Sujha Subramanian1, Florence Tangka2, Patrick Edwards3, Sonja Hoover3, Maggie Cole-Beebe3. 1. RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC, USA. Electronic address: ssubramanian@rti.org. 2. Centers for Disease Control and Prevention, 4770 Buford Hwy, Atlanta, GA, USA. 3. RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC, USA.
Abstract
BACKGROUND: This article reports on the methods and framework we have developed to guide economic evaluation of noncommunicable disease registries. METHODS: We developed a cost data collection instrument, the Centers for Disease Control and Prevention's (CDC's) International Registry Costing Tool (IntRegCosting Tool), based on established economics methods We performed in-depth case studies, site visit interviews, and pilot testing in 11 registries from multiple countries including India, Kenya, Uganda, Colombia, and Barbados to assess the overall quality of the data collected from cancer and cardiovascular registries. RESULTS: Overall, the registries were able to use the IntRegCosting Tool to assign operating expenditures to specific activities. We verified that registries were able to provide accurate estimation of labor costs, which is the largest expenditure incurred by registries. We also identified several factors that can influence the cost of registry operations, including size of the geographic area served, data collection approach, local cost of living, presence of rural areas, volume of cases, extent of consolidation of records to cases, and continuity of funding. CONCLUSION: Internal and external registry factors reveal that a single estimate for the cost of registry operations is not feasible; costs will vary on the basis of factors that may be beyond the control of the registries. Some factors, such as data collection approach, can be modified to improve the efficiency of registry operations. These findings will inform both future economic data collection using a web-based tool and cost and cost-effectiveness analyses of registry operations in low- and middle-income countries (LMICs) and other locations with similar characteristics.
BACKGROUND: This article reports on the methods and framework we have developed to guide economic evaluation of noncommunicable disease registries. METHODS: We developed a cost data collection instrument, the Centers for Disease Control and Prevention's (CDC's) International Registry Costing Tool (IntRegCosting Tool), based on established economics methods We performed in-depth case studies, site visit interviews, and pilot testing in 11 registries from multiple countries including India, Kenya, Uganda, Colombia, and Barbados to assess the overall quality of the data collected from cancer and cardiovascular registries. RESULTS: Overall, the registries were able to use the IntRegCosting Tool to assign operating expenditures to specific activities. We verified that registries were able to provide accurate estimation of labor costs, which is the largest expenditure incurred by registries. We also identified several factors that can influence the cost of registry operations, including size of the geographic area served, data collection approach, local cost of living, presence of rural areas, volume of cases, extent of consolidation of records to cases, and continuity of funding. CONCLUSION: Internal and external registry factors reveal that a single estimate for the cost of registry operations is not feasible; costs will vary on the basis of factors that may be beyond the control of the registries. Some factors, such as data collection approach, can be modified to improve the efficiency of registry operations. These findings will inform both future economic data collection using a web-based tool and cost and cost-effectiveness analyses of registry operations in low- and middle-income countries (LMICs) and other locations with similar characteristics.
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Authors: Florence K L Tangka; Sujha Subramanian; Patrick Edwards; Maggie Cole-Beebe; D Maxwell Parkin; Freddie Bray; Rachael Joseph; Les Mery; Mona Saraiya Journal: Cancer Epidemiol Date: 2016-10-25 Impact factor: 2.984
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Authors: Patrick Edwards; Lee E Buenconsejo-Lum; Florence K L Tangka; Youngju Jeong; Janos Baksa; Paran Pordell; Mona Saraiya; Sujha Subramanian Journal: Hawaii J Health Soc Welf Date: 2020-06-01