Data analytics skills play a major role in helping healthcare providers to unlock the potential of their data, by turning the data into actionable information for radical change within the organization. More and more healthcare organizations are using enterprise data warehouses in more innovative ways and as a basis for their strategy. Doing this requires the professional knowledge of data analysts. Data analysts can find ways to overcome the challenges that come with big data and data sorting. If a healthcare organization has a data analysts that do not have sufficient skill set to properly interpret all the incoming data, the organization should help the analyst acquire these skills by sending them to data training courses or paying for some other courses. This is because the field of data analysis is a dynamic and rapidly evolving field. It has to be so in order to keep track of all the new data that is being created. Healthcare data analysts will be constant aspect of modern healthcare, especially with more incentive programs set to rise in coming years. The healthcare data analyst’s roles and responsibilities may change from organization to organization. However, their overall goal will be to maintain patient safety while minimizing

 


Data Analysis


Making sense of the data available in the EDW should be the focus of every analytics team member because a lot of information is generated in healthcare, some of which lack relevant details to drive improvements once analyzed. This calls for a keen look at the set theory, and the ability to filter details through SQL, or a statistical reporting tool, or a combination of both. A good analyst should be able to sift through data to retrieve pertinent insights.
The benefit of introducing this system in healthcare is that it can help in the management of cost. For example, a lot of attention is given to the management of diabetic patients, since this chronic disease requires proper care and medication. Enlisting the services of an analyst in the clinical improvement team tasked to handle this condition, will guard against huge costs associated with mismanagement.


Export, Transform, and Load (ETL) Skills


Some of the major skills that data analysts can acquire are the skills to acquire, transform, and load data. These skills will help a data expert to take data from one system and feed it into another. EDW requires such individuals to pull information from disparate systems such as human resources, EHRS, and finance. A typical example is where a healthcare facility has an EMR system, a costing system, and a patient satisfaction system that do not interface or overlap.
The acquire/export, transform, and load procedure will aid in making copies of data found in each of the systems, to make the details available in the information warehouse. The advantage, in this case, is that integration of data from various systems is made possible through the ETL process.


Structured Query Language


Abbreviated as SQL, Structured Query Language allows an analytics team member to converse and manipulate databases directly through code. An expert with these skills can write SQL code without depending on a guided interface or intermediary such as the drag and drop tool. This will set them apart from those who rely on Crystal Reports GUI or Microsoft Access GUI tools, to generate SQL for their reports.
Such an understanding will give these individuals leverage in particular areas including;


•    Attaining a rudimentary understanding of querying as a result of access to fine-grained data control through SQL.
•    Ability to explore data that has not been filtered through a predefined data set or model, using a Business Intelligence (BI) tool.
•    No information from whichever source is withheld from one's knowledge


Using Visualization For Interpretation


Members of an analytics team should be in a position to interpret the details embedded in data, considering that BI reporting will only avail information in bits and pieces to give you a micro view. Interpretation, in this case, entails the provision of a logical flow that brings together multiple meanings, to create a story or what you could term as the bigger picture.


A practical example of how this skill can be applied in the healthcare sector is where data experts tasked with reporting on A1C testing, blood pressures, eye exams, and foot exams scour databases, to establish possible ways that A1C results are represented in the EDW. You can also perform the exercise on all the tests, to reap the benefit of identifying patients with care gaps such as those who have missed A1C testing, eye exams, foot exams, among others.


As a result, a healthcare facility with such a workforce will make better sense of how it is managing diabetic patients, through evidence-based medicine. It will also help in the evaluation of both clinical and financial outcomes, for an analytic team member to understand the business they support.