Transformation in Healthcare landscape
- Post by: Subhash Narayanan
- August 14, 2020
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The health care landscape is going to witness a remarkable shift in the coming decades. The seeds for such transformative changes have already begun showing results. The research and development into such technology-enabled devices and solutions are going to improve the healthcare delivery by making it swift and efficient. Most visible changes in the healthcare sector are going to be the approach of curative to preventive care; which would be the defining driving force behind the futuristic evolution of healthcare ecosystems. Globally companies are investing time and money in collecting data non-invasively, predicting the probability of diseases, to prescribing custom made treatment plan that is best suited for an individual. The early diagnosis of diseases using state of the art technologies integrating artificial intelligence (AI) and machine learning (ML) into a single platform would revolutionize treatment approaches multifariously. Though there is a common perception that medical costs using such devices may not be cheap, on the contrary, it is going to be much less costly than the usual. As the future of healthcare ecosystems looks bright and promising, it is equally going to make healthcare more affordable and sustainable to the rural population. However many such developments are in infancy?
Robotic surgeries are minimally invasive, and provide enhanced precision and utmost control while performing surgeries. More hospitals would adopt such technologies going forward. The surgeries that need more precision and control can be done effectively using robots. Prostate cancer surgeries that involve more complex nerve fibres and blood vessels attached to the gland can be carried out with enhanced accuracy using robotics.
The hospitals in the future would be more patient centric with superior outcomes, so the adoption of robotic surgery may increase in areas that need complex procedures.
This is an experimental technique that uses genes to treat or prevent disease. The treatment technique uses genes to treat or prevent diseases by inserting a gene into a patient’s cell instead of drugs or surgery. There are two different types of gene therapy depending on which types of cells are treated. For example, in Somatic gene therapy a section of DNA is transferred to any cell of the body that doesn't produce sperm or eggs. In the case of Germline gene therapy a section of DNA is transferred to cells that produce eggs or sperm.
It is also known as “Personalized Medicine” and aims to deliver the right treatment at the right time, by customizing treatment according to a person’s genetic makeup. Today, when you are diagnosed with cancer, you usually receive the same treatment as others who have same type and stage of cancer. Even so, different people may respond differently, and, until recently, doctors didn’t know why. After decades of research, scientists now understand that patients’ tumors have genetic changes that cause cancer to grow and spread. They have also learned that the changes that occur in one person’s cancer may not occur in others who have the same type of cancer. And, the same cancer-causing changes may be found in different types of cancer.
Even though researchers are making progress every day, the precision medicine approach to cancer treatment is not yet part of routine care for most patients. Many new treatments designed to target a specific change are being tested right now in precision medicine clinical trials.
Evidence-Based Medicine (EBM)
Evidence-based medicine is an interdisciplinary approach which uses techniques from science, engineering, biostatistics and epidemiology, such as meta-analysis, decision analysis, risk-benefit analysis, and randomized controlled trials to deliver “ the right care at the right time to the right patient.” (Source : AHRQ)
This involves data analytics to explore information stored in unstructured clinical notes by drawing meaningful insights, along with the use of quantum computing, which will help in genome sequencing and make EBM more effective.
The market for non-invasive diagnosis is driven by the prevalence of chronic diseases, such as neurological and cardiovascular diseases. The non-invasive cancer diagnostics are gaining more traction with the help of algorithms and AI. Human genome project had made available huge information on genomic and proteomic analysis, so with the help of AI, diagnosis for early detection and prediction of cancer and diabetics is possible.
Collaboration across value chain versus the competition
We are going to witness the entry of a large number of innovative healthcare solutions that leverage digital technology, aggregating various healthcare services and reaching a large consumer base. New entrants would become a critical stakeholder in the value chain by involving in early-stage decision-making processes and buying cycle. In the future, providers would explore collaboration models to benefit each other, and would also devise comprehensive care built on multi-platform format to cater to smart consumers. The dream of achieving universal healthcare (UHC-2030) built on public and private partnership models are expected to bring the requisite change. Private healthcare providers would seek opportunities in tier-3 cities and rural areas based on increasing healthcare coverage. The healthcare market is more likely to witness various collaborative initiatives that foster more dialogue resulting in a coherent partnership between public and private providers. India as a future economic power needs an efficient healthcare system to navigate its inherent challenges and march steadily towards its goals.