Customer Experience and Design

EMR 3.0 and Doctors Lacking an Analytic Engine

As a big fan of kevinmd.com, I enjoyed reading David Nash, MD’s take on how doctors need an “EMR 3.0” analytic engine for accountability and that creating an analytics tool that monitors gaps in care for a provider’s population is very important for accountable care. We also agree that as successful as the big EMR vendors have been that they don’t have an analytics engine that promotes accountability and measurements of quality and safety. My argument is that as a result of the large number of data sources in the typical healthcare organization due to the myriad of healthcare applications, the analytics engine needs to combine data from all of those sources, normalize the data and deliver the quality and gaps in care dashboards independent of the EMR system.

David’s practical idea that clinicians need an analytics engine that sits on top of the EMR, one that is capable of sweeping up clinical data and converting it to information that will improve clinical decision making, is accurate and exists today. Moving all of those data sources into a centralized enterprise data warehouse with a comprehensive and standard healthcare data model is the key to success. Reconciling the medical vocabularies to a set of consistent data elements empowers real analytics. Those capabilities exist in a well-established product called BI-Clinical from CitiusTech and that product has the key capabilities outlined on David’s wish list as an “accountable” primary care clinician in the modern healthcare environment, including:

  • A data warehouse that combines clinical, administrative and financial data
  • Calculates and reports on all 33 of the Accountable Care key measurements
  • Disease registries to monitor and evaluate patients – not just individually but as a population
  • Tracking of chronic disease management for patients with specific diagnosis like asthma
  • Information on medical management including appointments, receivables and operations
  • Ability to set and compare a practice with national benchmarks
  • Ease of accomplishing these analytics on-line and via mobile devices, like a tablet

The best aspect of this comprehensive analytics engine is that it is built on the Microsoft business intelligence products to keep the total cost of ownership down and it can be deployed as a cloud-based solution, if needed. If my response seems too enthusiastic, there are many incomplete or partial solutions for healthcare analytics in the marketplace that solve only one or two key aspects because they lack a measurement engine that comes with 600 pre-built key performance indicators including certified Meaningful Use metrics or Physician Quality Reporting metrics. It is a common complaint fielded by those of us in healthcare consulting: “We know that we collected the data in the EMR and it needs to be combined with cost data to evaluate treatment alternatives or the cost of outcomes.”

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I hope Dr. Nash is attending HIMSS 2013 in New Orleans and he can see this EMR 3.0 analytic engine solution in the CitiusTech booth (#4169), the Microsoft booth (#1127), shown as HealthBI, or the Perficient booth (#1555). I believe he will be impressed with how the BI solution addresses his wish list and is available today. Be sure and ask to see the Gaps in Care demonstration as well; it is really state of the art.

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Martin Sizemore

Enterprise Architect with specialized skills in Enterprise Application Integration (EAI) and Service Oriented Architecture (SOA). Consultant and a trusted advisor to Chief Executive Officers, COOs, CIOs and senior managers for global multi-national companies and healthcare organizations. Deep industry experience as a consultant in manufacturing, healthcare and financial services industries. Broad knowledge of IBM hardware and software offerings with numerous certifications and recognitions from IBM including On-Demand Computing and SOA Advisor. Experienced with Microsoft general software products and architecture, including Sharepoint and SQL Server. Deep technical skills in system integration, system and software selection, data architecture, data warehousing and infrastructure design including virtualization.

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