The following article, written by Senior Consultant Michael Askin, was published in Healthcare Reform Magazine
By Michael Askin
The spotlight on IT in the healthcare industry has never been more blinding. Healthcare reform has mandated IT investment in the name of improved clinical/quality outcomes, reduced medical errors and standardized care. Even without these reforms, however, the role of IT positively influencing the cost and quality of patient care has become increasingly important. At the center of demonstrating – and measuring – success is the Key Performance Indicator (KPI). The healthcare and benefits industries have a particularly large number of complex KPI. From research to patient care, to operations and finance, KPIs and their management (metadata management, master data management) are critical to overall organizational success.
Creating a KPI Monster
With increased reliance on KPIs comes a substantial increase in complexity and management costs. Creating even one new KPI means the exponential addition of – potentially – thousands of data points. Consider the many factors to be addressed in determining “ER waiting time:” information about each patient, symptoms they present with, severity of the condition, real-time calculations about number of patients in various stages of treatment, etc. On the benefits side, corporate benefits managers count on “Quality Ratings” to help them find the best health insurance plan for their employees. The “Quality Rating” measures cost efficiency as it relates to quality of care, and can be conceptualized as the resources used on each disease divided by the diseases in the plan’s insured population. Herein lies the potential for creating a monster. A KPI is very far downstream in the business objectives pipeline, and the work involved in its calculation creates interesting situations requiring providence (where the data came from, how it got here, and what happened to it along the way) and provability. The KPI lifecycle includes:
- Managing the sources of the data
- Data quality and cleansing
- Managing the definition of the data elements used in the KPI
- Tracking ownership of the KPI and data element definition
- Metadata management
- Transparent definition of the calculations used to create the KPI
- Maintaining KPI “trendability”
The healthcare and benefits industries have more stakeholders than is typical in most corporations, with each of those groups interested in different metadata about those KPIs. “Over 75 years of age” and “super senior” might be compatible in spoken language, but have a completely different taxonomy when expressed in metadata. Often, however, the IT systems responsible for KPI management are overly complex and serve too many disparate functions, and they’ve usually evolved over a long period by many, many people. As a result, the IT department’s management of these systems can become hyper-focused on routine execution of processes that could and should be automated, and ends up expending its resources on troubleshooting and supporting. Statisticians then spend more time manually calculating standard statistics than doing the value-add analysis they were hired to do.
Where KPI is King and MDM is Hero
The goal of the KPI is to measure performance in common terms. The role of Master Data Management (MDM) is to create a structured, common language, understandable to all stakeholders. Creating a well-structured, common language allows business users to talk to each other in their own terms, while creating data definitions and KPI that can be directly executed, without translation by an IT guy. This allows stakeholders to have more direct ownership of their data. Once everyone understands and speaks the same language, life becomes less about tedious maintenance and troubleshooting, and more about value-add and better outcomes:
- The potential for interpretation errors between the groups is dramatically minimized.
- All stakeholders can have their ownership and interest enforced on the KPI.
- KPI is “trendable” and reliable over time.
- As much as possible, statisticians and researchers are empowered to specify and own their KPI.
The value of a properly built and executed KPI strategy is that it leverages the talent and skills you already have, using well-proven technology. There’s no compelling reason to invest in risky, cutting edge technology because you already know exactly what you need. Just as importantly, when the underlying technology that executes the KPI-MDM pipeline needs to be updated, the stakeholders do not need to redefine the KPI/data points or use different tools to manage the data points. From an ROI perspective, the investment into an integrated KPI/MDM approach has proven value to healthcare – and any industry whose outcomes can be objectively measured. High quality data, communicated seamlessly across multiple stakeholders, drives better decision-making, and delivers improved outcomes.
About the Author
Michael Askin is a Senior Consultant at Mind Over Machines, a software and data consultancy that helps market leaders achieve exceptional results through tailored information systems. To contact the author, please email email@example.com or visit www.mindovermachines.com.