Prevalence and Incidence Trends of Attention Deficit/Hyperactivity Disorder in Children and Youth Aged 1-24 Years in Ontario, Canada: A Validation Study of Health Administrative Data Algorithms: Tendances de la prévalence et de l'incidence du trouble de déficit de l'attention/hyperactivité chez les enfants et les jeunes âgés de 1 à 24 ans, en Ontario, Canada: une étude de validation des algorithmes de données administratives de santé.

OBJECTIVE: To estimate prevalence and incidence rates over time in children and youth with attention deficit/hyperactivity disorder from the validation of population-based administrative data algorithms using family physicians' electronic medical records as a reference standard. METHODS: A retrospective cohort study was conducted in Ontario, Canada to identify attention deficit/hyperactivity disorder among children and youth aged 1-24 years in health administrative data derived from case-finding algorithms using family physicians' electronic medical records. Multiple administrative data algorithms identifying attention deficit/hyperactivity disorder cases were developed and tested from physician-diagnosis of attention deficit/hyperactivity disorder in the electronic medical record to determine their diagnostic accuracy. We calculated algorithm performance using sensitivity, specificity, and predictive values. The most optimal algorithm was used to estimate prevalence and incidence rates of attention deficit/hyperactivity disorder from 2014 to 2021 in Ontario. RESULTS: The optimal performing algorithm was "2 physician visits for attention deficit/hyperactivity disorder in 1 year or 1 attention deficit/hyperactivity disorder-specific prescription" with sensitivity: 83.2% (95% confidence interval [CI], 81.8% to 84.5%), specificity: 98.6% (95% CI, 98.5% to 98.7%), positive predictive value: 78.6% (95% CI, 77.1% to 80.0%) and negative predictive value: 98.9% (95% CI, 98.8% to 99.0%). From 2014, prevalence rates for attention deficit/hyperactivity disorder increased from 5.29 to 7.48 per 100 population in 2021 (N = 281,785). Males had higher prevalence rates (7.49 to 9.59 per 100 population, 1.3-fold increase) than females (2.96-5.26 per 100 population, 1.8-fold increase) from 2014 to 2021. Incidence rates increased from 2014 (0.53 per 100 population) until 2018, decreased in 2020 then rose steeply in 2021 (0.89 per 100 population, N = 34,013). Males also had higher incidence rates than females from 2014 to 2020 with females surpassing males in 2021 (0.70-0.81 per 100 male population,1.2-fold increase versus 0.36-0.97 per 100 female population, 2.7-fold increase). CONCLUSIONS: Attention deficit/hyperactivity disorder is increasing in prevalence. We developed an administrative data algorithm that can reliably identify children and youth with attention deficit/hyperactivity disorder with good diagnostic accuracy.

A comparison of family physician and dermatologist topical corticosteroid prescriptions: A population-based cross-sectional study.

BACKGROUND: Topical corticosteroids (TCS) are commonly prescribed to treat inflammatory skin diseases, and appropriate prescription is necessary for treatment success. OBJECTIVE: To quantify differences between TCS prescribed by dermatologists at consultation and family physicians for patients treated for any skin condition. METHODS: Using administrative health data in Ontario, we included all Ontario Drug Benefit recipients who filled at least one TCS prescription from a dermatologist at consultation and a family physician in the year prior between January 2014 and December 2019. We estimated mean differences and 95% confidence intervals in amount (in grams) and potency between the index dermatologist prescription and the highest and most recent family physician prescription amounts and potencies in the preceding year using linear mixed-effect models. RESULTS: A total of 69,335 persons were included. The mean dermatologist amount was 34% larger than the highest amount and 54% larger than the most recent amount prescribed by family physicians. There were small but statistically significant differences in potency using established 7-category and 4-category potency classification systems. CONCLUSIONS: Compared to family physicians, dermatologists prescribed substantially larger amounts and similarly potent TCS at consultation. Further research is needed to determine the effect of these differences on clinical outcomes.

The association between patients' frailty status, multimorbidity, and demographic characteristics and changes in primary care for chronic conditions during the COVID-19 pandemic: a pre-post study.

BACKGROUND: The purpose of this study was to assess the impact of SARS-COV-2 (Severe acute respiratory syndrome coronavirus 2) pandemic on primary care management (frequency of monitoring activities, regular prescriptions, and test results) of older adults with common chronic conditions (diabetes, hypertension, and chronic kidney disease) and to examine whether any changes were associated with age, sex, neighbourhood income, multimorbidity, and frailty. METHODS: A research database from a sub-set of McMaster University Sentinel and Information Collaboration family practices was used to identify patients ≥65 years of age with a frailty assessment and 1 or more of the conditions. Patient demographics, chronic conditions, and chronic disease management information were retrieved. Changes from 14 months pre to 14 months since the pandemic were described and associations between patient characteristics and changes in monitoring, prescriptions, and test results were analysed using regression models. RESULTS: The mean age of the 658 patients was 75 years. While the frequency of monitoring activities and prescriptions related to chronic conditions decreased overall, there were no clear trends across sub-groups of age, sex, frailty level, neighbourhood income, or number of conditions. The mean values of disease monitoring parameters (e.g. blood pressure) did not considerably change. The only significant regression model demonstrated that when controlling for all other variables, patients with 2 chronic conditions and those with 4 or more conditions were twice as likely to have reduced numbers of eGFR (Estimated glomerular filtration rate) measures compared to those with only 1 condition ((OR (odds ratio) = 2.40, 95% CI [1.19, 4.87]); (OR = 2.19, 95% CI [1.12, 4.25]), respectively). CONCLUSION: In the first 14 months of the pandemic, the frequency of common elements of chronic condition care did not notably change overall or among higher-risk patients.

Sex differences in the clinical presentation of early psychosis in a primary care setting.

Primary care is an important part of the help-seeking pathway for young people experiencing early psychosis, but sex differences in clinical presentation in these settings are unexplored. We aimed to identify sex differences in clinical presentation to primary care services in the 1-year period prior to a first diagnosis of psychotic disorder. We identified first-onset cases of non-affective psychotic disorder over a 10-year period (2005-2015) using health administrative data linked with electronic medical records (EMRs) from primary care (n = 465). Detailed information on encounters in the year prior to first diagnosis was abstracted, including psychiatric symptoms, other relevant behaviours, and diagnoses recorded by the family physician (FP). We used modified Poisson regression models to examine sex differences in the signs, symptoms, and diagnoses recorded by the FP, adjusting for various clinical and sociodemographic factors. Positive symptoms (PR = 0.76, 95%CI: 0.58, 0.98) and substance use (PR = 0.54, 95%CI: 0.40, 0.72) were less prevalent in the medical records of women. Visits by women were more likely to be assigned a diagnosis of depression or anxiety (PR = 1.18, 95%CI: 1.00, 1.38), personality disorder (PR = 5.49, 95%CI: 1.22, 24.62), psychological distress (PR = 11.29, 95%CI: 1.23, 103.91), and other mental or behavioral disorders (PR = 3.49, 95%CI: 1.14, 10.66) and less likely to be assigned a diagnosis of addiction (PR = 0.33, 95%CI: 0.13, 0.87). We identified evidence of sex differences in the clinical presentation of early psychosis and recorded diagnoses in the primary care EMR. Further research is needed to better understand sex differences in clinical presentation in the primary care context, which can facilitate better understanding, detection, and intervention for first-episode psychotic disorders.

Periodic screening for breast and cervical cancer in women with diabetes: a population-based cohort study.

PURPOSE: Diabetes is associated with poorer cancer outcomes. Screening for breast and cervical cancer is recommended by clinical guidelines; however, utilization of these tests in people with diabetes has been unclear due to methodological limitations in the evidence base. We used administrative data to determine the association between diabetes and the rates of becoming up-to-date with periodic breast and cervical cancer screening over a 20-year period. METHODS: Healthcare databases from Ontario, Canada, were linked to assemble two population-based cohorts of 50-70 and 21-70 year-olds between 1994 and 2011, eligible for breast and cervical cancer screening, respectively. Using age as the time scale, multivariable recurrent events models were implemented to examine the association between the presence of diabetes and the rates of becoming up-to-date with the recommended cancer screenings. RESULTS: In each of the breast and cervical cancer screening cohorts, there were, respectively, 1,516,302 (16% had diabetes at baseline) and 4,751,220 (9.5% had diabetes at baseline) screen-eligible women. In multivariable models, prevalent diabetes (duration ≥ 2 years) was associated with lower rates of becoming up-to-date with cervical (hazard ratio, HR 0.85, 95% confidence interval, CI 0.84-0.85) and breast (HR 0.94, CI 0.93-0.94) cancer screening, compared to no diabetes. CONCLUSIONS: Having diabetes is associated with decreased rates of becoming up-to-date with two recommended periodic cancer screenings, with a bigger reduction in the rates of becoming up-to-date with cervical cancer screening. Greater attention to cervical cancer preventive services is needed in women with diabetes.

The quality of diabetes care among cancer survivors: a retrospective cohort study.

BACKGROUND: As cancer survivorship continues to improve, management of co-morbid diabetes has become an increasingly important determinant of health outcomes for people with cancer. This study aimed to compare indicators of diabetes quality of care between people with diabetes and without a history of cancer. METHODS: We used the Electronic Medical Record Administrative data Linked Database (EMRALD), a database of Ontario primary care EMR charts linked to administrative data, to identify people with diabetes and at least 1 year follow-up. Persons with a history of cancer were matched 1:2 on age, sex and diabetes duration to those without cancer. We compared recommended diabetes quality of care indicators between persons with and without cancer using a matched cohort analysis. RESULTS: Among 229,627 people with diabetes, we identified 2275 people with cancer and 4550 matched controls; 86.5% had diabetes diagnosed after cancer. Compared to controls, cancer people with diabetes were significantly less likely to receive ACE inhibitors or angiotensin receptor blockers (OR 0.75 [95% CI 0.64-0.89]), receive statin therapy if age 50-80 years (OR 0.79 [95% CI 0.68-0.92]) and achieve an LDL cholesterol level <2.0 mmol/L (OR 0.82 [95% CI 0.74-0.91]). There were no differences in recommended clinical testing or achieving A1C and blood pressure targets between groups. CONCLUSION: Cancer survivors with diabetes are less likely to receive recommended cardiovascular risk-reducing therapies compared to people with diabetes without cancer of similar age, sex and diabetes duration. Further studies are warranted to determine if these associations are linked to worse survival, cardiovascular outcomes and quality of life.

The receipt of information by family physicians about their patient's emergency department visits: a record linkage study of electronic medical records to health administrative data.

BACKGROUND: Canadians are known to be frequent users of emergency department (ED) care. However, the exchange of information from ED visits to family physicians (FPs) is not well known. Our objectives were to determine whether Canadian FPs received information about their patient's ED visit and the patient characteristics related to the receipt of ED information. METHODS: This study was a descriptive record linkage study of FP Electronic Medical Record (EMR) data linked to health administrative data. Our study cohort included patients who had at least one ED visit in 2010 or 2015 in Ontario, Canada. An ED visit could include a transfer to or from another ED. The receipt of information from an ED note was examined in relation to patient age, sex, neighbourhood income quintiles, rurality and comorbidity. RESULTS: There were 26,609 patients in 2010 and 50,541 patients in 2015 with at least one ED visit. In 2010, 53.3% of FPs received an ED note for patients having a single ED visit compared to 41.0% in 2015. For patients with multiple ED visits, 58.2% of FPs received an ED note in 2010 compared to 45.7% in 2015. FPs were more likely to receive an ED note for patients not living in low income neighbourhoods, older patients, patients living in small urban areas and for patients having moderate comorbidity. FPs were less likely to receive a note for patients living in rural areas. CONCLUSIONS: Community-based FPs are more likely to get information after an ED visit for their older and sicker patients. However, FPs do not receive any information from EDs for over half their patients. Electronic health record technologies and their adoption by ED providers need to improve the seamless transfer of information about the care provided in EDs to FPs in the community.

Computerized Cognitive Testing in Primary Care: A Qualitative Study.

Computerized cognitive assessment tools may facilitate early identification of dementia in the primary care setting. We investigated primary care physicians' (PCPs') views on advantages and disadvantages of computerized testing based on their experience with the Computer Assessment of Mild Cognitive Impairment (CAMCI). Over a 2-month period, 259 patients, 65 years and older, from the family practice of 13 PCPs completed the CAMCI. Twelve PCPs participated in an individual interview. Generally, PCPs felt that the relationship between them and their patients helped facilitate cognitive testing; however, they thought available paper tests were time consuming and not sufficiently informative. Despite concerns regarding elderly patients' computer literacy, PCPs noticed high completion rates and that their patients had generally positive experiences completing the CAMCI. PCPs appreciated the time-saving advantage of the CAMCI and the immediately generated report, but thought the report should be shortened to 1 page and that PCPs should receive training in its interpretation. Our results suggest that computerized cognitive tools such as the CAMCI can address PCPs' concerns with cognitive testing in their offices. Recommendations to improve the practicality of computerized testing in primary care were suggested.

The Effects of Computerized Cognitive Testing of Older Patients on Primary Care Physicians' Approaches to Care: A Canadian Study.

BACKGROUND: We evaluated effects of providing primary care physicians (PCPs) with reports of their patients' results on the Computer Assessment of Mild Cognitive Impairment (CAMCI) by examining their documented care approaches after receipt of the report. METHODS: Patients were 65 years and above, without a diagnosis or previous workup for dementia, seen consecutively over 2 months by one of 13 PCPs. PCPs indicated whether they, patients, or families had concerns about patients' cognition. A total of 259 patients individually completed the CAMCI and results were provided to the PCP. Two raters blind to CAMCI results recorded care approaches documented by PCPs at the first visit within 3 months of report (n=181). RESULTS: In total, 28 different care approaches were grouped as related to Cognition or Safety/Self-Care. Negative binomial regression revealed that the number of care approaches was significantly associated with performance on the CAMCI for both Cognition and Safety/Self-care domains. These findings remained significant when covariates included PCPs' cognitive concern before CAMCI results, and patients' age, sex, number of comorbidities, and living arrangements. CONCLUSIONS: Our findings indicate that PCPs documented more care approaches in patients with greater cognitive impairment based on the CAMCI results and this was independent of their, the patients', or families' prior concerns about their patients' cognition.

Effect of comorbidities and medications on frequency of primary care visits among older patients.

OBJECTIVE: To determine if comorbidities and high-risk medications affect the frequency of family physician visits among older patients. DESIGN: Retrospective chart review. SETTING: Academic family health team at Sunnybrook Health Sciences Centre in Toronto, Ont. PARTICIPANTS: Among patients aged 65 years and older who were registered patients of the family health team between July 1, 2013, and June 30, 2014, the 5% who visited their family physicians most frequently and the 5% who visited their family physicians least frequently were selected for the study (N = 265). MAIN OUTCOME MEASURES: Predictors of frequent visits to family physicians. RESULTS: The significant predictors of being a high-frequency user were female sex (odds ratio [OR] = 2.20, P = .03), age older than 85 years (OR = 5.35, P = .001), and higher total number of medications (OR = 1.49, P < .001). Age-adjusted Charlson comorbidity index score, number of Beers criteria medications, and Anticholinergic Risk Scale score were not significant predictors (P > .05). CONCLUSION: Female sex, age older than 85, and higher total number of medications were independent significant predictors of higher frequency of family physician visits among older patients. Validated tools, such as the Charlson comorbidity index, Beers criteria, and Anticholinergic Risk Scale, did not independently predict the frequency of visits, indicating that predicting frequency of visits is likely complex.

Development and validation of an administrative data algorithm to estimate the disease burden and epidemiology of multiple sclerosis in Ontario, Canada.

BACKGROUND: Few studies have assessed the accuracy of administrative data for identifying multiple sclerosis (MS) patients. OBJECTIVES: To validate administrative data algorithms for MS, and describe the burden and epidemiology over time in Ontario, Canada. METHODS: We employed a validated search strategy to identify all MS patients within electronic medical records, to identify patients with and without MS (reference standard). We then developed and validated different combinations of administrative data for algorithms. The most accurate algorithm was used to estimate the burden and epidemiology of MS over time. RESULTS: The accuracy of the algorithm of one hospitalisation or five physician billings over 2 years provided both high sensitivity (84%) and positive predictive value (86%). Application of this algorithm to provincial data demonstrated an increasing cumulative burden of MS, from 13,326 patients (0.14%) in 2000 to 24,647 patients in 2010 (0.22%). Age-and-sex standardised prevalence increased from 133.9 to 207.3 MS patients per 100,000 persons in the population, from 2000 - 2010. During this same period, age-and-sex-standardised incidence varied from 17.9 to 19.4 patients per 100,000 persons. CONCLUSIONS: MS patients can be accurately identified from administrative data. Our findings illustrated a rising prevalence of MS over time. MS incidence rates also appear to be rising since 2009.

Are family physicians comprehensively using electronic medical records such that the data can be used for secondary purposes? A Canadian perspective.

BACKGROUND: With the introduction and implementation of a variety of government programs and policies to encourage adoption of electronic medical records (EMRs), EMRs are being increasingly adopted in North America. We sought to evaluate the completeness of a variety of EMR fields to determine if family physicians were comprehensively using their EMRs and the suitability of use of the data for secondary purposes in Ontario, Canada. METHODS: We examined EMR data from a convenience sample of family physicians distributed throughout Ontario within the Electronic Medical Record Administrative data Linked Database (EMRALD) as extracted in the summer of 2012. We identified all physicians with at least one year of EMR use. Measures were developed and rates of physician documentation of clinical encounters, electronic prescriptions, laboratory tests, blood pressure and weight, referrals, consultation letters, and all fields in the cumulative patient profile were calculated as a function of physician and patient time since starting on the EMR. RESULTS: Of the 167 physicians with at least one year of EMR use, we identified 186,237 patients. Overall, the fields with the highest level of completeness were for visit documentations and prescriptions (>70%). Improvements were observed with increasing trends of completeness overtime for almost all EMR fields according to increasing physician time on EMR. Assessment of the influence of patient time on EMR demonstrated an increasing likelihood of the population of EMR fields overtime, with the largest improvements occurring between the first and second years. CONCLUSIONS: All of the data fields examined appear to be reasonably complete within the first year of adoption with the biggest increase occurring the first to second year. Using all of the basic functions of the EMR appears to be occurring in the current environment of EMR adoption in Ontario. Thus the data appears to be suitable for secondary use.

A validation study of administrative data algorithms to identify patients with Parkinsonism with prevalence and incidence trends.

BACKGROUND: Epidemiological studies for identifying patients with Parkinson's disease (PD) or Parkinsonism (PKM) have been limited by their nonrandom sampling techniques and mainly veteran populations. This reduces their use for health services planning. The purpose of this study was to validate algorithms for the case ascertainment of PKM from administrative databases using primary care patients as the reference standard. METHODS: We conducted a retrospective chart abstraction using a random sample of 73,003 adults aged ≥ 20 years from a primary care Electronic Medical Record Administrative data Linked Database (EMRALD) in Ontario, Canada. Physician diagnosis in the EMR was used as the reference standard and population-based administrative databases were used to identify patients with PKM from the derivation of algorithms. We calculated algorithm performance using sensitivity, specificity, and predictive values and then determined the population-level prevalence and incidence trends with the most accurate algorithms. RESULTS: We selected, '2 physician billing codes in 1 year' as the optimal administrative data algorithm in adults and seniors (≥ 65 years) due to its sensitivity (70.6-72.3%), specificity (99.9-99.8%), positive predictive value (79.5-82.8%), negative predictive value (99.9-99.7%), and prevalence (0.28-1.20%), respectively. CONCLUSIONS: Algorithms using administrative databases can reliably identify patients with PKM with a high degree of accuracy.

Factors associated with primary care physicians' recognition of cognitive impairment in their older patients.

Although there are accurate screens for cognitive impairment, there is as yet no evidence that screening improves outcomes including primary care physicians' (PCP) medical decision making. PCPs' recognition of cognitive impairment being suboptimal, we investigated factors associated with improved recognition. Eligible patients were aged 65 years and above, without documented dementia or previous work-up for dementia, seen consecutively over 2 months by one of 13 PCPs. PCPs indicated whether they, the patient, or the family had concerns about each patient's cognition. We enrolled 130 patients with any cognitive concerns and a matched sample of 133 without cognitive concerns, and administered standardized neuropsychological tests. PCP's judgments of cognitive concern showed 61% sensitivity and 86% specificity against the neuropsychological standard. When combined with a Mini-Mental State Examination score ≤26, PCP recognition improved in sensitivity (82%) with some loss in specificity (74%). True positives increased when PCPs' practices included more cognitively impaired patients and when patients reported poor memory. False positives increased when patients had diabetes, reported poor memory, or no or light alcohol consumption. Medical decision making can be improved by the Mini-Mental State Examination and greater exposure to cognitively impaired patients, but knowledge of certain risk factors for cognitive impairment negatively affected these decisions.

Waiting to see the specialist: patient and provider characteristics of wait times from primary to specialty care.

BACKGROUND: Wait times are an important measure of access to various health care sectors and from a patient's perspective include several stages in their care. While mechanisms to improve wait times from specialty care have been developed across Canada, little is known about wait times from primary to specialty care. Our objectives were to calculate the wait times from when a referral is made by a family physician (FP) to when a patient sees a specialist physician and examine patient and provider factors related to these wait times. METHODS: Our study used the Electronic Medical Record Administrative data Linked Database (EMRALD) which is a linkage of FP electronic medical record (EMR) data to the Ontario, Canada administrative data. The EMR referral date was linked to the administrative physician claims date to calculate the wait times. Patient age, sex, socioeconomic status, comorbidity and FP continuity of care and physician age, sex, practice location, practice size and participation in a primary care delivery model were examined with respect to wait times. RESULTS: The median waits from medical specialists ranged from 39 to 76 days and for surgical specialists from 33 days to 66 days. With a few exceptions, patient factors were not associated with wait times from primary care to specialty care. Similarly physician factors were not consistently associated with wait times, except for FP practice location and size. CONCLUSIONS: Actual wait times for a referral from a FP to seeing a specialist physician are longer than those reported by physician surveys. Wait times from primary to specialty care need to be included in the calculation of surgical and diagnostic wait time benchmarks in Canada.

Factors associated with plans for early retirement among Ontario family physicians during the COVID-19 pandemic: a cross-sectional study.

BACKGROUND: Higher numbers of family physicians (FPs) stopped practicing or retired during the COVID-19 pandemic, worsening the family doctor shortage in Canada. Our study objective was to determine which factors were associated with FPs' plans to retire earlier during the COVID-19 pandemic. METHODS: We administered two cross-sectional online surveys to Ontario FPs asking whether they were "planning to retire earlier" as a result of the pandemic during the first and third COVID-19 pandemic waves (Apr-Jun 2020 and Mar-Jul 2021). We used logistic regression to determine which factors were associated with early retirement planning, adjusting for age. RESULTS: The age-adjusted proportion of FP respondents planning to retire earlier was 8.2% (of 393) in the first-wave and 20.5% (of 454) in the third-wave. Planning for earlier retirement during the third-wave was associated with age over 50 years (50-59 years odds ratio (OR) 5.37 (95% confidence interval (CI):2.33-12.31), 60 years and above OR 4.18 (95% CI: 1.90-10.23)), having difficulty handling increased non-clinical responsibilities (OR 2.95 (95% CI: 1.79-4.94)), feeling unsupported to work virtually (OR 1.96 (95% CI: 1.19-3.23)) or in-person (OR 2.70 (95% CI: 1.67-4.55)), feeling unable to provide good care (OR 1.82 (95% CI: 1.10-3.03)), feeling work was not valued (OR 1.92 (95% CI: 1.15-3.23)), feeling frightened of dealing with COVID-19 (OR 2.01 (95% CI: 1.19-3.38)), caring for an elderly relative (OR 2.36 (95% CI: 1.69-3.97)), having difficulty obtaining personal protective equipment (OR 2.00 (95% CI: 1.16-3.43)) or difficulty implementing infection control practices in clinic (OR 2.10 (95% CI: 1.12-3.89)). CONCLUSIONS: Over 20% of Ontario FP respondents were considering retiring earlier by the third-wave of the COVID-19 pandemic. Supporting FPs in their clinical and non-clinical roles, such that they feel able to provide good care and that their work is valued, reducing non-clinical (e.g., administrative) responsibilities, dealing with pandemic-related fears, and supporting infection control practices and personal protective equipment acquisition in clinic, particularly in those aged 50 years or older may help increase family physician retention during future pandemics.

Trends in attachment to a primary care provider in Ontario, 2008-2018: an interrupted time-series analysis.

BACKGROUND: Attachment to a regular primary care provider is associated with better health outcomes, but 15% of people in Canada lack a consistent source of ongoing primary care. We sought to evaluate trends in attachment to a primary care provider in Ontario in 2008-2018, through an equity lens and in relation to policy changes in implementation of payment reforms and team-based care. METHODS: Using linked, population-level administrative data, we conducted a retrospective observational study to calculate rates of patients attached to a regular primary care provider from Apr. 1, 2008, to Mar. 31, 2019. We evaluated the association of patient characteristics and attachment in 2018 using sex-stratified, adjusted, multivariable logistic regression models and used segmented piecewise regression to evaluate changing trends before and after implementation of a policy that restricted physician entry to alternate models. RESULTS: Attachment increased from 80.5% (n = 10 352 385) in 2008 to 88.9% of the population (n = 12 537 172) in 2018, but was lower among people with low comorbidity, high residential instability, material deprivation, rural residence and recent immigrants. Inequities narrowed for recent immigrants, males and people with lower incomes over the study period, but disparities persisted for these groups. Attachment grew by 1.47% annually until 2014 (p < 0.0001), but was stagnant thereafter (annual percent change of 0.13, p = 0.16). INTERPRETATION: Lack of sustained progress in attachment followed reduced levels of physician entry to alternate funding models. Although disparities narrowed for many groups over the study period, persistent gaps remained for immigrants and people with lower incomes; targeted interventions and policy changes are needed to address these persistent gaps.

Examining the immediate and ongoing impact of the COVID-19 pandemic on population-based estimates of dementia: a population-based time series analysis in Ontario, Canada.

OBJECTIVES: Population-based chronic disease surveillance systems were likely disrupted by the COVID-19 pandemic. The objective of this study was to examine the immediate and ongoing impact of the COVID-19 pandemic on the claims-based incidence of dementia. METHODS: We conducted a population-based time series analysis from January 2015 to December 2021 in Ontario, Canada. We calculated the monthly claims-based incidence of dementia using a validated case ascertainment algorithm drawing from routinely collected health administrative data. We used autoregressive linear models to compare the claims-based incidence of dementia during the COVID-19 period (2020-2021) to the expected incidence had the pandemic not occurred, controlling for seasonality and secular trends. We examined incidence by source of ascertainment and across strata of sex, age, community size and number of health conditions. RESULTS: The monthly claims-based incidence of dementia dropped from a 2019 average of 11.9 per 10 000 to 8.5 per 10 000 in April 2020 (32.6% lower than expected). The incidence returned to expected levels by late 2020. Across the COVID-19 period there were a cumulative 2990 (95% CI 2109 to 3704) fewer cases of dementia observed than expected, equivalent to 1.05 months of new cases. Despite the overall recovery, ascertainment rates continued to be lower than expected among individuals aged 65-74 years and in large urban areas. Ascertainment rates were higher than expected in hospital and among individuals with 11 or more health conditions. CONCLUSIONS: The claims-based incidence of dementia recovered to expected levels by late 2020, suggesting minimal long-term changes to population-based dementia surveillance. Continued monitoring of claims-based incidence is necessary to determine whether the lower than expected incidence among individuals aged 65-74 and in large urban areas, and higher than expected incidence among individuals with 11 or more health conditions, is transitory.

Factors associated with recurrent emergency department visits among people living with dementia: A retrospective cohort study.

BACKGROUND: Research on factors associated with recurrent emergency department (ED) visits and their implications for improving dementia care is lacking. The objective of this study was to examine associations between the individual characteristics of older adults living with dementia and recurrent ED visits. METHODS: We used health administrative databases to conduct a population-based retrospective cohort study among older adults with dementia in Ontario, Canada. We included community-dwelling adults 66 years and older who visited the ED between April 1, 2010, and March 31, 2019 and were discharged home. We recorded all ED visits within one year after the baseline visit. We used recurrent event Cox regression to examine associations between repeat ED visits and individual clinical, demographic, and health service use characteristics. We fit conditional inference trees to identify the most important factors and define subgroups of varying risk. RESULTS: Our cohort included 175,863 older adults with dementia. ED use in the year prior to baseline had the strongest association with recurrent visits (3+ vs.0 adjusted hazard ratio (aHR): 1.92 (1.89, 1.94), 2vs.0 aHR: 1.45 (1.43, 1.47), 1vs.0 aHR: 1.23 (1.21, 1.24)). The conditional inference tree utilized history of ED visits and comorbidity count to define 12 subgroups with ED revisit rates ranging from 0.79 to 7.27 per year. Older adults in higher risk groups were more likely to live in rural and low-income areas and had higher use of anticonvulsants, antipsychotics, and benzodiazepines. CONCLUSIONS: History of ED visits may be a useful measure to identify older adults with dementia who would benefit from additional interventions and supports. A substantial proportion of older adults with dementia have a pattern of recurrent visits and may benefit from dementia-friendly and geriatric-focused EDs. Collaborative medication review in the ED and closer follow-up and engagement with community supports could improve patient care and experience.

Predicting the target specialty of referral notes to estimate per-specialty wait times with machine learning.

BACKGROUND: Currently, in Canada, existing health administrative data and hospital-inputted portal systems are used to measure the wait times to receiving a procedure or therapy after a specialist visit. However, due to missing and inconsistent labelling, estimating the wait time prior to seeing a specialist physician requires costly manual coding to label primary care referral notes. METHODS: In this work, we represent the notes using word-count vectors and develop a logistic regression machine learning model to automatically label the target specialist physician from a primary care referral note. These labels are not available in the administrative system. We also study the effects of note length (measured in number of tokens) and dataset size (measured in number of notes per target specialty) on model performance to help other researchers determine if such an approach may be feasible for them. We then calculate the wait time by linking the specialist type from a primary care referral to a full consultation visit held in Ontario, Canada health administrative data. RESULTS: For many target specialties, we can reliably (F1Score ≥ 0.70) predict the target specialist type. Doing so enables the automated measurement of wait time from family physician referral to specialist physician visit. Of the six specialties with wait times estimated using both 2008 and 2015 data, two had a substantial increase (defined as a change such that the original value lay outside the 95% confidence interval) in both median and 75th percentile wait times, one had a substantial decrease in both median and 75th percentile wait times, and three has non-substantial increases. CONCLUSIONS: Automating these wait time measurements, which had previously been too time consuming and costly to evaluate at a population level, can be useful for health policy researchers studying the effects of policy decisions on patient access to care.