3T model to address health inequity

Massive health inequity affecting the vast rural population, and lack of employability and sustainable job opportunities for rural youth are the two major obstacles preventing holistic rural development in India.

In India, almost 30% of the rural population live without adequate access to primary healthcare (physical and mental) including genuine medicines and diagnostic tests. This is happening, despite government’s best efforts to strengthen the rural health system, due to three (3) major confounding factors – shortage and maldistribution of doctors and other health personnel, implementation and infrastructure limitations in the last-mile and over-reliance on complex expensive imported diagnostic technologies.

This triad of problems results in accumulation of diseases among the vulnerable segment, delayed presentation and consequent need of specialty treatment at high cost, health-related poverty shocks and untold misery. Loss of social productivity due to a mass of ‘sick’ people at the bottom of the pyramid perpetuates poverty among the society and the nation.

80% of medical practitioners in rural areas are unqualified; 20% of country’s organised health infrastructure inadequately serves 70% rural population; there is widespread shortage of doctors and other health workers - all these combine to result in a situation where rural people lack access to even basic primary healthcare.

Telemedicine was developed as a solution for improving access to primary care for the rural population. But it has certain limitations such as unavailability of actionable and analysable health data, no decrease in the consultation time, requirement of high band-width and large infrastructure, language and communication barrier, physical examination is not possible, zero scalability and replicability. 

On the other hand, there is a massive shortfall (National Skill Development Corporation estimates put this number at about 6.0 million in the country) in availability of skilled Allied Health Professionals (AHP) that significantly affect the quality of healthcare in institutions and growth of the health sector. This shortage is distributed across both hospital-based health professionals and community health workers. India is one of the 82 countries world-wide facing acute shortage of health human resources.

A large number of rural youths, particularly women or from scheduled caste (SC) and scheduled tribe (ST) background, drop out of formal education at Class X and XII. SC and ST students constitute 14.7% and 5.6% of the total enrolment, respectively. Gross Enrolment Ratio (GER) in Higher education in India is 27.1 (18-23 years of age). GER for SC and ST population are 23.5% and 18% respectively. Unemployment rate in India is 8.30%. Representation of women in the workforce is very poor.

The demand for primary care is 60% of the total need. Lack of access to basic healthcare for the rural underserved results in increasing societal disease burden. The same population report to city-based hospitals in an advanced stage of illness requiring complex and expensive treatment, thus risking health poverty and poor outcomes.

In a nutshell, India is facing dual burden in the health sector in terms of inadequate trained and certified health workers and lack of access to affordable healthcare for the rural communities. 

Through stakeholder engagement and experiential learning, we developed an innovative 3T model (Training, Task-shifting and Technology) to address the above-mentioned problem basket. On our own and with support from Central and State governments, Science & Technology Institutions we have implemented this model across multiple states in India. Early results may be summarized as - 16 schools – past and ongoing, >4500 rural youth trained, 65% female, 60% SCST; 8 clusters of digital clinics and a motor-boat based clinic at The Sunderbans; 174 health workers, 24,000 patients/year; access for 500,000 population; at revenue generating stage through fee-for-service).

We now intend to scale up the current initiative by establishing eight (8) more clusters of digital clinics in more fragile geographies. Each cluster will consist of one (1) fixed clinic and two (2) equipped cycle-borne mobile clinics. These RDHCs will be operated by 48 certified health workers (at the clinics) and doctors (at the back-end), supported by technologies (clinical decision support software - CDSS, frugal diagnostics and long-range wireless area network).

Advantages of digital health compared to Telemedicine

• Complete clinical information
• Less time; improved quality
• Comprehensive (tests, medicines, physical, dental and mental care, physiotherapy, health products)
• More scalable (low band-width, language/location-agnostic, less doctors)
• Versatile – eco-system approach for public health programs

 Implementation of 3T model

Train 48 rural SCST youth in our own affiliated centre (School for Skills: Allied Health Sciences) as “General Duty Assistant” who will be certified by National Skill Development Corporation, Government of India in this National Skills Qualifications Framework. They will be additionally trained in digital literacy, software operation and conduct of diagnostic tests using innovative devices.

Task-shifting – Through our unique Decision-support software, the trained health workers will consult patients in rural areas and transfer clinical information to the ‘remote’ doctors. Thus, the time taken by doctor to examine a patient will come down and so will the need to travel.

Technology – Guided by doctors’ advice the health workers will provide medicines and conduct diagnostic tests at these digital clinics. Reports will be provided to the patients instantly avoiding further travel. These devices are developed by various IITs in India, are our technology partners.

Our 3T model of digital primary care and public health sustains at about 20 patients/day through user-fee. Total cost, direct and indirect combined, to patient (Rs. 158/episode) in our model (consultation, medicines and tests) is less than available alternatives – ‘free’ public system (multiple visits, more time, non-availability), informal rural doctor (over-medication, over-investigation, lack of medical knowledge) and private medical care. 

With vast swathes of people living without access to primary care in the South-South geographies, and the health sector remaining a major driver of formal sector employment for skilled technicians, this integrated 3T model proposed by us offers a compelling opportunity at scale for significant expansion in a language and location-agnostic manner with a sustainable model. It creates long-lasting transformational impact across the entire value-chain – employment, women empowerment, frugal technology innovation, access to primary care for the underserved and reduction of cost of healthcare.

The solution serves multiple different stakeholders, most important being the underserved population living in remote or fragile geographies without access to primary care and public health solutions.

This target segment will have access to data-driven evidence-based primary physical and mental healthcare in an integrated platform; close to their homes, without the distance barrier. This particularly addresses the problems of women, children, elderly and persons with disabilities. There is simultaneous access to genuine medicines and basic diagnostic tests, along with a host of health products (Sanitary napkins, ORS etc.) and services (Wound dressings, physiotherapy, dietary advice etc.). This will lead to earlier detection, better management, close supervision and monitoring, prevention of complications and, therefore, both an overall reduction of out-of-pocket healthcare expense (both short and long-terms) and improve gradually societal health indices by reducing Disability-adjusted life-years – DALYs. Access to mental health services will reduce substance abuse, decrease in self-harm, intimate partner violence and overall incidence of depression.

The second and almost equally important group of beneficiaries include vast numbers of rural youth (mainly women and from disenfranchised backgrounds) with low formal education (middle school) and therefore unemployable. Through formal structured training as ‘Frontline Health Worker’ in a nationally approved qualification framework they are certified at a national level. Our enhanced curriculum ensures they become digitally literate and are able to handle various simple point-of-care diagnostic technologies. This group now has access to livelihood both in hospitals (which are desperately short of skilled health human resources) and in communities (which allows a larger number of women to join workforce due to avoiding migration from families).

The other beneficiaries include –

Technology research group – correct need identifications, translational environment, design ethnographic understanding, field validation opportunities and iterative development; all these combines to reduce the possibilities of failure to transfer technology from the lab to the community. The group of health workers being early adopters of technology eases community acceptance.

Public health professionals – various public health programs can be seamlessly implemented through the group of trained health workers. Data-driven measurement of effectiveness in a dynamic and longitudinal manner identifies early successes and failures and allows policy modifications in an agile manner.

Doctors – through task-shifting to health workers by the software system the doctors now have access to patients from wider geographies; they can also see a larger number of patients without the need to travel to difficult geographies with limited resources. The data-driven software, through its ML modelling, generates valuable information on disease biology and behaviour.

Social scientists – valuable insights on human development can be generated through this bottom-up, designed with user model of digital health delivery leveraging high-end but simple technologies, by groups of middle-school rural youth with six months of training as health workers.

Health economists – studying financial sustainability of this model that relies on multiple small revenue streams, each within the paying capacity of the rural population; and highly efficient cost model derived through streamlined processes could reveal a large mount of knowledge in health economics modelling.

Multi-speciality team – our team draws from a wide cross-section of specialists. They include doctors with - vast clinical experience, working at the interface between medical science and health technologies and public health expertise. It has engineers and scientists working on innovating deep-science but frugal health technologies, software engineers and data scientists, experts on statistics and mathematics, biologists, intercultural program managers, social entrepreneurs and program managers. The team has worked together, in individual capacities for far longer than the age of our organisation. Some of the individual members of the team have received the highest scientific awards in India due to their contribution to innovation of frugal health technologies.

Participation of globally renowned institutions – the team is drawn from some of the ‘Institutes of National Importance’ and ‘Higher Educational Institutions’ in India such as IIT Kharagpur and IIT Guwahati. University of Edinburgh and Nesten Inc, Irvine are other participants. The mentor group of this project has Prof. Marc Madou of University of California at Irvine, and Prof. Amitabha Ghosh, Former Director IIT Kharagpur.

Training model – our training model for rural youth as Frontline Health Workers is scalable, sustainable and received substantial support from the government and corporate bodies (through funds from CSR – Corporate Social Responsibility). Over 4500 rural youth, predominantly women have been trained through our 14 training schools in different parts of India.  

Technology preparedness – the software is operational across multiple locations with the set of functionalities that meet current project needs. The team is well-placed to undertake the next phase of development involving data analytics, machine learning algorithms and public health analytics. Omics integration is a future task. The LoRaWAN technology has undergone trial across multiple locations and is implemented. Multiple frugal diagnostic devices have been implemented; a pipeline of new innovations is set to roll out as soon as they receive national certification.

Business process – the lead member of the team, Prof. (Dr) Satadal Saha MS, FRCS (Eng.), apart from being a doctor, has been a professor at IIT Kharagpur & Guwahati; worked with International Finance Corporation (World Bank Group) on modelling of rural healthcare; performed in fragile geographies of Nigeria and similar places building sustainable business models with social impact in healthcare. He is supported by an appropriate leadership team that is highly process-oriented, expert in training health workers in adopting the processes and achieve functional efficiency.

Government support – the project has received support from various government agencies in India for its alignment with the government vision of digital technologies, frugal technology-driven self-reliant India and its commitment to reaching healthcare to every citizen however difficult the geography may be. We are also supported by widespread availability of internet in India at very low cost and easy access to English.

Thousands of health workers – finally, and probably the key issue, we have access to thousands of trained and certified health workers across multiple states in India for us to be able to mount a rapid scale in a short time.

Through the eight (8) existing clusters of digital clinics, we are covering a population size of about 300,000. The single motor-boat at The Sunderbans cover six (6) islands at this time. Each cluster provides health coverage to about 25,000 rural residents.

In out second year of full-fledged operation, we are providing treatment to about 7 patients per day per cluster who approach us for treatment and pays for the services. As was our original assumption, women and children constitute the majority of our patients. This is a direct result of breaking down the distance barrier to access by the cycle-borne mobile health workers delivering door-to-door healthcare services. The accompanying pictures show average cost to patient per episode (in INR – INR 82 to $1). It also shows the disease category break-up (not as per ICD-10 coding, which has not yet been introduced). 

We have already addressed the key project risks –

• Can rural youth with low formal education be trained as health workers with the competence to use a decision-support software for history-taking and basic examination of a patient, including dispensing medicines and undertaking basic diagnostic tests?
• Can a software be developed that is triggered by the patient’s chief complaint and opens up specific clinical algorithms covering common primary physical and mental health care requirements?
• Will a doctor be able to make sense out of the dataset transferred this way and agree to provide a safe clinical management plan to the health workers on a ‘remote’ basis?

In the current stage of functioning, we have also established that –

• Health workers acquire sufficient motivation, self-esteem and confidence in delivering digital health services, and particularly for the women, their respect in the community increases manyfold, making them stable in the system.
• Given overall adoption of digital technology in most social and government services (such as banking, social security etc.) community members faith and acceptance in ‘digital health’ services is gradually increasing. Clearly, the COVID pandemic and its consequent disruption facilitated this. In fact, the rural communities are now expecting more and more services from this platform.
• Doctors see clear benefit in the model, while recognising the limitations (such as certain forms of patient examination is not possible). The consensus is that about 70% of the illnesses can be safely managed this way.
• ‘Informal’ rural medical practitioners (Quacks), rather than viewing this as an existential threat, are more open to availing this for consulting with real doctors for some of their more difficult patients.

Our upcoming tasks are –

• Creating a somewhat larger footprint, through establishment of more such clinics covering a wider pool of ethnically diverse population for a definitive stage of stable functioning.
• Achieve financial sustainability over next 2-2.5 years. Our current pattern of revenue growth indicates this to be clearly possible as we have been able to manage the costs very effectively.
• Software upgradation, by incorporation of mental health algorithms, epidemiological data and building the data analytic model (AI-ML) that will enable us to expand into the public health domain – heat maps of various diseases of public health importance, disease risk-scoring for evidence-based practice, predictive tools for diagnosis and management (as suggestions to the real doctor).
• Add more diagnostic services in the pipeline.
• Alignment with government efforts and converging the last mile health centres into the digital model.
• Creating awareness about the model among a larger global audience.
• Improving flexibility of technology platform so that it is location and language agnostic, the clinical algorithms are easily customisable to be able to address the disease profiles of many different fragile geographies and make it a truly global solution.

It is for support to these upcoming tasks, we approach MIT Solve for a financial grant & other support.

Our proposal addresses the problem of lack of access to primary healthcare (physical and mental) for the underserved population. The proposed solution, part of which is already at work, leverages frugal innovative health technologies and aims to establish a data-driven approach to an integrated primary care/public health system. We identified three major challenges that need mitigation – doctors (absolute shortage and maldistribution with an urban bias, lack of diagnostic technologies that operate in the resource-poor geographies at the right price, data-thin nature of primary care system making evidence-based practice and measurement impossible. The devastating impact of these lead to increase in disease burden, specific hardships to women and children, near-total absence of mental health services and rising out-of-pocket expenses. Our solution is a 3T approach – i) Train large number of rural youth as certified & digitally literate Frontline Health Workers ii) Technology - introduce certified, easy-to-use, affordable and innovative diagnostic devices for primary care problems iii) Task-shifting – build a software (Phase I completed in collaboration with Johns Hopkins University USA) triggered by clinical algorithms that can be easily used by health workers even in low band-width conditions to record and transmit structured, meaningful clinical data to the ‘remote’ but real doctor, for the doctor to define a clinical management plan. The health workers also provide medicines and other services such as physiotherapy, access to oral rehydration solutions, sanitary napkins etc.; they undertake multiple health education and awareness programs at schools and focus groups (such as adolescent women, on reproductive health etc.). This system leads to i) increase in rural household earning through employment/self-employment ii) women’s empowerment as the health workers are predominantly women iii) prevents urban migration and maintains family and social eco-system iv) introduces modern deep-science technologies into the community in a culturally congruent manner v) provides multiple essential services, including mental health, under the same platform vi) enhances access, particularly to women and children, by reducing the distance to government health facilities through our cycle-borne mobile health workers and finally, vii) reduces out of pocket expenses significantly. All the technologies are location and language agnostic; through use of LoRaWAN technology (blockchain-based) the software can work in extremely low band-width conditions. The health data is secure, data analytic model (under development) allows multiple decision supports such as heat map of various diseases, risk scoring of NCDs such as Diabetes, understanding of environment and behaviour impact on disease prevalence and behaviour etc. We have already established 30 Digital Clinics (fixed centres and mobile units) in remote rural areas in India including a motor-boat based service at Sunderbans, world’s largest delta inhabited by marooned islanders. IIT Kharagpur & IIT Guwahati, two premier globally renowned science and technology institutions are innovating and providing technologies to power the system. Over 100 rural women, trained formally as frontline health workers are earning their livelihoods through the model that is delivering primary healthcare (physical and mental), along with medicines and diagnostic tests to over 20000 patients living in fragile geographies, every year.

Improved access to primary healthcare (physical and mental), genuine medicines and diagnostic tests for primary care:

Our model integrates rural youth, a band-width agnostic customisable decision-support software and frugal diagnostic devices, and synthesises an efficient and cost-effective service delivery model that is location and language-agnostic. This marks a paradigm shift in creating access to healthcare for the billions of people around fragile geographies. It is sustainable, as can be seen from the experience of our existing 30 digital clinics operated by over 100 community-based digitally literate health workers, mainly women. The model drastically reduces barriers to access, including cost and distance.

Reduction of substance abuse and mental health disorders:

The community health workers, upskilled through National Institute of Mental Health & Neurosciences (NIMHANS, Bangalore, India) in delivering mental health services have now integrated physical health services with mental health. Trust and confidence in a system that is designed and delivered by their own community members have created the potential for a paradigm shift in taboo reduction and access to mental health support.

Reduction of out-of-pocket expenses for accessing healthcare:

We have demonstrated that the average cost (including doctors consultation, medicines and battery of diagnostic tests) per patient per episode can be brought down to less than $2, thus marking a measurable reduction compared with existing alternatives – ‘free’ government system (direct and indirect costs taken together) and ‘informal practitioners (quacks)’ with indiscriminate medicine and test prescriptions. 

Data-driven evidence-based healthcare:

The clinical algorithm-based decision-support system operated by the health workers generates data that enables standardisation and uniformity of medical practice, thus improving overall quality of treatment outcome by the doctor. It also serves as a source of longitudinal and dynamic data that can be used for R&D purposes, public health policy & program formulation and measurement of effectiveness.

Reduction of prevalence diseases of public health importance:

Local health workers participate in program design and helps diffusing health education, awareness, school health programs and focused group discussions (women, adolescents) deep into the community members through village elders and opinion leaders, thus improving adoption and ushering in change in health-seeking behaviour among community members.

Reduction of Disability-adjusted Life-years (DALY) lost:

Effective processes, methods and technologies for earlier detection, regular digital management and better follow-up of NCDs (eg. Diabetes, Hypertension) and Communicable diseases (eg. TB) by community health workers in a data-driven environment reduces incidence of complications (earlier detection and institution of clinical intervention) and reduces loss of DALYs.

Women’s empowerment:

We preferentially focus on training local women as health workers that enable them to remain in their social and family ecosystem preventing disruptive migration while, at the same time, earning a livelihood through professional services.

Continuous measurement of outcome and policy adjustments:

One size does not fit all among racially and genetically diverse population groups. The data-driven software, with its integrated data analytics and forecasting ability measures outcomes, allows policy adjustments based on measured outcome and lends to further research into health sciences and technology development.

Bring an ever-increasing number of beneficiaries living in fragile geographies under the safety net of data-driven evidence-based primary care and public health programs, including safe medicines and basic diagnostics – through our current eight (8) clusters of digital clinics, we are reaching out to a population of about 300,000. By leveraging some of the existing trained health workers we already have in different geographies, we would like to more than double population coverage to 750,000 in next 2 years. By then, through adoption by others and governments, this can dramatically increase to a few millions in short time, as the technologies and processes are location and language agnostic. (SDG Goal 3.8.1)

Reduction of out-of-pocket expenses for accessing healthcare – in our model, current out-of-pocket expense per patient per episode is just less than $2 (including doctors’ consultation, medicines and basic diagnostic tests). Even with addition of more diagnostic tests as more devices are innovated and rolled out, over next six (6) years, our target is to peg the total cost to <$3 per patient per episode and the common diagnostic tests to below $1. This will reduce the number of households with high health expenditure as a percent of total household expenditure. (SDG Goal 3.8.2)

Reduction of substance abuse and mental health disorders – having upskilled a subset of the health workers to community mental health workers, we plan to integrate physical primary care services with mental health services for the vulnerable groups focusing on adolescents, substance abuse, intimate partner violence and depression. We expect 20% of our total patients to present with mental health disorders, and achieve substantial reduction in the above parameters among our beneficiary population. (SDG Goal 3.5.1; SDG Goal 3.4.2)

Data-driven evidence-based healthcare, with measurement of performance - the clinical algorithm-based decision-support system being used by the health workers on the field to deliver healthcare supported by the doctors, frugal diagnostics and medicines, monitoring and evaluation – all will facilitate earlier detection, better management, prevention of complications, lower cost, slow down clinical progression of multiple diseases of public health importance including NCDs and Infectious diseases such as TB. (SDG Goal 3.4.1)

Continuous measurement of outcome and policy adjustments – this is made easy as the health workers are in charge of data collection. Policy makers can now better measure the effectiveness of the programs more frequently and either make policy adjustments or develop newer policies.

Health workers density and Women’s empowerment – the sustainable and highly scalable model of training of health workers perfected over last 5-6 years has resulted in over 4500 trained and certified health human resources in multiple states. Our aim is to train, along with similar partner organisations, another 5000 in next 3 years. We preferentially focus on training local women as health workers that enable them to remain in their social and family ecosystem preventing disruptive migration while, at the same time, earning a livelihood through professional services. (SDG Goal 3.c.1, 4.3.1, 4.4.1)

The proposed model will catalyse a systemic change in healthcare delivery for people living in fragile geographies across the world. This marks a shift from a top-down approach to a “Design with user” system which is community-facing, community-owned, culturally congruent and diffuses into the population easily.

Our initiative is focused on leveraging various advanced technological components to revolutionize healthcare delivery, enhance data-driven medical practices, improve access to point-of-care diagnostics, and facilitate seamless communication between doctors and patients, particularly in remote areas.

We have developed a comprehensive software for operating eHealth clinics, especially in rural areas. This thinks like a doctor with its clinical algorithm to get a structured medical history and examination findings from the patient and send it to a backend doctor with minimum internet for further evaluation for 42 commonly reported symptoms. By further harnessing the power of ML algorithms and advanced data analytics, it will provide healthcare professionals with evidence-based recommendations for diagnosis, treatment, and management of various medical conditions, with a specific focus on primary care and public health. By integrating the latest medical knowledge and patient data, our software will significantly enhance the accuracy and efficiency of clinical decision-making, empowering doctors to provide evidence-based care.

A bouquet of microfluidics, imaging, and ML-based point-of-care diagnostics devices that can be implemented with minimally trained health workers at the extreme point of care are being developed by our collaborating institutes. Some have already been rolled out – Haemoglobin, Plasma Glucose, Albumin, ECG etc. A range of portable devices capable of conducting rapid and reliable tests for Creatinine, Calcium, Lipid profile, Kidney Function, etc, are in advanced stage of development. These user-friendly, cost-effective, multi-level diagnostic and screening devices are designed to operate in resource-limited settings. These frugal devices and IoT solutions will help doctors to make informed decisions quickly, leading to improved patient outcomes.

We are working on blockchain technology to revolutionize medical treatment documentation. By leveraging the immutability, encryption, and security features of blockchain, we aim to ensure the integrity and privacy of patient records. Authorized healthcare providers and public health researchers will have transparent access to these records, facilitating seamless continuity of care and enhancing patient safety.

To address the challenges of data connectivity, especially in rural areas, we plan to establish long-range wireless connectivity using LoRa technology. This infrastructure will enable real-time communication between healthcare professionals and patients, regardless of geographical barriers. Remote consultations, monitoring, and immediate medical assistance will become feasible, improving healthcare access for underserved communities. With this connected healthcare approach, we aim to bridge the gap between doctors and patients, particularly in remote areas.

We are developing a comprehensive infrastructure for a Health Data Lake to unlock the full potential of data analysis in public health. By integrating various types of health data from multiple sources into a centralized repository, the “Lake” will enable advanced data analysis and prediction for focused disease. With AI-ML integration, these data can be valuable for a better understanding of the disease. Many valuable insights can be provided by identifying patterns, trends, and correlations within the data. Data from diverse sources will not only help manage any public health issue but also enable monitoring of disease outbreaks, tracking the spread of infectious diseases, and detecting health emergencies.

Our Solution team is drawn from seven (7) countries, representing all major religions, ranging in age between 26 and 62 yrs. Seven (7) of its 22 members are women, five (5) in senior decision-making position. In a flat and open environment, with its diverging experiences and realities, the team is bound by optimism, shared faith and common hope that the solution will deliver long-lasting transformational impact. Openness to ideas, human-centred innovation, keen awareness of what will work for the beneficiaries and do all that, no more and no less, define who we are. Given the magnitude of the problem of lack of access to primary care our team knows they have the flexibility of either moving up the chain in the organisation or moving out to build their own solutions in their own geographies.

The field team has an even more expansive array of diversity, equity and inclusiveness. The health workers are trained from six (6) different states each with its own language, culture, custom, ethnicity, social adversities etc. Their esteem, understanding of their role and contribution to the society have uplifted their souls. That is the reason they played key role in designing the 3T model – a human-centred, bottom-up design developed with the user, culturally congruent, linguistically familiar, under their control and converging with their lives.

For software development, the health workers ability to navigate through the UI, their familiarity with the local language, people’s health-seeking behaviour, the common symptoms and how people express them all played a key role.

For diagnostic technologies, first few months were utilised in identifying the major problem that need solution, the constraints within which the solution has to perform, its design & environment considerations and cost. This design ethnographic understanding triggered various innovations. The initial prototypes were taken through field validation studies by the same health workers, their skill sets were matched to the usability of the technology and final designs were iteratively developed. Over 60% of our health workers are women, over 60% of them are from disenfranchised social backgrounds. They function as independent health entrepreneurs and see a clear path to impact, higher social acceptance and rising income. That keeps them engaged, without attrition.

The health workers being from the same communities that they will serve, engaging with the larger community members have been easy. Some of the opinion leaders, village elders, gate-keepers were probably their own and it led to a heightened level of trust at first approach. Subsequently as they began to experience treatment and financial benefits from the system, the engagement grew to a near-partnership.  

To summarise, a multi-country, multi-religious, gender-balanced solution team with diversity in age; a flat organisation with independent flow of ideas, an environment where growth paths are open intercalates with hundreds of rural community-based health workers in the field participating in human-centred design of process, technologies and business model as entrepreneurs who are culturally, linguistically and ethnographically identified with the beneficiary communities represent the diversity, equity and inclusiveness of our proposed solution.

Key resources

i) ‘Frontline Health Worker’s, trained from among local communities ii) Real, remote doctors (General Practitioners and Specialists) iii) Easy to use relevant frugal innovative diagnostic devices iv) Clinical algorithm-based decision-support software.

Partners & Key stakeholders

i) Government – guidelines for clinical establishments ii) Local government & administration – alignment for buy-in iii) Local opinion leaders – early engagement for program design, cultural adoption and community acceptance iv) Community members – creating awareness about safety and authenticity of digital health services to break down barriers and build trust v) Doctors – willing to rely on clinical data collected through health workers in an algorithm-based software vi) Supervision team – regular technical support, on-job upskilling, community engagement planning vii) Health workers – it is important to motivate them and gain their trust and confidence in this model of healthcare delivery.

Key activities

Each cluster of Digital clinic has one (1) fixed unit (rented 250 sft room) and two (2) bicycle-borne mobile teams equipped with IT, medicines and diagnostic devices. Services are provided six (6) days every week, 8 am to 5 pm. Health workers, on examination of patient, shares the data real-time with the remote doctors who, on data review and video consultation with the patient, provides clinical management advice in the same web-based software. The health worker follows doctor’s advice to dispense medicines, conduct tests (and inform the results to the doctor instantly). The services provided include – i) Doctors consultation (GP/Specialist) ii) Medicines iii) Diagnostic tests (Hb, Glucose, ECG, Albumin, ECG) iv) Vitals monitoring – Pulse, BP, BMI, Oxygen saturation v) Physiotherapy vi) Dietician vii) IM injection, Dressing viii) Oral Rehydration Salt, Sanitary Napkin etc.

Channels

i) Word-of-mouth from patients already treated ii) Engaging with influencers such as school teachers, village elders iii) Campaign activities - leaflet, flyers distribution iv) Community-facing activities - health check-up camps, participation in village fairs v) Involvement of ‘informal practitioners’ by offering them a formal platform for seeking advice on their patients from qualified doctors.

Beneficiaries:

i) the local rural population residing within a radius of 10 kms (distance served by the cycle routes and ii) the health workers, deriving their livelihood through this service model. Indirect beneficiaries include – i) Doctors, access to patients from a wider geography without requiring physical movement ii) Science & Technology researchers for technology innovation and iii) Public health professionals, for policy and implementation.

Cost structure:

Capital cost (One-time) for establishing each cluster of digital clinics is $10000. Expenses include salaries of health workers (largest), purchase of medicines and consumables, Internet, Power and Telephone expenses etc.. Back-end costs include doctors honorarium, IT maintenance and management-supervision costs. As the model scales, unit cost of management-supervision and IT maintenance reduces.

Revenues:

All services rendered through the clinics carry a user-fee. All tariff is less than $1 except consultation by specialist doctors ($1.25). At 20 patients/day, the cluster achieves financial break-even.

Surplus:

From year 4 onwards, as number of patients ramp up from 28 to 34/day, the clusters achieve surplus to the extent of About $5000 per year.

The ‘lived experience’ in the rural heartlands of India about the deprivation in access to primary healthcare and its devastating impact on disease burden and episodes of health-shock induced poverty led to a model hypothesis in a ‘Bottom-up’ manner through stakeholder engagement, mind-mapping and adopting a lean start-up approach.

First, we established training facilities for rural youth as ‘Frontline Health Worker’. Using own funds, government mandates and CSR (Corporate Social Responsibility) funds from companies we trained over 4500 rural youth across six(6) states in India (60% women, 60% from disadvantaged backgrounds) who received government certification.

Software technology development was undertaken through a collaboration with Johns Hopkins University; it was also partially funded by two more institutions in India – Jadavpur University and University of Calcutta.

R&D of frugal diagnostic devices, including field validation studies and upskilling of health workers, were undertaken through IIT Kharagpur at its ‘Common Research and Technology Development Hub for Affordable Healthcare’ led by Prof. Suman Chakraborty.

Data management and long-range wireless connectivity technology is being developed through Nesten Inc, Irvine, USA, led by Andrew Baek. The technology enables real-time communication between doctors and patients in remote areas, utilizing Long-Range (LoRa) wireless connectivity, and ensures highly secure data privacy through the incorporation of cryptographic encryption and blockchain.

First two (2) Digital Health Clinics were established through a grant from Department of Science & Technology, Government of India as a pilot to test the hypothesis and mitigate major project risks. Upon successful project implementation and validating its social value, a mandate was received from the Government of West Bengal for establishing eight (8) more clusters which has now been completed and they have been operational for 1.5 yrs. This grant period came to an end in March 2023.

Under a grant from ‘Indian Council of Medical Research’ (ICMR, Government of India) further software development work including Data analytic model development is ongoing at IIT Guwahati led by Prof. Palash Ghosh.

Now, all clusters are at a revenue-generating stage. The health workers have been organised into multiple ‘partnership firms’ of their own where they function as entrepreneurs, with an assured monthly basic income support along with an incentive model. The revenue is generated from sale of services and products.

We support them through technology (software and devices) maintenance, upskilling (technical, administrative, clinical), access to ‘remote’ doctors, business functions (stock, inventory, central purchase), public health program development and community engagement strategies. MIS is collected online in the software and reviewed on a daily basis. The health workers are trained through a documented ‘Process Manual’ ensuring efficient, on-time, effective and clinically safe operation.

The ramp-up in number of patients seeking healthcare by paying a user-fee, patient feedback (collected on a daily basis through direct questionnaire), local opinion, doctors’ response; all demonstrate clear sign of achieving financial sustainability in the next 2-2.5 years.

We also see clear possibility of substantial scale-up – organic, adoption by non-government organisations (Dechi Health Trust Fund, Nigeria), governments in their effort to manage the last-mile Subsidiary Health centres etc.

This section is a follow-up from the earlier one where we described the genesis of this project, current status and the path to sustainability.

The first stage, training of rural youth as health workers, started with own funding in FY2015. Based on the impact of the first few batches of students (percent of women and youth from disadvantaged backgrounds and successful employment), we received a mandate from ‘West Bengal Scheduled Caste Scheduled Tribe Other Backward Castes Development & Finance Corporation’, Government of West Bengal for training of 1750 SCST youth from 6 districts from West Bengal. Two more follow-up mandates were received from the same ‘Corporation’ as each mandate was completed to the government’s satisfaction.

Towards software development, financial support was received from Jadavpur University and University of Calcutta, with Johns Hopkins University providing technical support (through an agreement with us as its Global Healthcare Research Partner). Further support towards software upgradation has been received from ‘Indian Council of Medical Research’ (ICMR, Government of India) during 2021-22.

A competitive grant was received from Department of Science & Technology, Government of India to develop a pilot of the digital clinic program in 2018-19.

Based on successful execution of the pilot, we received a mandate from ‘West Bengal Scheduled Caste Scheduled Tribe Other Backward Castes Development & Finance Corporation’, Government of West Bengal to establish eight (8) more such clusters during 2019-20 and 2020-21. Two further competitive grants were received from “Federation of Indian Chambers of Commerce & Industries’ (Millennium Alliance Round 6 – 2020-21) and ‘Indian Council of Medical Research’ (ICMR, Government of India) (2021-22) for similar purpose.

Government of Assam mandated us to convert one existing government Subsidiary Health Centre into digital model as a test case. This was non-funded.

Multiple private organisations sought our support in areas of training, process, software and remote doctors where the projects were funded by these partner organisations. Examples include Dechi Health Trust Fund (Nigeria), Turiyo Foundation (West Bengal, India), Fluentic Ventures Pvt. Ltd. (Bihar, India). We received management fee for services provided.

IIT Kharagpur supported us through establishing a Diagnostic Centre where higher diagnostic tests that cannot be conducted at the digital clinics using point-of-care technologies, are conducted (2022-23).

We have also raised Venture Capital funding for software development and upgradation during 2022-23, as a pre-series funding. The table below shows the amount of funding received. 

Organisation

Amount (USD - $)

Jadavpur University and University of Calcutta

7500

West Bengal Scheduled Caste Scheduled Tribe Other Backward Castes Development & Finance Corporation (for training)

920,000

West Bengal Scheduled Caste Scheduled Tribe Other Backward Castes Development & Finance Corporation (for digital clinic)

205625

Department of Science & Technology, Government of India

37,500

Federation of Indian Chambers of Commerce & Industries

62,500

Indian Council of Medical Research

187,500

IIT Kharagpur (in the form of equipment)

37,500

Aditya Birla Group (CSR)

37,500

Dechi Health Trust Fund

9,756

Pontaq (VC)

31,250

Turiyo Foundation

Management fee basis

Fluentic Ventures Pvt. Ltd.

Management fee basis

Government of Assam

Non-funded