Defining a core set of research and development priorities for virtual care in the post-pandemic environment: a call to action.

Objectives: To identify research and development priorities for virtual care following the coronavirus disease 2019 pandemic from the perspective of key stakeholders (patients, clinicians, informaticians and academics).

Design: Qualitative study using a modified nominal group technique.

Setting: Online semi-structured interviews and workshops held in November 2022 and February 2023.

Barriers, facilitators and next steps for sustaining and scaling virtual hospital services in Australia: a qualitative descriptive study.

Objective: To describe the barriers to and facilitators of implementing and delivering virtual hospital (VH) services, and evidence and practice gaps where further research and policy changes are needed to drive continuous improvement.

Study Design: Qualitative descriptive study.

Setting, Participants: Online semi-structured interviews and a focus group were conducted between July 2022 and April 2023 with doctors, nurses and leadership staff involved in VH services at three sites in New South Wales, Australia.

Coordinating Health Care With Artificial Intelligence-Supported Technology for Patients With Atrial Fibrillation: Protocol for a Randomized Controlled Trial.

Background: Atrial fibrillation (AF) is an increasingly common chronic health condition for which integrated care that is multidisciplinary and patient-centric is recommended yet challenging to implement.

Objective: The aim of Coordinating Health Care With Artificial Intelligence-Supported Technology in AF is to evaluate the feasibility and potential efficacy of a digital intervention (AF-Support) comprising preprogrammed automated telephone calls (artificial intelligence conversational technology), SMS text messages, and emails, as well as an educational website, to support patients with AF in self-managing their condition and coordinate primary and secondary care follow-up.

Methods: Coordinating Health Care With Artificial Intelligence-Supported Technology in AF is a 6-month randomized controlled trial of adult patients with AF (n=385), who will be allocated in a ratio of 4:1 to AF-Support or usual care, with postintervention semistructured interviews.

Can existing electronic medical records be used to quantify cardiovascular risk at point of care?

Background: Using electronic data for cardiovascular risk stratification could help in prioritising healthcare access and optimise cardiovascular prevention.

Aims: To determine whether assessment of absolute cardiovascular risk (Australian absolute cardiovascular disease risk (ACVDR)) and short-term ischaemic risk (History, ECG, Age, Risk factors, and Troponin (HEART) score) is possible from available data in Electronic Medical Record (EMR) and My Health Record (MHR) of patients presenting with acute cardiac symptoms to a Rapid Access Cardiology Clinic (RACC).

Methods: Audit of EMR and MHR on 200 randomly selected adults who presented to RACC between 1 March 2017 and 4 February 2020.