3 Common Healthcare Data Platform Challenges

Data is an important asset in healthcare, and analyzing data is crucial to gaining new insights into patient populations. Self-service analytics platforms such as MDClone’s ADAMS environment empower clinicians, researchers, and other non-technical professionals to engage directly with their data to drive evidence-based decision-making. These platforms allow healthcare providers, medical scientists, and other professionals to get timely answers to improve clinical decisions, optimize clinical operations, and positively impact patient care and quality of life.

THE CHALLENGE

Data analytics platforms are not always intuitive or easy to use. Examples of challenges healthcare professionals may encounter when exploring data include:

• Lack of Simplicity
  A team at a medical school attempts to use an analytics platform for research on factors predisposing patients to hypertension. They find themselves limited to basic queries. The team doesn’t have the experience or skills necessary to leverage the software, and they end up frustrated and unable to tap into greater insights.

• Lack of Dynamic Capabilities
  A healthcare executive wants to know how many patients with chronic kidney disease were admitted to the hospital with end-stage renal disease within 15 years after initial diagnosis. The team runs an analysis of their chosen population, receives an answer to their query, and… that’s it. What if they want to adjust the parameters, compare two populations, explore their data using visualizations, or track efficacy over time? Each one of these items is another project, perhaps requiring weeks or months of additional work. Because the executive had to delegate the work to their team, they could not optimize and redirect questions in real time based on immediate feedback from the analysis.

• Lack of Specificity
  A clinician wants to determine how many patients with a specific type of stage 3 cancer who are taking a particular medication progress to stage 4 at any time within a one-year period. The clinician inputs the data and receives an answer back, but the answer is vague. The clinician still doesn’t know how many patients progressed within 6 months versus 9 months, how many patients were also receiving other adjunctive therapy, the dates the patients were diagnosed, or how long the patients had been taking the initial medication of interest.

THE SOLUTION

The MDClone ADAMS Platform was designed to overcome these challenges. ADAMS stands for Ask, Discover, Act, Measure, and Share. It’s a powerful and user-friendly self-service data analytics platform for healthcare collaboration, research, and innovation. With this powerful tool, non-technical users can ask any question and get rapid and deeply relevant insights.

“The future of healthcare is increasingly going to be about how we keep people well, not how we deliver more services to them,” said Dr. Philip R. O. Payne, Janet and Bernard Becker Professor, Director of the Institute for Informatics and Associate Dean for Health Information and Data Science at the Washington University School of Medicine in St. Louis. “All of those areas come down to our ability to use our data intelligently, and this technology is a game-changer because it allows us to do that.”

As an intuitive self-service analytics platform, ADAMS overcomes the challenges of other healthcare data platforms. In ADAMS, users find a self-service platform that offers:

• A User-Friendly Interface
  ADAMS features a simple design so that users of any skill level can easily navigate the platform.

• A Simple Approach to Questions
  Users can ask questions quickly and easily in ADAMS, narrowing their patient population down with its extensive, interactive toolkit, allowing them to direct their focus on a subcohort of interest.

• A Longitudinal View of Each Patient’s Journey
  ADAMS organizes information from any source longitudinally, creating a natural timeline for each patient from birth to death, from admission to discharge, and from diagnosis to treatment. The time-related structure allows the user to discover answers based on complex temporal relationships.

• Data Granularity Above and Beyond Other Platforms
  Structured and unstructured data can be imported into ADAMS and seamlessly transformed allowing easy incorporation into data analyses.

• Speed to Impact
  Users can get faster insights into patient populations, leading to faster decision-making and better care for their patients.

ADAMS allows users to ask questions and then interact with the resulting information in minutes. With ADAMS, users can engage with both clinical and non-clinical patient-oriented information as well as structured and unstructured information. With these capabilities, teams can work together to uncover insights and improve patient health in their organizations and beyond.