Despite the number of healthcare organizations collecting and using data, few have been able to truly harness the information to make measurable improvements in care quality and revenue, Sanket Shah, professor of Health Informatics at the University of Illinois at Chicago, says in an article at HealthITAnalytics.
He outlines basic steps to put healthcare analytics efforts on the right path, including:
- A comprehensive roadmap with leadership from the top: A roundtable discussion with clinical leaders about specific problems to be solved can be a good place to start. A few narrowly defined use cases can help organizations determine the data they need to collect and the tools they need to use that data effectively. Most organizations have access to claims data, but maturing analytics efforts combine more data sources, such as electronic health record data and information from wearables and mobile apps.
- Choose the right data: Rather than collecting and storing data indiscriminately, determine the data you need for the goal you have in mind, Shah says. Staying focused on targeted use cases can help prevent data hoarding and a yearly "data inventory" can help providers use resources wisely.
- Consider the pros and cons of outsourcing: While organizations without the in-house skills for population health, analytics initiatives and data warehousing might see farming it out as a solution, doing so is expensive and carries security risks. On the other hand, hiring analytics talent is expensive, too, so it's important to fully understand the trade-offs, he says.
"Not every organization understands that if they are going to acquire skilled professionals to drive their business forward, they need to invest," Shah says. "Either they need to commit to hiring the right people from outside the organization, or they have to train their internal folks, ensure they have a mentor program, and develop the right infrastructure that will support growth."
To learn more:
- read the article