Navigating the data deluge in healthcare

Digitization in healthcare in enabling better patient care by streamlining processes, enabling remote care and facilitating preventive analysis. However, with the implementation of advanced technologies, such as Internet of Medical Things (IoMT), telehealth, robotics, genomics, and nanotechnology, there has been a data deluge. According to IDC (International Data Corporation), data is globally expected to hit 175 zettabytes (10,000 TB) by 2025. 

The generation of this data in large volumes is saved in different formats and comes from multiple sources, which can hinder its effective utilization. Compiled, cleansed, synergized, integrated and readily available data, on the other hand, can harness the potential of innovation and help build the future of healthcare. 

Patient journeys through the healthcare system involve multiple touch points, which can leave room for misinterpretation or unnecessary duplication of medical information. The use of real-time data and analytics throughout the care continuum can ensure timely and successful care coordination, making a significant impact to patients’ overall experiences. 

Challenges to navigating the data deluge 

To extract valuable insights from the continuously expanding data assets, organizations need to overcome the barriers standing in their way. 

  • Multiple sources of unstructured data 

Healthcare organizations collect huge volumes of data from multiple sources including patients, providers, and pharmacy in addition to claims data, data from social determinants of health (SDOH), compliance-related data and plan-specific data. Many organizations are either incognizant of this exhaustive bank of information or the absence of standardization in data storage, preventing different stakeholders from getting the full picture of an individual’s health condition. Using a combination of identifiable and de-identifiable data sets to derive accurate insights can also be complicated with existing data regulations. Effective authorization processes need to be created to obtain scientifically precise facts from the available data without compromising patient privacy. 

  • Complexity of data 

Healthcare data today is complex and often lacks structure due to non-adherence to standards and stringent privacy policies and regulations. These roadblocks make it increasingly difficult to efficiently take advantage of this data bank.

A 4-step navigation framework 

To manage the data deluge effectively, organizations need to step back and re-evaluate their data strategy. Stakeholders can implement an easy 4-step framework to modernize, streamline, and simplify the health system using the existing massive data reserves: 

Step 1: Acquiring, storing, and understanding the data – The first vital step is to build processes that enable procurement of real-time data. Stakeholders also need to evaluate the pros and cons of storing data on different environments such as in-house/ premise data centres, the cloud, or a combination of these for ease of accessibility, understanding, and usage. 

Step 2: Standardize the data and run quality checks – Raw data requires standardization in order to be processed, compared, and understood. Once stored, it needs to be organized and tagged by its source, time of collection, contents, frequency of transfer, and so on.

Data must also be categorically standardized to serve its objective: to be leveraged within a business, at the enterprise level, for patient use, etc.

The data must undergo regular checks to ensure its quality, consistency and credibility. Implementation of artificial intelligence and machine learning models would also help in identifying data quality issues and anomalies. Data protection throughout the lifecycle, both at rest and in transit, is a critical part of creating a successful framework. 

Step 3: Integrate the data With a thorough understanding of the consumption use cases, it is imperative to integrate all the data lying in silos using solutions such as cloud-based Integration Platforms as a Service (iPaaS), federated learning models, graph databases and build linkages to draw deeper insights and actionable outcomes.

Step 4: Enable the application of data Once data is acquired, catalogued, protected, and integrated, the next step is to enable its use by identifying its potential users and the expected outcomes. This necessitates constant monitoring and analysis of the business landscape, and propagating that knowledge into the integration process, thereby creating a strong and seamless feedback loop.

Preparing for the deluge on the horizon 

The industry is moving toward building more robust end-to-end data pipelines with necessary solutions supporting governance that ease data management and enable its consumption. New regulations will further enforce the adoption of standard data formats. However, with the rapid growth of genomics, 5G networks, edge computing etc. the deluge of data would only escalate. 

With healthcare providers primed to offer precision treatments based on genome sequencing patterns for critical and chronic diseases, the healthcare sector will need to make itself future-ready to deal with the challenges of storing, processing, analysing, and safeguarding the complex data born from it. Building new solutions to manage and keep up with its increasing volume would require a strong technological workforce. The ever-increasing data arsenal is here to serve us, and the right innovative talent will enable us to use this tool to empower the health system and make it work better for everyone. 

The article has been written by Saikumar Chintareddy, Vice President – Software Engineering, Optum Global Solutions(India) Private Limited

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