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
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 out...
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| Vydané v: | BMC research notes Ročník 17; číslo 1; s. 157 - 5 |
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| Hlavní autori: | , , , , , , |
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BioMed Central
06.06.2024
BioMed Central Ltd Springer Nature B.V BMC |
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| Abstract | 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. |
|---|---|
| AbstractList | 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. ObjectiveIn 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 planThe 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.OBJECTIVEIn 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.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.ANALYSIS PLANThe 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. 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. 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. Keywords: International comparison, Multilevel analysis, Primary care, Health services research Abstract 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. |
| ArticleNumber | 157 |
| Audience | Academic |
| Author | Valderas, Jose Maria Timans, Rob Groenewegen, Peter Groene, Oliver Rijken, Mieke Spreeuwenberg, Peter Suñol, Rosa |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38845064$$D View this record in MEDLINE/PubMed |
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In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD)... In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD) initiated the... Objective In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD)... ObjectiveIn view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development (OECD)... Abstract Objective In view of the increasing number of people with (multiple) chronic conditions, the Organisation for Economic Co-operation and Development... |
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| SubjectTerms | Biomedical and Life Sciences Biomedicine Care and treatment Chronic Disease - therapy Chronic diseases Chronic illnesses Clinical outcomes Comparative analysis Data Analysis Data collection Diagnosis Family medicine Gender Health services research Humans International aspects International comparison Life Sciences Management Medicine/Public Health Multilevel Analysis Organisation for Economic Co-Operation and Development Patient outcomes Patient Reported Outcome Measures Patients Population Primary care Primary health care Primary Health Care - statistics & numerical data Questionnaires Research Note Sociodemographics Surveys Surveys and Questionnaires Variables |
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| Title | 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 |
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| Volume | 17 |
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