For over a decade now, big data has played a pivotal role in the healthcare industry. For starters, there has been a massive increase in healthcare data on the supply side. According to Allied Market Research, the market size for big data analytics in healthcare was US $16.87 billion in 2017. And, it is slated to touch US $67.82 billion by 2025.
Broadly, data analytics has influenced decision making at three levels: One, it has enhanced the ability of the healthcare professional to make better, informed decisions using data analysis. Two, insights from data have certainly helped key stakeholders from pharmaceutical companies and medical device players to insurance companies and even the government make systemic decisions. Three, healthcare enterprises make better business decisions on financial planning, marketing, operations, quality, and even risk management.
But there’s one thing that is a core process of any healthcare analytics project. And, that is data aggregation. The quality and robustness of the data aggregation process can make a major difference in the process of delivering insights.
Learn how Indium helped a health-tech firm to upgrade their legacy app to improve performance even as the user base increased
While this may very well be the case in most sectors, in the healthcare sector, data aggregation often becomes even more important and challenging. The key reason for this is that – individual patient data must never be shared and cannot be compromised. Unless, of course, patient-specific data is used to deliver care to the same patient.
The data picked up from EHRs (Electronic Health Records) must be aggregated as a group, without compromising on any healthcare regulation, HIPPA rules, and even medical ethics.
Additionally, for true insights to be drawn, data must be captured from multiple EHRs. Once captured, this data must be aggregated and prepared for analysis. While Data Quality Validation (DQV) is certainly a critical aspect, even more important is the adherence to rules and regulations, while still running a seamless data preparation process for analytics.
In this post, we focus on how Indium Software can play an important role in helping various companies in the digital healthcare industry run a seamless, cohesive data aggregation process from multiple EHRs.
Specifically, we can support companies in the following areas within the Digital Healthcare Landscape
Companies within each of these segments need data aggregation from multiple sources.
But, the quality of this data aggregation process must be top-notch and, more importantly, fit in with their current workflow.
Broadly, the following are the 4 pillars that make Data Aggregation extremely important:
Indium Software has served the healthcare and related industries for over a decade now, offering Data Analytics, AI, Digital Transformation and Software Testing services. We serve companies of all sizes – from mid-size growth companies to Fortune 500 companies.
As we further embrace Digital Health with renewed enthusiasm, now may be the time to leverage its full potential by deriving key insights from data.
If you have a specific query around our data aggregation service for the digital healthcare ecosystem, give us a shout.
For more information, visit: Healthcare And Life sciences
By Uma Raj
By Uma Raj
By Abishek Balakumar