‘There is always N + 1 innovative solutions for any problem, where N is the number of solutions that has been tried and 1 is the best solution’
With an estimated annual expenditure of $3 Trillion USD, US healthcare is the largest in the world and certainly not new to challenges. These challenges created a lot of opportunities for research and innovation, generating large volumes of useful data in the process. A few decades ago, the challenge was how to store this data and process it, but thanks to the technological advancements, we have moved forward.
The technological advancements have also brought in a lot of innovative solutions to solve some of the specific problems in the industry. Now we have a whole new breed of systems that interface with various stakeholders and collect data, resulting in exponential data growth. The type of data varies from patient medical records, health data from IOT devices and HIS, social-element inputs from third party systems, payer data from claims, feeds from clinical trials and pharmacies etc.
The IBM Watson study states that the volume of healthcare data has reached 150 exabytes and would soon be in zettabytes and yottabytes. That’s enough data to fill a stack of DVDs that would stretch from Earth to Mars! Also, the new waves of change in healthcare like patient-centric care and value-based payments have further pressed the need for collecting more and more patient data.
The big data ‘usability’ challenge
Our healthcare industry is facing an information overload with data growing at a staggering rate of 48% a year. That brings us to a new challenge- how to make meaningful use of such large volumes of data. A survey reveals that almost 44% of healthcare organizations are unable to use all the available data, costing our healthcare industry an enormous $350 billion per year.
This is, in fact, an unprecedented challenge that the healthcare innovation cycle is trying to address.
We are unable to utilize patient data in a holistic manner to make medical progress. For instance, helping Providers with timely access to accurate patient information is inevitable for evidence-based decision making and successful diagnosis. However, the data captured through multiple systems are not consolidated or shared, which is a roadblock for insightful analysis. Also, since it is collected through multiple systems, healthcare data is complex and requires complex analytics to ensure meaningful use.
All these hurdles are resultant of data sources working in silos and their inability to achieve interoperability among themselves.
Solution lies in Integration
The challenges in the usability of mounting patient data have stalled the innovation cycle which can be accelerated only via achieving interoperability between systems.
The National Institute of Health reports that integrating healthcare systems can help in cost reduction and economies-of-scale. Integrated system alone can facilitate seamless communication between providers which is essential for a seamless care episode. Building master patient data by enabling integration between multiple systems will give the stakeholders a 360o view of patient information. This helps significantly boost medical efficiency, control medical errors, reduce cost and improve population health outcomes.
A McKesson report states that better data integration can save US healthcare a whopping $300 billion a year. Government programs including Meaningful Use and the HITECH Act have made it mandatory for various IT systems to comply with interoperable standards to exchange patient data.
Many developments in the healthcare industry cannot deliver meaningful results without crossing the hurdle of data integration. Integration is no longer a ‘good-to-have’ option but a ‘necessity’ and it’s time to embrace this shift.
Before venturing into integration, there are certain pre-requisites you need to know for riding in the right direction. In the next post, we will take a look at various challenges in integration and the approaches to tackle these.
