Consensus-based framework for evaluating data modernization initiatives: the case of cancer registration and electronic reporting

Abstract

As part of its data modernization initiative (DMI), the Centers for Disease Control and Prevention, Division of Cancer Prevention and Control is testing and implementing innovative solutions to improve cancer surveillance data quality and timeliness. We describe a consensus-based effort to create a framework to guide the evaluation of cancer surveillance modernization efforts by addressing specific context, processes, and costs related to cancer registration. We drew on prior theories, consulted with experts, and sought feedback from cancer registry staff. We developed the cancer surveillance systems, context, outcomes, and process evaluation (CS-SCOPE) framework to explain the ways in which cancer registry data quality, timeliness, and efficiency are impacted by external and internal contextual factors and interrelated process and content factors. The framework includes implementation measures to understand acceptability of process changes along with outcome measures to assess DMI initiation and ongoing sustainability. The framework's components and structures can be tailored for use in other DMI evaluations.

Keywords: cancer surveillance; data modernization initiative; electronic reporting.

Figure 1.

Registries participating in interviews or focus groups. Note: States in light blue were not included in the study.

Figure 2.

CS-SCOPE framework for systematic evaluation of data modernization initiatives. Notes: The definitions for the implementation measures are: Acceptability—The perspective of the registry team members impacted by the change as to whether the new approach is agreeable or palatable; Feasibility—The extent to which the new processes or systems can be successfully embedded within existing workflow to seamlessly integrate and continue operations; Appropriateness—The compatibility or relevance of the data modernization innovations to the overall goals of the implementing organizations; Adoption—The action of implementing the change or the “uptake” of the data modernization practice; Resources—The investment required for implementation related to the start-up phase and ongoing efforts. The changes implemented can impact the resources expended on specific activities, as well as the staffing mix and budget categories; Sustainability—The extent to which the changes implemented can be maintained and supported over time after completion of the initial planning and implementation phases.

Figure 3.

Cancer surveillance cloud-based computing platform (CS-CBCP) simplified data flow schematic. Notes: EHR: electronic health record; CCR: Central Cancer Registry; LIS: Laboratory Information System.