Are you effectively using Broad Data

Healthcare management is becoming a more and more complex business. With myriad payors, complex billing processes, and an economic environment that often defies logic, the need for effective decision-making information has never been greater. This complexity has led to an entirely new industry, healthcare analytics.

Big companies in analytics most often focus on Big Data. That is voluminous patient interaction data to determine costs, charges, patients flows, discrete areas of utilization and various other highly complex, and highly important information.

However, all important information gathering doesn’t involve Big Data. Many important decisions being made in hospitals, health systems, payors and other participants in the healthcare vertical involve Broad Data. That may be a new term to you, but the differences are significant, both in analytical approach and in practical applications.

Big Data is most often looking at just that, thousands of terabytes to uncover patterns. Broad Data, on the other hand is looking at a wider range of data inputs that may or may not even be resident in your Big Data. For example, what is the value of buying a surgical robot to the market image and positioning of your organization? And, how does that value comport to the procedural value of the equipment and how does that relate to the opportunity to engage three additional payors because they refer their patients first to organizations with surgical robots, and how does it impact utilization, revenues and image that a prominent surgical group will join your staff only if you have a robot. Do you think you’ll find that answer in Big Data? You know you won’t.

But, you can answer that question logically if you focus on Broad Data. Broad Data Analysis, such as Cost Effectiveness Analysis, Markov Modeling and other BDAs that apply values to actions, opportunities, and outcome generally thought to be unmeasurable, will provide a valid metric for objective decision-making even when certain data elements are perceived, emphasis on “perceived,” to be subjective.

A quick example is organizational image. Data can show a relationship between organizational image and utilization. But that data will not be part of your Big Data. It will reside elsewhere. Plus, the relationship between the value of image, and a simple equipment acquisition ROI does not exist. Their relationship is relative, but it can be assigned a value. Broad Data is the process of modeling discrete, unrelated data elements that may necessitate establishing subject values in order to produce an objective final outcome.

If your objective is to provide the best decision-making for your organization and take a global view of your business, expanding your sights beyond ROI, and educating other decision-makers, Cost Effectiveness Analysis can make your organization more competitive and more profitable.

William Matzner, MD. is a recognized expert in Healthcare and Neuro Economics. With a Ph.D. in Economics, MBA and Medical Doctor degree, Dr. William Matzner will provide you with expert analysis on health and wellness programming, populations health management, disease management, new program development, facility development, equipment acquisitions, and other healthcare programs, acquisitions and initiatives. For more information about cost effectiveness analysis and improved financial accountability for your organization, visit Dr. Matzner at http://healthcareanalytics.biz