Policy and Practice June 2017

technology speaks By Debora Morris and Joseph Fiorentino

Yes, You Can! A New Data Mindset to Improve Health and Human Services Outcomes

H ealth and human services practi- tioners understand the need for policies and programs that are person centered—for a coordinated health and social care system that addresses the behavioral and social determinants of health and well-being. demands a new data mindset. Leaders can start with three practices that chal- lenge common wisdom about analytics in health and social care. 1. Go Beyond Compliance Health and human services agencies have traditionally looked to data as a means to meet federal compliance and operational reporting requirements. These responsibilities are regulatory by definition, and they are a foundational element of this work that will not go away. Even so, agencies can think beyond compliance when it comes to data analytics. They can check the box and think outside of it. Breaking away from a compliance mindset opens doors to new oppor- tunities to reinvent service delivery and build a stronger network of care in the process. Too few of the world’s social services agencies are actively doing this today. Consider that just 29 percent of them use advanced analytics for measuring performance and 21 percent use it to modernize and digitize processes to meet people’s technology expectations. 1 The biggest surprise is that a mere 15 percent of agencies use advanced analytics to improve service delivery and meet expectations. 2. Get Speed to Insight Agencies that want to develop their own targeted analytics programs and Building this foundation for a modern and responsive system

This lack of results happens because while data warehouses have their place in health and human services— for compliance, reporting, and other business intelligence needs—they do not have to be the starting points for analytics initiatives. These programs do not require perfect data, or even

get results quickly need different tools than most expect. Many decision- makers think that they must start with infrastructure. They assume the first step is to invest in data warehouses, data stores, and the hardware and software necessary to support them. This is an unnecessary heavy lift—an expensive three- to five-year project that more often than not does not yield desired results for data analytics.

See Data Mindset on page 31

Photo illustration by Chris Campbell

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