Unconditional cash transfers reduce homelessness.

Homelessness is an economic and social crisis. In a cluster-randomized controlled trial, we address a core cause of homelessness-lack of money-by providing a one-time unconditional cash transfer of CAD$7,500 to each of 50 individuals experiencing homelessness, with another 65 as controls in Vancouver, BC. Exploratory analyses showed that over 1 y, cash recipients spent fewer days homeless, increased savings and spending with no increase in temptation goods spending, and generated societal net savings of $777 per recipient via reduced time in shelters. Additional experiments revealed public mistrust toward the ability of homeless individuals to manage money and demonstrated interventions to increase public support for a cash transfer policy using counter-stereotypical or utilitarian messaging. Together, this research offers a new approach to address homelessness and provides insights into homelessness reduction policies.

Patient-Physician Sex Discordance and "Before Medically Advised" Discharge from Hospital: A Population-Based Retrospective Cohort Study.

BACKGROUND: Patient-physician sex discordance (when patient sex does not match physician sex) has been associated with reduced clinical rapport and adverse outcomes including post-operative mortality and unplanned hospital readmission. It remains unknown whether patient-physician sex discordance is associated with "before medically advised" hospital discharge (BMA discharge; commonly known as discharge "against medical advice"). OBJECTIVE: To evaluate whether patient-physician sex discordance is associated with BMA discharge. DESIGN: Retrospective cohort study using 15 years (2002-2017) of linked population-based administrative health data for all non-elective, non-obstetrical acute care hospitalizations from British Columbia, Canada. PARTICIPANTS: All individuals with eligible hospitalizations during study interval. MAIN MEASURES: Exposure: patient-physician sex discordance. OUTCOMES: BMA discharge (primary), 30-day hospital readmission or death (secondary). RESULTS: We identified 1,926,118 eligible index hospitalizations, 2.6% of which ended in BMA discharge. Among male patients, sex discordance was associated with BMA discharge (crude rate, 4.0% vs 2.9%; adjusted odds ratio [aOR] 1.08; 95%CI 1.03-1.14; p = 0.003). Among female patients, sex discordance was not associated with BMA discharge (crude rate, 2.0% vs 2.3%; aOR 1.02; 95%CI 0.96-1.08; p = 0.557). Compared to patient-physician sex discordance, younger patient age, prior substance use, and prior BMA discharge all had stronger associations with BMA discharge. CONCLUSIONS: Patient-physician sex discordance was associated with a small increase in BMA discharge among male patients. This finding may reflect communication gaps, differences in the care provided by male and female physicians, discriminatory attitudes among male patients, or residual confounding. Improved communication and better treatment of pain and opioid withdrawal may reduce BMA discharge.

"Before medically advised" departure from hospital and subsequent drug overdose: a population-based cohort study.

BACKGROUND: A substantial number of hospital admissions end in patient-initiated departure before medical treatment is complete. Whether "before medically advised" (BMA) discharge increases the risk of subsequent drug overdose remains uncertain. METHODS: We performed a retrospective cohort study using administrative health data from a 20% random sample of residents of British Columbia, Canada. We focused on nonelective, nonobstetric hospital stays occurring between 2015 and 2019. We used survival analysis to compare the rate of fatal or nonfatal illicit drug overdose in the first 30 days after BMA discharge versus the rate after physician-advised discharge. RESULTS: Overall, 6440 of 189 808 (3.4%) hospital stays ended in BMA discharge. Among 820 overdoses occurring in the first 30 days after any hospital discharge, 755 (92%) involved patients with a history of substance use disorder. Unadjusted overdose rates were 10-fold higher after BMA discharge than after physician-advised discharge, and BMA discharge was associated with subsequent overdose even after adjustment for potential confounders (crude incidence, 2.8% v. 0.3%; adjusted hazard ratio [HR] 1.58; 95% confidence interval [CI] 1.31-1.89). Before medically advised discharge was associated with increases in subsequent emergency department visits (adjusted HR 1.92; 95% CI 1.83-2.02) and unplanned hospital readmissions (adjusted HR 2.07; 95% CI 1.96-2.19), but there was no significant association with the uncommon outcomes of fatal overdose and all-cause mortality. INTERPRETATION: Before medically advised departure is associated with an increased risk of drug overdose in the first 30 days after discharge. Improved treatment of substance use disorder, expanded access to overdose prevention services, and new means of postdeparture outreach should be explored to reduce this risk.

Physician Financial Incentives for Use of Outpatient Intravenous Antimicrobial Therapy: An Interrupted Time Series Analysis.

BACKGROUND: In 2011, policymakers in British Columbia introduced a fee-for-service payment to incentivize infectious diseases physicians to supervise outpatient parenteral antimicrobial therapy (OPAT). Whether this policy increased use of OPAT remains uncertain. METHODS: We conducted a retrospective cohort study using population-based administrative data over a 14-year period (2004-2018). We focused on infections that required intravenous antimicrobials for ≥10 days (eg, osteomyelitis, joint infection, endocarditis) and used the monthly proportion of index hospitalizations with a length of stay shorter than the guideline-recommended "usual duration of intravenous antimicrobials" (LOS < UDIVA) as a surrogate for population-level OPAT use. We used interrupted time series analysis to determine whether policy introduction increased the proportion of hospitalizations with LOS < UDIVA. RESULTS: We identified 18 513 eligible hospitalizations. In the pre-policy period, 82.3% of hospitalizations exhibited LOS < UDIVA. Introduction of the incentive was not associated with a change in the proportion of hospitalizations with LOS < UDIVA, suggesting that the policy intervention did not increase OPAT use (step change, -0.06%; 95% confidence interval [CI], -2.69% to 2.58%; P = .97 and slope change, -0.001% per month; 95% CI, -.056% to .055%; P = .98). CONCLUSIONS: The introduction of a financial incentive for physicians did not appear to increase OPAT use. Policymakers should consider modifying the incentive design or addressing organizational barriers to expanded OPAT use.

Combining parametric and nonparametric models to estimate treatment effects in observational studies.

Performing causal inference in observational studies requires we assume confounding variables are correctly adjusted for. In settings with few discrete-valued confounders, standard models can be employed. However, as the number of confounders increases these models become less feasible as there are fewer observations available for each unique combination of confounding variables. In this paper, we propose a new model for estimating treatment effects in observational studies that incorporates both parametric and nonparametric outcome models. By conceptually splitting the data, we can combine these models while maintaining a conjugate framework, allowing us to avoid the use of Markov chain Monte Carlo (MCMC) methods. Approximations using the central limit theorem and random sampling allow our method to be scaled to high-dimensional confounders. Through simulation studies we show our method can be competitive with benchmark models while maintaining efficient computation, and illustrate the method on a large epidemiological health survey.

Distinguishing Primary Prevention From Secondary Prevention Implantable Cardioverter Defibrillators Using Administrative Health and Cardiac Device Registry Data.

Background: Administrative health data and cardiac device registries can be used to empirically evaluate outcomes and costs after implantable cardioverter defibrillator (ICD) implantation. These datasets often have incomplete information on the indication for implantation (primary vs secondary prevention of sudden cardiac death). Methods: We used 16 years of population-based cardiac device registry and administrative health data from British Columbia, Canada, to derive and internally validate statistical models that predict the likely indication for ICD implantation. We used chart review data as the reference standard for ICD indication in the Cardiac Device Registry database (CDR; 2004-2012 [Cardiac Services BC]) and nonmissing indication as the reference standard in the Heart Information System registry database (HEARTis; 2013-2019 [Cardiac Services BC]). We created 3 logistic regression prediction models in each database: one using only registry data, one using only administrative data, and one using both registry and administrative data. We assessed the predictive performance of each model using standard metrics after optimism correction with 200 bootstrap resamples. Results: Models that used registry data alone demonstrated excellent predictive performance (sensitivity ≥ 89%; specificity ≥ 87%). Models that used only administrative data performed well (sensitivity ≥ 84%; specificity ≥ 70%). Models that used both registry and administrative data showed modest gains over those that used registry data alone (sensitivity ≥ 90%; specificity ≥ 89%). Conclusions: Administrative health data and cardiac device registry data can distinguish secondary prevention ICDs from primary prevention ICDs with acceptable sensitivity and specificity. Imputation of missing ICD indication might make these data resources more useful for research and health system monitoring.

Contexte: Les données administratives de santé et les registres des dispositifs cardiaques peuvent être utilisés pour évaluer de manière empirique les résultats et les coûts associés aux défibrillateurs cardioverteurs implantables (DCI). Or, ces ensembles de données comportent souvent des informations incomplètes sur l'indication de l'implant (prévention primaire ou secondaire de la mort subite d'origine cardiaque). Méthodologie: Nous avons analysé 16 ans de données provenant du registre populationnel des dispositifs cardiaques et des données administratives de santé de la Colombie-Britannique, au Canada, pour alimenter des modèles statistiques prédisant l'indication probable de l'implant d'un DCI et pour effectuer une validation interne de ces modèles. Nous avons utilisé les données de la revue des dossiers médicaux comme norme de référence de l'indication des DCI dans le registre des dispositifs cardiaques (Cardiac Device Registry; 2004-2012 [Cardiac Services BC]) et les indications consignées comme norme de référence dans la banque de données Heart Information System (HEARTis; 2013-2019 [Cardiac Services BC]). Nous avons créé 3 modèles prédictifs par régression logistique dans chaque base de données : une utilisant seulement les données du registre, une utilisant seulement les données administratives et une utilisant les deux types de données. Nous avons évalué la performance de chaque modèle en matière de prédiction à l'aide de mesures normalisées, après correction pour l'optimisme de l'erreur à l'aide de 200 nouveaux échantillons obtenus par la méthode bootstrap. Résultats: Les modèles utilisant seulement les données du registre avaient une excellente performance prédictive (sensibilité ≥ 89 %; spécificité ≥ 87 %). Les modèles qui n'utilisaient que les données administratives donnaient quant à eux de bons résultats (sensibilité ≥ 84 %; spécificité ≥ 70 %). Enfin, les modèles qui utilisaient les données administratives et les données du registre ont donné des gains modestes par rapport aux modèles qui n'utilisaient que les données du registre (sensibilité ≥ 90 %; spécificité ≥ 89 %). Conclusions: Les données administratives de santé et les données des registres de dispositifs cardiaques permettent de distinguer les DCI implantés en prévention secondaire des DCI implantés en prévention primaire avec une sensibilité et une spécificité acceptables. Dans les cas où elle est absente, l'attribution d'une indication pour les DCI pourrait donc rendre ces ressources plus utiles pour la recherche et la surveillance du système de santé.

Schizophrenia, antipsychotic treatment adherence and driver responsibility for motor vehicle crash: a population-based retrospective study in British Columbia, Canada.

OBJECTIVE: To examine the relationship between schizophrenia, antipsychotic medication adherence and driver responsibility for motor vehicle crash. DESIGN: Retrospective observational cohort study using 20 years of population-based administrative health and driving data. SETTING: British Columbia, Canada. PARTICIPANTS: Licensed drivers who were involved in a police-attended motor vehicle crash in British Columbia over a 17-year study interval (2000-16). EXPOSURES: Incident schizophrenia was identified using hospitalisation and physician services data. Antipsychotic adherence was estimated using prescription fill data to calculate the 'medication possession ratio' (MPR) in the 30 days prior to crash. PRIMARY OUTCOME MEASURES: We deemed drivers 'responsible' or 'non-responsible' for their crash by applying a validated scoring tool to police-reported crash data. We used logistic regression to evaluate the association between crash responsibility and exposures of interest. RESULTS: Our cohort included 808 432 drivers involved in a police-attended crash and for whom crash responsibility could be established. In total, 1689 of the 2551 drivers with schizophrenia and 432 430 of the 805 881 drivers without schizophrenia were deemed responsible for their crash, corresponding to a significant association between schizophrenia and crash responsibility (66.2% vs 53.7%; adjusted OR (aOR), 1.67; 95% CI, 1.53 to 1.82; p<0.001). The magnitude of this association was modest relative to established crash risk factors (eg, learner license, age ≥65 years, impairment at time of crash). Among the 1833 drivers with schizophrenia, near-optimal antipsychotic adherence (MPR ≥0.8) in the 30 days prior to crash was not associated with lower crash responsibility (aOR, 1.04; 95% CI, 0.83 to 1.30; p=0.55). CONCLUSIONS: Crash-involved drivers with schizophrenia are more likely to be responsible for their crash, but the magnitude of risk is similar to socially acceptable risk factors such as older age or possession of a learner license. Contemporary driving restrictions for individuals with schizophrenia appear to adequately mitigate road risks, suggesting more stringent driving restrictions are not warranted.

Population-Based Trends in Complexity of Hospital Inpatients.

Importance: Clinical experience suggests that hospital inpatients have become more complex over time, but few studies have evaluated this impression. Objective: To assess whether there has been an increase in measures of hospital inpatient complexity over a 15-year period. Design, Setting and Participants: This cohort study used population-based administrative health data from nonelective hospitalizations from April 1, 2002, to January 31, 2017, to describe trends in the complexity of inpatients in British Columbia, Canada. Hospitalizations were included for individuals 18 years and older and for which the most responsible diagnosis did not correspond to pregnancy, childbirth, the puerperal period, or the perinatal period. Data analysis was performed from July to November 2023. Exposure: The passage of time (15-year study interval). Main Outcomes and Measures: Measures of complexity included patient characteristics at the time of admission (eg, advanced age, multimorbidity, polypharmacy, recent hospitalization), features of the index hospitalization (eg, admission via the emergency department, multiple acute medical problems, use of intensive care, prolonged length of stay, in-hospital adverse events, in-hospital death), and 30-day outcomes after hospital discharge (eg, unplanned readmission, all-cause mortality). Logistic regression was used to estimate the relative change in each measure of complexity over the entire 15-year study interval. Results: The final study cohort included 3 367 463 nonelective acute care hospital admissions occurring among 1 272 444 unique individuals (median [IQR] age, 66 [48-79] years; 49.1% female and 50.8% male individuals). Relative to the beginning of the study interval, inpatients at the end of the study interval were more likely to have been admitted via the emergency department (odds ratio [OR], 2.74; 95% CI, 2.71-2.77), to have multimorbidity (OR, 1.50; 95% CI, 1.47-1.53) and polypharmacy (OR, 1.82; 95% CI, 1.78-1.85) at presentation, to receive treatment for 5 or more acute medical issues (OR, 2.06; 95% CI, 2.02-2.09), and to experience an in-hospital adverse event (OR, 1.20; 95% CI, 1.19-1.22). The likelihood of an intensive care unit stay and of in-hospital death declined over the study interval (OR, 0.96; 95% CI, 0.95-0.97, and OR, 0.81; 95% CI, 0.80-0.83, respectively), but the risks of unplanned readmission and death in the 30 days after discharge increased (OR, 1.14; 95% CI, 1.12-1.16, and OR, 1.28; 95% CI, 1.25-1.31, respectively). Conclusions and Relevance: By most measures, hospital inpatients have become more complex over time. Health system planning should account for these trends.

Motor vehicle crash risk after cardioverter-defibrillator implantation: a population-based cohort study.

BACKGROUND: Limited empirical evidence informs driving restrictions after implantable cardioverter-defibrillator (ICD) implantation. We sought to evaluate real-world motor vehicle crash risks after ICD implantation. METHODS: We performed a retrospective cohort study using 22 years of population-based health and driving data from British Columbia, Canada (2019 population: 5 million). Individuals with a first ICD implantation between 1997 and 2019 were age and sex matched to three controls. The primary outcome was involvement as a driver in a crash that was attended by police or that resulted in an insurance claim. We used survival analysis to compare crash risk in the first 6 months after ICD implantation to crash risk during a corresponding 6-month interval among controls. RESULTS: A crash occurred prior to a censoring event for 296 of 9373 individuals with ICDs and for 1077 of 28 119 controls, suggesting ICD implantation was associated with a reduced risk of subsequent crash (crude incidence rate, 8.5 vs 10.5 crashes per 100 person-years; adjusted HR (aHR), 0.71; 95% CI 0.61 to 0.83; p<0.001). Results were similar after stratification by primary versus secondary prevention ICD. Relative to controls, ICD patients had more traffic contraventions in the 3 years prior to ICD implantation but fewer contraventions in the 6 months after implantation, suggesting individuals reduced their road exposure (hours or miles driven per week) or drove more conservatively after ICD implantation. CONCLUSIONS: Crash risk is lower in the 6 months after ICD implantation than among matched controls, likely because individuals reduced their road exposure in order to comply with contemporary postimplantation driving restrictions. Policymakers might consider liberalisation of postimplantation driving restrictions while monitoring crash rates.