Data plays a very important role in healthcare — aiding in care and business decisions. But with access to an abundance of datasets, deciphering which information is valuable can be a challenge. The first step, however, is to ensure the right data hygiene process is in place.
Clean data leads to better insights and risk prediction — and improved profitability. As you consider the quality of your data, the following best practices should be employed:
Process. Put steps in place to ensure data is clean — otherwise, you’re unlikely to have reliable insights. When it comes to patient-related data, a uniform enterprise master patient index (EMPI) tool is a great starting point.
Accuracy. Confirm contact information is correct. When patients/members move or change phone numbers, they don’t always update you. Having a process in place to help identify errors and precisely match information can save time and money.
Maintenance. Regularly review your data cleansing processes and make updates as needed. As the industry changes and more data becomes available, it’s important to continually adapt and improve your efforts. This regular maintenance may help identify holes in infrastructure, information and security.
Per an analysis done by Accenture, payers can realize up to $7 billion in value over the course of a year and half by using artificial intelligence-driven solutions.1 As for providers, a recent Black Book survey found 93% think data analytics is crucial to meet industry demands.2
Data fuels smarter, more automated workflows. As data-driven insights become more commonplace, it’s imperative to take a close look at your data strategies — where clean data should be front and center.