Healthcare Data Challenges
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The document outlines significant challenges in healthcare data management, including the creation of disparate data streams, limited metadata comprehension, and the tendency for teams to generate new data independently. It also highlights the difficulty of resolving these issues due to separate reporting structures and the obscurity of data experts within organizations. Suggested solutions include adopting standardized metrics, fostering collaboration among teams, and adhering to company data standards.
Healthcare Data Challenges
- 1. Healthcare Data Challenges Prepared by Angela Boyd 2017
- 2. Problem: Why is there so much data and so little value? Some of the Challenges Explained: -Multiple applications are used to create data (for varying purposes with varying levels of quality). Data degrades or changes as it moves throughout the organization. -Limited meta data may be available/easily understood by those trying to use the data. -People and projects with data needs often create new data flows because it seems easier than using existing data. -New data is created ‘in a vacuum’ for one reporting group/project without a view of enterprise needs/synergy with others that also need the data.
- 3. Problem: Why are data challenges so hard to fix? Some of the Challenges Explained: -Multiple applications are managed separately by differing reporting structures and processes. In many cases, people are not aware their data is used for reporting by other teams that secure a copy of a copy. -Subject matter experts of data, sometimes referred to as Data Heros, are hidden in the organization, or buried under requests to explain the data. Identifying and accessing these individuals can be difficult. -It is almost always faster/less expensive (up front) to create data ‘in a vacuum’ for one reporting group/project without a view of enterprise needs/synergy with others that also need the data. It’s later, you realize the costs of multiple groups creating the same/similar data, technical support, data storage, data quality, multiple platforms /licenses, data security risks/compliance audits, etc.
- 4. Solution: Tips to Try • Consider adopting a standardized metric template/business information requirements for reporting/metric catalog • Collaborate with other reporting teams to find synergy • Educate/communicate with others/find out what you don’t know and teach what you know • Ensure that you’re following company data standards and policies • The Reporting and Analytics Team(s) that are the best collaborators and communicators will grow and be relied upon by organization • Form close partnerships with your suppliers and consumers
Editor's Notes
- #3: A quick Google search for ‘data warehouse spaghetti diagram’ landed on EIM (Enterprise Information Management) Institute.org website where this diagram was sourced. Most people in healthcare are familiar with the problem that there are various reporting groups/BI teams that all may do similar work, with differing results. This is frustrating for leadership, and what often occurs is a new project or team forms to create a new data flow, because they are unable to understand existing data, may not have access to existing data or can’t get it in a format they can use, or they think they can do a better job of extracting/preparing the data than what is available. What you end up with is something like this diagram. Source: http://www.eiminstitute.org/resource-portals/data-warehousing/201cindependent201d-data-marts-being-stranded-on-islands-of-data-part-2/
- #5: -There are existing templates that you can use for a model, (you may be doing metrics for HITSP, CMS, and your internal Best In Class/Benchmarking and all have varying documentation for metrics). Consider developing a template of the essential attributes for each type of metric and report, and develop a template that you could use to not only explain the metrics you’re doing, but use it as a business information requirements to develop new metrics. -There are most likely other teams doing reporting on same or different tools, but there is always some synergy that can be found between teams doing like processes. Consider something as informal at brown bag lunches with neighboring teams or persons that also create metrics for the organization. -Make it a goal to get out and meet/present at local meet ups or industry organizations that discuss data and reporting ideas and best practices. -If you haven’t already, be sure to meet with your organization’s legal and/or compliance teams when there are company policies about data. Normally, there are limits to how long you can store data, how to keep data protected, and perhaps how data should be shared within the organization. -If there are multiple teams, it is essential to collaborate and communication well to stay a viable, relied upon team. And if you are the only team, but others do not find you easy to collaborate with, then you will not be the only team for long. -Stay close to those that support you both as a supplier and as a consumer of your data. May go without saying.