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MantraTalks Podcast with Richard Roy Mendonce: Covid-19 & the Disruption in Healthcare

11 minutes, 21 seconds read

The outbreak of COVID-19 has put immense pressure on the healthcare sector. The supply chain of medical supplies was hit. The sudden surge of patients made it difficult to manage the hospital operations. Since priority had to be given to COVID patients, regular consults and elective surgeries were delayed. 

To go one step further and understand the disruption in healthcare amidst these adverse conditions, we interviewed Mr. Richard Roy Mendonce, Head Digital Strategy at Yashoda Hospitals to shed light on the role of technology in combating the current challenges faced by healthcare and possible mitigation strategies.

Mr. Richard Roy Mendonce has a strong domain expertise within the Healthcare Industry and has successfully infused digital transformations in various organizations like Columbia Asia Group of Hospitals, Sakra World Hospital, and Manipal Hospitals Group that ensured better customer experience and increased business. 

A Digital Strategist, he currently leads the digital efforts at Yashoda Hospitals, which is among the oldest and biggest healthcare groups in the region. He has nearly a decade of experience in digital marketing, digital strategy and digital transformation, with a distinctive ability to develop highly effective and measurable strategies that drive revenue growth, new customers, brand awareness and reputation. 

Constantly inspired & fascinated by the dynamics of the digital landscape, he has developed a skill set built on the art of leveraging digital technologies focused to deliver positive user experiences and achieve business objectives. In 2019, he was awarded as one of the 50 Most Influential Strategy Leaders by COM Global at World Marketing Congress.

Connect with Mr. Richard Roy Mendonce – LinkedIn

Watch the interview: 

The excerpt from the interview:

Covid-19 & the Disruption in Healthcare

Many hospitals are reassessing their digital marketing strategy and budgets in light of the uncertain economic situation. Most healthcare organizations can benefit from taking this time to strategize and plan for the future, rather than putting the brakes on. Please share some key insights into the changing patient behavior and the steps you are taking to reach them? Also, How will the healthcare marketing landscape change Beyond COVID-19?

Mr. Richard: In terms of healthcare, especially telemedicine, COVID-19 has completely cut down the channel of visiting doctors in-person for a consult. Lack of options has increased more acceptance towards Telemedicine. A couple of months back, we compared the benefits and comfort of direct consultation to an online one. We were reluctant to have those experiences but now acceptance has increased. 

Another thing I feel is —  we do not need high-end technology or equipment. When we hear of telemedicine, what comes first to our mind is jazzy computers, high-tech connections, software, etc.; but that is not the case. Even a simple SMS/call/WhatsApp call is enough to connect with a doctor. We don’t really need any high-end equipment to start a telemedicine service. 

Today, most of the spending is being diverted to digital channels rather than traditional offline ones and it will continue to happen. Digital channels are more trackable, more efficient, and more controllable. Even digital connect to engage with offline channels is gaining momentum. Healthcare set-ups will have offline referral networks, business partners. Traditionally, there would be a sales team who go meet and connect with them. Now with the social distancing and lockdowns, even that connection is replaced with digital connections such as webinars, video calls, etc. 

Communication in marketing has also changed. Before COVID-19, the communication was “Don’t ignore your health, come to us”. During the COVID-19 situation, the communication was “Come to us only if it is an emergency, it’s better to stay at home”. Post COVID-19, the communication might be- “Wherever you are, we are accessible, come to us or use our online services.” 

Telemedicine in a Post-Pandemic India

In the short time since the Pandemic began, the impact of social distancing norms has changed our daily lives & routines. Due to which, services like live remote consultations and telemedicine are getting more attention. Telemedicine is likely a permanent beneficiary of the pandemic. Do you think it will remain a key mode of healthcare delivery even after restrictions are lifted? Are there other digitally-enabled services that can potentially find greater adoption in a Post-Pandemic India?

Mr. Richard: Telemedicine will continue to be one of the modes of care delivery but that will not replace the existing care delivery system. Rather, it will be a mix of both. People will opt for telemedicine for the initial consultation (a non-serious one) and post-treatment follow-ups or review visits or to update on reports. People might get accustomed to telemedicine services but I think that will never replace serious conditions or surgical specialty where doctors need to examine personally to deliver proper care. 

In terms of acceptance level of technology, there has been wider acceptance for non-clinical support systems. For example, chatbots in place to address customer service and AI-driven platforms to check symptoms and guide the patient to respective specialists. This is not for prescriptions, but to enable patients to help themselves in availing services. 

Related: Healthcare Chatbots: Innovative, Efficient, and Low-cost Care

Medical supplies: Another area where digital platforms should have a wider scale of adoption is traveling for non-essential medical supplies. Pharma delivery is one sector that can go entirely digital. We can also have a format where physical stores are eliminated. Delivery can be from warehouse to customer. 

Diagnostics: Apart from radiology, diagnostics can go completely digital. Home care such as remote ICUs, remote monitoring could have potentially greater adoption in the current scenario. 

Disruption in healthcare will also include technologies to strengthen medical education and training.

Operational Challenges in Healthcare

From the operations point of view, digital transformation alone cannot help in preparing for an outbreak of this scale. The reality is we also have to be prepared for the possibility of a next Pandemic wave. The pandemic itself is testing the digital readiness and operational resilience of hospitals, in digitizing services and bringing innovation into healthcare. What are the operational challenges, as far as digital capabilities go, that hospitals are facing currently? And, what steps must they take to bridge these gaps?

Mr. Richard: We all know that the entire system was not geared up for a pandemic of this scale. Hospitals are facing both operational and clinical challenges. However, I’ll address this one particular issue from a digital angle. 

The biggest challenge for any hospital is the lack of a digital care platform and is still heavily dependent on paper-based systems. Now we know that anything can be sanitized but how do we sanitize paper documents. Patients have to carry these documents, touch them, and exchange multiple hands which can be potential carriers of the virus. Now it is more important to keep all the medical records digitized. 

Another aspect is the nature of this virus which is highly communicable and is leading to the community spread of this disease. Therefore, hospitals have a responsibility to maintain data at a patient-level so that contact tracing becomes much more easier and automated. So, maybe a symptom can be added as a trigger in the system and automatically do a contact tracing and give a list of people they can reach out to.

Yet another aspect in healthcare which is prone to change is remote working. Most of the industries such as IT have already geared up for remote working but healthcare has not. Many of the processes still need people coming to the office and working on a computer that is in the network. So, the disruption in healthcare relies on digital platforms to ensure that staff is efficiently deployed.

Changes in the Patient Experience

Both outpatient and in-patient treatment for all major non-communicable diseases including emergencies have declined. Going forward, as the country tries to resume life in the New Normal, industries like retail are experimenting with touchless interfaces to boost the customer’s confidence in shopping in-store. What changes, if any, do you foresee to the physical patient experience?

Mr. Richard: Wherever possible, currently hospitals are trying to minimize contact. Like airports, one can print their boarding pass, even hospitals can ask the patients not to wait in a line at the reception but rather book an appointment and make payments online. Once the appointment is booked, patients can just come and wait for the doctor’s call. We have seen multiple robotic-assisted surgeries where contact with the patient is avoided. Similarly, some technologies may come up taking vitals from the patient in a no-contact manner. There are hospitals in the country that have introduced innovative robots who screen patients coming to the hospitals. There are lots of innovations possible in this area. 

Role of AR, VR and AI in Digital Healthcare 

Huge volumes of data are flowing into the cloud, not just from doctors’ offices and imaging centers, but also from remote devices and sensors worn or operated by patients. By harnessing the vast amounts of data and putting it to work in applications, it helps care providers to improve effectiveness and efficiencies. Do you see technologies like AR/VR/AI playing a role in the future of digital healthcare in India? Can you share some examples of areas that Yashoda Hospitals has begun experimentation or implementation with these technologies?

Mr. Richard: Artificial intelligence, Machine Learning, Augmented Reality, Virtual Reality, Cloud systems, etc. are the buzzwords these days. I do believe that these technologies will pick pace in the healthcare industry as well. But I see a challenge there. Though all the data is on the cloud, the data is held by individual stakeholders and corporations. And standardization of data is the biggest challenge right now. 

So, any company which is working towards utilizing these technologies should first look at technologies that can bring data on one platform which is usable, accessible, and standardized without compromising confidential information of the patient. In terms of innovation at Yashoda hospitals, we are working on a couple of them such as AI-based radiology systems, optimizing customer journeys in hospitals, manpower planning, etc. 

Related: Medical Image Management: DICOM Images Sharing Process

Let’s take the patient discharge process for instance. Transitioning a customer from ‘in-patient’ to ‘out-patient’ is a significant challenge for any hospital, since it involves multiple departments. You’ve even stated before that it takes the integrated view of HIS (hospital information systems), EMR (electronic medical records), inventory, billing, and real-time updates of treatment progress to facilitate discharge at the click of a button. What is your experience in the transformation process and the ground realities of addressing this critical pain point? 

Mr. Richard: Theoretically speaking, the discharge process takes a lot of time but the reason it takes so much time is because it involves multiple stakeholders at a time- internal as well as external. It further gets complicated when the insurance is involved. I think all healthcare providers are looking to simplify the discharge process. The only way it is possible is having technology cut across stakeholders and in real-time. So wherever possible, we can avoid these internal communication delays. 

Return to Normal: The way forward

As hospitals plan for the complicated return stage (once restrictions are lifted), the volume of footfalls, testing, etc. will gradually increase. What advice can you share with other healthcare leaders to prepare their organization on the frontline to manage specific risks regarding employee safety, patient outcomes, etc? What investments (in remote patient monitoring, medical equipment, CRM systems, etc.) should healthcare organizations be making to respond to ‘the return to normal’?

Mr. Richard: I think that the precautionary steps taken by most of the healthcare providers are commendable. It is much better than in other countries across the world. We are in touch with a few of the major chains and the precautions that are being taken are phenomenal. Starting from thermal screens and fever clinics at the entrance, social distancing blogs; we have implemented Cluster Systems within our hospitals. It is a system where the employees are clustered in certain areas to minimize cross-contamination between employees. 

In terms of investment in technology, clinical data can be good to start working on. A good EMR system that seamlessly integrates and exchanges data between all relevant information systems is the need of the time. This investment will not just be in terms of technology but also behavioral change. 

So the system has to be friendly to seamlessly capture the data and make it available across systems. Using data efficiently is important to guide clinical decision support, developing user experience protocols and creating empowerment for the patient. 

Summing up

COVID-19 has changed a lot in us. The lockdown has unlocked a lot of things. It is a good time to innovate. Essential services would be a keyword used for a very long time now in every aspect. Be it shopping, be it food, be it health. And social distancing will be a new lifestyle. 

In this session, Mr. Richard shared insights on the disruption in healthcare and the importance of technological innovations in the new normal for hospitals.


AI is going to be essential for Insurers to gain that competitive edge in the post-pandemic world. Check out Hitee — an industry-pecific chatbot for driving customer engagement. For your specific requirements, please feel free to write to us at hello@mantralabsglobal.com.

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Lake, Lakehouse, or Warehouse? Picking the Perfect Data Playground

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In 1997, the world watched in awe as IBM’s Deep Blue, a machine designed to play chess, defeated world champion Garry Kasparov. This moment wasn’t just a milestone for technology; it was a profound demonstration of data’s potential. Deep Blue analyzed millions of structured moves to anticipate outcomes. But imagine if it had access to unstructured data—Kasparov’s interviews, emotions, and instinctive reactions. Would the game have unfolded differently?

This historic clash mirrors today’s challenge in data architectures: leveraging structured, unstructured, and hybrid data systems to stay ahead. Let’s explore the nuances between Data Warehouses, Data Lakes, and Data Lakehouses—and uncover how they empower organizations to make game-changing decisions.

Deep Blue’s triumph was rooted in its ability to process structured data—moves on the chessboard, sequences of play, and pre-defined rules. Similarly, in the business world, structured data forms the backbone of decision-making. Customer transaction histories, financial ledgers, and inventory records are the “chess moves” of enterprises, neatly organized into rows and columns, ready for analysis. But as businesses grew, so did their need for a system that could not only store this structured data but also transform it into actionable insights efficiently. This need birthed the data warehouse.

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:

FeatureData WarehouseData LakeData Lakehouse
Data TypeStructuredStructured, Semi-Structured, UnstructuredBoth
Schema ApproachSchema-on-WriteSchema-on-ReadBoth
Query PerformanceOptimized for BISlower; requires specialized toolsHigh performance for both BI and AI
AccessibilityEasy for analysts with SQL toolsRequires technical expertiseAccessible to both analysts and data scientists
Cost EfficiencyHighLowModerate
ScalabilityLimitedHighHigh
GovernanceStrongWeakStrong
Use CasesBI, ComplianceAI/ML, Data ExplorationReal-Time Analytics, Unified Workloads
Best Fit ForFinance, HealthcareMedia, IoT, ResearchRetail, 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.

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