Assessing your hospital's readiness for business intelligence  

Ensuring the right vision and leadership is in place before you implement a performance analytics solution is key, but even before taking that step you might want to ask yourself: What is my facility’s level of business intelligence (BI) maturity?

Matthew Esham, Director of Business Intelligence/Analytics at LUMEDX, is a former cardiovascular service line leader at Christiana Care Health System in Delaware, which was honored for the Most Innovative Use of Business Intelligence during the Intelligent Hospital Awards program at the Healthcare Information and Management Systems Society (HIMSS) Conference and Exhibition in 2014.

Christiana Care saved $3 million in three years using performance analytics to identify opportunities to lower costs and improve quality of care, under Esham’s guidance. This achievement was presented at the 2016 HIMSS conference.

Since joining LUMEDX in 2017, Esham has worked with multiple facilities around the country implementing HealthView Analytics (HVA) and has developed a framework for assessing readiness.

Level 1: Ad Hoc. At this level, the culling and parsing of data, including the reporting structure, is driven by short-term “right now” needs. There is little or no formal decision-making process and this data is often purely volume based, so it doesn’t typically include structured key performance indicators (KPIs). 

Level 2: Schedule Driven. Reports are domain-driven, meaning one department may have its own system for data aggregation and analysis, while another in the same facility may have a different system. Data collection is often single system-focused, so there is no coordination with other systems and limited data management. Typically, at this level the reporting structure is somewhat regimented and done on a weekly, monthly, or quarterly basis.

Level 3: Defined. Hospitals at this level have common, defined data structures that are KPI-driven. They have centrally managed data structures with departmental expertise, and a somewhat sophisticated approach to data management. The challenge at this point is twofold: Managing dirty data and managing “the noise” so you can focus on the valuable data that will help you measure actual performance.   

Level 4: Predictive. This is the holy grail of hospital-based BI. The three characteristics of a system at this level are predictive data, population management, and point of care integration. Data analysis is focused on high-impact, high-cost events, and the system itself is optimized across the enterprise, to prevent siloed data.

Read the previous blog post “Making Way for Business Intelligence Maturity” to learn more about the common pain points that interfere with hospitals’ effectiveness in collecting data, analyzing it, and then acting on the insights the data reveals.

Posted by Jana Ballinger 10/31/2019 Categories: Analytics Business Intelligence HealthView Analytics