Epidemiology of multimorbidity in childhood cancer survivors: a matched cohort study of inpatient hospitalisations in Western Australia.

Background: Childhood cancer survivors (CCS) experience an elevated burden of health complications, underscoring the importance of understanding the patterns of multimorbidity to guide the management of survivors with complex medical needs.

Methods: We examined the patterns of hospitalisations with multimorbidity in 5-year CCS (n = 2938) and age- and sex-matched non-cancer comparisons (n = 24,792) using statewide records of inpatient admissions in Western Australia from 1987 to 2019.

Results: Multimorbidity rates were higher for CCS (10.

Co-Design and Evaluation Protocol for the RECOVER Model of Care After Childhood Cancer Treatment.

Advances in diagnosis and treatment have significantly increased survival rates for childhood cancer, leading to a growing population of long-term survivors. However, these survivors face substantial physical and psychological sequelae that affect both the child and their family. We developed the RECOVER model of care to support childhood cancer survivors as they transition from the end of their planned treatment to survivorship, addressing the broader health and wellness needs beyond medical surveillance.

Baseline Characteristics of Frailty and Disease Stage in Older People Living With CKD.

Introduction: The GOAL trial, a cluster randomized controlled trial, investigated the effect of comprehensive geriatric assessment (CGA) on frail older people with chronic kidney disease (CKD). This paper describes the following: (i) participant baseline characteristics, and (ii) their relationship with CKD stage and frailty severity.

Methods: Sixteen kidney outpatient clinics (clusters) were randomly allocated 1:1 to CGA or usual care.

Decades in the Making: The Evolution of Digital Health Research Infrastructure Through Synthetic Data, Common Data Models, and Federated Learning.

Traditionally, medical research is based on randomized controlled trials (RCTs) for interventions such as drugs and operative procedures. However, increasingly, there is a need for health research to evolve. RCTs are expensive to run, are generally formulated with a single research question in mind, and analyze a limited dataset for a restricted period.

Artificial intelligence after the bedside: co-design of AI-based clinical informatics workflows to routinely analyse patient-reported experience measures in hospitals.

Objective: To co-design artificial intelligence (AI)-based clinical informatics workflows to routinely analyse patient-reported experience measures (PREMs) in hospitals.

Methods: The context was public hospitals (n=114) and health services (n=16) in a large state in Australia serving a population of ~5 million. We conducted a participatory action research study with multidisciplinary healthcare professionals, managers, data analysts, consumer representatives and industry professionals (n=16) across three phases: (1) defining the problem, (2) current workflow and co-designing a future workflow and (3) developing proof-of-concept AI-based workflows.

System-wide analysis of qualitative hospital incident data: Feasibility of semi-automated content analysis to uncover insights.

Background: Advances in technology have increased the ease of reporting hospital incidents, resulting in large amounts of qualitative descriptive data. Health services have little experience analysing these data at scale to incorporate into routine reporting.

Objective: We aimed to explore the feasibility of applying a semi-automated content analysis (SACA) tool (Leximancer™) to qualitative descriptions of system-wide hospital incidents to provide insights into safety issues at all health service levels.

Healthcare dashboard technologies and data visualization for lipid management: A scoping review.

Background: Lipid disorders significantly increase cardiovascular disease (CVD) risk, the leading cause of mortality worldwide. Effective lipid management is critical for improving health outcomes. Traditional screening methods face challenges due to data complexity and the need for timely decision-making.

Association between preterm birth and economic and educational outcomes in adulthood: A population-based matched cohort study.

Background And Objectives: Preterm birth (PTB) affects ~10% of births worldwide; however, most literature focused on short-term clinical outcomes, with much less focus on long-term socioeconomic outcomes after PTB. We examined associations between PTB and individuals' income, employment, and educational outcomes during early adulthood.

Methods: We conducted a population-level matched cohort study including all live births in Canada between 1990 and 1996, followed until 2018.

Medical imaging utilization in migrants compared with nonmigrants in a universal healthcare system: A population-based matched cohort study.

Background: Medical imaging is an integral part of healthcare. Globalization has resulted in increased mobilization of migrants to new host nations. The association between migration status and utilization of medical imaging is unknown.

From many voices, one question: Community co-design of a population-based qualitative cancer research study.

Purpose: This study formed the development stage of a population-based survey aiming to: (i) understand the needs and experiences of people affected by cancer in Queensland, Australia and (ii) recruit a pool of participants for ongoing cancer survivorship research. The current study aimed to co-design and test a single qualitative survey question and study invitation materials to maximise acceptability of, and participation in, the survey and future research.

Methods: Fifty-two community members, including cancer survivors and caregivers, participated across 15 co-design workshops and 20 pretest interviews.

Examining emotional and behavioural trajectories in siblings of children with life-limiting conditions.

Background: Healthy siblings of children with life-limiting conditions often experience emotional and behavioural struggles over the course of the ill child's condition(s). Resources to support these siblings are limited due to a lack of understanding about their needs. Therefore, this study was designed to characterize the emotional and behavioural trajectories among siblings of children with progressive, life-limiting genetic, metabolic, or neurological conditions over a 12-month observation period.

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers.

Background: Efforts are underway to capitalize on the computational power of the data collected in electronic medical records (EMRs) to achieve a learning health system (LHS). Artificial intelligence (AI) in health care has promised to improve clinical outcomes, and many researchers are developing AI algorithms on retrospective data sets. Integrating these algorithms with real-time EMR data is rare.

What is measured matters: A scoping review of analysis methods used for qualitative patient reported experience measure data.

Introduction: Hospitals are increasingly turning to patients for valuable feedback regarding their care experience. A common method to collect this information is patient reported experience measures (PREMs) surveys. Health care workers report qualitative PREMs as more interesting, relevant, and informative than quantitative survey responses.

Preterm Birth, Family Income, and Intergenerational Income Mobility.

Importance: Preterm birth (PTB) has been associated with lower income in adulthood, but associations with intergenerational income mobility and the role of family socioeconomic status (SES) as modifying factor are unclear.

Objectives: To assess whether the association between PTB and income differs according to family SES at birth and to assess the association between PTB and intergenerational income mobility.

Design, Setting, And Participants: This study comprised a matched cohort of live births in Canada between January 1, 1990, and December 31, 1996, with follow-up until December 31, 2018.

Corrigendum: Second malignant neoplasms within 5 years from first primary diagnosis in pediatric oncology patients in Canada: a population-based retrospective cohort study.

[This corrects the article DOI: 10.3389/fonc.2024.

Childhood cancer models of survivorship care: a scoping review of elements of care and reported outcomes.

Purpose: This study aimed to systematically map elements of care and respective outcomes described in the literature for different models of post-treatment care for survivors of childhood cancer.

Methods: MEDLINE, CINAHL, and Embase were searched with combinations of free text terms, synonyms, and MeSH terms using Boolean operators and are current to January 2024. We included studies that described post-treatment cancer survivorship models of care and reported patient or service level elements of care or outcomes, which we mapped to the Quality of Cancer Survivorship Care Framework domains.

Second malignant neoplasms within 5 years from first primary diagnosis in pediatric oncology patients in Canada: a population-based retrospective cohort study.

Introduction: From the advancement of treatment of pediatric cancer diagnosis, the five-year survival rate has increased significantly. However, the adverse consequence of improved survival rate is the second malignant neoplasm. Although previous studies provided information on the incidence and risk of SMN in long term survivors of childhood cancer, there is still scarce information known for short term (< 5 years) prognosis.

Physical function patient-reported outcomes among adolescent and young adult cancer survivors: A systematic review.

Background: The physical challenges faced by adolescents and young adults (AYA) after a cancer diagnosis may be different from those experienced by paediatric and older adult cancer patients. Patient-reported outcome measures (PROMs) are valuable tools that can be useful in exploring the experiences of AYAs and identifying important issues, recurrent themes and areas to potentially improve quality of life.

Objective: We compared patient-reported physical function outcomes between AYAs diagnosed with cancer and non-cancer controls.

Psychiatric disorders in childhood cancer survivors: A retrospective matched cohort study of inpatient hospitalisations and community-based mental health services utilisation in Western Australia.

Objective: We examined the impact of long-term mental health outcomes on healthcare services utilisation among childhood cancer survivors in Western Australia using linked hospitalisations and community-based mental healthcare records from 1987 to 2019.

Method: The study cohort included 2977 childhood cancer survivors diagnosed with cancer at age < 18 years in Western Australia from 1982 to 2014 and a matched non-cancer control group of 24,994 individuals. Adjusted hazard ratios of recurrent events were estimated using the Andersen-Gill model.

Development and validation of thromboembolism diagnostic algorithms in children with cancer from real-world data.

Objective: To evaluate the accuracy of diagnostic algorithms developed using the International Classification of Diseases (ICD-9-CM and ICD-10-CA) diagnostic codes and physician billing codes for thromboembolism (TE) from health administrative data compared to chart review diagnoses of TE in children with cancer.

Methods: Using data linkage between the Pediatric Oncology Group of Ontario Network Information System (Ontario pediatric cancer registry) and various administrative data housed at ICES, eight algorithms were developed including a single reference to one of the billing codes, multiple references with varying time intervals, and combinations of various billing codes during primary cancer therapy for the whole cohort and, for early (<04/2002) and later (≥04/2002, solely ICD-10 codes) periods. Reference standard was chart review data from prior studies (from 1990 to 2016) among children (≤19 years) with cancer and radiologically confirmed TE.

Patient Reported Fatigue Among Adolescent and Young Adult Cancer Patients Compared to Non-Cancer Patients: A Systematic Review and Meta-Analysis.

Adolescent and young adult (AYA) cancer patients and survivors are a growing population due to more frequent diagnoses and improved survival. Fatigue is a common symptom experienced by cancer patients and it is often missed by health care professionals. Patient reported outcome measures (PROMs) can assist in evaluating patient reported fatigue.

Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy.

Background: There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of inconsistent methods of estimating baseline serum creatinine (sCr) may result in a poor understanding of these models' effectiveness in clinical practice. Until now, the performance of such models with different baselines has not been compared on a single dataset.