Integrating Employee Health A Model Program for NASA (2005) / Chapter Skim
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6 Data Integration and Health Management
6 Data Integration and Health Management
Pages 150-170
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Data that are collected on occupationally related health programs can serve a variety of purposes in an integrated data management system. First, data can be used to report statistical information on program usage and effectiveness.
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. ORGANIZATIONAL FRAMEWORK FOR DATA MANAGEMENT The Four Faces of Measurement: An Organizing Principle An effective data management and measurement system can support organizational objectives such as · Decision making, · Accountability, · Improvement, and · Surveillance, including longitudinal analyses and knowledge discovery.
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. This approach includes data collection and measurement that identifies potential problems, barriers, or opportunities for improvement; facilitates the implementation of improvement initiatives; and follows with data collection to measure the improvement or change that has taken place.
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A DATA MANAGEMENT SYSTEM FOR AN EFFECTIVE INTEGRATED HEALTH MANAGEMENT PROGRAM A data-driven approach is the core technology needed to implement an integrated and sustainable health management program to achieve world-class status. Figure 6-1 illustrates a systems approach that represents a comprehensive data management strategy.
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Data collection Internal with external Internal with external staff expertise as required expertise as required Sample sizes Large or specific to identified Large population Data collection Sufficiently complex to · Complex process assurance acceptable level of · Requires moderate effort accuracy, reliability and and cost validity to take action Confidentiality and · Very high · None for purposes of Privacy · De-identified data only comparison -- the goal is · Comply to HIPAA and exposure and transparency ADA regulations · De-identified data only · Comply to HIPAA and ADA regulations
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DATA INTEGRATION AND HEALTH MANAGEMENT 155 Surveillance, Longitudinal Analysis, and Improvement Knowledge Discovery · Program staff Program leadership at every level · Center leadership · HQ leadership · Understanding of process and user · Notice patterns and trends groups or employees · Explain areas of concern · Baseline assessment · Monitor population health statistics of special · Evaluation of changes interest Specific to individual centers Universally applicable to all levels of NASA · Few · Many · Easy to collect · Complex collection · Simple · Precise, reliable, and valid · Approximate Short, current Long, past Consider, but rarely measure Measure and/or control · Ongoing · Ongoing · Insync with improvement cycles · Specific to issue or topic needing to · Insync with program be examined implementation efforts Internal Internal if expertise is available; otherwise external Small Large · Simple Highly complex · Minimum cost required · Integrated with program implementation · Usually repeated frequently in order to create sun charts · Very high · High · De-identified data only · De-identified data only · Comply to HIPAA and ADA · Comply to HIPAA and ADA regulations regulations
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156 analyses analyses Centers Centers level- comparisons level- comparisons and NASA and between between Center and and within within #n comparisons comparisons and and Center analyses analyses level- level NASA Group Headquarters #2 Individual n 2 1 Time Center Time Time NASA. for #1 management Center data n 2 n to 1 Time 2 1 n Time Time Time Time 2 Time Time 1 Time Time approach -based specific- -based Priorities Elements systems A Agency Report Center Report Group Data Individual Data 6-1 FIGURE
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Following such common and preferred processes and protocols provides an opportunity to report data in a standardized manner and ensures consistency in data integrity, collection, and management processes. Data Management, Protocols and Data Standards and Elements Core data elements also need to be standardized to generate meaningful metrics comparison.
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Data Capability Maximizing an organization's data capability requires placing computer hardware and software as well as data collection and input into the data warehouse. The multiple functional and relational databases that are created by accessing the data warehouse require similar analytical characteristics for uniform report generation.
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In the case of NASA, each individual center would have to manage its own program eligibility requirements because of differences in contract agreements. Data Elements and Priorities Health Behaviors and Other Personal Risk Factors Health behavior data are considered core measures for programs designed to influence the overall health of an individual.
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However, because these are the most frequently used outcome measures to demonstrate success of occupational health management programs, they are important metrics to collect. This problem can be overcome by the use of proxies for medical or pharmacy claims.
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Program Participation The number and range of employees who participate often determine the success of a health management program. These data are necessary to assess the effect of participation and changes in health status and environmental policies.
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. Whereas most traditional health promotion programs target populations defined as at-risk for a single risk factor (smoker, high blood pressure, high cholesterol, overweight and obese, etc.)
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, which protects health insurance coverage for workers and their families when they change or lose their jobs, and Title II, the Administrative Simplification provisions, which require that the U.S. Department of Health and Human Services (USDHHS)
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FINDINGS The committee gathered evidence for NASA's investment in the health of its workforce, both civil servants and contract employees, from information and data provided by the agency, invited presentations, and site visits to selected NASA centers. Although the overall goal of occupational health-related programs -- to improve and maintain the health status of the workforce -- was clear, evidence for consistency in program application, implementation, and evaluation between centers was less apparent, and evidence showing that the goals and objectives of the various centers are coordinated was not found.
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Data Collection and Management Site visit observations of specific occupational health programs at NASA, findings from the literature, and comparisons with "best practice" models described in Chapter 4 further indicated that there was a
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Closing the Gap Between Traditional and World-Class, Integrated Health Programs Although the NASA health program has a long and distinguished history, the current traditional approach to occupational health care does not meet the needs of a world-class program. Data management agencywide as well as at the level of the individual centers is an important area for improvement.
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However, it does indicate a need for more consistent and uniform metrics to maintain and improve the quality of NASA's occupational health programs. RECOMMENDATIONS As discussed above, NASA can, through intra-agency cooperation and data sharing, become a world-class best practice organization through both center-specific as well as NASA-wide improvements in strategies and tactics for collection and management of employee health data.
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, factors that contribute to program success (e.g., as measured by employee participation rates or behavior change) , barriers and facilitators that contribute to worker participation in programs -- and how these barriers and facilitators differ by type of worker, center, and other factors -- and factors that contribute to each center's ability to initiate, implement, and sustain integrated health programs.
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2001. Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III)
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2000. Gender-specific effects of modifiable health risk factors on coro nary heart disease and related expenditures.
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