Methods to address and measure challenges
Developing sound comparison standards is a critical part of the process to identify performance improvement opportunities in health systems, hospitals and departments. The comparison group method is the traditional approach health systems employ to set operational benchmarks for performance evaluations. The criterion selected for the benchmarks is based on what the health system determines to be relevant.
This approach is valid but can result in narrower comparison groups that leave out evaluation data from facilities that offer similar services but do not match the self-identified set of criteria.
There is an alternative approach for health care systems that levels the playing field to ensure evidence-based data drives operational benchmarks. When used in addition to – or instead of – the comparison group method, health systems can employ an empirical method to uncover improvement opportunities across all hospitals and departments.
The benefits of the empirical method
The empirical method addresses the challenge inherent in operational benchmarking to understand what factors have an impact on performance and how to apply those parameters to generate comparison groups. By using an empirical approach incorporated into analytic methods applied against data, health systems can access comparison groups that account for operational characteristics that impact performance without manual effort or limitations on the compare group size.
It is important to understand key elements of the empirical operational benchmarking methodology to appreciate the level of rigor required to make comparisons based on validated, multi-year data sets from a large number of facilities.
- Large data sets drive decision-making – the basis of the empirical operational benchmarking methodology is an analysis of four years of annual data that includes data from the system, facility and department levels. Each level has attributes that require consideration in the development of benchmarks to produce comparisons on a fair basis that consider the varied needs of all facilities.
The empirical model considers benchmarking data from multiple levels, including system, facility and department and incorporates an adjustment factor for every measurement period to account for changes over time.
- Quality data produces quality results – implicit in the application of the empirical operational benchmarking methodology is that all analyses use data that passes strict consistency and completeness quality checks. Key performance indicators and workload units are based on the highest ranked measurements in each hospital department.
Facility- and department-specific characteristics reflect actual workloads and other factors that impact measurements. The model also correlates characteristics and factors to remove redundant criteria. It also only includes data that has a consistent impact on operations by weeding out temporary factors.
Enabling fair comparisons
The goal of operational performance evaluations is to identify opportunities to improve quality of care, patient outcomes and costs. The empirical operational benchmarking method adds to health systems’ abilities to equitably identify improvement opportunities with a complete picture of current performance and emerging trends.