient journey, with potential implications for clinical outcomes and health policy. Primary care electronic medical record (EMR) databases offer opportunities to examine referral patterns. Until recently, software techniques were not available to model these kinds of multi-level count data. Objective:  To establish methodology for determining referral rates from FPs to medical specialists using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) EMR database. Method: Retrospective cohort study, mixed effects and multi-level negative binomial regression modelling with 87,258 eligible patients between 2007 and 2012. Mean referrals compared by patient sex, age, chronic conditions, FP visits, and urban/rural practice location.  Proportion of variance in referral rates attributable to the patient and practice levels. Results:  On average, males had 0.26, and females 0.31 referrals in a 12-month period.  Referrals were significantly higher for females, increased with age, FP visits, and number of chronic conditions (p<.0001). Overall, 14% of the variance in referrals could be attributed to the practice level, and 86% to patient level characteristics. Conclusions:  Both patient and practice characteristics influenced referral patterns. The methodologic insights gained from this study have relevance to future studies on many research questions that utilize count data, both within primary care and broader health services research. The utility of the CPCSSN database will continue to increase in tandem with data quality improvements, providing a valuable resource to study Canadian referral patterns over time

    Teaching SBIRT through simulation: Educational case studies from nursing, psychology, social work, and medical residency programs

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    The prevalence of substance use disorders remains high in the United States and healthcare professionals are largely ill-equipped to intervene with patients experiencing substance misuse or use disorders. To address this issue, substance abuse intervention curricula such as Screening, Brief Intervention, and Referral to Treatment (SBIRT) are being integrated into university healthcare programs through the use of simulation to provide healthcare students with the necessary skills to address patient substance use. Teaching SBIRT with simulation provides students with an authentic clinical environment in which to learn and refine clinical skills. Simulation also supports reflective practice by providing an opportunity for instructors and peers to directly observe and provide feedback on students' patient care. Additionally, students can review (through video recording) and reflect on their own performance within the simulation to build self-awareness and improve their skills and approach to clinical work. This paper describes how SBIRT simulation was integrated into nursing, psychology, and social work curricula at a medium-sized northwest university and a family medicine residency program in the same community. Satisfaction with SBIRT simulation as well as students’ perceived change in confidence in addressing substance use was recorded. Overall, instructors, students, and medical residents were highly satisfied with simulation experiences. Students and medical residents also reported increases in understanding of and confidence in executing SBIRT. Simulation implementation strategies and resources are provided and discussed.Ye

    Systematic review on the instruments used for measuring the association of the level of multimorbidity and clinically important outcomes

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    Objectives There are multiple instruments for measuring multimorbidity. The main objective of this systematic review was to provide a list of instruments that are suitable for use in studies aiming to measure the association of a specific outcome with different levels of multimorbidity as the main independent variable in community-dwelling individuals. The secondary objective was to provide details of the requirements, strengths and limitations of these instruments, and the chosen outcomes. Methods We conducted the review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO registration number: CRD42018105297). We searched MEDLINE, Embase and CINAHL electronic databases published in English and manually searched the Journal of Comorbidity between 1 January 2010 and 23 October 2020 inclusive. Studies also had to select adult patients from primary care or general population and had at least one specified outcome variable. Two authors screened the titles, abstracts and full texts independently. Disagreements were resolved with a third author. The modified Newcastle-Ottawa Scale was used for quality assessment. Results Ninety-six studies were identified, with 69 of them rated to have a low risk of bias. In total, 33 unique instruments were described. Disease Count and weighted indices like Charlson Comorbidity Index were commonly used. Other approaches included pharmaceutical-based instruments. Disease Count was the common instrument used for measuring all three essential core outcomes of multimorbidity research: Mortality, mental health and quality of life. There was a rise in the development of novel weighted indices by using prognostic models. The data obtained for measuring multimorbidity were from sources including medical records, patient self-reports and large administrative databases. Conclusions We listed the details of 33 instruments for measuring the level of multimorbidity as a resource for investigators interested in the measurement of multimorbidity for its association with or prediction of a specific outcome. © 2021 Author(s). Published by BMJ

    Primary care bonus payments and patient-reported access in urban Ontario: a cross-sectional study

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    BACKGROUND: Rurality strongly correlates with higher pay-for-performance access bonuses, despite higher emergency department use and fewer primary care services than in urban settings. We sought to evaluate the relation between patient-reported access to primary care and access bonus payments in urban settings. METHODS: We conducted a cross-sectional, secondary data analysis using Ontario survey and health administrative data from 2013 to 2017. We used administrative data to calculate annual access bonuses for eligible urban family physicians. We linked this payment data to adult (≥ 16 yr) patient data from the Health Care Experiences Survey to examine the relation between access bonus achievement (in quintiles of the proportion of bonus achieved, from lowest [Q1, reference category] to highest [Q5]) and 4 patient-reported access outcomes. The average survey response rate to the patient survey during the study period was 51%. We stratified urban geography into large, medium and small settings. In a multilevel regression model, we adjusted for patient-, physician- and practice-level covariates. We tested linear trends, adjusted for clustering, for each outcome. RESULTS: We linked 18 893 respondents to 3940 physicians in 414 bonus-eligible practices. Physicians in small urban settings earned the highest proportion of their maximum potential access bonuses. Access bonus achievement was positively associated with telephone access (Q2 odds ratio [OR] 1.18, 95% confidence interval [CI] 0.98-1.42; Q3 OR 1.34, 95% CI 1.10-1.63; Q4 OR 1.46, 95% CI 1.19-1.79; Q5 OR 1.87, 95% CI 1.50-2.33), after hours access (Q2 OR 1.26, 95% CI 1.09-1.47; Q3 OR 1.46, 95% CI 1.23-1.74; Q4 OR 1.77, 95% CI 1.46-2.15; Q5 OR 1.88, 95% CI 1.52-2.32), wait time for care (Q2 OR 1.01, 95% CI 0.85-1.20; Q3 OR 1.17, 95% CI 0.97-1.41; Q4 OR 1.27, 95% CI 1.05-1.55; Q5 OR 1.63, 95% CI 1.32-2.00) and timeliness (Q2 OR 1.29, 95% CI 0.98-1.69; Q3 OR 1.29, 95% CI 0.94-1.77; Q4 OR 1.58, 95% CI 1.16-2.13; Q5 OR 1.98, 95% CI 1.38-2.82). When stratified by geography, we observed several of these associations in large urban settings, but not in small urban settings. Trend tests were statistically significant for all 4 outcomes. INTERPRETATION: Although the access bonus correlated with access in larger urban settings, it did not in smaller settings, aligning with previous research questioning its utility in smaller geographies. The access bonus may benefit from a redesign that considers geography and patient experience

    Primary Care Informatics Response to Covid-19 Pandemic: Adaptation, Progress, and Lessons from Four Countries with High ICT Development

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    OBJECTIVE: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned. METHODS: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives. RESULTS: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits. CONCLUSIONS: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted
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