A Study to Examine Health Behavior Change Strategies for Primary Care
| Status: | Completed |
|---|---|
| Conditions: | Smoking Cessation |
| Therapuetic Areas: | Pulmonary / Respiratory Diseases |
| Healthy: | No |
| Age Range: | 2 - Any |
| Updated: | 4/21/2016 |
| Start Date: | June 2005 |
| End Date: | January 2013 |
Common Measures, Better Outcomes (COMBO)
Prescription for Health is a national program of The Robert Wood Johnson Foundation (RWJF)
in collaboration with the Agency for Healthcare Research and Quality (AHRQ). A major goal of
Prescription for Health is to measure the extent to which comprehensive strategies are
effective in changing patient behavior and quality of life relative to four target health
risk behaviors: diet, smoking, alcohol use, and physical activity. The funded projects will
use a common set of survey instruments to help measure outcomes and draw overarching
conclusions across projects. This study will only be analyzing aggregated data and does not
have responsibility for recruitment of patients, randomization (if applicable), or
interventions. Individual project designs may differ.
in collaboration with the Agency for Healthcare Research and Quality (AHRQ). A major goal of
Prescription for Health is to measure the extent to which comprehensive strategies are
effective in changing patient behavior and quality of life relative to four target health
risk behaviors: diet, smoking, alcohol use, and physical activity. The funded projects will
use a common set of survey instruments to help measure outcomes and draw overarching
conclusions across projects. This study will only be analyzing aggregated data and does not
have responsibility for recruitment of patients, randomization (if applicable), or
interventions. Individual project designs may differ.
The data will be collected by and submitted from up to 10 practice-based research networks
over a two-year period. We will: 1) aggregate de-identified data and 2) analyze the
aggregated data. We will not identify or recruit study subjects, administer surveys to
patients, or conduct any interventions with patients or practices. The individual research
networks will submit only de-identified data to a central data repository for subsequent
analysis by us. Individual research networks will submit their own protocols for review by
their IRBs in order to collect patient-specific data, conduct interventions, and submit
de-identified data to our central repository.
By combining data from funded projects we will be able to answer questions that individual
projects would not be able to answer. The analysis will use the combined set of data to gain
statistical power sufficient to test hypotheses of interest, determine the distribution of
responses to the selected measures in patients in primary care practices, assess the impact
of types of interventions, compare the impact of different types of interventions, determine
if these measures can be used routinely, and conclude how useful, if at all, the selected
measures were in Prescription for Health projects. Statistical analysis will include basic
descriptive statistics and distributions of scores at baseline and follow-up and more
complex hierarchical linear modeling, which seeks to understand effects in multi-site
studies (across sites or groups of sites). We will not directly evaluate specific research
network interventions, but will assess them as part of larger groups. This study will report
only aggregated results and will not name individual primary care practices or research
networks.
over a two-year period. We will: 1) aggregate de-identified data and 2) analyze the
aggregated data. We will not identify or recruit study subjects, administer surveys to
patients, or conduct any interventions with patients or practices. The individual research
networks will submit only de-identified data to a central data repository for subsequent
analysis by us. Individual research networks will submit their own protocols for review by
their IRBs in order to collect patient-specific data, conduct interventions, and submit
de-identified data to our central repository.
By combining data from funded projects we will be able to answer questions that individual
projects would not be able to answer. The analysis will use the combined set of data to gain
statistical power sufficient to test hypotheses of interest, determine the distribution of
responses to the selected measures in patients in primary care practices, assess the impact
of types of interventions, compare the impact of different types of interventions, determine
if these measures can be used routinely, and conclude how useful, if at all, the selected
measures were in Prescription for Health projects. Statistical analysis will include basic
descriptive statistics and distributions of scores at baseline and follow-up and more
complex hierarchical linear modeling, which seeks to understand effects in multi-site
studies (across sites or groups of sites). We will not directly evaluate specific research
network interventions, but will assess them as part of larger groups. This study will report
only aggregated results and will not name individual primary care practices or research
networks.
Inclusion Criteria:
- varies by project
Exclusion Criteria:
- varies by project
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