Comparative analytics: putting data to work
- In a recent survey about financial reporting challenges, 64% of hospital and health system finance executives cited challenges in pulling data from multiple sources into a single report and 52% noted difficulties in accessing clean, consistent and trusted data.
- Individuals at all levels of the organization should be able to drill down quickly for data on specific targets or goals.
- The breadth and depth of data enable platform users to identify relevant peer groups for comparative analytics across multiple performance dimensions.
Healthcare leaders have access to ever-increasing amounts of data but concerns with the accessibility and integrity of data mean that, in many organizations, data sit idle or underutilized. In a recent survey of hospital and health system finance executives, when asked to identify financial reporting challenges, 64% of respondents cited challenges in pulling data from multiple sources into a single report, and 52% cited challenges in accessing clean, consistent and trusted data.
These ranked as the second and third greatest financial reporting challenges finance executives face, surpassed only by the need to create better dashboards and visuals. It is not surprising, then, that 96% of respondents said their organization should be doing more to leverage financial and operational data to inform strategic decisions (Spence, J., and Sussman, J., 2019 CFO Outlook: Performance Management Trends and Priorities in Healthcare, Kaufman, Hall & Associates, LLC, 2019.)
The need for comparative analytics
Senior finance executives are clearly struggling, both in their efforts to get access to data and in their ability to put that data to work. A solution is needed that not only provides single-source access to clean, consistent and trusted data, but also enables analysis of these data within a framework that best supports strategic decision-making. An internal view of data alone is insufficient to determine whether strategic goals are ambitious enough for effective enterprise performance improvement within an increasingly competitive healthcare landscape. Comparative analytics provide the framework needed to ensure organizations are keeping pace with their peers.
An effective comparative analytics platform should include financial data, patient and clinical data, financial and labor benchmarks and clinical benchmarks drawn from a large group of hospitals (many hundreds) that are representative of the nation’s hospitals by geography, bed size and type — from large academic hospitals to small critical access hospitals. The breadth and depth of data enable platform users to identify relevant peer groups for comparative analytics across multiple performance dimensions.
Attributes of data in an effective comparative analytics platform
The value of a comparative analytics platform is derived from the breadth and depth of its data. But for that data to be helpful to the user, it must have the following four attributes.
A single source. If decision-makers come to the table with data from different sources, their ability to arrive at a conclusion will be undermined quickly by arguments over whose data are correct. To ensure that decision-making across the enterprise is based on a common source of information, a single-source data platform is essential. The platform should aggregate and integrate external and internal data across the spectrum of financial data and benchmark sources used by hospitals for planning, cost and decision support, management analytics and clinical transformation.
Structured and clean. Hospitals receive data from multiple internal and external sources and systems. To ensure both credibility and comparability, these data must be accurately classified and standardized. Data should first be structured through the application of a common taxonomy. It then should be “scrubbed” for regulatory compliance and professionally normalized and classified with data definitions, measure definitions and peer group definitions applied across expense, labor, revenue, volume, clinical and other data.
A platform that combines advanced statistical techniques with machine learning can largely automate this process, minimizing the need for time-consuming labor and the possibility of human error. The result is structured and clean data for apples-to-apples comparisons.
Appropriate and accessible. Depending on an individual’s role within the organization, analytic needs can range from broad and general to narrow and specific.
C-suite executive team members require a broad view across the industry and organization and the ability to quickly discern general performance trends in key strategic dimensions.
The CFO and finance staff need analytics on overall hospital performance compared with specific peer groups along multiple dimensions.
Department managers require analytics on department-specific metrics and indicators driving performance so they can budget and track progress of initiatives for which they are accountable.
Data for these different user groups should be easily obtained and clearly visualized, and individuals at all levels of the organization should have the ability to drill down quickly into their reports for information related to specific targets or goals and whether goals are being met.
Timely. The value of data deteriorates over time. Executives and managers should not have to struggle with enterprise-level data that are many months to years out of date, or even more problematically, that come from various sources with different time periods. Data from both internal and external sources should be refreshed each month on a real-time basis. Real-time data change the way in which information is used and support real-time diagnosis and decision-making as executives and managers monitor the progress and impact of ongoing initiatives and performance.
The power of data put to work
A leadership team’s ability to sustain high-value care delivery and long-term strategic-financial viability of the organization is increasingly dependent on how effectively its executives apply comparative analytics to inform improvement efforts related to financial performance, quality, patient experience and other performance dimensions. Clean, integrated and trusted data, provided in real time, are ready to be put to work for an organization, enabling real insights at all levels for continuous, enterprise-wide performance improvement that becomes part of an organization’s culture.