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Dr. Ram Kumar Mishra
25 June 2018

Patient engagement or patient centered approach is the latest healthcare trend that is transforming clinical trials. Traditional system of medical discovery considered patients as a group of people participating in clinical trials. A particular therapeutic delivery was believed to be same for all patients. A standard clinical trial setup comprised of patients and clinicians, and both collaborated with the sponsors to determine the safety and/or efficacy of an intervention. Despite the involvement of patients, clinicians and sponsors, these trials traditionally focused on the practicability and comfort to the sponsors. There were no considerations of a patient as unique individuals with different preferences, needs, and desires. While clinical trials remained an integral part of bench-to-bedside model of drug discovery and development, the ever-increasing complexity of clinical-trials and escalating costs forced sponsors to shift their focus to newer avenues to build trust and rapport among the masses. Consequently, recent day clinical trial services or solutions became more and more patient centric.

How digitalization can help pharma?

Engaging patients in the clinical trial process can help pharmaceutical companies identify the advantages of the new patient-centric approach. Decentralized or site-less clinical trials are indeed mobile trial sites that leverage internet-enabled mobile technology and smart wearable devices empowered by internet of things (IOT), to capture patient data. What’s more, online social media conversations have important implications for the healthcare industry. Recent times have witnessed an increase in the plethora of social listening tools that can enable firms to listen in. Volumes of social messages can now be converted to a structured patient voice that can significantly impact the strategy of all healthcare businesses. Listening to patients or other key stakeholders talk freely about their experiences, preferences, and needs around disease management and product usage is a step towards a patient-centric approach.

Let’s find out how a data-based approach can enable a patient-centric ecosystem for clinical trials.

1. Patient Recruitment

Digitally pre-screening patients for a trial and learning early on if a patient is the right candidate will enable faster, yet efficient patient recruitment, thereby reducing the overall trial time. By using big data analytics on electronic health records, eligible patients can be identified from a given population. This also helps sponsors and clinicians to determine if a population has enough number of patients to start, identify a specific patient pool for a clinical trial in a short time span, and speed up the patient on-boarding and profiling processes.

2. Gaining Insights about Patients

Data analytics and insights can help companies to make accurate and complete data-driven decisions. Social listening tools help to gather actionable insights. Patients participating in educational forums and online clinical trial communities create useful online information repositories. Such patient-engagement resources can be utilized to learn and improve overall clinical trial outcomes.

Since healthcare industry is a largely regulated industry, different stakeholders such as healthcare providers, payers, and pharmaceutical companies always give first priority to accurate documentation. Effective documentation will help in making sense of patient data by leveraging big data analytics.

3. Real World Evidence

Real World Evidence (RWE) can help companies retrieve a very objective set of patient data based on real-world experience. Patients often have different characteristics and different treatment protocols that might differ from controlled clinical-trials conditions. Present day clinical trials adapt a generalized approach for all the patients. To evaluate real world product effectiveness, more information is required about intervention efficacy in different age groups, gender, and ethnicity. Other factors like co-morbid conditions also play a major role in treatment outcomes. Thus, real world evidence can provide important health information that has been ignored by traditional clinical trials setup. The data obtained from RWE can provide key insights thereby enabling healthcare stakeholders to mass personalize their products or offerings to a segment of one. RWE also improves both safety and effectiveness for patients thereby significantly lowering medical costs.

4. Electronic Records

Electronic health records play an important role in data sharing and health analytics. With more hospitals adopting electronic health records (EHR), healthcare stakeholders (claim agencies, marketing, forecasting teams, suppliers and government) are able to easily and seamlessly exchange data between them. Digital data supports clinical research because it is considered more secure and versatile than physical form of data, and it facilitates retrospective analysis of patient records.

Patient-engagement is transforming the form and function of clinical trials. More and more companies are coming forward to partner with patients to develop new drugs and devices to meet patients’ expectations in real-world conditions. While currently there is no consensus regarding the ideal approach for patient engagement, regulatory agencies and pharmaceutical companies are leaning towards a patient-centric ecosystem. With the patients feeling empowered and being heard, it would be a win-win situation for every business in healthcare.

About the author(s)
Dr. Ram Kumar Mishra

Dr. Ram Kumar Mishra is Assistant manager in the Analytics and Insights unit at Tata Consultancy Services (TCS). Dr. Mishra works with the Medical Writing and Health Economics and Outcomes Research (HEOR) team to deliver epidemiological systematic literature reviews. He focuses on health economics techniques with applications in healthcare analytics. Dr. Mishra holds a Ph.D. in Computer Aided Drug Design and Neuroscience from BITS, Pilani, India. He has a patent for a series of compounds to treat epilepsy and neuropathic pain to his credit.