By Rajkamal Rentala
In the past few years, the constantly increasing availability of real-world data sources has transformed the analytics and decision-making domain in the healthcare life sciences segment. Accessibility of this data at the patient level provides opportunities for patient-centric analytics, offering deeper insights into how they are diagnosed, treated, and beyond. Given this backdrop, one needs to understand the resulting health outcomes and the cost of achieving such outcomes. The greater availability of patient-level data helps practitioners better understand the patient journey. Every day, the healthcare industry generates massive mounds of data from a wide variety of sources. These include patient records, hospital administration data, and claims.
Although a broad spectrum of data is available, often, the sources are fragmented and incomplete. Since patients are end-consumers, they need to be brought to the forefront of the decision-making process.
The Paradigm Shift
Worldwide, pharma organizations are now focusing on the development of drugs for rare diseases and the opportunities to create innovative therapy regimens to treat patients. But this requires accessing patient narratives that go beyond treatment and diagnosis. Undoubtedly, easy access to online platforms and other sources has made today’s patients more knowledgeable. Consequently, their expectations have soared vis-à-vis access to care, early diagnosis, prevention, ongoing education, and seamless care coordination. Present-day patients wish to self-manage their health. As a result, they expect pharma firms to provide value beyond the pill. However, the million-dollar question is: are pharma companies
prepared to manage such diverse and burgeoning patient expectations?
The Current Challenges
Despite significant technological advancements, bringing together disjointed data sets continues to be a hurdle in the highly regulated healthcare industry. Since the data from patients’ pre- and post-diagnosis periods is primarily unstructured, it cannot beutilized in its present form. Therefore, much more needs to be done in this space to connect the data dots for better usage in the healthcare ecosystem.
Another issue: in the effort to understand the end-to-end management of diseases, less than adequate attention is paid to the patient journey. Presently, patient journeys are typically perceived from the perspective of the treatment pathways by utilizing only one or two sources of data. However, more insights could be gained if their journeys are analyzed holistically using cohesive data.
Opportunities to Impact Patient Outcomes
Improving treatment decisions: One can trace the entire patient journey by streamlining disjointed patient-centric data into a consolidated data hub. After that, well-informed clinical and commercial decision-making is possible, which results in actionable patient-specific insights.
Empowering patients via involvement in decision-making: By creating holistic patient engagement strategies that go beyond medication and compliance norms, one can enhance patients’ experiences as well as their involvement in the decision-making process. This would eventually help improve medication adherence, one of the biggest challenges the healthcare industry faces.
Enhancing patient care and delivering a holistic patient experience: By using predictive analytics in the healthcare sphere, one can improve overall patient care, hospital administrative functions, supply chain efficiencies, and management of chronic conditions. Backed by data insights, healthcare providers can enhance patient outcomes while providing better, comprehensive care via faster, more accurate diagnoses and personalized healthcare delivery.
Conclusion – Boosting the Healthcare Industry’s Efficiency
The value of patient data remains incalculable in a segment where millions of priceless data pieces move continuously from one end of the spectrum to the other. Thanks to technological advancements, one could convert this data into knowledge or information that can then be used to offer improved healthcare services to the ultimate consumers. Considering the impact of data analytics in areas as diverse as disease prediction, cancer therapy, and medication research, the delivery of healthcare services is poised to change. Unlike other businesses, however, the healthcare industry has been much slower in adopting novel technologies. Nonetheless, its influence is already being felt within a short span.
By leveraging advanced analytics tools and given the continuing geometric growth in the quantum of data that may be analyzed, almost every element of healthcare can be affected. This includes the accuracy of insurance prices, automation of administrative processes, and the application of artificial intelligence in diagnostics. Finally, pharma players must explore partnerships with varied stakeholders within the healthcare space who can facilitate access to patients and their invaluable data.
(The author is a Director, Decision Science, Axtria Inc. Views expressed are personal and do not reflect the official position or policy of the FinancialExpress.com.)
