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Background: The Dixon-Woods et al. Candidacy Framework, a valuable tool since its 2006 introduction, has been widely utilized to analyze access to various services in diverse contexts, including healthcare. This social constructionist approach examines micro, meso, and macro influences on access, offering concrete explanations for access challenges rooted in socially patterned influences. This study employed the Candidacy Framework to explore the experiences of individuals living with rheumatoid arthritis (RA) and their formal care providers. The investigation extended to assessing supports and innovations in RA diagnosis and management, particularly in primary care. Methods: This systematic review is a Critical Interpretive Synthesis (CIS) of qualitative and mixed methods literature. The CIS aimed to generate theory from identified constructs across the reviewed literature. The study found alignment between the seven dimensions of the Candidacy Framework and key themes emerging from the data. Notably absent from the framework was an eighth dimension, identified as the "embodied relational self." This dimension, central to the model, prompted the proposal of a revised framework specific to healthcare for chronic conditions. Results: The CIS revealed that the eight dimensions, including the embodied relational self, provided a comprehensive understanding of the experiences and perspectives of individuals with RA and their care providers. The proposed Candidacy 2.0 (Chronic Condition (CC)) model demonstrated how integrating approaches like Intersectionality, concordance, and recursivity enhanced the framework when the embodied self was central. Conclusions: The study concludes that while the original Candidacy Framework serves as a robust foundation, a revised version, Candidacy 2.0 (CC), is warranted for chronic conditions. The addition of the embodied relational self dimension enriches the model, accommodating the complexities of accessing healthcare for chronic conditions. Trial Registration: This study did not involve a health care intervention on human participants, and as such, trial registration is not applicable. However, our review is registered with the Open Science Framework at https://doi.org/10.17605/OSF.IO/ASX5C. [ABSTRACT FROM AUTHOR]

Background: Local field potentials (LFPs) represent the summation of periodic (oscillations) and aperiodic (fractal) signals. Although previous studies showed changes in beta band oscillations and burst characteristics of the subthalamic nucleus (STN) in Parkinson's disease (PD), how aperiodic activity in the STN is related to PD pathophysiology is unknown. Objectives: The study aimed to characterize the long‐term effects of STN–deep brain stimulation (DBS) and dopaminergic medications on aperiodic activities and beta bursts. Methods: A total of 10 patients with PD participated in this longitudinal study. Simultaneous bilateral STN‐LFP recordings were conducted in six separate visits during a period of 18 months using the Activa PC + S device in the off and on dopaminergic medication states. We used irregular‐resampling auto‐spectral analysis to separate oscillations and aperiodic components (exponent and offset) in the power spectrum of STN‐LFP signals in beta band. Results: Our results revealed a systematic increase in both the exponent and the offset of the aperiodic spectrum over 18 months following the DBS implantation, independent of the dopaminergic medication state of patients with PD. In contrast, beta burst durations and amplitudes were stable over time and were suppressed by dopaminergic medications. Conclusions: These findings indicate that oscillations and aperiodic activities reflect at least partially distinct yet complementary neural mechanisms, which should be considered in the design of robust biomarkers to optimize adaptive DBS. Given the link between increased gamma‐aminobutyric acidergic (GABAergic) transmission and higher aperiodic activity, our findings suggest that long‐term STN‐DBS may relate to increased inhibition in the basal ganglia. © 2022 International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Background: The dementias are long-term, chronic conditions caused by progressive neurological degeneration. Current literature suggests that cardiovascular disease risk factors may contribute to the onset of dementia; however, evidence of these associations is inconsistent.Objectives: This study aimed to examine the impact of risk factors on dementia onset in older adults diagnosed and managed in Canadian primary care settings.Methods: A retrospective cohort study was employed utilizing electronic medical records data in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). Patients aged 65+ years with no dementia diagnosis at baseline who were followed from 2009 to 2017 with a run-in year to exclude existing undiagnosed dementia cases. Multivariate Cox proportional hazard models were used to estimate risk.Results: Age was associated with an increased incidence risk of dementia in both examined age groups: 65-79 years (13%) and 80+ years (5%). History of depression increased dementia risk by 38% and 34% in the age groups. There were significant associations with lower social deprivation area quintile, smoking history, osteoarthritis, and diabetes mellitus in patients aged 65-79 years but not in those aged 80+ years. Sex, hypertension, obesity, dyslipidemia, and the use of antihypertensive medications and statins were not associated with risk of incident dementia diagnosis.Conclusions: The association between chronic health conditions and dementia onset is complicated. Primary care electronic medical record data might be useful for research in this topic, though follow-up time is still relatively short to observe a clear causal relationship. Future studies with more complete data may provide evidence for dementia preventive strategies within primary care practice. [ABSTRACT FROM AUTHOR]

Background: Dementia is an increasing concern in many countries, especially in those experiencing rapid growth in the proportion of older adults in their population.Objective: This study aims to describe trends and demographic characteristics of incident dementia cases in community-dwelling older adults managed by primary care physicians.Methods: We used electronic medical records from the Canadian Primary Care Sentinel Surveillance Network database to conduct a retrospective analysis to determine the number of, and trends for, incident diagnoses of dementia. Age-standardized annual incidence rates were calculated. Participants in our cohort are Canadian community dwelling seniors aged 65+ years who were not diagnosed with dementia before baseline with at least six years of record at their primary care clinics.Results: The cohort consisted of 39 067 patients of whom 57% were females; the mean (SD) follow-up was 8.4 (1.5) years. During follow-up, 4935 patients were diagnosed with dementia. The risk for dementia diagnosis increased with increasing age but decreased in the last four years among people aged 80 and older at baseline (P < 0.001). People with dementia were more likely to be females (P = 0.001) and urban residents (P < 0.001), they are less likely to be classified into the least deprived group (P = 0.012).Conclusions: The incidence of dementia diagnosis increased with age except in the oldest old in both sexes. This may be attributed to the effect of mortality competing risk. Future research on the association between risk factors and dementia should consider studying dementia among the oldest old separately to minimize bias. [ABSTRACT FROM AUTHOR]

Objectives: This paper explores the role of immigrant-serving agencies in facilitating access to dementia services and supports provided by dementia service agencies (particularly the health authority and local chapters of the Alzheimer Society) through their propensity to develop trusting relationships between staff and clients. Design: Our research is a qualitative case study of Punjabi and Korean speakers living in the Lower Mainland of BC, Canada. Data are drawn from interviews with 15 dyads of persons with dementia and their family caregivers (10 Punjabi, 5 Korean), six focus groups (one focus group with each of 8–10 older men, older women, and mixed gender working age adults in each community). We also interviewed 20 managerial and frontline staff of dementia service agencies, i.e. the health authority and the local Alzheimer Society (n = 11) and two immigrant-serving agencies (n = 9), each dedicated to either Punjabi or Korean-speaking clients. We adopted the Candidacy framework for understanding access to dementia services and supports and the concept of trust as guiding precepts in this study. Results: Families of persons with dementia are pivotal to identification of a problem requiring professional help, navigation to appropriate services and acceptance of services offered. However, trust in family members should not be taken for granted, since family dynamics are complex. Alternative sources of trusted support are therefore needed. Immigrant-serving agencies are more often instrumental in establishing trusted relationships between their staff and clients, but they often lack detailed knowledge about heath conditions, their treatment and management, and they lack power to implement statutory care. Conclusions: Partnerships between mainstream mental health/dementia services and the community sector have proven successful in increasing the accessibility of specialized resources, while maximizing their combined trustworthiness, accessibility and effectiveness. Such partnerships should become fundamental components of health service strategy and provision for vulnerable and underserved immigrant older adults. [ABSTRACT FROM AUTHOR]

Background: Most antibiotics dispensed by community pharmacies in Canada are prescribed by family physicians, but using the prescribing information contained within primary care electronic medical records (EMRs) for secondary purposes can be challenging owing to variable data quality. We used antibiotic medications as an exemplar to validate a machine-learning approach for cleaning and coding medication data in a pan-Canadian primary care EMR database., Methods: The Canadian Primary Care Sentinel Surveillance Network database contained an estimated 42 million medication records, which we mapped to an Anatomic Therapeutic Chemical (ATC) code by applying a semisupervised classification model developed using reference standard labels derived from the Health Canada Drug Product Database. We validated the resulting ATC codes in a subset of antibiotic records (16 119 unique strings) to determine whether the algorithm correctly classified the medication according to manual review of the original medication record., Results: In the antibiotic subset, the algorithm showed high validity (sensitivity 99.5%, specificity 92.4%, positive predictive value 98.6%, negative predictive value 97.0%) in classifying whether the medication was an antibiotic., Interpretation: Our machine-learning algorithm classified unstructured antibiotic medication data from primary care with a high degree of accuracy. Access to cleaned EMR data can support important secondary uses, including community-based antibiotic prescribing surveillance and practice improvement., Competing Interests: Competing interests: None declared., (© 2023 CMA Impact Inc. or its licensors.)

The International Classification of Diseases, Ninth Revision (ICD-9) was released in the 1970s and adopted in Canada for physician billing claims in 1979 (CIHI n.d.b.; WHO & International Conference for the Ninth Revision of the International Classification of Diseases 1977). ICD-9 is no longer adequate for representing our modern healthcare environment and patient needs. We summarize the findings from a small survey of ICD-9 users across Canada - such as family physicians, researchers and decision makers - who describe the limitations of ICD-9 and the features that they would desire in a new or updated classification system., (Copyright © 2022 Longwoods Publishing.)