Administrative Data In Ontario Research Articles

Virtual Versus In-Person Follow-up After a Psychiatric Emergency Visit: A Population-Based Cohort Study: Suivi virtuel opposé à en personne après une visite à l'urgence psychiatrique : une étude de cohorte dans la population.

With increased utilization of virtual care in mental health, examining its appropriateness in various clinical scenarios is warranted. This study aimed to compare the risk of adverse psychiatric outcomes following virtual versus in-person mental health follow-up care after a psychiatric emergency department (ED) visit. Using population-based health administrative data in Ontario (2021), we identified 28,232 adults discharged from a psychiatric ED visit who had a follow-up mental health visit within 14 days postdischarge. We compared those whose first follow-up visit was virtual (telephone or video) versus in-person on their risk for experiencing either a repeat psychiatric ED visit, psychiatric hospitalization, intentional self-injury, or suicide in the 15-90 days post-ED visit. Cox proportional hazard models generated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs), adjusted for age, income quintile, psychiatric hospitalization, and intentional self-injury in the 2 years prior to ED visit. We stratified by sex and diagnosis at index ED visits based on the International Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) coding. About 65% (n = 18,354) of first follow-up visits were virtual, while 35% (n = 9,878) were in-person. About 13.9% and 14.6% of the virtual and in-person groups, respectively, experienced the composite outcome, corresponding to incidence rates of 60.9 versus 74.2 per 1000 person-years (aHR 0.95, 95% CI 0.89 to 1.01). Results were similar for individual elements of the composite outcome, when stratifying by sex and index psychiatric diagnosis, when varying exposure (7 days) and outcome periods (60 and 30 days), and comparing "only" virtual versus "any" in-person follow-up during the 14-day follow-up. These results support virtual care as a modality to increase access to follow-up after an acute care psychiatric encounter across a wide range of diagnoses. Prospective trials to discern whether this is due to the comparable efficacy of virtual and in-person care, or due solely to appropriate patient selection may be warranted.

Enhancing population-level research among people who inject drugs: a validation and retrospective cohort study using health administrative data in Ontario, Canada

ObjectiveHealth administrative data can support population-level research among people who inject drugs (PWID), however these data sources remain underutilized due to the difficulty in identifying drug use in routinely collected data. We validated case-ascertainment algorithms to identify PWID and tested their application in a hepatitis C (HCV) cohort in Ontario, Canada. ApproachWe conducted a validation study using reference standard cohorts of PWID recruited via community-based studies and population controls linked to health administrative data in Ontario, Canada (1992-2020). Tested case-ascertainment algorithms included combinations of hospitalizations/emergency department (ED) visits for drug use/poisoning, physician visits for drug use, opioid agonist treatment (OAT), or injecting-related infections. Sensitivity and specificity were estimated for lifetime history and recent injecting (past 1-5 years). We applied a high-performing algorithm among all Ontarians with laboratory-confirmed HCV between 1999-2018, to identify a sub-cohort of PWID with HCV. ResultsAn algorithm including ≥1 hospitalization/ED visit or ≥1 physician visit for drug use or ≥1 OAT record had high accuracy for identifying IDU history (91.6% sensitivity, 94.2% specificity) and recent IDU (using 3 years lookback: 80.4% sensitivity, 99% specificity). When applied to a provincial cohort of 112,947 Ontarians diagnosed with HCV, this algorithm estimated 46% (N=52,248) had a history of IDU, of whom 52% (N=27,246) had an indication of recent IDU (within the past 3 years). ConclusionThe methods developed in this study can enhance the capacity of population-level health research among people who inject drugs and support applied public health interventions towards hepatitis C elimination.

Identifying homelessness using health administrative data in Ontario, Canada: how coding policies impact case validity

Conducting longitudinal research about the health of people experiencing homelessness poses unique challenges. In Canada, we previously demonstrated that identification through health administrative databases permits population-level studies, despite relatively low sensitivity. Since then, coding of homelessness became mandatory in hospitals nationally. As a result, case validity since 2018 is unknown. We re-validated case definitions for identifying homelessness in health administrative databases between 2018 and 2022 against the longitudinally collected housing history of a representative sample of people experiencing homelessness (n=640) and randomly selected, housed people (n=128,000) in Toronto, Canada. We calculated sensitivity, specificity, positive and negative predictive values, and positive likelihood ratios for 42 unique case definitions. We compared the resulting true positives against false positives and false negatives to identify potential causes of misclassification. The optimal case (best sensitivity/scalability beyond Ontario) definition included any indicator during a hospital-based encounter within 180 days of a period of homelessness (sensitivity=52.9%; specificity=99.5%). Among periods of homelessness with ≥1 hospital-based encounter, the optimal case definition had good sensitivity (75.1%) with minimal reduction in specificity (98.5%). Review of false positives suggests homeless status is sometimes improperly carried forward in healthcare encounters occurring after transitioning out of homelessness. Case definitions to identify homelessness using health administrative data exhibit moderate sensitivity and excellent specificity, with two-fold increases in sensitivity since the implementation of mandatory coding in Canada. Mandatory collection of social determinants of health information within administrative data present invaluable opportunities for advancing research on the health and healthcare needs of people experiencing homelessness.

Mental health service use among mothers and other birthing parents during the COVID-19 pandemic in Ontario, Canada

BackgroundParents have reported increased symptoms of depression and anxiety during the COVID-19 pandemic. This study evaluated changes in mental health and addiction (MHA)-related health service use among mothers and other birthing parents during the COVID-19 pandemic. MethodsWe conducted a repeated cross-sectional study using health administrative data in Ontario, Canada. The population included all mothers and birthing parents (≥1 child aged 1–18, no children <1 to exclude postpartum parents) between January 2016 and December 2021. We compared rates of MHA-related outpatient physician visits, hospitalizations, and emergency department (ED) visits during COVID-19 (March 2020–December 2021) to pre-COVID-19 (pre-March 2020). ResultsMHA-related outpatient visit rates increased by 17 % (rate ratio (RR) 1.17, 95 % CI 1.16–1.18) during COVID-19. Monthly utilization rates remained higher than expected across the COVID-19 period. MHA-related ED visit rates remained lower than expected during COVID-19, while MHA-related hospitalization rates returned to expected levels by August 2020. The largest relative increases in MHA-related outpatient visits during COVID-19 were in mothers and other birthing parents living in higher income (RR 1.20, 95 % CI 1.19–1.22) or urban areas (RR 1.20, 95 % CI 1.18–1.21), with children aged 1–3 years (RR 1.23, 95 % CI 1.20–1.25) and with no history of MHA-related health service use (RR 1.20, 95 % CI 1.19–1.21). LimitationsThis study only captured physician-delivered MHA-related health service use. ConclusionsThe COVID-19 pandemic was associated with an increase in MHA-related outpatient visits among mothers and other birthing parents. These findings point to the need for improvements in mental health service access.

Postdischarge opioid use after lumbar spine surgery among older adults in Ontario: a population-based cohort study.

Prescription opioid use places a considerable economic burden on health care systems. Older patients undergoing surgical procedures for painful conditions commonly receive opioids pre- and postoperatively, and are susceptible to adverse reactions. This study explores predictors of prolonged postoperative opioid use among older patients after lumbar spine surgery and the consequences in terms of health care utilization and costs. We conducted a retrospective population-based cohort study using Ontario administrative data from older adults undergoing spine surgery between 2006 and 2017. Data were analyzed from 90 days preoperatively to 1 year after hospital discharge, with last postoperative opioid prescriptions stratified into 90-day increments. We used multivariable ordinal logistic regression to identify predictors of long-term opioid use and generalized linear modelling to examine resource utilization and health care costs (2021 Canadian dollars). Of 15 109 patients included, 40.8% received preoperative opioid prescriptions. Preoperative opioid use strongly predicted prolonged postoperative use (odds ratio [OR] 4.47, 95% confidence interval [CI] 4.16-4.79), with 48.3% of patients who received preoperative opioids continuing to use opioids for longer than 9 months, relative to 12.7% of those without preoperative use. Several other risk factors for prolonged use were identified. Patients receiving long-term postoperative opioids incurred greater health care costs relative to those with opioids prescribed for fewer than 90 days (OR 1.49, 95% CI 1.44-1.54). Among older adults undergoing spine surgery, preoperative opioid use was a strong predictor of prolonged postoperative use, which was associated with increased health care costs. These results form an important baseline for future studies evaluating strategies to reduce opioid use targeting older surgical populations.

Identification of homelessness using health administrative data in Ontario, Canada following a national coding mandate: a validation study

ObjectivesConducting longitudinal health research about people experiencing homelessness poses unique challenges. Identification through administrative data permits large, cost-effective studies; however, case validity in Ontario is unknown after a 2018 Canada-wide policy change mandating homelessness coding in hospital databases. We validated case definitions for identifying homelessness using Ontario health administrative databases after introduction of this coding mandate. Study Design and SettingWe assessed 42 case definitions in a representative sample of people experiencing homelessness in Toronto (n = 640) from whom longitudinal housing history (ranging from 2018 to 2022) was obtained, and a randomly selected sample of presumably housed people (n = 128,000) in Toronto. We evaluated sensitivity, specificity, positive and negative predictive values, and positive likelihood ratios to select an optimal definition, and compared the resulting true positives against false positives and false negatives to identify potential causes of misclassification. ResultsThe optimal case definition included any homelessness indicator during a hospital-based encounter within 180 days of a period of homelessness (sensitivity = 52.9%; specificity = 99.5%). For periods of homelessness with ≥1 hospital-based healthcare encounter, the optimal case definition had greatly improved sensitivity (75.1%) while retaining excellent specificity (98.5%). Review of false positives suggested that homeless status is sometimes erroneously carried forward in healthcare databases after an individual transitioned out of homelessness. ConclusionCase definitions to identify homelessness using Ontario health administrative data exhibit moderate to good sensitivity and excellent specificity. Sensitivity has more than doubled since the implementation of a national coding mandate. Mandatory collection and reporting of homelessness information within administrative data present invaluable opportunities for advancing research on the health and healthcare needs of people experiencing homelessness.

Trends and outcomes in patients receiving neoadjuvant chemotherapy for breast cancer in Ontario: A population-based study.

e12664 Background: Modern neoadjuvant chemotherapy (NAC) regimens in breast cancer offer higher rates of pathologic complete response, an ability to guide further adjuvant treatment, and may de-escalate surgery. However, the utilization of NAC has been heterogeneous in Ontario. This study aimed to describe trends in NAC use in Ontario, report survival outcomes, and explore factors associated with overall survival in these patients. Methods: This was a population-based cohort study using linked health administrative data in Ontario, Canada. From the Ontario Cancer Registry, we identified women ≥18 years who underwent neoadjuvant chemotherapy followed by surgery for operable (cT1N1, cT2-3N0, or cT2-3N1) breast cancer between 2012 and 2020. Patients were divided by receptor subtype (triple negative breast cancer [TNBC], ER+/HER2-, ER+/HER2+, ER-/HER2+) and characteristics were compared using standardized mean differences (SMDs). Five-year overall survival (OS) and breast cancer-specific survival (BCSS) were determined and reported for each subtype. Associations with OS and BCSS were calculated for patient and disease characteristics using univariate and multivariable Cox proportional hazards models and Fine and Gray models, respectively. Results: 3,804 women underwent NAC for cT1N1, cT2-3N0, or cT2-3N1 breast cancer in Ontario between 2012 and 2020. The largest contributing subtype was ER+/HER2- patients (39.3%) followed by those with HER2+ disease (ER-/HER2+ 13.8%, ER+/HER2+ 23.4%), and TNBC (23.5%). The median age was 50 years (IQR 42-59 years). Most patients were clinically node-positive (2,736; 71.9%), and underwent mastectomy (2,397; 63.0%). There was a significant increase in the number of patients receiving NAC in Ontario, from 217 in 2012 to 667 in 2019 ( p&lt;0.001), with a greater increase among patients with TNBC or HER2+ disease. Compared to those with ER+/HER2- disease, TNBC patients were treated for smaller tumours (28.6% T3 vs. 39.8%; SMD = 0.24), and were more likely to be node-negative (39.1% N0 vs. 22.1%; SMD = 0.38). Similar trends for nodal status were found for patients with ER-/HER2+ (26.7% N0) and ER+/HER2+ cancer (27.9% N0). 5-year OS for the entire cohort was 88.1% (95% CI 87.1 – 89.2%). Survival was highest for ER+/HER2+ patients (94.2%, 95% CI 92.6 – 95.8%) and lowest for TNBC patients (80.1%, 95% CI 77.5 – 82.8%). Similar patterns were seen for BCSS. Factors associated with OS in a multivariable model included older age (increase in 5 years HR 1.1, 95% CI 1.07 – 1.14), N1 status (HR 1.99, 95% CI 1.61 – 2.47), larger tumour size (T3 HR 1.83, 95% CI 1.34 – 2.5), mastectomy (HR 1.45, 95% CI 1.2 – 1.75), and TNBC (versus ER+/HER2- HR 1.9, 95% CI 1.56 – 2.32). Conclusions: The use of NAC has increased in Ontario, particularly among TNBC and HER2+ patients. Women with TNBC have worse outcomes compared to those with ER+/HER2- disease, despite being treated for less advanced disease.

A population-based analysis of the management of symptoms of depression among patients with stage IV non-small cell lung cancer (NSCLC) in Ontario, Canada.

Patients with lung cancer can experience significant psychological morbidities including depression. We characterize patterns and factors associated with interventions for symptoms of depression in stage IV non-small cell lung cancer (NSCLC). We conducted a population-based cohort study using health services administrative data in Ontario, Canada of stage IV NSCLC diagnosed from January 2007 to September 2018. A positive symptom of depression score was defined by reporting at least one ESAS (Edmonton Symptom Assessment System) depression score ≥ 2 following diagnosis until the end of follow-up (September 2019). Patient factors included age, sex, comorbidity burden, rurality of residence, and neighbourhood income quintile. Interventions included psychiatry assessment, psychology referral, social work referral and anti-depressant medical therapy (for patients ≥ 65years with universal drug coverage). Multivariable modified Poisson regression models were used to examine the association between patient factors and intervention use for patients who reported symptoms of depression. In the cohort of 13,159 patients with stage IV NSCLC lung cancer, symptoms of depression were prevalent (71.4%, n = 9,397). Patients who reported symptoms of depression were more likely to receive psychiatry assessment/psychology referral (7.8% vs 3.5%; SD [standardized difference] 0.19), social work referral (17.4% vs 11.9%; SD 0.16) and anti-depressant prescriptions (23.8% vs 13.8%; SD 0.26) when compared to patients who did not report symptoms of depression respectively. In multivariable analyses, older patients were less likely to receive any intervention. Females were more likely to obtain a psychiatry assessment/psychology referral or social work referral. In addition, patients from non-major urban or rural residences were less likely to receive psychiatry assessment/psychology referral or social work referral, however patients from rural residences were more likely to be prescribed anti-depressants. There is high prevalence of symptoms of depression in stage IV NSCLC. We identify patient populations, including older patients and rural patients, who are less likely to receive interventions that will help identifying and screening for symptoms of depression.

D3 Interim results for Myasthenia Gravis-resource utilization, epidemiology, survival &amp; treatment patterns (MG-REST) study in Ontario, Canada

Background: Reliable real-world data on the burden of MG is needed to inform Canadian clinical and policy decisions in the era of new MG therapeutics, including FcRn inhibitors. Given the lack of recent Canadian data on MG disease burden, the MG-REST Study aims to estimate the clinical burden of MG in Ontario. Methods: Ontario administrative data from ICES were utilized for a retrospective population-based cohort study of adults with MG identified through a validated algorithm (April 2013-March 2019) and followed for up to seven years (March 2020) to determine myasthenic crisis characteristics and overall survival (OS). Results: The MG cohort (n=2,601) had an average age of 65.7 years and 53.3% were males. Incidence of first myasthenic crisis was 9%, with 87% of events occurring at/after diagnosis. MG OS was 89%, 85% and 75% at 1-year, 2-years and 5-years, respectively, while OS after first crisis was 60%, 52%, and 39% for the same years. Conclusions: Despite the availability of conventional therapies throughout the study, MG crisis remains a serious, common complication of MG, with decreased survival at 1-year post-crisis (29% difference versus 1-year OS following MG diagnosis). Study highlights MG burden and unmet need for new effective therapies for MG treatment.

Association between opioid use disorder and palliative care: a cohort study using linked health administrative data in Ontario, Canada.

People with opioid use disorder (OUD) are at risk of premature death and can benefit from palliative care. We sought to compare palliative care provision for decedents with and without OUD. We conducted a cohort study using health administrative databases in Ontario, Canada, to identify people who died between July 1, 2015, and Dec. 31, 2021. The exposure was OUD, defined as having emergency department visits, hospital admissions, or pharmacologic treatments suggestive of OUD within 3 years of death. Our primary outcome was receipt of 1 or more palliative care services during the last 90 days before death. Secondary outcomes included setting, initiation, and intensity of palliative care. We conducted a secondary analysis excluding sudden deaths (e.g., opioid toxicity, injury). Of 679 840 decedents, 11 200 (1.6%) had OUD. Compared with people without OUD, those with OUD died at a younger age and were more likely to live in neighbourhoods with high marginalization indices. We found people with OUD were less likely to receive palliative care at the end of their lives (adjusted relative risk [RR] 0.84, 95% confidence interval [CI] 0.82-0.86), but this difference did not exist after excluding people who died suddenly (adjusted RR 0.99, 95% CI 0.96-1.01). People with OUD were less likely to receive palliative care in clinics and their homes regardless of cause of death. Opioid use disorder can be a chronic, life-limiting illness, and people with OUD are less likely to receive palliative care in communities during the 90 days before death. Health care providers should receive training in palliative care and addiction medicine to support people with OUD.

Validation of case-ascertainment algorithms using health administrative data to identify people who inject drugs in Ontario, Canada

ObjectivesHealth administrative data can be used to improve the health of people who inject drugs by informing public health surveillance and program planning, monitoring, and evaluation. However, methodological gaps in the use of these data persist due to challenges in accurately identifying injection drug use (IDU) at the population level. In this study, we validated case-ascertainment algorithms for identifying people who inject drugs using health administrative data in Ontario, Canada. Study Design and SettingData from cohorts of people with recent (past 12 months) IDU, including those participating in community-based research studies or seeking drug treatment, were linked to health administrative data in Ontario from 1992 to 2020. We assessed the validity of algorithms to identify IDU over varying look-back periods (ie, all years of data [1992 onwards] or within the past 1–5 years), including inpatient and outpatient physician billing claims for drug use, emergency department (ED) visits or hospitalizations for drug use or injection-related infections, and opioid agonist treatment (OAT). ResultsAlgorithms were validated using data from 15,241 people with recent IDU (918 in community cohorts and 14,323 seeking drug treatment). An algorithm consisting of ≥1 physician visit, ED visit, or hospitalization for drug use, or OAT record could effectively identify IDU history (91.6% sensitivity and 94.2% specificity) and recent IDU (using 3-year look back: 80.4% sensitivity, 99% specificity) among community cohorts. Algorithms were generally more sensitive among people who inject drugs seeking drug treatment. ConclusionValidated algorithms using health administrative data performed well in identifying people who inject drugs. Despite their high sensitivity and specificity, the positive predictive value of these algorithms will vary depending on the underlying prevalence of IDU in the population in which they are applied.

Changes in End-of-Life Symptom Management Prescribing among Long-Term Care Residents during COVID-19

ObjectiveTo examine changes in the prescribing of end-of-life symptom management medications in long-term care (LTC) homes during the COVID-19 pandemic. DesignRetrospective cohort study using routinely collected health administrative data in Ontario, Canada. Setting and ParticipantsWe included all individuals who died in LTC homes between January 1, 2017, and March 31, 2021. We separated the study into 2 periods: before COVID-19 (January 1, 2017, to March 17, 2020) and during COVID-19 (March 18, 2020, to March 31, 2021). MethodsFor each LTC home, we measured the percentage of residents who died before and during COVID-19 who had a subcutaneous symptom management medication prescription in their last 14 days of life. We grouped LTC homes into quintiles based on their mean prescribing rates before COVID-19, and examined changes in prescribing during COVID-19 and COVID-19 outcomes across quintiles. ResultsWe captured 75,438 LTC residents who died in Ontario's 626 LTC homes during the entire study period, with 19,522 (25.9%) dying during COVID-19. The mean prescribing rate during COVID-19 ranged from 46.9% to 79.4% between the lowest and highest prescribing quintiles. During COVID-19, the mean prescribing rate in the lowest prescribing quintile increased by 9.6% compared to before COVID-19. Compared to LTC homes in the highest prescribing quintile, homes in the lowest prescribing quintile experienced the highest proportion of COVID-19 outbreaks (73.4% vs 50.0%), the largest mean outbreak intensity (0.27 vs 0.09 cases/bed), the highest mean total days with a COVID-19 outbreak (72.7 vs 24.2 days), and the greatest proportion of decedents who were transferred and died outside of LTC (22.1% vs 8.6%). Conclusions and ImplicationsLTC homes in Ontario had wide variations in the prescribing rates of end-of-life symptom management medications before and during COVID-19. Homes in the lower prescribing quintiles had more COVID-19 cases per bed and days spent in an outbreak.

Association of virtual end-of-life care with healthcare outcomes before and during the COVID-19 pandemic: A population-based study.

The use of virtual care for people at the end-of-life significantly increased during the COVID-19 pandemic, but its association with acute healthcare use and location of death is unknown. The objective of this study was to measure the association between the use of virtual end-of-life care with acute healthcare use and an out-of-hospital death before vs. after the introduction of specialized fee codes that enabled broader delivery of virtual care during the COVID-19 pandemic. This was a population-based cohort study of 323,995 adults in their last 90 days of life between January 25, 2018 and December 31, 2021 using health administrative data in Ontario, Canada. Primary outcomes were acute healthcare use (emergency department, hospitalization) and location of death (in or out-of-hospital). Prior to March 14, 2020, 13,974 (8%) people received at least 1 virtual end-of-life care visit, which was associated with a 16% higher rate of emergency department use (adjusted Rate Ratio [aRR] 1.16, 95%CI 1.12 to 1.20), a 17% higher rate of hospitalization (aRR 1.17, 95%CI 1.15 to 1.20), and a 34% higher risk of an out-of-hospital death (aRR 1.34, 95%CI 1.31 to 1.37) compared to people who did not receive virtual end-of-life care. After March 14, 2020, 104,165 (71%) people received at least 1 virtual end-of-life care visit, which was associated with a 58% higher rate of an emergency department visit (aRR 1.58, 95%CI 1.54 to 1.62), a 45% higher rate of hospitalization (aRR 1.45, 95%CI 1.42 to 1.47), and a 65% higher risk of an out-of-hospital death (aRR 1.65, 95%CI 1.61 to 1.69) compared to people who did not receive virtual end-of-life care. The use of virtual end-of-life care was associated with higher acute healthcare use in the last 90 days of life and a higher likelihood of dying out-of-hospital, and these rates increased during the pandemic.

Machine Learning to Allocate Palliative Care Consultations During Cancer Treatment.

For patients with advanced cancer, early consultations with palliative care (PC) specialists reduce costs, improve quality of life, and prolong survival. However, capacity limitations prevent all patients from receiving PC shortly after diagnosis. We evaluated whether a prognostic machine learning system could promote early PC, given existing capacity. Using population-level administrative data in Ontario, Canada, we assembled a cohort of patients with incurable cancer who received palliative-intent systemic therapy between July 1, 2014, and December 30, 2019. We developed a machine learning system that predicted death within 1 year of each treatment using demographics, cancer characteristics, treatments, symptoms, laboratory values, and history of acute care admissions. We trained the system in patients who started treatment before July 1, 2017, and evaluated the potential impact of the system on PC in subsequent patients. Among 560,210 treatments received by 54,628 patients, death occurred within 1 year of 45.2% of treatments. The machine learning system recommended the same number of PC consultations observed with usual care at the 60.0% 1-year risk of death, with a first-alarm positive predictive value of 69.7% and an outcome-level sensitivity of 74.9%. Compared with usual care, system-guided care could increase early PC by 8.5% overall (95% CI, 7.5 to 9.5; P < .001) and by 15.3% (95% CI, 13.9 to 16.6; P < .001) among patients who live 6 months beyond their first treatment, without requiring more PC consultations in total or substantially increasing PC among patients with a prognosis exceeding 2 years. Prognostic machine learning systems could increase early PC despite existing resource constraints. These results demonstrate an urgent need to deploy and evaluate prognostic systems in real-time clinical practice to increase access to early PC.

A Frailty Index to Predict Mortality, Resource Utilization and Costs in Patients Undergoing Coronary Artery Bypass Graft Surgery in Ontario

BackgroundPeople living with frailty are vulnerable to poor outcomes and incur higher health care costs after coronary artery bypass graft (CABG) surgery. Frailty-defining instruments for population-level research in the CABG setting have not been established. The objectives of the study were to develop a preoperative frailty index for CABG (pFI-C) surgery using Ontario administrative data; assess pFI-C suitability in predicting clinical and economic outcomes; and compare pFI-C predictive capabilities with other indices. MethodsA retrospective cohort study was conducted using health administrative data of 50,682 CABG patients. The pFI-C comprised 27 frailty-related health deficits. Associations between index scores and mortality, resource use and health care costs (2022 Canadian dollars [CAD]) were assessed using multivariable regression models. Capabilities of the pFI-C in predicting mortality were evaluated using concordance statistics; goodness of fit of the models was assessed using Akakie Information Criterion. ResultsAs assessed by the pFI-C, 22% of the cohort lived with frailty. The pFI-C score was strongly associated with mortality per 10% increase (odds ratio [OR], 3.04; 95% confidence interval [CI], [2.83,3.27]), and was significantly associated with resource utilization and costs. The predictive performances of the pFI-C, Charlson, and Elixhauser indices and Johns Hopkins Aggregated Diagnostic Groups were similar, and mortality models containing the pFI-C had a concordance (C)-statistic of 0.784. Cost models containing the pFI-C showed the best fit. ConclusionsThe pFI-C is predictive of mortality and associated with resource utilization and costs during the year following CABG. This index could aid in identifying a subgroup of high-risk CABG patients who could benefit from targeted perioperative health care interventions.

Trajectories of P2Y12 inhibitor adherence in patients with acute coronary syndromes.

P2Y12 inhibitors (P2Y12i) reduce cardiac events after acute coronary syndromes (ACS). However, suboptimal P2Y12i adherence persists. We aimed to examine P2Y12i non-adherence using group-based trajectory methods and to identify adherence predictors. We conducted a population-based, retrospective cohort study using administrative data in Ontario, Canada of patients ≥65 years admitted for ACS between April 2014 and March 2018 with a P2Y12i dispensed within 7 days of discharge. We used group-based trajectory models to characterize longitudinal 1-year adherence patterns. Predictors associated with each adherence trajectory were identified by multinomial logistic regression. We included 11 917 patients using clopidogrel and 9763 using ticagrelor, aged [mean ± SD]: 77.33 ± 8.31/73.59 ± 6.79 years; men: 56.2%/65.4%, respectively. We identified 3 longitudinal adherence trajectories, that differed by agent: 75% of clopidogrel and 68% of ticagrelor patients showed a consistently adherent trajectory, while 13%/17% were gradually, and 12%/15% were rapidly non-adherent, respectively (p < 0.001). Differing baseline characteristics in each cohort were associated with observed adherence trajectories. Concomitant atrial fibrillation and prior bleeding history were associated with non-adherence among clopidogrel users. Among ticagrelor users, women and older persons were more likely to be rapidly non-adherent, adherence declining steeply starting 1 month post-ACS. We identified distinct adherence trajectories for clopidogrel and ticagrelor post-ACS, with 3 out of 4 clopidogrel patients but only 2 out of 3 ticagrelor patients in the consistently adherent trajectory. Intensive interventions targeted to the period of steep adherence decline post-ACS, particularly for women and older persons initiating ticagrelor, and patients with atrial fibrillation on clopidogrel should be considered and investigated further.

Defining major surgical complications using administrative data in Ontario: a validation study.

Although surgical complications are often included as an outcome of surgical research conducted using administrative data, little validation work has been performed. We sought to evaluate the diagnostic performance of an algorithm designed to capture major surgical complications using health administrative data. This retrospective study included patients who underwent high-risk elective general surgery at a single institution in Ontario, Canada, from Sept. 1, 2016, to Sept. 1, 2017. Patients were identified for inclusion using the local operative database. Medical records were reviewed by trained clinicians to abstract postoperative complications. Data were linked to administrative data holdings, and a series of code-based algorithms were applied to capture a composite indicator of major surgical complications. We used sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy to evaluate the performance of our administrative data algorithm, as compared with data abstracted from the institutional charting system. The study included a total of 270 patients. According to the data from the chart audit, 55% of patients experienced at least 1 major surgical complication. Overall sensitivity, specificity, PPV, NPV and accuracy for the composite outcome was 72%, 80%, 82%, 70% and 76%, respectively. Diagnostic performance was poor for several of the individual complications. Our results showed that administrative data holdings can be used to capture a composite indicator of major surgical complications with adequate sensitivity and specificity. Additional work is required to identify suitable algorithms for several specific complications.

Clinical index to quantify the 1-year risk for common postpartum mental disorders at the time of delivery (PMH CAREPLAN): development and internal validation.

Common postpartum mental health (PMH) disorders such as depression and anxiety are preventable, but determining individual-level risk is difficult. To create and internally validate a clinical risk index for common PMH disorders. Using population-based health administrative data in Ontario, Canada, comprising sociodemographic, clinical and health service variables easily collectible from hospital birth records, we developed and internally validated a predictive model for common PMH disorders and converted the final model into a risk index. We developed the model in 75% of the cohort (n = 152 362), validating it in the remaining 25% (n = 75 772). The 1-year prevalence of common PMH disorders was 6.0%. Independently associated variables (forming the mnemonic PMH CAREPLAN) that made up the risk index were: (P) prenatal care provider; (M) mental health diagnosis history and medications during pregnancy; (H) psychiatric hospital admissions or emergency department visits; (C) conception type and complications; (A) apprehension of newborn by child services (newborn taken into care); (R) region of maternal origin; (E) extremes of gestational age at birth; (P) primary maternal language; (L) lactation intention; (A) maternal age; (N) number of prenatal visits. In the index (scored 0-39), 1-year common PMH disorder risk ranged from 1.5 to 40.5%. Discrimination (C-statistic) was 0.69 in development and validation samples; the 95% confidence interval of expected risk encompassed observed risk for all scores in development and validation samples, indicating adequate risk index calibration. Individual-level risk of developing a common postpartum mental health disorder can be estimated with data feasibly collectable from birth records. Next steps are external validation and evaluation of various cut-off scores for their utility in guiding postpartum individuals to interventions that reduce their risk of illness.

Virtual care use prior to emergency department admissions during a stable COVID-19 period in Ontario, Canada.

The increased use of telemedicine to provide virtual outpatient visits during the pandemic has led to concerns about potential increased emergency department (ED) admissions and outpatient service use prior to such admissions. We examined the frequency of virtual visits use prior to ED admissions and characterized the patients with prior virtual visit use and the physicians who provided these outpatient visits. We conducted a retrospective, population-based, cross-sectional analysis using linked health administrative data in Ontario, Canada to identify patients who had an ED admission between July 1 and September 30, 2021 and patients with an ED admissions during the same period in 2019. We grouped patients based on their use of outpatient services in the 7 days prior to admission and reported their sociodemographic characteristics and healthcare utilization. There were 1,080,334 ED admissions in 2021 vs. 1,113,230 in 2019. In 2021, 74% of these admissions had no prior outpatient visits (virtual or in-person) within 7 days of admission, compared to 75% in 2019. Only 3% of ED admissions had both virtual and in-person visits in the 7 days prior to ED admission. Patients with prior virtual care use were more likely to be hospitalized than those without any outpatient care (13% vs 7.7.%). The net amount of ED admissions and outpatient care prior to admission remained the same over a period of the COVID-19 pandemic when cases were relatively stable. Virtual care seemed to be able to appropriately triage patients to the ED and virtual visits replaced in-person visits ahead of ED admissions, as opposed to being additive.

The Association Between Surgical Axillary Staging, Adjuvant Treatment Use and Survival in Older Women with Early Stage Breast Cancer: A Population-Based Study.

Choosing Wisely guidelines recommend against surgical axillary staging (AS) in women ≥70 years with ER+/HER2- early stage breast cancer (BC). This study examined the impact of AS omission on survival in older patients with BC. This was a population-based cohort study using health administrative data in Ontario, Canada. We identified women aged 65-95 years who underwent surgery for Stage I/II BC between 2010 and 2016. Patients were weighted by propensity scores for receipt of AS that included patient and disease characteristics using overlap weights. Association with overall survival (OS) was calculated using weighted Cox models, and breast cancer-specific survival (BCSS) was calculated using weighted Fine and Gray models, adjusting for biomarkers and adjuvant treatments. Adjuvant treatment receipt was modelled with weighted log-binomial models. Among 17,370 older women, the 1771 (10.2%) who did not undergo AS were older, more comorbid, and less likely to undergo mastectomy. Women who did not undergo AS were less likely to receive adjuvant chemotherapy (RR 0.68, 95% CI 0.57-0.82), endocrine therapy (RR 0.85, 95% CI 0.81-0.89) or radiotherapy (RR 0.69, 95% CI 0.65-0.74). After weighting and adjustment, there was no significant difference in BCSS (sdHR 0.98, 95% CI 0.77-1.25), but women who did not undergo AS had worse OS (HR 1.14, 95% CI 1.04-1.25). The results among 6215 ER+/HER2- women ≥70 years undergoing SLNB vs no AS were similar. The omission of AS in older women with early stage BC was not associated with adverse BCSS, although OS was worse.