The Changing Research Landscape: What Are the New Building Blocks for Our Field?
- Rothchild I.
- Husereau D.
- Jacobs P.
- Manns B.
- et al.
- Bhavnani S.P.
- Parakh K.
- Atreja A.
- et al.
Health Services Delivery: What Are the Needs?
- Husereau D.
- Jacobs P.
- Manns B.
- et al.
- Warnes C.A.
- Williams R.G.
- Bashore T.M.
- et al.
- Warnes C.A.
- Williams R.G.
- Bashore T.M.
- et al.
Precision Delivery of Health Services: How Do We Move Forward in the Next Decade?
Congenital Heart Disease Research: What Are the Challenges?
The genotype-phenotype mismatch
The data-to-evidence gap
- Zaragoza-Macias E.
- Zaidi A.N.
- Dendukuri N.
- Marelli A.
- Oster M.
- Bhatt A.B.
- Zaragoza-Macias E.
- Dendukuri N.
- Marelli A.
|Guideline||Recommendations (n)||Classes of recommendations (n)||Level of evidence (n)|
|Proportions||n = 85||45%||47%||8%||0%||6%||93%|
|Proportions||n = 99||43%||52%||4%||0%||1%||40%||59%|
From data sources to data science: how do we get there?
- Boris J.R.
- Beland M.J.
- Bergensen L.J.
- et al.
Strategy for patient-oriented research.
Health research data.
The Future: Where Do We Need to Go?
Adult congenital heart disease research agendas
Emerging research constructs
|CHD outcomes in pediatric and adult patients||CHD trajectories across the life course|
|Age (chronologic)||Aging (biologic)|
|Episodes of illness||Periods of wellness|
|Life span||Health span|
|Quality of care to standardise clinical practice||Quality of care to personalise clinical practice|
|Risk prediction||Benefit prediction|
|Research methods and tools|
|Epidemiology of disease||Life-course health development|
|Knowledge translation||Implementation science|
|Hypothesis-driven prediction models||Machine learning–generated prediction algorithms|
|Randomised clinical trials for single drug benefit||Comparative effectiveness for composite medical therapies|
|Digital health tool implementation||Digital health tool testing|
|Claims data||Secondary big health data|
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