Ashvini Danigond, Founder and CEO, Manorama Infosolutions Pvt Ltd

Ashvini Danigond, Founder and CEO of Manorama Infosolutions Pvt Ltd (MIPL), is a successful global entrepreneur and tech-innovator working on Innovations in healthcare information technology (IT). She has been conceptualizing, architecting, and delivering world-class healthcare solutions for over 17 years. With Master’s degrees in Healthcare, Computer Sciences, and a degree in Law, this enables her in adopting a unique 360-degree command of Data Sciences covering Domain, Technology, and Regulatory nuances.


The Covid-19 pandemic has been responsible for testing the ultimate limits of the healthcare system since last year. Against the backdrop of the second wave of the Covid-19 cases, if the present status of the healthcare system in the country is to be analyzed, the relatively slow pace in the adoption of digital technology, and resistance to share ownership data of patient treatment has created a lot of challenges at the district administration level. For instance, whether it comes to planning for Remdesivir stocks, vaccination drives, medical oxygen availability, or ultimately bed management in a particular hospital, the specter that confronts society is a grave one. In fact, the situation is such that there is no centralized repository available in India to understand the current status of the pandemic. In India, generally, the data collected for patients is split between the government and private healthcare systems, this, too, is done partially.

For that matter, consider another scenario, which pertains to mutation of the novel coronavirus. The current Covid-19 cases may be a mixture of various strains. After proper identification of the first lot of the novel coronavirus strain, a new double mutant strain of the SARS-CoV-2 virus has been detected in India. Similar strains have been detected in more than 17 other countries across the globe. However, the ground reality is that the healthcare community in India does not have any statistics available to plan their activities or devise any further course of action.

On the other hand, consider a situation that is related to the supply of coronavirus vaccine. At the end of February 2021, the demand for Covaxin was very low. Out of the seven companies permitted to manufacture this medicine in India, at least 6 lakh doses available with pharma companies were on the verge of expiry, so everyone was forced to cut down production. The demand, however, started to spike around mid-March 2021. Earlier, this medicine was administered at a later stage. but now doctors are almost treating it as the first line of treatment, especially in Maharashtra.

Companies have enhanced efforts for production, but the cycle to ramp up production to optimum capacity is 45 days. The maximum doses India can produce is around 42 lakh per month. Companies have been supplying available stock only to hospitals. Hospitals have to upload patient details in every case. This is to prevent black marketing. However, for pharma companies meeting the demand continues to remain a challenge.

Further, there is the exacerbation of the Covid-19 crisis in the form of a shortage of medical oxygen in various states. Take, for instance, Maharashtra’s total production capacity is around 1,150-1,200 metric tons. The State government has reserved 80 percent of the supply for medical use. But as per the statement issued by the chief minister of Maharashtra, the medical use had already reached 700 metric tons, which now should be between 850-900 metric tons. So, now 100 percent will be required to be reserved for medical use and have to think beyond it as well.

Need for Digitisation in Healthcare Sector Ever Than Before

In the context of the above-mentioned critical scenarios in the healthcare sector, digitization of the healthcare ecosystem and processes becomes imperative, if the situation has to be improved any time soon for all stakeholders in the long run.

All these years, the Indian healthcare market, propelled by challenges—mainly an aging population, a shift in the disease burden, rural accessibility to healthcare, manpower shortage, low insurance penetration, inadequate public sector investment, and inconsistent quality standards, has been in the need for major intervention. Today, this need for digital technology intervention is more than ever before as the nation continues to grapple with the global pandemic.

A case in point would be to showcase that across western nations, Electronic Health Records (EHRs) are a vital data resource for research uses. India, however, continues to be in the early stages of the adoption of digitizing patient records. While a few states have mandated the use of EHRs in public hospitals, besides, a few large and specialty hospitals have also adopted the use of EHRs, these records are generally to maintain summary records of patients to consider for billing purposes rather than for clinical purposes.

It has been observed that limited population health management (PHM) tools appear to be available with authorities. Population health management—working to improve the health outcomes of groups instead of individuals—makes financial sense when hospitals are paid capitated rates to care for populations or when it can be used to increase the volume of care delivered.

Similarly, access to health records of patients across multiple settings can be available through health information exchanges (HIE), which aggregate data in a particular region and make it available to healthcare providers through a single interface or Application Programming Interface (API). HIE can enable providers to develop analytical insights to risk-profile their patient populations and intervene in a timely manner.

For companies engaged in healthcare in India, clinical data management continues to pose a significant challenge. Time and again, it has been pointed through various studies that such challenges prove to be hindrances in the care delivered to patients. Moreover, physicians, including clinical staff tend to spend a considerable amount of time accessing and updating documents, resulting in more man-hours being spent at the job for documentation work leading to undue stress.

In India, big data and analytics are being leveraged to aggregate data to drive more tailored products and services. It has provided instruments for the accumulation, management, analysis, and assimilation of large volumes of diverse, structured, and unstructured data generated by the healthcare systems. Big data holds the potential in addressing a multitude of challenges, once patient health records are digitized, and longitudinal patient records are created and maintained.

Healthcare Big Data Analytics (BDA) has the potential to improve the quality of care and bring better efficiency and delivery models by finding the associations from massive volumes of healthcare data, thereby offering a wider perspective of clinical expertise based on medical evidence and various tests. BDA mainly performs three types of analytics: descriptive analytics, predictive analytics, and prescriptive analytics. Descriptive analytics facilitates exploration insights and allows healthcare practitioners to understand what is happening in a given situation. Predictive analytics involves various statistical techniques used to analyze and extract valuable insights from big data. On the other hand, prescriptive analytics is comparatively a modern type of analytics that combines descriptive and predictive analytics. This then when modeled using AI/ML tools can give us intelligent insights resulting in better clinical and operational outcomes.  

In order to enhance accuracy in diagnosis, longitudinal clinical data of people is extremely useful and can help analyze a whole variety of problems, involving symptoms, pharmaceuticals, and dosage. It would be much more difficult for medical professionals to come to the right conclusions without this knowledge.

Similarly, Artificial Intelligence (AI) and Machine Learning (ML) hold the potential in upping the ante in the healthcare ecosystem. From identifying new molecules to predicting adverse events, from forecasting across the supply chain to predicting the next best action for the healthcare staff to suggesting the best line of treatment, the usage of AI in healthcare is quite diverse and deep. In addition, Genetic and Deep Learning techniques along with advanced technology options like Quantum computing, can open newer vistas in advanced healthcare.

Summing It Up

In India, the adoption of digital technology to streamline processes like medical record-keeping, sharing of healthcare data, appointments, and other healthcare processes would prove beneficial in making informed decisions on treatments and prevent citizens from being exploited by some unscrupulous elements due to general lack of awareness.

Through digital technology, there is an ease in the patients’ transfer from one healthcare provider to another and also ensures transparency in the pricing of the services provided within the healthcare sector.

Telemedicine and e-pharmacy, envisioned under the National Digital Health Mission (NDHM), have already gained traction during the ongoing pandemic, when patients have limited access to the healthcare providers, especially in far-flung areas. 

Steps have been initiated in the right direction with the Health Facility Registry (HFR), which will have a live and consolidated database of healthcare resources and infrastructure within the country. This will also help in policy planning to address the gaps in the system. Overall, it is hoped that disease burden assessment would be made easy for policymakers. The spread of non-communicable diseases (NCD) can be easily monitored and remedial measures can be given at the earlier stages rather than waiting for the situation to reach a critical stage.

The government using the available data can ensure the health policies are implemented based on geographical, demographic, and risk-factor-based monitoring of health. It reduces the expenses on healthcare for patients by minimizing the need for repetition of tests and other medical activities in case the healthcare provider is changed. Further, the duplicity of tests is avoided by bringing in testing standardization and helping to analyze whether correct care is extended to a particular patient. In addition, providing unique identification to the doctors and health facilities can ensure the quality and accountability of the health services.

Interoperability of the health data further encourages free entry and facilitates competition and entrepreneurship among small and large players, both in the private and public sectors. Further, it is imperative to incentivize healthcare providers for the adoption of digital healthcare ecosystems as part of their delivery and care models.

All in all, digital evolution in healthcare is quite necessary for making a critical difference. The right time is, now.

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