Issue link: https://beckershealthcare.uberflip.com/i/289185
75 Executive Briefing: Data Analytics Sponsored by: Creating a Foundation for Actionable Analytics A sk most healthcare leaders what drives good patient out- comes and strong financial performance and you'll likely get the same answer: Data, and not just any data. To get a full picture of their patients' health status, organizations need high- quality data from a multitude of sources, including claims, clinical, administrative and socio-demographic data banks. Such data can help payers, providers and the myriad support services that work with them understand how care is given, to what populations it is extended and how individual practitioners are performing. It may sound impressive to say that your organization has access to terabytes of patient information, but without robust technology and smart people to manipulate it, that data is simply words and numbers without context. In a day and age when understanding patient risk is critically important, healthcare organizations must be able to cull robust data to build risk-bearing care systems and the financial models that will sustain positive patient outcomes. And it all starts with quality data. What is "good data?" With respect to data quality, many factors come into play. Raw data from claims or from an EMR database are not suitable for analysis. Turning raw data into usable information requires prepa- ration, including normalization and validation. Only then can an organization gain trustworthy insights from the information and put it to use in maximizing patient care, reducing risk and strengthen- ing a business's bottom line. While the concept of data quality is widely accepted, most health- care organizations define "good data" in different ways. One com- mon thread, however, is the overwhelming need to gather and analyze information from one end of the spectrum to the other — from all data sources and from all sites of care. To get a full picture of their patients' health status, organizations need high-quality data from a multitude of sources, including claims data, clinical data from electronic health records, administrative/abstracted data from facility information systems and socio-demographic data from public sources such as census data. Human error is always a risk in data gathering and entry. It's not uncommon for patient data sitting within health system data marts to show men having babies, people born in 1776 and Daffy Duck coming to an emergency room. And organizations must pay close attention to the sources of their data. "For example, while my company was cleansing data for a provider organization, we reviewed a lab feed that contained whole sections of lab values that could not possibly be human. As it happened, that lab was also serving veterinarians, and there was no designation for human versus non-human patients in the data," said A.G. Breitenstein, chief product officer for Optum. "That's an outlier example, certainly, but it's indicative of the fact that data can't be trusted on its face — it must be analyzed and cleansed to ensure its quality." More importantly, quality data must be actionable. "If data gath- ering is done simply for data's sake, it is not worth doing," said Adrian J. Rawlinson, MD, of Brown and Toland Physicians in San Francisco. "Actionable data is useful clinical data that provides, for example, a pursuit list of high-risk patients or those likely to be admitted in the next six months," he said. "Anybody can create data or build dashboards and employ these tools. It is really a question of what you are going to do with it and how you are going to put it to best use once you have it." One important use of actionable data is the development of ac- curate registries for care management. Registries, which are col- lections of health and demographic data for patients with specific health conditions, are traditionally built from claims data. Combin- ing actionable clinical data with claims data provides organiza- tions with a truer cohort of patients with the same disease. Without to get a full picture of their patients' health status, organizations need high-quality data from a multitude of sources, including: • Claims data • Clinical data • Administrative data • Socio-demographic data Get your free analytics eBook. Visit optum.com/gamechange to download the new eBook, Moneyball Analytics, and begin changing your game. Get in the analytics game. We understand health care analytics can be intimidating. But with the right data and processes, analytics have the potential to change the game for health care providers. From reducing costs to improving health outcomes, a smarter game plan founded on the right data and analytics can create a winning combination for providers and patients across the care continuum.