BACKGROUND: The lack of comparable metrics to evaluate prevention and early detection patient navigation programs impeded the ability to identify best practices. METHODS: The Prevention and Early Detection Workgroup of the Patient Navigation Leadership Summit was charged with making recommendations for common clinical metrics specific to the prevention and early detection phase of the cancer care continuum. The workgroup began with a review of existing literature to characterize variability in published navigation metrics; then developed a list of priority recommendations that would be applicable to the range of navigation settings (clinical, academic, or community-based). RESULTS: Recommendations for researchers and program evaluators included the following: 1) Clearly document key program characteristics; 2) Use a set of core data elements to form the basis of your reported metrics; and 3) Prioritize data collection using methods with the least amount of bias. CONCLUSIONS: If navigation programs explicitly state the context of their evaluation and choose from among the common set of data elements, meaningful comparisons among existing programs should be feasible.
BACKGROUND: The lack of comparable metrics to evaluate prevention and early detection patient navigation programs impeded the ability to identify best practices. METHODS: The Prevention and Early Detection Workgroup of the Patient Navigation Leadership Summit was charged with making recommendations for common clinical metrics specific to the prevention and early detection phase of the cancer care continuum. The workgroup began with a review of existing literature to characterize variability in published navigation metrics; then developed a list of priority recommendations that would be applicable to the range of navigation settings (clinical, academic, or community-based). RESULTS: Recommendations for researchers and program evaluators included the following: 1) Clearly document key program characteristics; 2) Use a set of core data elements to form the basis of your reported metrics; and 3) Prioritize data collection using methods with the least amount of bias. CONCLUSIONS: If navigation programs explicitly state the context of their evaluation and choose from among the common set of data elements, meaningful comparisons among existing programs should be feasible.
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