Virtual health: Delivering care through technology

Virtual Care, Telehealth, Telemedicine, etc. are terms used very synonymously. Indeed they are interrelated, however, Virtual Care is a broader term in which healthcare providers use digital tools to communicate and deliver care to their patients. Telehealth and Telemedicine are a part of Virtual Care where doctors deliver care to their patients, remotely via phone, video, or instant messaging. Virtual health includes care delivery beyond video consultation where hospitals provide services using technology such as wearables for remote monitoring, instruments for post-op care and second opinions, e-pharma services, and medical information, etc.

The outbreak of the COVID-19 pandemic gave an impetus to Virtual Care, but even in the Pre-COVID time, the Healthcare sector was slowly gearing up for this next wave in care delivery. What COVID-19 did was, help patients get acclimatized to the digital health tools and services.

What does Virtual Health help with?

The pandemic has brought the burning issues of the healthcare sector to center stage. Patient experience and access to healthcare services are key differentiators for people while choosing a healthcare provider. Let’s take a look at some of these issues addressed by technology in the healthcare sector-

The increasing number of patients

Apart from the pandemic, there’s already been a rise in the number of patients due to drastic changes in lifestyle and food habits, an increase in pollution levels, increase in new types of viruses, etc. This has caused undue stress on healthcare institutions and workers and has led to the deterioration of the quality of patient care. Virtual Health technology such as mobile healthcare apps, EHR (Electronic Health Record), video conferencing, etc. has helped reduce the pressure on hospitals.

Difficulty in traveling for old patients

The pace of life is increasing at a rapid rate. It is getting insanely difficult for the elder population to navigate through the traffic and commute long distances for a check-up. Many times, they have to depend on their family members to take them to hospitals. Moreover, they are at risk of exposure to viruses in hospitals and clinics. Now that they have had the experience of virtual consultations, they prefer care delivery at home rather than going to hospitals.

Chronic Diseases treatment

The number of people above the age of 45 face health issues. Some patients are suffering from chronic diseases regardless of age. Regular monitoring of their vitals is very important. Moreover people now prefer Virtual healthcare services which are easily accessible and save a lot of time, effort, and money. Now that people have found these services effective, they will opt for online consults rather than frequent in-person visits.

Post-op Care

The duration of post-operative care is quite long and tedious. If given a choice, people will lean towards wearables which will help keep doctors posted on the status of the treatment. Many times, the cost of post-op care is more than the actual treatment and sometimes is not covered under insurance. Virtual care-delivery services will help reduce the financial burden of people going through these treatments.

Follow-ups/Second opinion

Some health conditions need multiple follow-ups and second opinions to figure out the right approach to treat the issue. It is much easier for patients to do follow-up consults virtually rather than going through the tedious process of appointment booking, commuting, and waiting for their turn. It helps reduce the queue outside the doctor’s office as well. Some health issues need a second opinion, sometimes both by patients and doctors. Virtual Healthcare technologies make it possible for them to take second opinions from doctors all over the world. With electronic records and image sharing, doctors can diagnose the problem better.

What does Virtual Health include?

Virtual Health can be broadly divided into below applications-

mHealth Applications

Mobile health applications have widespread use. From symptom checkers to appointment booking, from fitness trackers to uploading medical records, from video conferencing features to chatbot integrations, mobile healthcare apps in India are on a rise mainly because of easy accessibility for the tech-savvy customers. According to a study by NCBI, among the 22 selected mobile healthcare apps in India, Practo, mfine, DocsApp, 1mg, Netmeds, Lybrate, MediBuddy, and Medlife were found to be the eight most popular ones with over a million downloads and on average four-plus user rating out of five. All the above apps are mainly being used for online consults. This just goes about showing that people prefer having homecare services instead of stepping out.

E-Triage Tools

The rising number of patients with different stages of COVID symptoms was a task to deal with. E-triage software here enables hospitals to triage patients into different sections when there’s an overload of patients at a particular time. Now, in the case of home care, e-triage tools help patients to access the gravity of their health condition and notify the healthcare provider accordingly. Such tools help reduce A&E waiting time and improve NHS performance. Many companies are building healthcare software integrating the E-triage module within EHR, telemedicine, clinical decision making, billing, etc. In India, Persistent Systems’ cutting edge platform has a Nurse Triage system that enables nurses to see the queue of patients and triage via phone calls. Once the calls are done, a triage report is generated and sent to care providers. Many leading doctors feel that AI in image triage will see a boost in near future.

Remote Patient Monitoring

There are multiple benefits such as reduced post-op expenditure, time wastage, less exposure to other diseases, etc. The global remote patient monitoring devices market is expected to expand at a CAGR of 7.1% during the forecast period (2019–2027) according to Coherent Market Insights. Some of the top players in this space are Biotronik, Boston Scientific Corporation, CAS Medical Systems, CONTEC MEDICAL, Dragerwerk, GE Healthcare, Guangdong Biolight Meditech, Medtronic, Mindray Medical, Nihon Kohden, Philips Healthcare, Spacelabs Healthcare, Abbott. Companies such as GE Healthcare and Philips Healthcare have done a great job with building remote patient monitoring systems within the hospital premises as well as homecare for COVID patients. The main goal was to reduce the exposure of healthcare workers to at-risk patients.

Synchronous and Asynchronous Telehealth

Synchronous telehealth, in other words, Telemedicine is where there is a live conversation between the patient and the doctor. Asynchronous telehealth involves the exchange of recorded data e.g. images, video, medical reports, pathology reports between patients and doctors, at times between doctors as well. Similar to mHealth space, companies like Practo, 1mg, Lybrate, Medlife, and Portea Medical in India are some of the top players in telehealth and telemedicine. Lybrate’s USP lies in CMS (Clinical Management System) which helps doctors with tedious tasks of managing patients and providing better care. Meanwhile, Portea Medical’s home consults and pharma delivery have more relevance with the audience as it combines technology with a touch of personalization.

Digital Therapeutics

Digital Therapeutics delivers evidence-based therapies with the help of software which can be used both as a preventive measure as well as treatment application. The effectiveness of the medication and lifestyle changes on patients are monitored by leveraging technology. In India, major non-communicable diseases that account for 62% of the total mortality rate are CVD, diabetes, respiratory conditions, and cancer. Prominent global players in this space include Noom (US), Livongo Health (US), Omada Health (US), WellDoc (US), Pear Therapeutics (US), Proteus Digital Health (US), Propeller Health (US), Akili Interactive Labs (US), Better Therapeutics (US), etc. Omada Health is the pioneer in the DTx (Digital Therapeutics) that focused primarily on diabetes and pre-diabetes but now is branching out in the mental health space as well. In India, Altran (a part of Capgemini) is into building personalized DTx applications for clients. Whereas a start-up called Wellthy Therapeutics has ready solutions catering to multiple diseases.

Future of Virtual Health

Undoubtedly, there has been a massive increase in the adoption of Virtual Health technologies as people have gotten accustomed to the ease of certain services at home. In the coming future, mobile health apps, remote patient monitoring, and Digital therapeutics see a surge in demand from the customers. According to a study by Markets and Markets, “The global digital therapeutics market is projected to reach USD 6.9 billion by 2025 from USD 2.1 billion in 2020, at a CAGR of 26.7% during the forecast period (2020–2025).” A study by Fortune Business Insights, “The global mHealth market size is projected to reach USD 293.29 billion by 2026, exhibiting a CAGR of 29.1% during the forecast period.” A Research and Markets report says, “The remote patient monitoring market is expected to reach US$31.326 billion by the end of 2023.” Apart from the above, development in digital infrastructure such as virtual health stations where doctors can provide consultations globally, mobile ICUs, MRIs, X-rays, ultrasound equipment, the establishment of rural virtual care units reaching the remote areas of the country are some of the trends which will gain momentum. The focus would always lie upon the personalization of the virtual care experience for patients driven by data exchange and interoperability.

Indeed, there are certain challenges to the implementation of these technologies, lack of infrastructure, and digital literacy amongst elders and lower strata of society. Many healthcare institutions still have inhibitions while investing in digital technologies fearing rejection from the customers. It will be crucial for care providers to choose the right partner for implementing these technologies and create awareness amongst people to adopt them.

In a Nutshell

The success of virtual care relies on how well the digital experience is designed for the patient. “By 2025, as many as 95 percent of all customer interactions will be through channels supported by artificial intelligence (AI) technology” – Microsoft. The use of algorithms and AI for personalizing these experiences will be the key.

Find out more about unchartered territories in ‘Blue Ocean’ of Digital Health. Watch our webinar hosted by Parag Sharma (CEO, Mantra Labs) where he shares his insights on untapped opportunities using digital self-care tools within behavioral healthcare & emotional wellness.

Further Readings:

Why was Data Warehouse the Best Move on the Board?

Data warehouses act as the strategic command centers for enterprises. By employing a schema-on-write approach, they ensure data is cleaned, validated, and formatted before storage. This guarantees high accuracy and consistency, making them indispensable for industries like finance and healthcare. For instance, global banks rely on data warehouses to calculate real-time risk assessments or detect fraud—a necessity when billions of transactions are processed daily, tools like Amazon Redshift, Snowflake Data Warehouse, and Azure Data Warehouse are vital. Similarly, hospitals use them to streamline patient care by integrating records, billing, and treatment plans into unified dashboards.

The impact is evident: according to a report by Global Market Insights, the global data warehouse market is projected to reach $30.4 billion by 2025, driven by the growing demand for business intelligence and real-time analytics. Yet, much like Deep Blue’s limitations in analyzing Kasparov’s emotional state, data warehouses face challenges when encountering data that doesn’t fit neatly into predefined schemas.

The question remains—what happens when businesses need to explore data outside these structured confines? The next evolution takes us to the flexible and expansive realm of data lakes, designed to embrace unstructured chaos.

The True Depth of Data Lakes

While structured data lays the foundation for traditional analytics, the modern business environment is far more complex, organizations today recognize the untapped potential in unstructured and semi-structured data. Social media conversations, customer reviews, IoT sensor feeds, audio recordings, and video content—these are the modern equivalents of Kasparov’s instinctive reactions and emotional expressions. They hold valuable insights but exist in forms that defy the rigid schemas of data warehouses.

Data lake is the system designed to embrace this chaos. Unlike warehouses, which demand structure upfront, data lakes operate on a schema-on-read approach, storing raw data in its native format until it’s needed for analysis. This flexibility makes data lakes ideal for capturing unstructured and semi-structured information. For example, Netflix uses data lakes to ingest billions of daily streaming logs, combining semi-structured metadata with unstructured viewing behaviors to deliver hyper-personalized recommendations. Similarly, Tesla stores vast amounts of raw sensor data from its autonomous vehicles in data lakes to train machine learning models.

However, this openness comes with challenges. Without proper governance, data lakes risk devolving into “data swamps,” where valuable insights are buried under poorly cataloged, duplicated, or irrelevant information. Forrester analysts estimate that 60%-73% of enterprise data goes unused for analytics, highlighting the governance gap in traditional lake implementations.

Is the Data Lakehouse the Best of Both Worlds?

This gap gave rise to the data lakehouse, a hybrid approach that marries the flexibility of data lakes with the structure and governance of warehouses. The lakehouse supports both structured and unstructured data, enabling real-time querying for business intelligence (BI) while also accommodating AI/ML workloads. Tools like Databricks Lakehouse and Snowflake Lakehouse integrate features like ACID transactions and unified metadata layers, ensuring data remains clean, compliant, and accessible.

Retailers, for instance, use lakehouses to analyze customer behavior in real time while simultaneously training AI models for predictive recommendations. Streaming services like Disney+ integrate structured subscriber data with unstructured viewing habits, enhancing personalization and engagement. In manufacturing, lakehouses process vast IoT sensor data alongside operational records, predicting maintenance needs and reducing downtime. According to a report by Databricks, organizations implementing lakehouse architectures have achieved up to 40% cost reductions and accelerated insights, proving their value as a future-ready data solution.

As businesses navigate this evolving data ecosystem, the choice between these architectures depends on their unique needs. Below is a comparison table highlighting the key attributes of data warehouses, data lakes, and data lakehouses:

Feature	Data Warehouse	Data Lake	Data Lakehouse
Data Type	Structured	Structured, Semi-Structured, Unstructured	Both
Schema Approach	Schema-on-Write	Schema-on-Read	Both
Query Performance	Optimized for BI	Slower; requires specialized tools	High performance for both BI and AI
Accessibility	Easy for analysts with SQL tools	Requires technical expertise	Accessible to both analysts and data scientists
Cost Efficiency	High	Low	Moderate
Scalability	Limited	High	High
Governance	Strong	Weak	Strong
Use Cases	BI, Compliance	AI/ML, Data Exploration	Real-Time Analytics, Unified Workloads
Best Fit For	Finance, Healthcare	Media, IoT, Research	Retail, E-commerce, Multi-Industry

Conclusion

The interplay between data warehouses, data lakes, and data lakehouses is a tale of adaptation and convergence. Just as IBM’s Deep Blue showcased the power of structured data but left questions about unstructured insights, businesses today must decide how to harness the vast potential of their data. From tools like Azure Data Lake, Amazon Redshift, and Snowflake Data Warehouse to advanced platforms like Databricks Lakehouse, the possibilities are limitless.

Ultimately, the path forward depends on an organization’s specific goals—whether optimizing BI, exploring AI/ML, or achieving unified analytics. The synergy of data engineering, data analytics, and database activity monitoring ensures that insights are not just generated but are actionable. To accelerate AI transformation journeys for evolving organizations, leveraging cutting-edge platforms like Snowflake combined with deep expertise is crucial.

At Mantra Labs, we specialize in crafting tailored data science and engineering solutions that empower businesses to achieve their analytics goals. Our experience with platforms like Snowflake and our deep domain expertise makes us the ideal partner for driving data-driven innovation and unlocking the next wave of growth for your enterprise.

Virtual health: Delivering care through technology