Here are four tips for implementing and managing data analytic solutions that give healthcare executives the ability to make informed decisions leading to improved patient care and greater efficiencies across clinical, operational and financial business units:
- Identify the kind of data to target and create a strategic analytics plan: This includes determining what business and clinical questions need to be answered and then assessing what types of analytics are required. Certain types of analytics are expensive and more difficult to implement. Weigh the benefit of each desired analytics use-case against the cost and the complexity of the proposed solution.
- Establish data governance policies: Building a foundation for actionable data that stakeholders in the organization trust requires strong “data governance.” The best analytics tools are ineffective without this. Adopt a data governance model as part of your analytics strategy, including a governing body comprising clinical, administrative, and IT stakeholders; formal data management processes; and a written operational plan that details roles and responsibilities for capturing, curating, and managing enterprise data.
- Determine appropriate access to the specified data: Conduct readiness assessments of target data systems. Then, decide where the data will reside and be queried, such as in an enterprise data warehouse or in the data’s native location.
- Create output of data in a meaningful and useful format: The measure of success in a healthcare analytics solution is in the eye of the beholder such as the administrator or the clinician that relies on the data to make decisions. Make a point of periodically reviewing the usefulness of reports and data with these stakeholders and improving them.
To learn more, explore the Logicalis healthcare web site, then download the data sheet about healthcare analytics at http://ow.ly/JcJKw.