Latest findings highlight the continuing uncertainty over the utility of compulsory psychiatric treatment in the community.

Community treatment orders (CTOs) have been introduced in many jurisdictions with evidence of increasing use over time as well as a disproportionate use in marginalised populations. Rates of CTOs also vary widely, both internationally and within the same country, for reasons that are poorly understood. This is despite evidence for effectiveness being mixed and, as a result, there have been calls for a reappraisal of this type of legislation. In the UK, a parliamentary committee on reforming the existing Mental Health Act recommended abolishing CTOs other than for people in the criminal justice system. Two recent Australian papers based on large state-wide administrative data-sets give conflicting results and came to markedly different conclusions regarding the desirability of reducing CTO rates. The debate about the effectiveness of CTOs therefore remains unresolved. This is of concern beyond Australia, as other jurisdictions such as England, Scotland and Canada have similar clinician-initiated orders.

Ascertaining the Francophone population in Ontario: validating the language variable in health data.

BACKGROUND: Language barriers can impact health care and outcomes. Valid and reliable language data is central to studying health inequalities in linguistic minorities. In Canada, language variables are available in administrative health databases; however, the validity of these variables has not been studied. This study assessed concordance between language variables from administrative health databases and language variables from the Canadian Community Health Survey (CCHS) to identify Francophones in Ontario. METHODS: An Ontario combined sample of CCHS cycles from 2000 to 2012 (from participants who consented to link their data) was individually linked to three administrative databases (home care, long-term care [LTC], and mental health admissions). In total, 27,111 respondents had at least one encounter in one of the three databases. Language spoken at home (LOSH) and first official language spoken (FOLS) from CCHS were used as reference standards to assess their concordance with the language variables in administrative health databases, using the Cohen kappa, sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV). RESULTS: Language variables from home care and LTC databases had the highest agreement with LOSH (kappa = 0.76 [95%CI, 0.735-0.793] and 0.75 [95%CI, 0.70-0.80], respectively) and FOLS (kappa = 0.66 for both). Sensitivity was higher with LOSH as the reference standard (75.5% [95%CI, 71.6-79.0] and 74.2% [95%CI, 67.3-80.1] for home care and LTC, respectively). With FOLS as the reference standard, the language variables in both data sources had modest sensitivity (53.1% [95%CI, 49.8-56.4] and 54.1% [95%CI, 48.3-59.7] in home care and LTC, respectively) but very high specificity (99.8% [95%CI, 99.7-99.9] and 99.6% [95%CI, 99.4-99.8]) and predictive values. The language variable from mental health admissions had poor agreement with all language variables in the CCHS. CONCLUSIONS: Language variables in home care and LTC health databases were most consistent with the language often spoken at home. Studies using language variables from administrative data can use the sensitivity and specificity reported from this study to gauge the level of mis-ascertainment error and the resulting bias.

The relationship between relational continuity and family physician follow-up after an antidepressant prescription in older adults: a retrospective cohort study.

BACKGROUND: Side effects can occur within hours to days of starting antidepressant medications, whereas full therapeutic benefit for mood typically takes up to four weeks. This mismatch between time to harm and lag to benefit often leads to premature discontinuation of antidepressants, a phenomenon that can be partially reversed through early doctor-patient communication and follow-up. We investigated the relationship between relational continuity of care - the number of years family physicians have cared for older adult patients - and early follow-up care for patients prescribed antidepressants. METHODS: A retrospective cohort study was conducted on residents of Ontario, Canada aged 66 years or older who were dispensed their first antidepressant prescription through the provincial drug insurance program between April 1, 2016, and March 31, 2019. The study utilized multivariable regression to estimate the relationship between relational continuity and 30-day follow-up with the prescribing family physician. Separate estimates were generated for older adults living in urban, non-major urban, and rural communities. RESULTS: The study found a small positive relationship between relational continuity of care and follow-up care by the prescribing family physician for patients dispensed a first antidepressant prescription (RRR = 1.005; 95% CI = 1.004, 1.006). The relationship was moderated by the patients' location of dwelling, where the effect was stronger for older adults residing in non-major urban (RRR = 1.009; 95% CI = 1.007, 1.012) and rural communities (RRR = 1.006; 95% CI = 1.002, 1.011). CONCLUSIONS: Our findings do not provide strong evidence of a relationship between relational continuity of care and higher quality management of antidepressant prescriptions. However, the relationship is slightly more pronounced in rural communities where access to continuous primary care and specialized mental health services is more limited. This may support the ongoing need for the recruitment and retention of primary care providers in rural communities.

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

OBJECTIVE: To examine changes in the prescribing of end-of-life symptom management medications in long-term care (LTC) homes during the COVID-19 pandemic. DESIGN: Retrospective cohort study using routinely collected health administrative data in Ontario, Canada. SETTING AND PARTICIPANTS: We 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). METHODS: For 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. RESULTS: We 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 IMPLICATIONS: LTC 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.

Palliative End-of-Life Medication Prescribing Rates in Long-Term Care: A Retrospective Cohort Study.

BACKGROUND: Medications are often needed to manage distressing end-of-life symptoms (eg, pain, agitation). OBJECTIVES: In this study, we describe the variation in prescribing rates of symptom relief medications at the end of life among long-term care (LTC) decedents. We evaluate the extent these medications are prescribed in LTC homes and whether prescribing rates of end-of-life symptom management can be used as an indicator of quality end-of-life care. DESIGN: Retrospective cohort study using administrative health data. SETTING AND PARTICIPANTS: LTC decedents in all 626 publicly funded LTC homes in Ontario, Canada, between January 1, 2017, and March 17, 2020. METHODS: For each LTC home, we measured the percent of decedents who received 1+ prescription(s) for a subcutaneous end-of-life symptom management medication ("end-of-life medication") in their last 14 days of life. We then ranked LTC homes into quintiles based on prescribing rates. RESULTS: We identified 55,916 LTC residents who died in LTC. On average, two-thirds of decedents (64.7%) in LTC homes were prescribed at least 1 subcutaneous end-of-life medication in the last 2 weeks of life. Opioids were the most common prescribed medication (overall average prescribing rate of 62.7%). LTC homes in the lowest prescribing quintile had a mean of 37.3% of decedents prescribed an end-of-life medication, and the highest quintile mean was 82.5%. In addition, across these quintiles, the lowest prescribing quintile had a high average (30.3%) of LTC residents transferred out of LTC in the 14 days compared with the highest prescribing quintile (12.7%). CONCLUSIONS AND IMPLICATIONS: Across Ontario's LTC homes, there are large differences in prescribing rates for subcutaneous end-of-life symptom relief medications. Although future work may elucidate why the variability exists, this study provides evidence that administrative data can provide valuable insight into the systemic delivery of end-of-life care.

Real-World Cost-Consequence Analysis of an Integrated Chronic Disease Management Program in Saskatchewan, Canada.

An integrated disease management program otherwise called a clinical pathway was recently implemented in Saskatchewan, Canada for patients living with chronic obstructive pulmonary disease (COPD). This study compared the real-world costs and consequences of the COPD clinical pathway program with 2 control treatment programs. The study comprised adult COPD patients in Regina (clinical pathway group, N = 759) matched on propensity scores to 2 independent control groups of similar adults in (1) Regina (historical controls, N = 759) and (2) Saskatoon (contemporaneous controls, N = 759). The study measures included patient-level healthcare costs and acute COPD exacerbation outcomes, both tracked in population-based administrative health data over a one-year follow-up period. Analyses included Cox proportional hazards models and differences in means between groups. The bias-corrected and accelerated bootstrap method was used to calculate 95% confidence intervals (CI). The COPD pathway patients had lower risks of moderate (hazard ratio [HR] =0.57, 95% CI [0.40-0.83]) and severe (HR = 0.43, 95% CI [0.28-0.66]) exacerbations compared to the historical control group, but similar risks compared with the contemporaneous control group. The COPD pathway patients experienced fewer episodes of exacerbations compared with the historical control group (mean difference = -0.30, 95% CI [-0.40, -0.20]) and the contemporaneous control group (mean difference = -0.12, 95% CI [-0.20, -0.03]). Average annual healthcare costs in Canadian dollars were marginally higher among patients in the COPD clinical pathway (mean = $10 549, standard deviation [SD] =$18 149) than those in the contemporaneous control group ($8841, SD = $17 120), but comparable to the historical control group ($10 677, SD = $21 201). The COPD pathway provides better outcomes at about the same costs when compared to the historical controls, but only slightly better outcomes and at a marginally higher cost when compared to the contemporaneous controls.

Validation of an algorithm for identifying incident cancer cases based on long-term illness and diagnosis related group program data from the French National Health Insurance Information System (SNDS).

PURPOSE: Three generic claims-based algorithms based on the Illness Classification of Diseases (10th revision- ICD-10) codes, French Long-Term Illness (LTI) data, and the Diagnosis Related Group program (DRG) were developed to identify retirees with cancer using data from the French national health insurance information system (Système national des données de santé or SNDS) which covers the entire French population. The present study aimed to calculate the algorithms' performances and to describe false positives and negatives in detail. METHODS: Between 2011 and 2016, data from 7544 participants of the French retired self-employed craftsperson cohort (ESPrI) were first matched to the SNDS data, and then toFrench population-based cancer registries data, used as the gold standard. Performance indicators, such as sensitivity and positive predictive values, were estimated for the three algorithms in a subcohort of ESPrI. RESULTS: The third algorithm, which combined the LTI and DRG program data, presented the best sensitivities (90.9%-100%) and positive predictive values (58.1%-95.2%) according to cancer sites. The majority of false positives were in fact nearby organ sites (e.g., stomach for esophagus) and carcinoma in situ. Most false negatives were probably due to under declaration of LTI. CONCLUSION: Validated algorithms using data from the SNDS can be used for passive epidemiological follow-up for some cancer sites in the ESPrI cohort.

Defining a Childhood Type 1 Diabetes Cohort, Clinical Practice Measures, and Outcomes Within Administrative Data in British Columbia.

OBJECTIVE: We used administrative data to 1) establish a cohort of individuals with childhood-onset type 1 diabetes (T1D) in British Columbia (BC), and 2) define T1D-related clinical practice measures. METHODS: We applied a validated diabetes case-finding definition and differentiating algorithm to linked administrative data (1992-1993 to 2019-2020). Cases were removed when they did not meet inclusion criteria for childhood-onset T1D. Clinical practice measures were defined based on clinical practice guidelines. RESULTS: We developed an administrative cohort that included 5,901 individuals with childhood-diagnosed T1D between April 1, 1996, and March 31, 2020. The mean age was 22.31 (standard deviation 8.21) years. Clinical practice measures derived included diabetes outpatient visits (N=4,935) and glycated hemoglobin tests (N=4,935), and screening for thyroid function (N=4,457), retinopathy (N=1,602), and nephropathy (N=2,369). CONCLUSIONS: We established an administrative cohort of ∼6,000 individuals with childhood-onset T1D with 20+ years of follow-up data that can be used to describe the association between clinical practice measures and clinical outcomes.

The impact of team-based primary care on medication-related outcomes in older adults: A comparative analysis of two Canadian provinces.

Objective: To evaluate if access to team-based primary care is related to medication management outcomes for older adults. Methods: We completed two retrospective cohort studies using administrative health data for older adults (66+) in Ontario (n = 428,852) and Québec (n = 310,198) who were rostered with a family physician (FP) between the 2001/02 and 2017/18 fiscal years. We generated matched comparison groups of older adults rostered to an FP practicing in a team-based model, and older adults rostered to an FP in a non-team model. We compared the following outcomes between these groups: any adverse drug reactions (ADRs), any potentially inappropriate prescription (PIP), and polypharmacy. Average treatment effects of access to team-based care were estimated using a difference-in-differences estimator. Results: The risk of an ADR was 22 % higher (RR = 1.22, 95 % CI = 1.18, 1.26) for older adults rostered to a team-based FP in Québec and 6 % lower (RR = 0.943, 95 % CI = 0.907, 0.978) in Ontario. However, absolute risk differences were less than 0.5 %. Differences in the risk of polypharmacy were small in Québec (RR = 1.005, 95 % CI = 1.001, 1.009) and Ontario (RR = 1.004, 95 % CI = 1.001, 1.007) and had absolute risk differences of less than 1 % in both provinces. Effects on PIP were not statistically or clinically significant in adjusted models. Interpretation: We did not find evidence that access to team-based primary care in Ontario or Québec meaningfully improved medication management outcomes for older adults.

Validation of an ICD-Based Algorithm to Identify Sepsis: A Retrospective Study.

Background: Sepsis surveillance was important for resources allocation, prevention, and development of health policy. Objective: The aim of the study was to validate a modified International Classification of Diseases (ICD)-10 based algorithm for identifying hospitalized patients with sepsis. Methods: We retrospectively analyzed a prospective, single-center cohort of adult patients who were consecutively admitted to one medical ICU ward and ten non-ICU wards with suspected or confirmed infections during a 6-month period. A modified ICD-10 based algorithm was validated against a reference standard of Sequential Organ Failure Assessment (SOFA) score based on Sepsis-3. Sensitivity (SE), specificity (SP), positive predictive value (PPV), negative predictive value (NPV), and areas under the receiver operating characteristic curves (AUROCs) were calculated for modified ICD-10 criteria, eSOFA criteria, Martin's criteria, and Angus's criteria. Results: Of the 547 patients in the cohort, 332 (61%) patients met Sepsis-3 criteria and 274 (50%) met modified ICD-10 criteria. In the ICU setting, modified ICD-10 criteria had SE (84.47%), SP (88.57%), PPV (95.60), and NPV (65.96). In non-ICU settings, modified ICD-10 had SE (64.19%), SP (80.00%), PPV (80.33), and NPV (63.72). In the whole cohort, the AUROCs of modified ICD-10 criteria, eSOFA, Angus's criteria, and Martin's criteria were 0.76, 0.75, 0.62, and 0.62, respectively. Conclusion: This study demonstrated that modified ICD-10 criteria had higher validity compared with Angus's criteria and Martin's criteria. Validity of the modified ICD-10 criteria was similar to eSOFA criteria. Modified ICD-10 algorithm can be used to provide an accurate estimate of population-based sepsis burden of China.

Ascertaining asthma status in epidemiologic studies: a comparison between administrative health data and self-report.

BACKGROUND: Studies have suggested that agreement between administrative health data and self-report for asthma status ranges from fair to good, but few studies benefited from administrative health data over a long period. We aimed to (1) evaluate agreement between asthma status ascertained in administrative health data covering a period of 30 years and from self-report, and (2) identify determinants of agreement between the two sources. METHODS: We used administrative health data (1983-2012) from the Quebec Birth Cohort on Immunity and Health, which included 81,496 individuals born in the province of Quebec, Canada, in 1974. Additional information, including self-reported asthma, was collected by telephone interview with 1643 participants in 2012. By design, half of them had childhood asthma based on health services utilization. Results were weighted according to the inverse of the sampling probabilities. Five algorithms were applied to administrative health data (having ≥ 2 physician claims over a 1-, 2-, 3-, 5-, or 30-year interval or ≥ 1 hospitalization), to enable comparisons with previous studies. We estimated the proportion of overall agreement and Kappa, between asthma status derived from algorithms and self-reports. We used logistic regression to identify factors associated with agreement. RESULTS: Applying the five algorithms, the prevalence of asthma ranged from 49 to 55% among the 1643 participants. At interview (mean age = 37 years), 49% and 47% of participants respectively reported ever having asthma and asthma diagnosed by a physician. Proportions of agreement between administrative health data and self-report ranged from 88 to 91%, with Kappas ranging from 0.57 (95% CI: 0.52-0.63) to 0.67 (95% CI: 0.62-0.72); the highest values were obtained with the [≥ 2 physician claims over a 30-year interval or ≥ 1 hospitalization] algorithm. Having sought health services for allergic diseases other than asthma was related to lower agreement (Odds ratio = 0.41; 95% CI: 0.25-0.65 comparing ≥ 1 health services to none). CONCLUSIONS: These findings indicate good agreement between asthma status defined from administrative health data and self-report. Agreement was higher than previously observed, which may be due to the 30-year lookback window in administrative data. Our findings support using both administrative health data and self-report in population-based epidemiological studies.

Characterizing opioid agonist therapy uptake and factors associated with treatment retention among people with HIV in British Columbia, Canada.

Accidental overdoses are now the leading cause of death among people with HIV (PWH) in British Columbia (BC). We examined the utilization and retention of opioid agonist therapy (OAT). Adult PWH (≥19 years) with ≥ 1 OAT dispensation in BC between 2008 and 2020 were included (n = 1,515). OAT treatment episodes were formed based on specific criteria for slow-release oral morphine (SROM), methadone, injectable OAT (iOAT), and buprenorphine/naloxone. Retention in treatment was defined as any episode lasting ≥ 12 months. Logistic regression with generalized estimating equations modeled retention-associated factors. There was a 56.6% decline in OAT retention over time. Buprenorphine treatment exhibited significantly lower odds of retention (OR: 0.58; 95% CI: 0.36-0.92) compared to methadone. Conversely, no significant change in retention odds was observed for SROM (0.72; 0.33-1.54) and iOAT (0.81; 0.31-2.12). Factors associated with increased odds of retention included a 10-year increase in age (1.69; 1.46-1.95), previous retention history (1.96; 1.40-2.73), achieving OAT therapeutic dose (8.22; 6.67-10.14), and suppressed HIV viral load (1.35; 1.10-1.67). Individuals with a lifetime HCV diagnosis receiving iOAT were more likely to retain (3.61; 1.20-10.83). Each additional year on OAT during the study period was associated with a 4% increase in the odds of retention. A significant proportion of PWH had a history of OAT prescribing but experienced low retention rates. Retention outcomes were more positive for SROM and iOAT. The association between OAT medication type and retention odds may be particularly influenced by HCV diagnosis. Optimal management of opioid use disorder among PWH, with an emphasis on attaining the therapeutic dose is crucial.

Breaking the 80:20 rule in health research using large administrative data sets.

Objective: To explore the application of online analytic processing (OLAP) to improve the efficiency of analytics using large administrative health data sets. Methods: 18 years of administrative health data (1994/95 to 2012/13) were obtained from the Alberta Ministry of Health in Canada. The data sets included hospitalization, ambulatory care and practitioner claims data. Reference files were obtained that provided information including patient demographics, resident postal code, facility, and provider details. Population counts and projections for each year, sex, age were included for rate calculations. These sources were used to develop a data cube using OLAP tools. Results: Time required for analyses was reduced to 5% of that required when comparing run-time for simple queries that did not require linkage of data sets. The data cube negated the need for many intermediary steps for data extraction and analyses for research activities. Conventional methods required over 250 GB of server space for multiple analytic subsets, compared to only 10.3 GB for the data cube. Conclusions: Cross-training in information technology and health analytics is recommended to provide capacity to better leverage OLAP tools which are available with many common applications.

Risk of severe infections after the introduction of biologic DMARDs in people with newly diagnosed rheumatoid arthritis: a population-based interrupted time-series analysis.

OBJECTIVES: To determine the impact of the introduction of biologic DMARDs (bDMARDs) on severe infections among people newly diagnosed with RA compared with non-RA individuals. METHODS: In this population-based retrospective cohort study using administrative data (from 1990-2015) for British Columbia, Canada, all incident RA patients diagnosed between 1995 and 2007 were identified. General population controls with no inflammatory arthritis were matched to RA patients based on age and gender, and were assigned the diagnosis date (i.e. index date) of the RA patients they were matched with. RA/controls were then divided into quarterly cohorts according to their index dates. The outcome of interest was all severe infections necessitating hospitalization or occurring during hospitalization after the index date. We calculated 8-year severe infection rates for each cohort and conducted interrupted time-series analyses to compare severe infection trends in RA/controls with index date during pre-bDMARDs (1995-2001) and post-bDMARDs (2003-2007) periods. RESULTS: A total of 60 226 and 588 499 incident RA/controls were identified. We identified 14 245 severe infections in RA, and 79 819 severe infections in controls. The 8-year severe infection rates decreased among RA/controls with increasing calendar year of index date in the pre-bDMARDs period, but increased over time only among RA, not controls, with index date in the post-bDMARDs period. The adjusted difference between the pre- and post-bDMARDs secular trends in 8-year severe infection rates was 1.85 (P = 0.001) in RA and 0.12 (P = 0.29) in non-RA. CONCLUSION: RA onset after bDMARDs introduction was associated with an elevated severe infection risk in RA patients compared with matched non-RA individuals.

Emergency department crowding negatively influences outcomes for adults presenting for chronic obstructive pulmonary disease.

OBJECTIVES: Emergency department (ED) crowding leads to poor outcomes. Patients with respiratory conditions like chronic obstructive pulmonary disease (COPD) are especially vulnerable to crowding-related delays in care. We aimed to assess the associations of ED crowding metrics with outcomes for patients presenting with COPD. METHODS: We conducted a population-based cohort study of adult patients presenting with a diagnosis of COPD to 18 high-volume EDs between 2014 and 2019 in Alberta, Canada. Administrative databases provided date and time data on key stages of the presentation including physician initial assessment and disposition decision. Crowding metrics were calculated using facility-specific median physician initial assessment and length of stay. Patient presentations were grouped by acuity and mixed-effects regression models were fit to adjust for the clustering at the facility level. RESULTS: There were 49,085 presentations for COPD made by 25,734 patients (median age = 73 years). A 1-h increase in the physician initial assessment metric was associated with an increase in physician initial assessment for COPD patients by 23, 53, and 59 min for the high, moderate, and low acuity groups, respectively, adjusted for other predictors. For the low acuity group, this metric was associated with an increased length of stay of 73 min for admitted individuals. Similarly, an increase in the length of stay metric was also associated with an increased likelihood of being admitted for all acuity groups. CONCLUSIONS: For patients with COPD, ED crowding results in delays in assessment increased length of stay, and increased proportion of patients admitted. These results suggest that ED crowding mitigation efforts to provide timely care for patients with COPD are urgently needed. TRIAL REGISTRATION: N/A.

RéSUMé: OBJECTIFS: L'encombrement des services d'urgence entraîne de mauvais résultats. Les patients souffrant de maladies respiratoires telles que la maladie pulmonaire obstructive chronique (MPOC) sont particulièrement vulnérables aux retards de soins liés à l'encombrement. Notre avons cherché à évaluer les associations entre les paramètres d'encombrement des services d'urgence et les résultats pour les patients présentant une MPOC. MéTHODES: Nous avons mené une étude de cohorte basée sur la population de patients adultes se présentant avec un diagnostic de MPOC dans dix-huit services d'urgence à haut volume entre 2014 et 2019 en Alberta, au Canada. Les bases de données administratives ont fourni des données sur la date et l'heure des principales étapes de la présentation, y compris l'évaluation initiale par le médecin et la décision de sortie. Les mesures d'encombrement ont été calculées à partir de l'évaluation initiale médiane du médecin et de la durée du séjour propres à l'établissement. Les présentations des patients ont été regroupées par gravité et des modèles de régression à effets mixtes ont été ajustés pour tenir compte du regroupement au niveau de l'établissement. RéSULTATS: Il y a eu 49 085 présentations pour la MPOC effectuées par 25 734 patients (âge médian = 73 ans). Une augmentation d'une heure de l'évaluation initiale par le médecin était associée à une augmentation de l'évaluation initiale par le médecin pour les patients atteints de MPOC de 23, 53 et 59 min pour les groupes de gravité élevée, modérée et faible, respectivement, après ajustement pour d'autres facteurs prédictifs. Pour le groupe de faible gravité, ce paramètre était associé à une augmentation de la durée de séjour de 73 min pour les personnes admises. De même, une augmentation de la durée du séjour était également associée à une probabilité accrue d'admission pour tous les groupes de gravité. CONCLUSIONS: Pour les patients atteints de MPOC, l'encombrement des urgences entraîne des retards dans l'évaluation, une augmentation de la durée du séjour et une augmentation de la proportion de patients admis. Ces résultats suggèrent qu'il est urgent d'atténuer l'encombrement des urgences afin de fournir des soins en temps opportun aux patients atteints de MPOC. ENREGISTREMENT DE L'ESSAI: N/A.

A method for generating synthetic longitudinal health data.

Getting access to administrative health data for research purposes is a difficult and time-consuming process due to increasingly demanding privacy regulations. An alternative method for sharing administrative health data would be to share synthetic datasets where the records do not correspond to real individuals, but the patterns and relationships seen in the data are reproduced. This paper assesses the feasibility of generating synthetic administrative health data using a recurrent deep learning model. Our data comes from 120,000 individuals from Alberta Health's administrative health database. We assess how similar our synthetic data is to the real data using utility assessments that assess the structure and general patterns in the data as well as by recreating a specific analysis in the real data commonly applied to this type of administrative health data. We also assess the privacy risks associated with the use of this synthetic dataset. Generic utility assessments that used Hellinger distance to quantify the difference in distributions between real and synthetic datasets for event types (0.027), attributes (mean 0.0417), Markov transition matrices (order 1 mean absolute difference: 0.0896, sd: 0.159; order 2: mean Hellinger distance 0.2195, sd: 0.2724), the Hellinger distance between the joint distributions was 0.352, and the similarity of random cohorts generated from real and synthetic data had a mean Hellinger distance of 0.3 and mean Euclidean distance of 0.064, indicating small differences between the distributions in the real data and the synthetic data. By applying a realistic analysis to both real and synthetic datasets, Cox regression hazard ratios achieved a mean confidence interval overlap of 68% for adjusted hazard ratios among 5 key outcomes of interest, indicating synthetic data produces similar analytic results to real data. The privacy assessment concluded that the attribution disclosure risk associated with this synthetic dataset was substantially less than the typical 0.09 acceptable risk threshold. Based on these metrics our results show that our synthetic data is suitably similar to the real data and could be shared for research purposes thereby alleviating concerns associated with the sharing of real data in some circumstances.

Proton Pump Inhibitor Use Before and After a Diagnosis of Inflammatory Bowel Disease.

BACKGROUND: Proton pump inhibitors (PPIs) have an impact on the gut microbiome. We investigated whether increased use of PPIs was associated with a diagnosis of inflammatory bowel disease (IBD). METHODS: The University of Manitoba IBD Epidemiology Database includes all Manitobans diagnosed with IBD between 1984 and 2018 with age-, sex-, and geography-matched control subjects and comprehensive prescription drug data from April 1995. Subjects were considered to be users if they received 2 PPI prescriptions. We assessed PPI prescriptions prediagnosis and for 3 years postdiagnosis of IBD. The absolute and relative rates were calculated and compared for PPI use pre- and post-IBD diagnosis. RESULTS: A total of 5920 subjects were diagnosed with IBD after April 1996. Rates of PPI use in control subjects increased gradually from 1.5% to 6.5% over 15 years. Persons with IBD had a higher rate of PPI use, peaking up to 17% within 1 year of IBD diagnosis with a rate ratio (RR) of 3.1 (95% confidence interval [CI], 2.9-3.3). Furthermore, persons with Crohn's disease (RR, 4.2; 95% CI, 3.7-4.6) were more likely to have been PPI users prediagnosis than persons with ulcerative colitis (RR, 2.4; 95% CI, 2.2-2.7). Important predictors of increased PPI use were older age, year of data collection, and Crohn's disease diagnosis. CONCLUSIONS: Persons with IBD have higher PPI use preceding their diagnosis. Possibly, the use of a PPI alters the gut microbiome, increasing the risk for IBD diagnosis; or persons with IBD have increased rates of dyspepsia, warranting PPI use; or some IBD symptoms are treated with PPIs whether warranted or not.

Proton pump inhibitor (PPI) use is increased in persons with IBD for up to years prior to their diagnosis, raising the possibility that their use increases the risk for inflammatory bowel disease (IBD), or alternatively, persons with IBD have more upper gastrointestinal complaints. Another possibility is that early IBD-related symptoms are being managed rightly or wrongly with PPI therapy. Further, there is an increased use of PPI therapy post­IBD diagnosis compared with matched control subjects. While the use of PPI therapy in persons with IBD may be appropriate, physicians need to rigorously review their use at all times, especially in persons with IBD, as in this population their use may be excessive and possibly detrimental.

Real word challenges in integrating electronic medical record and administrative health data for regional quality improvement in diabetes: a retrospective cross-sectional analysis.

BACKGROUND: Linked electronic medical records and administrative data have the potential to support a learning health system and data-driven quality improvement. However, data completeness and accuracy must first be assessed before their application. We evaluated the processes, feasibility, and limitations of linking electronic medical records and administrative data for the purpose of quality improvement within five specialist diabetes clinics in Edmonton, Alberta, a province known for its robust health data infrastructure. METHODS: We conducted a retrospective cross-sectional analysis using electronic medical record and administrative data for individuals ≥ 18 years attending the clinics between March 2017 and December 2018. Descriptive statistics were produced for demographics, service use, diabetes type, and standard diabetes benchmarks. The systematic and iterative process of obtaining results is described. RESULTS: The process of integrating electronic medical record with administrative data for quality improvement was found to be non-linear and iterative and involved four phases: project planning, information generating, limitations analysis, and action. After limitations analysis, questions were grouped into those that were answerable with confidence, answerable with limitations, and not answerable with available data. Factors contributing to data limitations included inaccurate data entry, coding, collation, migration and synthesis, changes in laboratory reporting, and information not captured in existing databases. CONCLUSION: Electronic medical records and administrative databases can be powerful tools to establish clinical practice patterns, inform data-driven quality improvement at a regional level, and support a learning health system. However, there are substantial data limitations that must be addressed before these sources can be reliably leveraged.

The Association Between Problematic Use of Alcohol and Drugs and Repeat Self-Harm and Suicidal Ideation.

Aims: We investigated the association between problematic use of alcohol and/or drugs (PUAD) and the incidence, urgency, and mode of discharge for a subsequent episode of self-harm (SH) or suicidal ideation (SI). Methods: This was a retrospective population-based cohort study of individuals admitted to hospital for an index episode of SH/SI (2010-2014) using linked data from hospital admissions and emergency department (ED) presentations. The outcome variables were (1) subsequent presentation to the ED for SH/SI, (2) triage category, and (3) mode of departure. Key predictors were PUAD. Results: In total, 23,007 individuals were admitted to hospital for an index SH/SI, of whom 8% had a subsequent presentation to an ED for SH/SI within a year. The odds of subsequent presentation was increased in those with problematic alcohol use (AOR 1.62, 95% CI 1.36, 1.92), drug use (AOR 1.28, 95% CI 1.07, 1.53), and mental health diagnoses (AOR 1.63, 95% CI 1.44, 1.85). Those with problematic alcohol use were more likely to be assigned to the most urgent triage categories (AOR 1.84, 95% CI 1.32, 2.56). Limitations: Defining SH and PUAD using administrative data is challenging, and the true prevalence is likely to be underestimated. Conclusion: The findings underscore the importance of drug health intervention as a key component of self-harm prevention.

Individualized Prospective Prediction of Opioid Use Disorder.

OBJECTIVE: Opioid use disorder (OUD) is a chronic relapsing disorder with a problematic pattern of opioid use, affecting nearly 27 million people worldwide. Machine learning (ML)-based prediction of OUD may lead to early detection and intervention. However, most ML prediction studies were not based on representative data sources and prospective validations, limiting their potential to predict future new cases. In the current study, we aimed to develop and prospectively validate an ML model that could predict individual OUD cases based on representative large-scale health data. METHOD: We present an ensemble machine-learning model trained on a cross-linked Canadian administrative health data set from 2014 to 2018 (n = 699,164), with validation of model-predicted OUD cases on a hold-out sample from 2014 to 2018 (n = 174,791) and prospective prediction of OUD cases on a non-overlapping sample from 2019 (n = 316,039). We used administrative records of OUD diagnosis for each subject based on International Classification of Diseases (ICD) codes. RESULTS: With 6409 OUD cases in 2019 (mean [SD], 45.34 [14.28], 3400 males), our model prospectively predicted OUD cases at a high accuracy (balanced accuracy, 86%, sensitivity, 93%; specificity 79%). In accord with prior findings, the top risk factors for OUD in this model were opioid use indicators and a history of other substance use disorders. CONCLUSION: Our study presents an individualized prospective prediction of OUD cases by applying ML to large administrative health datasets. Such prospective predictions based on ML would be essential for potential future clinical applications in the early detection of OUD.