By Balu Nair, Gray Matter Analytics CTO
The healthcare industry is going through a major, disruptive shift. The metrics for service providers have evolved from cost and number of services to quality, outcomes and efficiency of service. Moreover, an individual service provider’s scores and their comparison against peers are easily accessible as they are published, helping consumers choose the right providers. In a recent Forbes article, the Centers for Medicaid & Medicare Services (CMS) is continuing to work toward transformative change, with the goal of generating more accountability, greater transparency, and better value for both patients and taxpayers. Providers are now acutely feeling the financial, operational and reputational impacts of this significant shift.
Healthcare organizations can gain timely insights through analytics. Today, most of the insights available to a provider organization are through traditional reporting using tools like spreadsheets, business intelligence queries and reports from electronic medical records (EMR) and other operational systems. Some organizations have built a limited degree of enterprise data integration for analysis and reporting through expensive data warehousing technologies. All these capabilities are providing “after the fact” or retrospective insights, which is not timely or provides limited, if any, opportunities for taking proactive actions. Moreover, there are other valuable sources of data, including those collected from smart and portable medical devices, and socio-economic sources that are not currently being integrated.
Analytics can help health systems predict avoidable readmissions, adverse events, patient risk, utilization, etc. For example, an analytics solution for readmissions can integrate data from medical records, claims, social sources and portable medical devices to predict the probability of patient readmission at the time of admission, during their stay, at discharge and during post discharge periods. With the availability of the right socio-economic data, analytics can even predict readmissions before a patient admission. These predictive insights can aid the health system in planning care, discharge actions and post-discharge care coordination. On an aggregate level, the health system can predict measures and financial impact that affect healthcare delivery and operational efficiencies. According Health Data Management, these insights will lead to corrective actions, which will improve quality and performance well before penalties are applied by CMS and other payers.