A study to guide the design and implementation of a chronic disease management register in a regional health service

Abstract

Background. The mounting burden of chronic disease associated with population ageing creates a challenge for health systems. Healthcare organisations are addressing this challenge by exploring new ways to improve patient health outcomes, including through the use of information technologies. Aim. This research aimed to identify key design features of a chronic disease management (CDM) register for the public sector health services provided in the Australian Capital Territory. Methods and setting. ACT Health, a government agency, is the largest health service provider in the ACT. An organisational analysis of ACT Health was conducted using qualitative, quantitative, and participant observation methods. Three index conditions- Chronic Heart Failure, Chronic Obstructive Pulmonary Disease, and Diabetes Mellitus Type 2 defined information according to the 'International Statistical Classification of Diseases and Health Related Problems: lOth Revision, Australian Modification' (ICD-10-AM)­ were chosen for data collection and analysis. Results. ACT Health policies support evidence-based CDM interventions, but their implementation has been slow and disjointed. This research found that support for CDM in ACT Health is within the 'basic support' range as measured by the MacColl Institute's Assessment of Chronic Illness Care (ACIC) survey. The survey revealed continuity of care as a concern. On the positive side, factor analysis of the survey results identified a novel 'patient empowerment' factor that was strength within ACT Health. This patient empowerment factor is somewhat more than a concept; it is one of the powerful predictors of positive outcomes for CDM interventions, and has policy importance in this particular regional health system for working toward CDM goals. In the participant observation aspect of this research, these findings were taken up to enrich the design features for an effective CDM register by incorporating the views of health professionals, patients and their carers. This research identified five data categories and associated variables required to support a CDM register. These five data categories are patient details, medical details, provider details, prevention details, and case coordination details. The prevention detail category is the centre of a CDM register intervention and consists of diagnostic, therapeutic and behavioural sub-categories. However, the research identified challenges regarding availability and completeness of these data in all five categories. Combining the survey and participant observation suggests that electronically incorporating standardised clinical information into a CDM register should enhance multidisciplinary communication, care planning and coordinated service delivery. A clinical data repository with data extraction and filtration systems compliant with the Health Level Seven International (HL7) metadata standard would enable the organisation to populate a CDM register's data fields from multiple sources. Conclusion. A health service specific CDM register based on established data standards can actively support effective CDM interventions within the service. Further expansion toward a population-based CDM register would depend on implementation of local and national e-Health initiatives to standardise clinical information for automatic extraction into CDM registers. The research provides policy and design recommendations to further strengthen chronic care processes to benefit patients with chronic diseases, their carers and health service providers.