Online geographic information systems for improving health planning practice : lessons learned from the case study of Logan-Beaudesert, Australia

This study examines the impact of utilising a Decision Support System (DSS) in a practical health planning study. Specifically, it presents a real-world case of a community-based initiative aiming to improve overall public health outcomes. Previous studies have emphasised that because of a lack of effective information, systems and an absence of frameworks for making informed decisions in health planning, it has become imperative to develop innovative approaches and methods in health planning practice. Online Geographical Information Systems (GIS) has been suggested as one of the innovative methods that will inform decision-makers and improve the overall health planning process. However, a number of gaps in knowledge have been identified within health planning practice: lack of methods to develop these tools in a collaborative manner; lack of capacity to use the GIS application among health decision-makers perspectives, and lack of understanding about the potential impact of such systems on users. This study addresses the abovementioned gaps and introduces an online GIS-based Health Decision Support System (HDSS), which has been developed to improve collaborative health planning in the Logan-Beaudesert region of Queensland, Australia. The study demonstrates a participatory and iterative approach undertaken to design and develop the HDSS. It then explores the perceived user satisfaction and impact of the tool on a selected group of health decision makers. Finally, it illustrates how decision-making processes have changed since its implementation. The overall findings suggest that the online GIS-based HDSS is an effective tool, which has the potential to play an important role in the future in terms of improving local community health planning practice. However, the findings also indicate that decision-making processes are not merely informed by using the HDSS tool. Instead, they seem to enhance the overall sense of collaboration in health planning practice. Thus, to support the Healthy Cities approach, communities will need to encourage decision-making based on the use of evidence, participation and consensus, which subsequently transfers into informed actions.

Subjective and Objective Indicators of Recovery in Severe Mental Illness: a Cross-Sectional Study

Background: This study aimed to determine whether subjective dimensions of recovery such as empowerment are associated with self-report of more objective indicators such as level of participation in the community and income from employment. A secondary aim was to investigate the extent to which diagnosis or other consumer characteristics mediated any relationship between these variables. Methods: The Community Integration Measure, the Empowerment Scale, the Recovery Assessment Scale, and the Camberwell Assessment of Needs Short Appraisal Schedule were administered to a convenience sample of 161 consumers with severe mental illness. Results: The majority of participants had a primary diagnosis of schizophreniform, anxiety/depression or bipolar affective disorder. The Empowerment Scale was quite strongly correlated with the Recovery Assessment Scale and the Community Integration Measure. Participants with a diagnosis of bipolar affective disorder had signifi cantly higher recovery and empowerment scores than participants with schizophrenia or depression. Both empowerment and recovery scores were significantly higher for people engaged in paid employment than for those receiving social security benefits. Conclusions: The measurement of subjective dimensions of recovery such as empowerment has validity in evaluation of global recovery for people with severe mental illness. A diagnosis of bipolar disorder is associated with higher scores on subjective and objective indicators of recovery.