We are collecting much more data than ever, including patient-generated data from various smart devices, but we still face several roadblocks to provide a holistic view of patients. To get a true 360° patient view, we need to address or navigate through several key challenges.

1. EHR (Electronic Health Record) Data Silos: Most people have dental insurance/dentists and medical insurance/general physicians for their needs. Similarly, EHR systems focus on medical practices/hospitals or dental practices with minimum connection, if any, between the two. Research shows that several disease states, including specialty care diseases like oncology, reveal early signs in dental screenings. Still, it is not a top priority for EHR software vendors to provide a comprehensive view of patients across their dentist and medical doctor.

2. Multiple EHR Software Solutions: Several EHR software vendors are on the market, and physician practices are left to make the judgment call of picking the right tool for them. While there is patient-related data sharing between physicians using the same EMR systems, interoperability remains a challenge when physicians participate in different hospitals using different EMR systems. Even as a patient, there is a high possibility that your primary physician uses a different EMR than an urgent care facility, so your data is not easily accessible when you are admitted to urgent care.

And, as of now, there is no single profile view to generate the complete health background (active medications, surgeries performed, known allergies, lab results) of an individual that is agnostic to the EMR system the physician is using.

Ultimately, the focus of EMR system improvements needs to reside in better connectivity to billing systems as well as support for specialists’ needs instead of sharing patient information between competing products. But, limited progress has been made in sharing information across EMR systems such as Direct Secure Messaging and FHIR (Fast Health Interoperability Resources), which is still in its initial stages.

3. Lack of Clear Data Strategy: Every organization knows they need to collect data to be competitive, but many times there is not a clear definition of what classifies as data or what will the data be used for. For many healthcare organizations, data seems to be more of a learning experience than an established practice.

4. Discovery Phase: Organizations must start with a discovery phase of the data they want to collect. For instance, they should consider what additional data they need to fill the gaps in order to gain market advantage. This phase should also include an examination of common data language, understanding of what data elements can be exchanged between organizations, and data de-identification needs.

In an era in which technology can track where we parked our car in terms of geo-location features, healthcare technology needs to evolve to its next level of providing the connected patient view.

  • Sangeeta Krishnan

    Sangeeta Krishnan is Head of Enterprise Data Management at Asembia. Sangeeta has spent the past few years evangelizing an industry-wide shift to data science and has successfully led the transformation of the data landscape at her current workplace—Asembia, an industry leader in providing collaborative solutions to the specialty pharma sector.

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