Senior onderzoeker Zorgstelsel en Sturing; hoogleraar 'Sociale en geografische aspecten van gezondheid en zorg', Universiteit Utrecht
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Data analysis plan of the OECD PaRIS survey: leveraging a multi-level approach to analyse data collected from people living with chronic conditions and their primary care practices in 20 countries.
Groenewegen, P., Spreeuwenberg, P., Timans, R., Groene, O., Suñol, R. Data analysis plan of the OECD PaRIS survey: leveraging a multi-level approach to analyse data collected from people living with chronic conditions and their primary care practices in 20 countries. BMC Research Notes: 2024, 17(1), p. Art. nr. 157.
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Objective
In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD) initiated the International Survey of People Living with Chronic Conditions (PaRIS survey), which aims to provide insight in patient-reported outcomes and experiences of chronic care provided by primary care practices to support policy development. The objective of this research note is to describe the structure of the data, collected in the PaRIS survey and how the data will be analysed in a multilevel approach for cross-country comparison.
Analysis plan
The data structure of the PaRIS survey represents three levels: countries/health systems, primary care practices and patients. Multilevel analysis is used because of its accuracy in estimating country-level outcomes, its flexibility in modelling relationships, and its opportunities in connecting to relevant policy questions. Country-level outcomes will be estimated to facilitate cross-country comparison and (future) within-country comparison over time. Characteristics of patients that potentially explain variation in patient-reported outcomes and experiences can be linked to primary care practice and country/health system characteristics. This makes it possible to address policy-relevant questions relating, e.g., to the impact of chronic care management on patients with a specific chronic condition.
In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD) initiated the International Survey of People Living with Chronic Conditions (PaRIS survey), which aims to provide insight in patient-reported outcomes and experiences of chronic care provided by primary care practices to support policy development. The objective of this research note is to describe the structure of the data, collected in the PaRIS survey and how the data will be analysed in a multilevel approach for cross-country comparison.
Analysis plan
The data structure of the PaRIS survey represents three levels: countries/health systems, primary care practices and patients. Multilevel analysis is used because of its accuracy in estimating country-level outcomes, its flexibility in modelling relationships, and its opportunities in connecting to relevant policy questions. Country-level outcomes will be estimated to facilitate cross-country comparison and (future) within-country comparison over time. Characteristics of patients that potentially explain variation in patient-reported outcomes and experiences can be linked to primary care practice and country/health system characteristics. This makes it possible to address policy-relevant questions relating, e.g., to the impact of chronic care management on patients with a specific chronic condition.
Objective
In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD) initiated the International Survey of People Living with Chronic Conditions (PaRIS survey), which aims to provide insight in patient-reported outcomes and experiences of chronic care provided by primary care practices to support policy development. The objective of this research note is to describe the structure of the data, collected in the PaRIS survey and how the data will be analysed in a multilevel approach for cross-country comparison.
Analysis plan
The data structure of the PaRIS survey represents three levels: countries/health systems, primary care practices and patients. Multilevel analysis is used because of its accuracy in estimating country-level outcomes, its flexibility in modelling relationships, and its opportunities in connecting to relevant policy questions. Country-level outcomes will be estimated to facilitate cross-country comparison and (future) within-country comparison over time. Characteristics of patients that potentially explain variation in patient-reported outcomes and experiences can be linked to primary care practice and country/health system characteristics. This makes it possible to address policy-relevant questions relating, e.g., to the impact of chronic care management on patients with a specific chronic condition.
In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD) initiated the International Survey of People Living with Chronic Conditions (PaRIS survey), which aims to provide insight in patient-reported outcomes and experiences of chronic care provided by primary care practices to support policy development. The objective of this research note is to describe the structure of the data, collected in the PaRIS survey and how the data will be analysed in a multilevel approach for cross-country comparison.
Analysis plan
The data structure of the PaRIS survey represents three levels: countries/health systems, primary care practices and patients. Multilevel analysis is used because of its accuracy in estimating country-level outcomes, its flexibility in modelling relationships, and its opportunities in connecting to relevant policy questions. Country-level outcomes will be estimated to facilitate cross-country comparison and (future) within-country comparison over time. Characteristics of patients that potentially explain variation in patient-reported outcomes and experiences can be linked to primary care practice and country/health system characteristics. This makes it possible to address policy-relevant questions relating, e.g., to the impact of chronic care management on patients with a specific chronic condition.