Corrigendum to “Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature” [Int. J. Med. Inform. 82 (2013) 10–24]

IntroductionCanadians are living longer, many with multiple chronic conditions. This population of older, frail Canadians continues to grow in size as do concurrent demands for community-based, outpatient and ambulatory models of care. Ideally, a multifaceted, proactive, planned and integrated care model includes ehealth. Although several factors are known to facilitate the implementation of ehealth in chronic disease management (CDM), for example, adequate support, usability, alignment of programme objectives, there is a growing body of inconclusive evidence on what is critical for implementation. We aim to achieve a fulsome understanding of factors critical to implementation by conducting a realist review—an approach suitable for understanding complex interventions. Our proposed review will identify factors critical to the implementation of ehealth in CDM (heart failure, chronic obstructive pulmonary disease, chronic kidney disease and/or diabetes (type 1 or 2)) without limitations to care setting, language, publication year or geography. Findings will be presented in configurations of contexts, mechanisms and outcomes (CMOs).Methods and analysisA search strategy will be iteratively developed based on the concepts of ‘implementation’ and ‘adoption’ of ‘ehealth’ interventions used within ‘CDM’ to identify the peer-reviewed and grey literature published before 31 March 2021 from five databases (Medline, Embase, Cochrane, CINAHL and PsychInfo) on ehealth interventions actively involving a healthcare provider for CDM among adults. Data extraction and synthesis will be guided by Realist and Meta-review Evidence Synthesis: Evolving Standards (RAMESES) guidelines informing core concepts of CMOs, and a study output will include a middle-range-theory describing the implementation of ehealth in CDM.Ethics and disseminationFindings will be published in an open-access peer-reviewed journal and presented at relevant conferences. A multistakeholder (patients, caregivers, healthcare providers and practitioners, decision-makers and policy-makers) perspective will be used in our dissemination approach. No formal ethics approval is required for this review.PROSPERO registration numberCRD42020208275.

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The Evidence-base for Using Ontologies and Semantic Integration Methodologies to Support Integrated Chronic Disease Management in Primary and Ambulatory Care: Realist Review

Yearbook of Medical Informatics ◽

10.1055/s-0038-1638846 ◽

2013 ◽

Vol 22 (01) ◽

pp. 147-154 ◽

Cited By ~ 6

Author(s):

H. Liyanage ◽

S.-T. Liaw ◽

C. Kuziemsky ◽

A. L. Terry ◽

S. Jones ◽

...

Keyword(s):

Chronic Disease ◽

Disease Management ◽

Ambulatory Care ◽

Chronic Disease Management ◽

Community Support ◽

Realist Review ◽

Evidence Base ◽

Semantic Integration ◽

Data Sources ◽

Integration Methods

Summary Background: Most chronic diseases are managed in primary and ambulatory care. The chronic care model (CCM) suggests a wide range of community, technological, team and patient factors contribute to effective chronic disease management. Ontologies have the capability to enable formalised linkage of heterogeneous data sources as might be found across the elements of the CCM. Objective: To describe the evidence base for using ontologies and other semantic integration methods to support chronic disease management. Method: We reviewed the evidence-base for the use of ontologies and other semantic integration methods within and across the elements of the CCM. We report them using a realist review describing the context in which the mechanism was applied, and any outcome measures. Results: Most evidence was descriptive with an almost complete absence of empirical research and important gaps in the evidence-base. We found some use of ontologies and semantic integration methods for community support of the medical home and for care in the community. Ubiquitous information technology (IT) and other IT tools were deployed to support self-management support, use of shared registries, health behavioural models and knowledge discovery tools to improve delivery system design. Data quality issues restricted the use of clinical data; however there was an increased use of interoperable data and health system integration. Conclusions: Ontologies and semantic integration methods are emergent with limited evidence-base for their implementation. However, they have the potential to integrate the disparate community wide data sources to provide the information necessary for effective chronic disease management.

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