The following is a guest article by Kevin Campbell, CEO and founding partner of DTA Healthcare Solutions.
Healthcare metrics are a pain. They are seemingly impossible to define with just the right inclusion and exclusion criteria to satisfy everybody in the organization. The Quality and Finance departments have different definitions for the same metric, and that causes no shortage of conflict in meetings when the numbers don’t match. Sorting through the discrepancies takes an incredible amount of time, and trying to unify the metrics takes even longer.
And yet metrics are so important to healthcare organizations. They are used to monitor safety, adherence to clinical best practices, financial health, patient satisfaction, provider performance, and operational efficiency. They are tied to how the organization, and individuals within the organization, are compensated. Many metrics are published on the web for all to see and use in deciding which provider to go to for care.
Given the high importance of metrics to healthcare organizations, coupled with the intense level of work (and rework) associated with them, you would think we would have a formalized way of dealing with them by now. But within most organizations, we don’t, and it’s time.
The phrase “Enterprise Data Governance” is often meant to encompass governance of everything data-related in an organization, from data entry to storage to analysis to reporting to advanced analytics. However, the term “Analytics Governance” has emerged to address the use of data to answer questions. When Analytics Governance is split out, then “Data Governance” usually applies only to the part of the data lifecycle from data entry through storage/data management. Because Enterprise Data Governance is such a large and often overwhelming undertaking, breaking down the effort into smaller chunks is helpful and necessary as long as we don’t lose sight of the whole. For example, analytics is much more difficult and requires much more manual scrubbing and mapping when the underlying data isn’t clean and standardized, so if Analytics Governance is attempted in isolation of Data Governance, it won’t get very far very fast.
Current EDG Subdivisions
Looking at the diagram above, there’s something missing that is vitally important when it comes to data, at least in the healthcare context we operate in: metrics. Arguably, since metrics are a use of data, it could be argued that metrics should fall under Analytics Governance. But we believe that metrics are worthy of calling out as a separate category for several reasons:
- Metrics garner a high amount of attention in healthcare organizations and are important to all levels of administration and to caregivers as well.
- Healthcare metrics are complex; and the more clinical the subject matter, the more complex metric inclusions and exclusions become.
- Performance against externally-defined metrics is often tied to reimbursement by both government and commercial payers.
- Performance against externally and internally-defined metrics is often tied to individual compensation (primarily of physicians and executives).
- There are multiple departments within a healthcare organization that develop metrics, and those metrics can be very similar (for example both Finance and Performance Improvement are often interested in Average Length of Stay, however they are usually calculated differently). This seeming duplication can cause enormous confusion.
- There is an incredible amount of waste and rework involved in the development, validation, and maintenance of metrics across the organization.
- “Analytics” tends to refer to answering questions that haven’t already been answered, performing data discovery, and looking out to the unknown future. Metrics, however, are generally products of “settled science” (so to speak). For example, the best practice for treating patients presenting at the Emergency Department with stroke-like symptoms is known; metrics are used to measure and monitor adherence to those best practices.
Therefore, we propose adding a third subdivision to the discipline of Enterprise Data Governance: Metric Governance.
Proposed EDW Subdivisions
Like Analytics Governance, attempting Metric Governance in isolation is very challenging and inefficient, so the underlying data (Data Governance) must be taken into consideration as well. But addressing metrics in their own category as a way to divide up an overwhelming and complex body of work into smaller focus areas just makes sense. Plus the tasks involved with Metric Governance are unique in comparison to Data and Analytics Governance. Specifically, for each metric the governance process involves:
- Identifying an owner responsible for the definition and performance of the metric
- Gathering input from those with “skin in the game” related to the metric, as well as any external definitions that need to be considered, and then facilitating an agreed-upon enterprise metric definition
- Creating the detailed metric definition with inclusions and exclusions fully spelled out
- Creating and monitoring goals related to the metric
- Working with the metric developer to ensure the actual metric matches the agreed-upon definition
- Monitoring and validating the metric on an ongoing basis to ensure it continues to measure what was intended (especially since underlying data has an irritating tendency to change without anybody knowing about it!)
- Working with BI developers to make sure metrics are being pulled from the metric repository and not recreated in each report and dashboard, and that metrics are being displayed in a helpful and informative way
- Creating metric documentation and ensuring that information is widely and readily available (and understandable) to those throughout the organization who require it
Adding Metric Governance as a subdivision under Enterprise Data Governance may only be an urgent need in the healthcare industry, due to the incredible complexity of and focus on metrics. We’ll leave it to others to determine if other industries would benefit from this nuance. But regardless of the world outside healthcare, we’re convinced that healthcare organizations would benefit from a much more formal discipline of Metric Governance than exists today.
Want to learn more about metric governance, check out this webinar on “Introducing Metric Governance“.
About Kevin Campbell
Kevin Campbell is the CEO and a founding partner of DTA Healthcare Solutions, a healthcare data and analytics consulting firm that began in 2012. Kevin has over 17 years of experience in data warehousing, analytics, and data governance, serving as both the lead data architect in a large healthcare system as well as a consultant to many other healthcare organizations. He has experience as diverse as developing an organizational productivity tracking system, performing process improvement (Lean/Six Sigma black belt), and creating enterprise data warehouse and business intelligence strategies for multiple healthcare systems. He is skilled in developing data systems that promote metric standardization, business logic centralization, and overall analytic and business intelligence transparency.
DTA Healthcare Solutions is a proud sponsor of Healthcare Scene.
