Is your job composed of data analysis? Are you in charge of mapping or testing a healthcare enterprise data warehouse (EDW) implementation? Are you working with programs on Oracle, DB2, Google BigQuery or Db2 Warehouse on Cloud? Why? Employees can often get accustomed to the daily routine and lose sight of the big picture.

Organizations are continuously integrating data from electronic medical records (EMR), pharmacy reports and numerous other systems. From this process, we become far removed from the real benefactors of our work. These benefactors include clinicians, researchers and most importantly, the patients. In other words, we can sometimes forget why we are putting in this effort to provide value.

Of the countless reasons for integrating healthcare data, here are three that show the real-world benefits of compiling data in an EDW.

Research

At one client’s site, we developed interfaces between our IBM UDMH Warehouse and a research system using REDCap sitting on top of a MySQL data base. Researchers were then able to use the data to determine what cancer treatments worked best based on patient conditions. These data-driven treatments were developed and implemented thanks to the wealth of EMR and other data collected in the EDW.

Patient Safety

There are many success stories of using EDW data to improve patient safety. One is tracking patients with multi-drug-resistant pathogens. For example, if a patient possesses a history of multi-drug-resistant pathogen exposure and checks into a hospital; the infection control is notified immediately, and steps can be taken to prevent the spread of the pathogen. Having that information available throughout the given healthcare system and across disparate systems will help to drastically reduce the spread of those pathogens to other patients.

Reporting Optimization

All healthcare systems provide reports and information to various government entities. Gathering the data to provide that government-mandated information can be extremely time-consuming and expensive. The EDW helps data administrators to obtain, organize, and analyze the massive amounts of data throughout the system. Furthermore, freeing up healthcare resources to do what they do best, provide patient care.

Technologies continuously develop to assist in workflow efficiency. These technologies have a great and measurable impact on the success of a business. So when you are working feverishly on implementing that first or updated enterprise data warehouse, remember that it will help improve patient care and save lives.

Healthcare organizations have been implementing the IBM UDMH (Unified Data Model for Healthcare) for the last seven years because they realize that connecting critical data helps gain insight into improving care, controlling risk, managing population health and providing accurate reporting both internally and externally.

To reap these benefits, there is a critical need to plan the IBM UDMH journey in advance, ensuring the implementation will meet goals, objectives and expectations generally. There are many considerations to be considered in this planning effort, three of these will be discussed in this blog.

Determine the Tenancy Structure

The UDMH model is designed to support a multi-tenant data repository. Before diving in head first, the following need to be considered: Should tenancy be defined by organization? By site? By some combination thereof? By something else? Is there a true need for multitenancy within the organization in question? The proper decision on how to apply tenancy will ensure that the data is secure, provides the ability to report and analyze within and across the enterprise and positions the organization for future growth and expansion.

Source System Integration

Disparate sources will feed data into the UDMH based repository, including data domains such as: clinical data, claims data, pharmacy data, and many others. Ensuring the proper integration of the sourced data will eliminate or reduce redundancy and grain inconsistencies, and enable timely and accurate reporting and analysis going forward.

Master Data Management and Reference Data Management

Managing patient, practitioner, location and other master data is also critical to reducing duplicate instances of the information ingested, and plays a key role in providing successful and accurate reporting and analytics. Additionally, to report and analyze the data consistently across the organization, decisions related to the normalization of reference codes, such as NDC codes, RXNorm, GPI codes, to name a few, is critical to maintaining a consistent and quality data set within the UDMH based repository. The UDMH is designed to support the management of data from across disparate sources and codes, however proper planning can impact the effectiveness and ease of use of the implementation.

This may seem like a large and daunting task but Perficient has worked with many health systems and has established repeatable implementation patterns and understands the pros and cons of these decisions, and works with health systems to guide them through this process. It is our goal and experience to make your UDMH implementation go smoothly, and position your organization for success.

The Perficient Healthcare Leadership team will be available at HIMSS 2018 in Las Vegas, NV in booth #2671 to talk about our real-world experience with data, analytics, and IBM’s UDMH. We are looking forward to talking with you.