The Healthcare industry, which is usually cautious and measured in technology adoption, saw hyper-growth in adopting digital transformation initiatives and innovations, thanks to the onset of the global pandemic. Data-driven initiatives have become a valuable source of efficient healthcare service delivery and competitive differentiation. A data-driven approach can contribute towards standardization of processes and meaningful use of patient data for performance optimization, cost optimization, improving revenue cycles, healthcare management, and health outcomes. The approach will improve patient care, quality of service, outcomes, experience, and satisfaction level. The right set of people, processes, tools, and technologies and their correct implementation can help healthcare organizations make informed, data-driven decisions.

With rapid advances in technology, the sources of health data have been increasing. Data is not limited only to EHRs and EMRs these days. Other sources include medical monitoring devices, fitness tracking apps, social and demographic information, and wearables that collect patients’ health, fitness, and lifestyle patterns. Providers can implement intelligent systems to make proper use of this data to drive positive healthcare outcomes. They can suggest preventive measures such as avoiding a particular exercise or identifying an allergic food item. They can indicate the need to visit a doctor or prevent a severe ailment or incident.

A unique example of simple preventive care can be seen in the latest contact-tracing application used by many governments worldwide to control the deadly coronavirus spread. Secured tracking of an individual’s location and tracing their proximity with potentially infected individuals, and then drawing a graph of people who came in contact with them helped many governments to arrest the outbreak at the right time. The presence of this intelligence on the ground also helped payers and providers to plan resources accurately and efficiently.

We can see another use case that involves applying computer vision for spatial analysis to determine the people count in an area, monitor the social distancing rules, or keep a check on the headcount at the entry-exit points. Organizations can use the data streams for proactive governance like planning, resource allocation, infrastructure, and logistics. Payers and providers can see patterns and gain insights regarding upcoming trends and scale their infrastructure to ensure continued patient care, cost optimization, and improved revenue cycle management.

Patients perform numerous activities and transactions via multiple paths at multiple touchpoints. Integrating all the sources becomes essential to get a comprehensive picture, especially when diagnosing and treating a patient. Providers must also collect and model the appropriate data based on real-world scenarios to get the best business value and outcome for themselves. Towards streamlining operations and standardizing data collection and storage, the healthcare industry is making good progress. Standards such as EHR, HIPAA, HL7, NCPDP, IHTSDO, DirectTrust, or CDISC have evolved to help organizations exchange data and interoperate.

Technology solution partners can implement the latest solutions based on paradigms, including event-driven architectures, microservices, HTTP web services, and web-hooks to integrate from diverse sources in real-time or on-demand.

Despite all the above possibilities and a wide range of benefits, these data-driven initiatives come with a few challenges. One of them is the security and privacy of an individual’s health and medical history. Mobilizing such sensitive data to solve business problems may prove challenging as standards and regulations are constantly evolving. Even between EHR and EMR, the former is more difficult to maintain because it is a longitudinal collection of individual patient’s electronic health information. EMR, in contrast, is the patient record created by providers for specific encounters in hospitals and ambulatory environments. It is comparatively easier to set up and maintain but can serve as a data source for an EHR. However, the standardization format can vary between providers, presenting a challenge to integrate into a patient record.

Healthcare data is heavily regulated to avoid mismanagement. The regulations vary from one geography to another and can change over time. Frequent changes to the underlying data formats and collating data across geographical boundaries with different legal and regulatory restrictions can hinder deep analysis and implementation of intelligent systems that usually need data in a consistent form.

According to a 2020 IDC report, the sum of the world’s data – the DataSphere — will grow from 59 zettabytes in 2020 to a mind-boggling 175 zettabytes by 2025. The healthcare data sphere is expected to grow at a CAGR of 36% during the forecast period. In another survey, the global healthcare analytics market is expected to increase to USD 24.55 Bn by 2021, up from USD 14 Bn in 2019. 

With increasing demand, competitive pressures, and technological advancements, healthcare organizations must build a data-driven strategy with a vision of 10-15 years into the future. Healthcare providers must leverage the abundance of quality data to gain insights and optimally use their resources to provide standardized, efficient, and quality patient care.