Healthcare Data Analytics has proven itself to be one of the major advancements that will take the healthcare industry to an advanced level. Many systems have been attempting to implement healthcare analytics in a haphazard and inferior way. For example, many vendors have been selling short-term point solutions which address just a narrow set of needs and do not establish a fundamental approach to analytics that will be sustainable and thrive as more and bigger data is being analyzed. Analytics is an important tool for all businesses in industries including the healthcare industry. Analytics is the discovery, interpretation, and communication of meaningful patterns in data. These patterns once recognized, helps in both large scale and small scale day to day decision making. Analytics is especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance.
To handle this data and carry out the analytics, you need health data analysts to help optimize the data. As an organization, when a data analyst is hired, the data analyst needs to be given the right job description and put in the right team to work with the right people so his or her skill set and value can be optimized for maximum result.
Four Ways to Optimize Your Healthcare Data Analyst’s Value
There are four ways to empower data analysts to provide the insights necessary to drive improvements:
Provide Analysts with a Data Warehouse:
The most effective way to empower analysts to identify value-added improvements is by implementing an enterprise data warehouse (EDW). The EDW becomes a one-stop shop for data aggregation. Using just one login, analysts can access any data across the entire health system. Some people don’t think an EDW is necessary; that it’s possible to bring the data together manually on an as-needed basis. This sounds fine in theory, but an EDW provides many other critical attributes: metadata, security, auditing, and common linkable identifiers.
Provide Analysts with Full Access to a Testing Environment:
Give analysts access to the EDW can significantly limit their effectiveness. Give analysts ample opportunity to build, break, and rebuild data sets within the EDW. Analysts should be able to use the data warehouse like a sandbox in which they can store anything they consider useful.
Provide Analysts with Data Discovery Tools:
Data discovery tools, such as business intelligence (BI) tools, make it easy for analysts to explore the data and look for useful oddities or trends. But not all BI tools are sufficient for in-depth data analysis. BI tools might feature nifty charts and graphs help the masses understand what the data is saying. But they also need to make it possible for analysts to drill into the data to find trends and meaningful correlations. The right data discovery tool should enable analysts to build intertwined, insightful reports that lead to system improvements.
Provide Analysts with Direction:
Analysts need direction Healthcare data analysts need direction, not step-by-step instructions about what their reports should contain. Step-by-step instructions result in one-off reports linked to very precise requests. Providing direction, on the other hand, leads to deeper, more meaningful insights that help solve problems and make improvements. The best report requests provide enough direction to put the analysts on the right track and enough leeway to encourage analysts to ask more questions as they analyze the data.
Provide analysts with direction, time to investigate the problem, and a forum for asking detailed questions:
The end product will be substantially better because it includes not only what the requester initially wanted, but also additional insights that go deeper into the data—which might be exactly what the organization needs.