The shift to value-based payment is closer than you might think. Its sharpened focus—set against a backdrop of regulatory reform, industry-wide consolidation, and cost pressures—is driving organizations to optimize operations and find opportunities to be more efficient, save money, and gain deeper understanding of available data and outcomes.
Yet, it’s often data—or rather the lack of reliable, easily accessible and sharable data—that continues to be an obstacle. In fact, one fifth of healthcare CIOs said in the last year at least one patient suffered an adverse event due to mismatched records. Simply missing a key data element not only affects patient care outcomes but also increases costs. For example, when discharged, high-risk patients require intervention, but if their phone number was not verified, they cannot be contacted, which often results in an unnecessary emergency department (ED) visit or inpatient admission and the costs are high: $930 per ED visit and $12,824 per inpatient stay.
There are also gaps for different stakeholders—health plans, physicians and care teams—who don’t have the data they need to deliver the most effective care. For instance, while 75% of health plan executives said electronic health records (EHRs) have everything physicians need, only 54% of doctors agreed. Moreover, 85% of physicians say access to quality and performance measures specific to their patients is key to achieving value-based care.
In order to be successful under the expanding influence of value-based care models, organizations must be committed to long-term quality improvements, including quality measures and clean, reliable data. By taking a long-term, platform approach to data and quality management, organizations can create the right foundation for monitoring and improving quality metrics, managing risk and improving outcomes under value-based contracts.
Data Management is the Foundation for Long-Term Quality Improvements
There is no shortage of valuable data available from a wide range of sources. The challenge is to facilitate analytics and decision support using this myriad data at scale.