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Table 4 Results of portfolio analysis of de-implementation grants (N = 20)

From: Studying de-implementation in health: an analysis of funded research grants

Domain Code Total
n %
Study objectives Understand or characterize factors influencing de-implementation 14 70
Develop strategies to facilitate de-implementation 15 75
Health area Cancer 8 40
Cardiovascular disease 1 5
Geriatric syndromes 1 5
Hormone imbalance 1 5
Infectious diseases 3 15
Kidney disease 1 5
Mental health 2 10
Neurological 1 5
Multiplea 1 5
Not specified 1 5
Continuum of care Prevention 2 10
Screening and/or detection 5 25
Diagnosis 3 15
Treatment 14 70
Surveillance 2 10
Not specified 1 5
Health service or practice Drugs, medications, or therapies 15 75
Preventive or screening tests 8 40
Target patient population Children (< 18 years old) 2 10
Adults (18–64 years old) 12 60
Older adults (65+ years old) 11 55
Study setting Clinical care 16 80
Hospital 4 20
Nursing homes/assisted living facilities 2 10
Schools 1 5
Study design and methods Experimental 7 35
Measurement/algorithm development 1 5
Mixed methods 4 20
Observational 7 35
Qualitative 3 15
Quasi-experimental 5 25
Systems science 4 20
Proposed data source Primary (e.g., original data collection) 13 65
Secondary (e.g., claims data) 13 65
  1. Codes were not mutually exclusive. More than one code could be applied to a grant. Numbers may add up to more than 20 (100%) in some cases. Codes were extracted from the text of the full grant application, including abstract, specific aims, and research plan
  2. aMultiple: multiple preventive services in primary care settings but health domain not specified