Nurse practitioner and physician end-of-life home visits and end-of-life outcomes.

OBJECTIVES: Physicians and nurse practitioners (NPs) play critical roles in supporting palliative and end-of-life care in the community. We examined healthcare outcomes among patients who received home visits from physicians and NPs in the 90 days before death. METHODS: We conducted a retrospective cohort study using linked data of adult home care users in Ontario, Canada, who died between 1 January 2018 and 31 December 2019. Healthcare outcomes included medications for pain and symptom management, emergency department (ED) visits, hospitalisations and a community-based death. We compared the characteristics of and outcomes in decedents who received a home visit from an NP, physician and both to those who did not receive a home visit. RESULTS: Half (56.9%) of adult decedents in Ontario did not receive a home visit from a provider in the last 90 days of life; 34.5% received at least one visit from a physician, 3.8% from an NP and 4.9% from both. Compared with those without any visits, having at least one home visit reduced the odds of hospitalisation and ED visits, and increased the odds of receiving medications for pain and symptom management and achieving a community-based death. Observed effects were larger in patients who received at least one visit from both. CONCLUSIONS: Beyond home care, receiving home visits from primary care providers near the end of life may be associated with better outcomes that are aligned with patients' preferences-emphasising the importance of NPs and physicians' role in supporting people near the end of life.

Development and Validation of a Predictive Risk Algorithm for Bleeding in Individuals on Long-term Hemodialysis: An International Prospective Cohort Study (BLEED-HD).

Background: Individuals with kidney disease are at a high risk of bleeding and as such tools that identify those at highest risk may aid mitigation strategies. Objective: We set out to develop and validate a prediction equation (BLEED-HD) to identify patients on maintenance hemodialysis at high risk of bleeding. Design: International prospective cohort study (development); retrospective cohort study (validation). Settings: Development: 15 countries (Dialysis Outcomes and Practice Patterns Study [DOPPS] phase 2-6 from 2002 to 2018); Validation: Ontario, Canada. Patients: Development: 53 147 patients; Validation: 19 318 patients. Measurements: Hospitalization for a bleeding event. Methods: Cox proportional hazards models. Results: Among the DOPPS cohort (mean age, 63.7 years; female, 39.7%), a bleeding event occurred in 2773 patients (5.2%, event rate 32 per 1000 person-years), with a median follow-up of 1.6 (interquartile range [IQR], 0.9-2.1) years. BLEED-HD included 6 variables: age, sex, country, previous gastrointestinal bleeding, prosthetic heart valve, and vitamin K antagonist use. The observed 3-year probability of bleeding by deciles of risk ranged from 2.2% to 10.8%. Model discrimination was low to moderate (c-statistic = 0.65) with excellent calibration (Brier score range = 0.036-0.095). Discrimination and calibration of BLEED-HD were similar in an external validation of 19 318 patients from Ontario, Canada. Compared to existing bleeding scores, BLEED-HD demonstrated better discrimination and calibration (c-statistic: HEMORRHAGE = 0.59, HAS-BLED = 0.59, and ATRIA = 0.57, c-stat difference, net reclassification index [NRI], and integrated discrimination index [IDI] all P value <.0001). Limitations: Dialysis procedure anticoagulation was not available; validation cohort was considerably older than the development cohort. Conclusion: In patients on maintenance hemodialysis, BLEED-HD is a simple risk equation that may be more applicable than existing risk tools in predicting the risk of bleeding in this high-risk population.

Contexte: Les personnes atteintes d'insuffisance rénale présentent un risque élevé d'hémorragie. Des outils permettant de déceler les personnes les plus exposées au risque pourrait aider à mettre en œuvre des stratégies d'atténuation. Objectifs: Nous avons mis au point et validé une équation prédictive (BLEED-HD) afin d'identifier les patients sous hémodialyse d'entretien qui présentent un risque élevé d'hémorragie. Type d'étude: Étude de cohorte prospective internationale (développement); étude de cohorte rétrospective (validation). Cadre: Développement: dans 15 pays (étude DOPPS phases 2 à 6 entre 2002 et 2018); validation: en Ontario (Canada). Sujets: Développement: 53 147 patients; validation: 19 318 patients. Mesures: Hospitalisation pour un événement hémorragique. Méthodologie: Modèles à risques proportionnels de Cox. Résultats: Dans la cohorte DOPPS (âge moyen: 63,7 ans; 39,7 % de femmes), 2 773 patients avaient subi un événement hémorragique (5,2 %; taux d'événements: 32 pour 1 000 années-personnes) avec un suivi médian de 1,6 an (ÉIQ: 0,9 à 2,1). BLEED-HD prend six variables en compte: âge, sexe, pays d'origine, saignement gastro-intestinal antérieur, présence d'une valve cardiaque prothétique et utilisation d'un antagoniste de la vitamine K. La probabilité observée de saignements dans les 3 ans par déciles de risque allait de 2,2 à 10,8 %. La discrimination du modèle variait de faible à modérée (statistique c: 0,65) avec un excellent étalonnage (plage de score de Brier: 0,036-0,095). La discrimination et l'étalonnage de se sont avérés semblables lors de la validation externe auprès de 19 318 patients de l'Ontario (Canada). Par rapport aux scores d'hémorragie existants, l'équation BLEED-HD a démontré une meilleure discrimination et un meilleur étalonnage (statistique c: HEMORRHAGE 0,59; HAS-BLED 0,59 et ATRIA 0,57; différence dans les c-stat, indices NRI et IDI toutes valeurs de p < 0,0001). Limites: L'information sur l'anticoagulant utilisé dans la procédure de dialyse n'était pas disponible; la cohorte de validation était beaucoup plus âgée que la cohorte de développement. Conclusion: Pour les patients sous hémodialyse d'entretien, BLEED-HD est une équation simple de calcul du risque qui peut être plus facilement applicable que les outils existants pour prédire le risque d'hémorragie dans cette population à haut risque.

Clinical and economic impact of a community-based, hybrid model of in-person and virtual care in a Canadian rural setting: a cross-sectional population-based comparative study.

OBJECTIVES: To determine the clinical and economic impact of a community-based, hybrid model of in-person and virtual care by comparing health-system performance of the rural jurisdiction where this model was implemented with neighbouring jurisdictions without such a model and the broader regional health system. DESIGN: A cross-sectional comparative study. SETTING: Ontario, Canada, with a focus on three largely rural public health units from 1 April 2018 until 31 March 2021. PARTICIPANTS: All residents of Ontario, Canada under the age of 105 eligible for the Ontario Health Insurance Plan during the study period. INTERVENTIONS: An innovative, community-based, hybrid model of in-person and virtual care, the Virtual Triage and Assessment Centre (VTAC), was implemented in Renfrew County, Ontario on 27 March 2020. MAIN OUTCOME MEASURES: Primary outcome was a change in emergency department (ED) visits anywhere in Ontario, secondary outcomes included changes in hospitalisations and health-system costs, using per cent changes in mean monthly values of linked health-system administrative data for 2 years preimplementation and 1 year postimplementation. RESULTS: Renfrew County saw larger declines in ED visits (-34.4%, 95% CI -41.9% to -26.0%) and hospitalisations (-11.1%, 95% CI -19.7% to -1.5%) and slower growth in health-system costs than other rural regions studied. VTAC patients' low-acuity ED visits decreased by -32.9%, high-acuity visits increased by 8.2%, and hospitalisations increased by 30.0%. CONCLUSION: After implementing VTAC, Renfrew County saw reduced ED visits and hospitalisations and slower health-system cost growth compared with neighbouring rural jurisdictions. VTAC patients experienced reduced unnecessary ED visits and increased appropriate care. Community-based, hybrid models of in-person and virtual care may reduce the burden on emergency and hospital services in rural, remote and underserved regions. Further study is required to evaluate potential for scale and spread.

A population-based study of factors associated with systemic treatment in advanced prostate cancer decedents.

INTRODUCTION: Life-prolonging therapies (LPTs) are rapidly evolving for the treatment of advanced prostate cancer, although factors associated with real-world uptake are not well characterized. METHODS: In this cohort of prostate-cancer decedents, we analyzed factors associated with LPT access. Population-level databases from Ontario, Canada identified patients 65 years or older with prostate cancer receiving androgen deprivation therapy and who died of prostate cancer between 2013 and 2017. Univariate and multivariable analyses assessed the association between baseline characteristics and receipt of LPT in the 2 years prior to death. RESULTS: Of 3575 patients who died of prostate cancer, 40.4% (n = 1443) received LPT, which comprised abiraterone (66.3%), docetaxel (50.3%), enzalutamide (17.2%), radium-223 (10.0%), and/or cabazitaxel (3.5%). Use of LPT increased by year of death (2013: 22.7%, 2014: 31.8%, 2015: 41.8%, 2016: 49.1%, and 2017: 57.9%, p < 0.0001), driven by uptake of all agents except docetaxel. Adjusted odds of use were higher for patients seen at Regional Cancer Centers (OR: 1.8, 95% CI: 1.5-2.1) and who received prior prostate-directed therapy (OR: 1.3, 95% CI: 1.0-1.5), but lower with advanced age (≥85: OR: 0.54, 95% CI:0.39-0.75), increased chronic conditions (≥6: OR: 0.62, 95% CI: 0.43-0.92), and long-term care residency (OR: 0.38, 95% CI: 0.17-0.89). Income, stage at presentation, and distance to the cancer center were not associated with LPT uptake. CONCLUSION: In this cohort of prostate cancer-decedents, real-world uptake of novel prostate cancer therapies occurred at substantially higher rates for patients receiving care at Regional Cancer Centers, reinforcing the potential benefits for treatment access for patients referred to specialist centers.

A Time Series Analysis Evaluating Antibiotic Prescription Rates in Long-Term Care during the COVID-19 Pandemic in Alberta and Ontario, Canada.

The COVID-19 pandemic affected access to care, and the associated public health measures influenced the transmission of other infectious diseases. The pandemic has dramatically changed antibiotic prescribing in the community. We aimed to determine the impact of the COVID-19 pandemic and the resulting control measures on oral antibiotic prescribing in long-term care facilities (LTCFs) in Alberta and Ontario, Canada using linked administrative data. Antibiotic prescription data were collected for LTCF residents 65 years and older in Alberta and Ontario from 1 January 2017 until 31 December 2020. Weekly prescription rates per 1000 residents, stratified by age, sex, antibiotic class, and selected individual agents, were calculated. Interrupted time series analyses using SARIMA models were performed to test for changes in antibiotic prescription rates after the start of the pandemic (1 March 2020). The average annual cohort size was 18,489 for Alberta and 96,614 for Ontario. A significant decrease in overall weekly prescription rates after the start of the pandemic compared to pre-pandemic was found in Alberta, but not in Ontario. Furthermore, a significant decrease in prescription rates was observed for antibiotics mainly used to treat respiratory tract infections: amoxicillin in both provinces (Alberta: −0.6 per 1000 LTCF residents decrease in weekly prescription rate, p = 0.006; Ontario: −0.8, p < 0.001); and doxycycline (−0.2, p = 0.005) and penicillin (−0.04, p = 0.014) in Ontario. In Ontario, azithromycin was prescribed at a significantly higher rate after the start of the pandemic (0.7 per 1000 LTCF residents increase in weekly prescription rate, p = 0.011). A decrease in prescription rates for antibiotics that are largely used to treat respiratory tract infections is in keeping with the lower observed rates for respiratory infections resulting from pandemic control measures. The results should be considered in the contexts of different LTCF systems and provincial public health responses to the pandemic.

The Collapse of Infectious Disease Diagnoses Commonly Due to Communicable Respiratory Pathogens During the Coronavirus Disease 2019 Pandemic: A Time Series and Hierarchical Clustering Analysis.

Background: Nonpharmaceutical interventions such as physical distancing and mandatory masking were adopted in many jurisdictions during the coronavirus disease 2019 pandemic to decrease spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We determined the effects of these interventions on incidence of healthcare utilization for other infectious diseases. Methods: Using a healthcare administrative dataset, we employed an interrupted time series analysis to measure changes in healthcare visits for various infectious diseases across the province of Ontario, Canada, from January 2017 to December 2020. We used a hierarchical clustering algorithm to group diagnoses that demonstrated similar patterns of change through the pandemic months. Results: We found that visits for infectious diseases commonly caused by communicable respiratory pathogens (eg, acute bronchitis, acute sinusitis) formed distinct clusters from diagnoses that often originate from pathogens derived from the patient's own flora (eg, urinary tract infection, cellulitis). Moreover, infectious diagnoses commonly arising from communicable respiratory pathogens (hierarchical cluster 1: highly impacted diagnoses) were significantly decreased, with a rate ratio (RR) of 0.35 (95% confidence interval [CI], .30-.40; P < .001) after the introduction of public health interventions in April-December 2020, whereas infections typically arising from the patient's own flora (hierarchical cluster 3: minimally impacted diagnoses) did not demonstrate a sustained change in incidence (RR, 0.95 [95% CI, .90-1.01]; P = .085). Conclusions: Public health measures to curtail the incidence of SARS-CoV-2 were widely effective against other communicable respiratory infectious diseases with similar modes of transmission but had little effect on infectious diseases not strongly dependent on person-to-person transmission.