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A multifaceted quality improvement intervention for CVD risk management in Australian primary healthcare: a protocol for a process evaluation.

Patel B, Patel A, Jan S, Usherwood T, Harris M, Panaretto K, Zwar N, Redfern J, Jansen J, Doust J, Peiris D - Implement Sci (2014)

Bottom Line: Despite the widespread availability of evidence-based clinical guidelines and validated risk predication equations for prevention and management of CVD, their translation into routine practice is limited.We developed a multifaceted quality improvement intervention for CVD risk management which incorporates electronic decision support, patient risk communication tools, computerised audit and feedback tools, and monthly, peer-ranked performance feedback via a web portal.Our aims are to understand how, why, and for whom the intervention produced the observed outcomes and to develop effective strategies for translation and dissemination.

View Article: PubMed Central - PubMed

Affiliation: The George Institute for Global Health, University of Sydney, Sydney, NSW, 2006, Australia. bpatel@georgeinstitute.org.au.

ABSTRACT

Background: Cardiovascular disease (CVD) is the leading cause of death and disability worldwide. Despite the widespread availability of evidence-based clinical guidelines and validated risk predication equations for prevention and management of CVD, their translation into routine practice is limited. We developed a multifaceted quality improvement intervention for CVD risk management which incorporates electronic decision support, patient risk communication tools, computerised audit and feedback tools, and monthly, peer-ranked performance feedback via a web portal. The intervention was implemented in a cluster randomised controlled trial in 60 primary healthcare services in Australia. Overall, there were improvements in risk factor recording and in prescribing of recommended treatments among under-treated individuals, but it is unclear how this intervention was used in practice and what factors promoted or hindered its use. This information is necessary to optimise intervention impact and maximally implement it in a post-trial context. In this study protocol, we outline our methods to conduct a theory-based, process evaluation of the intervention. Our aims are to understand how, why, and for whom the intervention produced the observed outcomes and to develop effective strategies for translation and dissemination.

Methods/design: We will conduct four discrete but inter-related studies taking a mixed methods approach. Our quantitative studies will examine (1) the longer term effectiveness of the intervention post-trial, (2) patient and health service level correlates with trial outcomes, and (3) the health economic impact of implementing the intervention at scale. The qualitative studies will (1) identify healthcare provider perspectives on implementation barriers and enablers and (2) use video ethnography and patient semi-structured interviews to understand how cardiovascular risk is communicated in the doctor/patient interaction both with and without the use of intervention. We will also assess the costs of implementing the intervention in Australian primary healthcare settings which will inform scale-up considerations.

Discussion: This mixed methods evaluation will provide a detailed understanding of the process of implementing a quality improvement intervention and identify the factors that might influence scalability and sustainability.

Trials registration: 12611000478910.

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Related in: MedlinePlus

Real-time decision support interface.
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Fig1: Real-time decision support interface.

Mentions: There have been few randomised evaluations of QI interventions in the Australian primary healthcare setting. We designed a multifaceted QI intervention for CVD risk management in Australian primary healthcare. The intervention drew on two established QI mechanisms: 1) electronic decision support and 2) audit and feedback (summary of the clinical performance over a specified period of time) [32-37]. The intervention was evaluated in the TORPEDO study, a cluster-randomised controlled trial (cRCT) involving 60 health services. Details of the trial are published elsewhere [38]. In brief, the system was integrated with the healthcare provider’s EHRs, and included (1) a real-time decision support interface using an algorithm derived from several evidence based national guidelines (Figure 1); (2) a patient risk communication interface which included ‘what if scenarios’ to show the benefits from particular health risk factor improvement during a consultation (Figure 2); (3) an automated clinical audit tool for extraction of data and review of health service performance (Figure 3); and (4) a web portal where services can view peer-ranked performance over time (Figure 4). Healthcare providers could use the point-of-care tool as part of a routine clinical consultation. For the audit and feedback component, quality indicators were developed for patients who had visited the health service at least three times in the preceding 2 years and once in the preceding 6 months. The population studied was based on national guideline recommendations for CVD risk screening and included Aboriginal and Torres Strait Islander people over 35 years and all others over 45 years [38].Figure 1


A multifaceted quality improvement intervention for CVD risk management in Australian primary healthcare: a protocol for a process evaluation.

Patel B, Patel A, Jan S, Usherwood T, Harris M, Panaretto K, Zwar N, Redfern J, Jansen J, Doust J, Peiris D - Implement Sci (2014)

Real-time decision support interface.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4279909&req=5

Fig1: Real-time decision support interface.
Mentions: There have been few randomised evaluations of QI interventions in the Australian primary healthcare setting. We designed a multifaceted QI intervention for CVD risk management in Australian primary healthcare. The intervention drew on two established QI mechanisms: 1) electronic decision support and 2) audit and feedback (summary of the clinical performance over a specified period of time) [32-37]. The intervention was evaluated in the TORPEDO study, a cluster-randomised controlled trial (cRCT) involving 60 health services. Details of the trial are published elsewhere [38]. In brief, the system was integrated with the healthcare provider’s EHRs, and included (1) a real-time decision support interface using an algorithm derived from several evidence based national guidelines (Figure 1); (2) a patient risk communication interface which included ‘what if scenarios’ to show the benefits from particular health risk factor improvement during a consultation (Figure 2); (3) an automated clinical audit tool for extraction of data and review of health service performance (Figure 3); and (4) a web portal where services can view peer-ranked performance over time (Figure 4). Healthcare providers could use the point-of-care tool as part of a routine clinical consultation. For the audit and feedback component, quality indicators were developed for patients who had visited the health service at least three times in the preceding 2 years and once in the preceding 6 months. The population studied was based on national guideline recommendations for CVD risk screening and included Aboriginal and Torres Strait Islander people over 35 years and all others over 45 years [38].Figure 1

Bottom Line: Despite the widespread availability of evidence-based clinical guidelines and validated risk predication equations for prevention and management of CVD, their translation into routine practice is limited.We developed a multifaceted quality improvement intervention for CVD risk management which incorporates electronic decision support, patient risk communication tools, computerised audit and feedback tools, and monthly, peer-ranked performance feedback via a web portal.Our aims are to understand how, why, and for whom the intervention produced the observed outcomes and to develop effective strategies for translation and dissemination.

View Article: PubMed Central - PubMed

Affiliation: The George Institute for Global Health, University of Sydney, Sydney, NSW, 2006, Australia. bpatel@georgeinstitute.org.au.

ABSTRACT

Background: Cardiovascular disease (CVD) is the leading cause of death and disability worldwide. Despite the widespread availability of evidence-based clinical guidelines and validated risk predication equations for prevention and management of CVD, their translation into routine practice is limited. We developed a multifaceted quality improvement intervention for CVD risk management which incorporates electronic decision support, patient risk communication tools, computerised audit and feedback tools, and monthly, peer-ranked performance feedback via a web portal. The intervention was implemented in a cluster randomised controlled trial in 60 primary healthcare services in Australia. Overall, there were improvements in risk factor recording and in prescribing of recommended treatments among under-treated individuals, but it is unclear how this intervention was used in practice and what factors promoted or hindered its use. This information is necessary to optimise intervention impact and maximally implement it in a post-trial context. In this study protocol, we outline our methods to conduct a theory-based, process evaluation of the intervention. Our aims are to understand how, why, and for whom the intervention produced the observed outcomes and to develop effective strategies for translation and dissemination.

Methods/design: We will conduct four discrete but inter-related studies taking a mixed methods approach. Our quantitative studies will examine (1) the longer term effectiveness of the intervention post-trial, (2) patient and health service level correlates with trial outcomes, and (3) the health economic impact of implementing the intervention at scale. The qualitative studies will (1) identify healthcare provider perspectives on implementation barriers and enablers and (2) use video ethnography and patient semi-structured interviews to understand how cardiovascular risk is communicated in the doctor/patient interaction both with and without the use of intervention. We will also assess the costs of implementing the intervention in Australian primary healthcare settings which will inform scale-up considerations.

Discussion: This mixed methods evaluation will provide a detailed understanding of the process of implementing a quality improvement intervention and identify the factors that might influence scalability and sustainability.

Trials registration: 12611000478910.

Show MeSH
Related in: MedlinePlus