During Phase I of the initiative, RTZ Associates developed MSSPCare, an electronic integrated information system designed to meet all of the operational, clinical, management, fiscal and state reporting needs of California's largest home- and community-based services program, the Multi-Purpose Senior Services Program (MSSP). The proposed Phase II project will build on Phase I by building a common core data set across MSSPCare and the information system called PACECare that was developed subsequent to Phase I for the national PACE program. Currently, there is a national and state effort to compare long term care programs, evaluate their strengths and weaknesses and to develop best practice models. The proposed Phase II project will create an operational data warehouse for comparing client information across sites, across programs, and across states for the purpose of improving program management and quality. Specifically, the Phase II project will use the data warehouse to prepare cross-site summary reports, to compare client populations and outcomes, and to prepare Benchmark Reports for the comparison of individual sites to other like programs. Phase II will also employ the data warehouse to address a priority issue revealed in the Phase I and PACECare project development phases: medication management outcomes. This issue has recently become more pressing due to the passage of the Medicare Prescription Drug Improvement and Modernization Act (MMA), which renders prescription drugs more accessible than ever to seniors. Specifically, The Phase II Project will: 1. Develop a common core MSSPCare/PACECare data set, compatible with the Minimum Data Set for Homecare Assessments (MDS-HC), for comparing client characteristics, 2. Develop a standardized drug interaction detection software across both information systems, 3. Build a multi-site data warehouse and use the analyses generated to improve program management and quality, 4. Use the data warehouse to improve clinical practice to detect redundant medications and potentially dangerous interactions, 5. Study the impacts of the medication problem detection software on prescription patterns and client outcomes, and 6. Evaluate the adoption rates, use patterns, costs and benefits of the enterprise software system and data warehouse. ? ?
