Describing COVID-19 immunizations for First Nations people on-reserve in Alberta using real-time integration of point of care and provincial data.

Background: COVID-19 profoundly impacted First Nation peoples. Historically, records of on- and off-reserve vaccine delivery have been fragmented. For the first time in Canada, we aimed to describe complete immunization rates, on- and off-reserve vaccine delivery, for COVID-19 in Alberta, Canada among First Nations on-reserve.

Characterizing dose changes and tapering among opioid users: A brief report on a population-level study in Alberta, Canada.

Objective: Monitoring changes in oral morphine equivalents (OMEs) is an important parameter to understand how opioids are being used at the population level. However, changes in opioid doses and tapering have not been well defined.

Design: We conducted a population-based exploratory data analysis (EDA) to characterize changes in opioid doses and tapering of opioids among patients in Alberta (AB).

Effectiveness of RADAR on diabetes processes of care for First Nations communities in Alberta, Canada.

The epidemic of type-2 diabetes in First Nations communities is tragic. Culturally-appropriate approaches addressing multiple components, focusing beyond glycemic control, are urgently needed. Using an intention-to-treat framework, 13 processes of care indicators were assessed to compare proportions of patients who received care at baseline relative to 2-year follow-up.

Defining opioid naïve and implications for monitoring opioid use: A population-based study in Alberta, Canada.

Purpose: Reducing initial exposure of "opioid naïve" patients to opioids is a public health priority. Identifying opioid naïve patients is difficult, as numerous definitions are used. The objective is to summarize current definitions and evaluate their impact on opioid naïve measures in Alberta.

Predicting 30-day risk from benzodiazepine/Z-drug dispensations in older adults using administrative data: A prognostic machine learning approach.

Objective: To develop a machine-learning (ML) model using administrative data to estimate risk of adverse outcomes within 30-days of a benzodiazepine (BZRA) dispensation in older adults for use by health departments/regulators.

Design, Setting And Participants: This study was conducted in Alberta, Canada during 2018-2019 in Albertans 65 years of age and older. Those with any history of malignancy or palliative care were excluded.

Effectiveness of RADAR: An Innovative Model to Organize Diabetes Care in First Nations Communities.

Challenges exist for the management of diabetes care in First Nations populations. RADAR (Reorganizing the Approach to Diabetes through the Application of Registries) is a culturally appropriate, innovative care model that incorporates a disease registry and electronic health record for local care provision with remote coordination, tailored for First Nations people. This study assessed the effectiveness of RADAR on patient outcomes and diabetes care organization in participating communities in Alberta, Canada.

Development and Validation of a Machine Learning Model to Estimate Risk of Adverse Outcomes Within 30 Days of Opioid Dispensation.

Importance: Machine learning approaches can assist opioid stewardship by identifying high-risk opioid prescribing for potential interventions.

Objective: To develop a machine learning model for deployment that can estimate the risk of adverse outcomes within 30 days of an opioid dispensation as a potential component of prescription drug monitoring programs using access to real-world data.

Design, Setting, And Participants: This prognostic study used population-level administrative health data to construct a machine learning model.

Mental health experiences with COVID-19 public health measures in an Alberta First Nations Community.

Background: First Nations (FN) people of Canada experience health, social, and systemic inequities due to colonization. Consequently, COVID-19 has placed further mental health stress on people related to personal finances, employment security and worry over infection, resulting in exacerbated effects of unresolved past medical and physical traumas. This study aims to understand the experiences related to mental health in an Alberta FN community during the early stages of the pandemic.

Appropriateness of COVID-19 public health guidelines for an Alberta First Nations community.

Objectives: The First Nations people experience significant challenges that may influence the ability to follow COVID-19 public health directives on-reserve. This study aimed to describe experiences, perceptions and circumstances of an Alberta First Nations community, related to COVID-19 public health advice. We hypothesized that many challenges ensued when following and implementing advice from public health experts.

Predicting 30-Day Readmissions in Patients With Heart Failure Using Administrative Data: A Machine Learning Approach.

Background: We sought to develop machine learning (ML) models trained on administrative data which predict risk of readmission in patients with heart failure and to evaluate and compare the ML model with the currently used LaCE score using clinically informative metrics.

Methods And Results: This prognostic study was conducted in Alberta, Canada, on 9845 patients with confirmed heart failure admitted to hospital between 2012 and 2019. The outcome was unplanned all-cause hospital readmission within 30 days of discharge.

Safe opioid prescribing: a prognostic machine learning approach to predicting 30-day risk after an opioid dispensation in Alberta, Canada.

Objective: To develop machine learning models employing administrative health data that can estimate risk of adverse outcomes within 30 days of an opioid dispensation for use by health departments or prescription monitoring programmes.

Design, Setting And Participants: This prognostic study was conducted in Alberta, Canada between 2017 and 2018. Participants included all patients 18 years of age and older who received at least one opioid dispensation.

Concurrent use of opioids and benzodiazepines/Z-drugs in Alberta, Canada and the risk of hospitalisation and death: a case cross-over study.

Objectives: Coprescribing of benzodiazepines/Z-drugs (BZDs) and opioids is a drug-use pattern of considerable concern due to risk of adverse events. The objective of this study is to estimate the effect of concurrent use of BZDs on the risk of hospitalisations/emergency department (ED) visits and deaths among opioid users.

Design, Setting And Participants: We conducted a population-based case cross-over study during 2016-2018 involving Albertans 18 years of age and over who received opioids.

Addressing the gaps in diabetes care in first nations communities with the reorganizing the approach to diabetes through the application of registries (RADAR): the project protocol.

Background: Type-2 diabetes rates in First Nations communities are 3-5 times higher than the general Canadian population, resulting in a high burden of disease, complications and comorbidity. Limited community nursing capacity, isolated environments and a lack of electronic health records (EHR)/registries lead to a reactive, disorganized approach to diabetes care for many First Nations people. The Reorganizing the Approach to Diabetes through the Application of Registries (RADAR) project was developed in alignments with federal calls for innovative, culturally relevant, community-specific programs for people with type-2 diabetes developed and delivered in partnership with target communities.

The integration of barcode scanning technology into Canadian public health immunization settings.

Background: As part of a series of feasibility studies following the development of Canadian vaccine barcode standards, we compared barcode scanning with manual methods for entering vaccine data into electronic client immunization records in public health settings.

Methods: Two software vendors incorporated barcode scanning functionality into their systems so that Algoma Public Health (APH) in Ontario and four First Nations (FN) communities in Alberta could participate in our study. We compared the recording of client immunization data (vaccine name, lot number, expiry date) using barcode scanning of vaccine vials vs.