Reporting Framework for Value Based Care
Learn how a provider's relative performance, or 'value', can be evaluated through three key components in an equation: quality, efficiency, and cost.
Data quality is the foundation of any data warehouse. As the old saying goes “garbage in – garbage out.” If there are inconsistencies or irregularities in the data loaded into a data warehouse, all analyses based on those data are potentially flawed.
Healthcare data are complex, and even data from organizations well experienced in claims administration and data transmission contain errors from time to time. Having processes in place to detect and correct data problems is critical for any healthcare information platform, but even with the best of processes, errors from submitted data result in increased costs and often delay data warehouse updates.
Many MedInsight clients are dependent on multiple data supplier partners to provide source data for their healthcare data warehouse. Some are of these clients are self-insured employers requesting data from the organizations who administer their claims. Others are community or business coalitions and some are states building all payer claims databases. As the number of data sources increases, the complexity and potential for error increases.
Establishing strong partnerships with all your data suppliers is the one of the best ways support efficient data warehouse updates.
Different organizations have different relationships with their data suppliers, so the possible techniques for keeping data suppliers engaged in the success of a data warehouse often vary from one client to a next. Below are some ways to engage data suppliers in the project.
All organizations are busy. Claims administrators have to focus on many different priorities to meet the needs of their customers, but if data suppliers are fully engaged in a data warehouse initiative, and incorporate data quality processes with each data submission, everyone will save time and money by avoiding rework.