Digital Health Technology for Real-World Clinical Outcome Measurement Using Patient-Generated Data: Systematic Scoping Review.

BACKGROUND: Digital health technologies (DHTs) play an ever-expanding role in health care management and delivery. Beyond their use as interventions, DHTs also serve as a vehicle for real-world data collection to characterize patients, their care journeys, and their responses to other clinical interventions. There is a need to comprehensively map the evidence-across all conditions and technology types-on DHT measurement of patient outcomes in the real world. OBJECTIVE: We aimed to investigate the use of DHTs to measure real-world clinical outcomes using patient-generated data. METHODS: We conducted this systematic scoping review in accordance with the Joanna Briggs Institute methodology. Detailed eligibility criteria documented in a preregistered protocol informed a search strategy for the following databases: MEDLINE (Ovid), CINAHL, Cochrane (CENTRAL), Embase, PsycINFO, ClinicalTrials.gov, and the EU Clinical Trials Register. We considered studies published between 2000 and 2022 wherein digital health data were collected, passively or actively, from patients with any specified health condition outside of clinical visits. Categories for key concepts, such as DHT type and analytical applications, were established where needed. Following screening and full-text review, data were extracted and analyzed using predefined fields, and findings were reported in accordance with established guidelines. RESULTS: The search strategy identified 11,015 publications, with 7308 records after duplicates and reviews were removed. After screening and full-text review, 510 studies were included for extraction. These studies encompassed 169 different conditions in over 20 therapeutic areas and 44 countries. The DHTs used for mental health and addictions research (111/510, 21.8%) were the most prevalent. The most common type of DHT, mobile apps, was observed in approximately half of the studies (250/510, 49%). Most studies used only 1 DHT (346/510, 67.8%); however, the majority of technologies used were able to collect more than 1 type of data, with the most common being physiological data (189/510, 37.1%), clinical symptoms data (188/510, 36.9%), and behavioral data (171/510, 33.5%). Overall, there has been real growth in the depth and breadth of evidence, number of DHT types, and use of artificial intelligence and advanced analytics over time. CONCLUSIONS: This scoping review offers a comprehensive view of the variety of types of technology, data, collection methods, analytical approaches, and therapeutic applications within this growing body of evidence. To unlock the full potential of DHT for measuring health outcomes and capturing digital biomarkers, there is a need for more rigorous research that goes beyond technology validation to demonstrate whether robust real-world data can be reliably captured from patients in their daily life and whether its capture improves patient outcomes. This study provides a valuable repository of DHT studies to inform subsequent research by health care providers, policy makers, and the life sciences industry. TRIAL REGISTRATION: Open Science Framework 5TMKY; https://osf.io/5tmky/.

Real World Studies of Psoriasis and Mental Illness in Newfoundland and Labrador.

BACKGROUND: Psoriasis is a chronic, immune-mediated inflammatory disease with an implied connection to psychiatric disorders. OBJECTIVE: This study aims to illustrate an association between psoriasis and psychiatric disorders using real world data gathered from the Newfoundland and Labrador population. METHODS: Data on 15,100 patients with psoriasis and 75,500 controls (1:5) was collected from the Newfoundland and Labrador Centre for Health Information's Electronic Health Records. The cases and controls were matched for age, sex, and geography. Indicators for psychiatric disorders include diagnosis of mental illnesses from physician's visits and hospitalization records (all coded for mental health using ICD-9 and ICD-10 codes). RESULTS: 9,991 (66.2%) cases were identified to have at least one visit with a diagnostic code for mental illness compared to 42,276 (56.0%), P < .0001 in the control group. The percentage of people coded for anxiety was 36.50% compared to 28.95%, P < .0001; depression was 37.04% compared to 30.19%, P < .0001; and adjustment disorder was 6.89% versus 5.48%, P < .0001, among those with and without psoriasis, respectively. The greatest risk for anxiety [OR 1.4 (1.20, 1.67)] and depression [OR 1.65 (1.36, 2.00)] among psoriasis patients was between the 0 to 20 age group. Women with psoriasis are more likely to have anxiety [OR 1.08 (1.03, 1.13)], depression [OR 1.04 (1.01, 1.09)] and adjustment disorder [OR 1.07 (0.98, 1.17)] compared to female controls. CONCLUSION: Our result shows that patients with psoriasis have an increased prevalence of mental illness. Using real world data to carry out further investigations will better elucidate this association and provide an increased understanding of the association between psoriasis and mental disorders.

Walking the Path Together: Indigenous Health Data at ICES.

Indigenous data governance principles assert that Indigenous communities have a right to data that identifies their people or communities, and a right to determine the use of that data in ways that support Indigenous health and self-determination. Indigenous-driven use of the databases held at the Institute for Clinical Evaluative Sciences (ICES) has resulted in ongoing partnerships between ICES and diverse Indigenous organizations and communities. To respond to this emerging and complex landscape, ICES has established a team whose goal is to support the infrastructure for responding to community-initiated research priorities. ICES works closely with Indigenous partners to develop unique data governance agreements and supports processes, which ensure that ICES scientists must work with Indigenous organizations when conducting research that involves Indigenous peoples.

Do parents' support behaviours predict whether or not their children get sufficient sleep? A cross-sectional study.

BACKGROUND: Sleep is an essential component of healthy cognitive and physical development. Lack of sleep may put children at risk for a variety of mental and physical health outcomes, including overweight, obesity and related chronic diseases. Given that children's sleep duration has decreased in recent decades, there is a need to understand the determinants of child sleep, including the role of parental support behaviours. This study aims to determine the relative contribution of different types of parental support behaviours for predicting the likelihood that children meet recently established Canadian sleep guidelines. METHODS: Data were collected using Computer Assisted Telephone Interviews (CATI) of parents or guardians with at least one child under the age of 18 living in Ontario, Canada. To align with sleep guidelines, parents included in this analysis had at least one child between 5 and 17 years of age (n = 1622). Two multivariable logistic regression models were built to predict whether or not parents reported their child was meeting sleep guidelines - one for weekday sleep and another for sleep on weekends. Independent variables included parent and child age and gender, motivational and regulatory parental support behaviours, and socio-demographic characteristics. RESULTS: On weekdays, enforcing rules about child bedtime was a significant positive predictor of children meeting sleep guidelines (OR: 1.59; 95% CI: 1.03-2.44); while encouraging the child to go to bed at a specific time was a significant negative predictor of child meeting sleep guidelines (OR: 0.29; 95% CI: 0.13-0.65). On weekends, none of the parental support behaviours contributed significantly to the predictions of child sleep. For both weekdays and weekends, the child's age group was an important predictor of children meeting sleep guidelines. CONCLUSIONS: The contribution of parental support behaviours to predictions of children meeting sleep guidelines varied with the type of support provided, and weekend versus weekday sleep. While only enforcing bedtime rules on weekdays contributed to children meeting sleep guidelines, the importance of children getting a good night's sleep, and the capacity of parents to help them do so, should be emphasized in public health efforts promoting healthy child development.

The impact of different types of parental support behaviours on child physical activity, healthy eating, and screen time: a cross-sectional study.

BACKGROUND: In Canada, 31.5 % of children are overweight or obese, putting them at an increased risk of chronic co-morbidities and premature mortality. Physical activity, healthy eating, and screen time are important behavioural determinants of childhood overweight and obesity that are influenced by the family environment, and particularly parents' support behaviours. However, there is currently a limited understanding of which types of these support behaviours have the greatest positive impact on healthy child behaviours. This study aims to determine the relative contribution of different types of parental support behaviours for predicting the likelihood that children meet established guidelines for daily physical activity, daily fruit and vegetable consumption, and recreational screen time. METHODS: A Computer Assisted Telephone Interview survey was used to collect data from a random sample of parents or guardians with at least one child under the age of 18 in Ontario (n = 3,206). Three multivariable logistic regression models were built to predict whether or not parents reported their child was meeting guidelines. Independent variables included parent and child age and gender, multiple indicators of parental support behaviours, and socio-demographic characteristics. Parental support behaviours were categorized post-hoc as motivational, instrumental, regulatory, and conditional based on an adapted framework. RESULTS: Controlling for all other factors in the model, several parental support behaviours were found to be significant predictors of children meeting established health guidelines. For example, conditional support behaviours including taking the child to places where they can be active (OR: 2.06; 95 % CI: 1.32-3.21), and eating meals as a family away from the TV (95 % CI: 1.15-2.41) were significant positive predictors of children meeting physical activity and fruit and vegetable guidelines, respectively. CONCLUSIONS: Health promotion efforts aimed at improving particular parent support behaviours could be effective levers for mitigating the burden of excess body weight in childhood. As such, the influence of support behaviours should be fully considered in any comprehensive approach to prevention and reduction of childhood overweight and obesity.

Laying the foundation for Real-world evidence studies: a case study from Newfoundland and Labrador.

The Janssen and Newfoundland and Labrador Health Innovation Partnership (JANL-HIP) was established to carry out Real-World Evidence (RWE) projects to generate evidence about disease pathways, healthcare delivery, the effects of clinical interventions. Doing so will support and influence clinical decision-making in Newfoundland and Labrador (NL). This case study describes the foundational elements necessary for a real-world evidence generation project in NL and may provide learning for the effective execution of real-world studies in other jurisdictions. It uses an ongoing project in psoriatic disease in NL to illustrate the partnership and the benefits of RWE studies. Ultimately, the JANL-HIP RWE project aims to inform decisions that will drive improvements in health outcomes, system delivery, and policy mutually beneficial to health ecosystem stakeholders.

Unlocking First Nations health information through data linkage.

INTRODUCTION: The importance of Indigenous data sovereignty and Indigenous-led research processes is increasingly being recognized in Canada and internationally. For First Nations in Ontario, Canada, access to routinely-collected demographic and health systems data is critical to planning and measuring health status and outcomes in their populations. Linkage of this data with the Indian Register (IR), under First Nations data governance, has unlocked data for use by First Nations organizations and communities. OBJECTIVES: To describe the linkage of the IR database to the Ontario Registered Persons Database (RPDB) within the context of Indigenous data sovereignty principles. METHODS: Deterministic and probabilistic record linkage methods were used to link the IR to the RPDB. There is no established population of First Nations people living in Ontario with which we could establish a linkage rate. Accordingly, several approaches were taken to determine a denominator that would represent the total population of First Nations we would hope to link to the RPDB. RESULTS: Overall, 201,678 individuals in the national IR database matched to Ontario health records by way of the RPDB, of which 98,562 were female and 103,116 were male. Of those First Nations individuals linked to the RPDB, 90.2% (n=181,915) lived in Ontario when they first registered with IR, or were affiliated with an Ontario First Nation Community. The proportion of registered First Nations people linking to the RPDB improved across time, from 62.8% in the 1960s to 94.5% in 2012. CONCLUSION: This linkage of the IR and RPDB has resulted in the creation of the largest First Nations health research study cohort in Canada. The linked data are being used by First Nations communities to answer questions that ultimately promote wellbeing, effective policy, and healing.