Notice ID: RFQ1484167
In order to achieve higher levels of program success, the Center for Medicare (CM) Medicare Contractor Management Group (MCMG) is adding to its existing Health Data Analytics capabilities to provide increased focus and deeper research into the Medicare operations to yield the greatest value. MCMG must design a strategy that is consciously responsive to the dynamic needs of CM’s operational programs.
To provide data analytic support services for CM/MCMG. The contractor will provide data analysis to support measure refinements and development and execution of a methodology to assess performance. The contractor will also provide assistance with the projection of cost expenditures, model development and imputation, development of dashboards and other ad-hoc analysis to support CM/MCMG.
The contractor shall have analytic knowledge and expertise as well as experience with programming in SAS to complete the analytic tasks described in this SOW and develop analysis with high levels of accuracy and quality.
The main data analytic support tasks are listed below:
- Measure development/refinements
- Model development and imputation
- Projections of expenditures
Task 2.1: Measure development/refinements
The contractor will provide analytic support and be a consultant to measure development and refinements to assess cost control and performance of MACs. The contractor will perform analysis of cost, workload, and other metric data to develop potential measures or refine existing measures. The contractor will calculate historical values and distributions over time by the MAC and develop benchmarks for each measure. The contractor will also provide expertise and input on measure development to ensure high quality metrics are developed. The contractor will continue to update measures of interest with additional data as it becomes available.
Task 2.2: Model Development and imputation
The contractor will develop models and interpret the results of the models to aid in CMS’ understanding of workload, performance, and cost.
The contractor will develop analytic files utilizing the current spectrum of CMS data sources. These analytic files will then be used for model development. The contractor will develop models as requested by CMS, such as, but not limited to, models for each MAC function to aid in the understanding of the relationship between cost and workload/performance. The models will support CMS efforts to help senior leaders to better manage and understand CMS programs. The contractor will provide interpretations of the model results and assessment of model performance. The contractor will also provide imputations from models to assess costs for each MAC activity (such as the cost to process a claim).
The contractor will also develop and maintain a secure hosted environment for the data modeling and analytics.
Task 2.3: Projections of expenditures
The contractor will provide technical support as needed for cost analysis and develop models to examine and/or predict events on the basis of current or past data. The contractor will use historical costs and workload data along with models that take into account seasonality to project the cost expenditures in the future and aid with cost trend analysis. The contractor will develop models to predict cost expenditures at both a functional and overall level.
Task 3: Dashboard Development
The contractor will develop a dashboard with cost, workload, unit cost, ftes, costs per fte, workload per fte, and other metrics of interest by WBS and function for each MAC. The dashboard will have national numbers as well as statistics for individual MACs which will allow for an understanding of the MAC’s cost. The dashboard will be updated on a quarterly basis and be used to inform CORs and others of costs for MAC operations (cost to process a claim, cost of an appeal, etc) and to track costs over time.
The contractor will obtain raw cost data, Operational Productivity Report (OPR) data, and workload data from CMS, format and import the data into SAS, merge the data files, and create analytic files that will be incorporated into the dashboard.
The dashboard will be easily accessible to MCMG, formatted in a way that is easy to interpret, and easy to manipulate to look at individual MAC performance compared to national performance for different time periods. The dashboard may be used to assess cost control and trends over time.
The dashboard will be set up in a SAS Visual Analytic environment or similar environment…
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