A novel technology for harmonizing and analyzing cancer data. Observations from integrating health connect in Newfoundland and Labrador, Canada.

Objective: This article aims to describe the implementation of a new health information technology system called Health Connect that is harmonizing cancer data in the Canadian province of Newfoundland and Labrador; explain high-level technical details of this technology; provide concrete examples of how this technology is helping to improve cancer care in the province, and to discuss its future expansion and implications. Methods: We give a technical description of the Health Connect architecture, how it integrated numerous data sources into a single, scalable health information system for cancer data and highlight its artificial intelligence and analytics capacity. Results: We illustrated two practical achievements of Health Connect. First, an analytical dashboard that was used to pinpoint variations in colon cancer screening uptake in small defined geographic regions of the province; and second, a natural language processing algorithm that provided AI-assisted decision support in interpreting appropriate follow-up action based on assessments of breast mammography reports. Conclusion: Health Connect is a cutting-edge, health systems solution for harmonizing cancer screening data for practical decision-making. The long term goal is to integrate all cancer care data holdings into Health Connect to build a comprehensive health information system for cancer care in the province.

Development and preliminary testing of the psychosocial adjustment to hereditary diseases scale.

BACKGROUND: The presence of Lynch syndrome (LS) can bring a lifetime of uncertainty to an entire family as members adjust to living with a high lifetime cancer risk. The research base on how individuals and families adjust to genetic-linked diseases following predictive genetic testing has increased our understanding of short-term impacts but gaps continue to exist in knowledge of important factors that facilitate or impede long-term adjustment. The failure of existing scales to detect psychosocial adjustment challenges in this population has led researchers to question the adequate sensitivity of these instruments. Furthermore, we have limited insight into the role of the family in promoting adjustment. METHODS: The purpose of this study was to develop and initially validate the Psychosocial Adjustment to Hereditary Diseases (PAHD) scale. This scale consists of two subscales, the Burden of Knowing (BK) and Family Connectedness (FC). Items for the two subscales were generated from a qualitative data base and tested in a sample of 243 participants from families with LS. RESULTS: The Multitrait/Multi-Item Analysis Program-Revised (MAP-R) was used to evaluate the psychometric properties of the PAHD. The findings support the convergent and discriminant validity of the subscales. Construct validity was confirmed by factor analysis and Cronbach's alpha supported a strong internal consistency for BK (0.83) and FC (0.84). CONCLUSION: Preliminary testing suggests that the PAHD is a psychometrically sound scale capable of assessing psychosocial adjustment. We conclude that the PAHD may be a valuable monitoring tool to identify individuals and families who may require therapeutic interventions.

Does higher continuity of family physician care reduce hospitalizations in elderly people with diabetes?

The objective of this study was to investigate the relationship between continuity of family physician (FP) care and inpatient hospitalizations in elderly people with diabetes who have universally-insured health care. We constructed a population-based retrospective cohort study using a sample of 1143 people aged 65 years or older with newly diagnosed diabetes who were selected from a longitudinal surveillance database in the province of Newfoundland and Labrador (NL), Canada. Continuity of FP care was estimated by 3 chronological indices (Continuity of Care [COC], Usual Provider Continuity [UPC], and Sequential Continuity [SECON]) using administrative physician claims data. Age, sex, number of chronic conditions, and income were used as control variables. People with high continuity had lower crude rates of hospitalization than those with lower continuity. Log-linear regression analysis showed that higher continuity was associated with decreased rates of hospitalization in an unadjusted model [rate ratio (95% confidence interval)]; COC: 0.73 (0.61-0.86); UPC: 0.71 (0.59-0.86); SECON: 0.64 (0.52-0.78), and after adjusting for control variables; COC: 0.82 (0.69-0.97); UPC: 0.82 (0.68-0.98); SECON: 0.75 (0.61-0.91). Other significant predictors of reduced hospitalizations were female sex, fewer chronic conditions, and higher income. The findings suggest that high levels of continuity of FP care are associated with reduced hospitalizations in elderly people with diabetes within a universally-insured health care system.