Need for an integrated database

Based on the discussion in this chapter, chronic care and secondary prevention requires monitoring of care management processes and intervention outcomes. The CCM is the most acceptable approach where a service specific disease register is the central feature to manage population and individuals with chronic illnesses (Bodenheimer et al. 2002a). The use of a service specific disease register has roles to tailor CDM

interventions according to the need of patients and health care professionals (Benedetti et al. 2006).

The implementation of an evidence-based guideline, reminder system, patient self- management support and a service specific disease management register are collectively known as care management processes (CMPs). The CMP elements are integrated in the CCM to support delivery of chronic care and prevention interventions. Healthcare organisations with a CDM register are more capable of generating actions than those without a register (Schmittdiel et al. 2005). However, except for diabetes, the concept of disease registers had not been implemented for other common chronic conditions on a wide scale.

Substantial evidence demonstrates that a disease-specific register is an important system element to make sure of implementation of evidence-based chronic care. A CDM register incorporated within a health system also facilitates service planning (Penn et al. 2004). A CDM register links clinical data with other relevant service databases and

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enhances insights into the effectiveness of clinical and prevention interventions (Ivanov 2001).

The study ‘Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF)’ evaluated a national hospital-based initiative on quality of care for HF patients. The initiative used a web-based register and collected both outcome and administrative data. Under this study, 259 US-based hospitals participated and submitted data on 48,612 patients. The reports from the web-based register helped when comparing performances between hospitals and provided feedback to treating teams (Fonarow et al. 2007).

In searching for clinical and financial benefits of information technology (IT) in disease management programs, Bu and others used different IT models. These IT models include disease register, remote monitoring, and self-management support for diabetes patients in the US. The project examined the impact of IT on care delivery, clinical outcomes and costs. The results suggested that IT-based disease management programs assist secondary prevention and appearance of complications (Bu et al. 2007).

Healthcare demands multi-disciplinary interaction for collaborative diagnosis, treatment assessment, planning and decision-making. These elements need support to a greater degree in healthcare organisations than other sectors. This collaboration can deliver optimum output with the use of clinical data (Hummel 2000; Connell and Young 2007).

IT-based clinical information systems can facilitate CDM processes through setting up reminder systems. The reminder system provides feedback to physicians on

performance, and they link primary care teams to comply with practice guidelines. Presence of a disease register within an IT-based clinical information system can assist care teams in efficient service planning and implementation of prevention interventions.

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A disease register contains relevant clinical and administrative data of a group of patients with particular chronic conditions of interest (Bodenheimer et al. 2002a).

Healthcare organisations with an electronic medical record (EMR) system help providers to easily access and recover clinical records. The EMR supports health care providers at the point of care but has limited roles in the CDM. A disease register is a more affordable and practical tool than an EMR for population-based interventions (California HealthCare Foundation 2004). A disease register can identify the patients with specific illnesses of interest and provides information about care delivery processes in relation to evidence-based guidelines. A CDM register linked with EMR can generate more inclusive information about the patients (Metzger 2004).

Based on the analysis of literature review, an active CDM register is able to

 link between care strategies and patients’ care according to CCM  support evidence-based care

 develop reports on key indicators and their outcomes including trend data for benchmarking continuous quality improvement

 connect health service delivery teams for collaborative and multidisciplinary approach to ensure continuity of care and self-management supports

 establish reminder systems for providers

 support improving health system performance through research and evaluation of chronic care programs

 inform organisational leaders, health policy people and health planners for delivery system redesign in relation to workforce, technology and funding.

A CDM register can help to build epidemiological roles in CDM programs. This approach supports CDM programs and policies to define specific management issues,

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identify important program elements and assess the outcomes of interventions. The epidemiological functions of a CDM register can also help organisation leaders and clinicians to prioritise effective prevention elements (Remington et al. 2003; López- Pousa et al. 2006). Chronic care programs using a CDM register results in a

comprehensive venture to evaluate quality of care and address current CDM concerns in an epidemiologically sound manner (Australian Commission on Safety and Quality in Health Care 2008; McNeil et al. 2010).

The National Chronic Disease Strategy of Australia provides necessary directions to improve chronic care, and secondary prevention (National Health Priority Action Council 2006). Based on the national strategy, ACT Health has incorporated the CDM register as an action component to strengthen chronic care programs (ACT Health 2008a). The integration of a CDM register in this chronic disease strategy is a result of timely policy support. This further explains the presence of a supportive policy

environment, leadership and acceptance by relevant stakeholders in this region.

CDM programs have improved a lot but healthcare facilities are not able to deliver optimum chronic care according to the need of patients. This is due to inadequate use of clinical data as the pathway of communication between clinicians or other allied health providers. The current programs also could not effectively include patients as a part of the treating team. All these have impacts on organisational and individual health providers’ ability to offer recommended chronic care (Jacobsen and Sevin 2008).

CDM programs need specific administrative, clinical and prevention indicators for performance management. In reality, physician organisations have low acceptance rates for technology, so introducing a CDM register is a challenge (Green et al. 2006). The challenge is also part of the issues in relation to the use of clinical data (Arzberger et al.

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2004). The other challenges are related to the selection of key indicators, data collection, ways of data analysis, and ways to maintain integrity of patients’ data.

Healthcare organisations need to implement a service specific disease register designed for chronic conditions. Most of the existing clinical registers are built for research purposes and have varying degrees of limitations. The existing clinical information system also does not have the capacity to connect independent service databases for efficient delivery of care (Quam and Smith 2005; McNeil et al. 2010). Development of a clinical quality register for chronic conditions will help health systems to report on individual patient outcomes as well as effectiveness of chronic disease prevention interventions (Zgibor et al. 2007).

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3

Chapter Three

Methodology

3.5 Data collection methods

3.5.1 Assessment of Chronic Illness Care (ACIC) survey 3.5.2 Key informants’ interview

3.5.3 Participant observation 3.5.4 Analysis of SCIPPS transcripts 3.6 Framework for analysis

3.7 Research management 3.8 Field work

3.9 Data analysis

3.10Ethical considerations

3.1 Introduction

This chapter describes the research methods in detail. The methods give an overview of the nature of the research and the data. This chapter also describes research settings, research participants, data sources, data collection methods, data analysis framework and ethical aspects of the research.

The aim of the research is to get insights into the appropriate design features of a CDM register and organisational contexts to implement it. The study methods aimed to investigate an organisation’s mission and explore the roles of a CDM register to improve chronic care quality, health system performance and care coordination.

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The research followed a multi-method approach in a combination of qualitative, quantitative and participant observation approaches. The study was set in a provincial Australian health service (ACT Health) of around 5,000 staff serving a regional population of 500,000. The basis for this multi-method approach is to relate data with existing chronic care interventions, identify design features of a CDM register (Morse and Field 1995) and obtain generalisability of results across methods (Eid et al. 2009).

The participant observation method supported both the qualitative and quantitative data to make research results more valuable. The qualitative method helped to understand chronic care processes, inputs (Miller et al. 2007) and quantitative illustrations.

Similarly, statistical findings and quantitative illustrations helped to interpret qualitative references, expert views and explanations.

The research methods finally evolved in (i) an organisational analysis of ACT Health combined with (ii) a system requirement analysis of a CDM register and (iii) a structural analysis of how the CDM register can be managed.