Analytics and Operational Intelligence Projects in Healthcare! Oxymoron or possibility?

For many industries, the terms Business Intelligence”  has been around for more than a decade. “BI” has been much sought after over the last decade and it is finally healthcare’s turn to take advantage of analytics or intelligence initiatives to better the care of the population.

Being able to provide a predictive view of your operations, analytical tools have the ability to offer unlimited possibilities for healthcare organizations as a well-structured analytics application can give the organization a great return on investment for the organization and for the population the organization serves.

Analytics projects cut across the organization and managing an analytics project is much more involved than managing a traditional IT project as different techniques may be involved for a successful outcome. Depending on the organization, different operational users will be responsible for prioritizing and gathering their requirements for the project. They will need to document them as formal requirements.

The earlier phase will give us the ability to be able to understand the gap existing in the operations and the knowledge required to properly develop a roadmap for the project and understand the duration, cost and other project resources that would be required to successfully complete the objectives set out in a Project Charter and being able to understand your analytics and operational intelligence requirements is foremost. Being able to translate operational needs into technical requirements documents is necessary. This will help the technical resources into understand what their deliverables need to be and keeps them in sync with their operational counterparts.

In addition, I’ve seen that many recommendations is to not just talk to “Operational Power Users”. Every operational and clinical group has it’s Champion or go to individual when someone needs data for analysis. Those are your Power Users and they typically know where the data is and how to get analyze it and get at it. These people are the “C” in the RACI chart you put together, but make sure that you don’t assume that they represent the typical usage of the rest of the group, but only themselves.

Once the objectives are defined, the project architect will identify and select (if not already known) the right tools and technology for the initiative. They will create the data models and also map the workflow required from the source to the target system and work more often than not, with the ETL individuals from the database team and be able to define the operational and data requirements. As the team moves on to the development phase of the initiative and create and develop operational analytics content such as models, reports and queries.

Testing of the analytics content and system load is critical before any go live and operational user testers will be required to provide feedback on overall on any defects or functionalities, features, and data accuracy. Technical team testing will also be required to ensure the integration and performance of entire system is defect/bug free.

Being able to have a great deployment of your analytics solution is now is where the rubber hits the road. Making sure that your resources, infrastructure or otherwise, set up and configuration and completed dry runs ahead of time will require a great deal of collaboration and all of the resources working in concert to ensure success.

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