SMS-based citizen health tracking & response building system

The proposed solution solves the following issues:

• Lack of regular monitoring of citizen health in Least Developed Countries due to dearth of technical resources.
• Challenges in data collection, cleaning, storage and analysis in the local communities.
• Unpreparedness of state government of Least Developed Countries to respond to any disease outbreak. 

The solution is based on Short Messaging Service (SMS) services and offline reporting of ailments by doctors without dependency on internet facilities or day-long telecom network. It requires the doctors to take up the responsibility of anonymously recording the number of patients received on each day for every ailment and then reporting to the centralized datacenter at the end of day using SMS. This will help government and public healthcare institutions to track the frequency, volume and severity of a disease and to predict a potential outbreak/ epidemic, which can further spur capacity development for responding to such outbreaks. 

The solution is customized as follows, for under-connected villages, small towns with moderate connectivity, and remote marginalized regions. 

Reporting template - 

Doctors in remote areas, villages and small towns will be equipped with Reporting Templates - which is a sheet of paper for recording the ailment of each patient anonymously. The doctor needs to use strikes for maintaining a count under each category of disease-age-severity-gender. 

Villages with low connectivity and low digital literacy of doctors –

• Each public healthcare center (clinic/ nursing home/ small hospital/ checkup centers) will be assigned a unique Public Health Care ID (PHC-ID) to distinctly identify in the ecosystem of healthcare centers of the country.
• Each doctor in every public & private healthcare center in the town is provided with adequate number of Reporting Template – 1 sheet of paper for ailment reporting.
• Doctor receives a patient, checks for the ailment and based on diagnosis he/she records the ailment details in the Template.
• Details regarding severity of a disease, gender of patient and age of patients will be recorded using strike marks. This will also ensure that the patients’ data stays anonymous.
• The process of recording the details needs just 30 seconds, which is almost equal to the time taken between the exit of current patient and entry of next patient.
• At the end of the day, the doctor will need to type in the Template details in a SMS using a predefined format and send to a specific number, which is connected to the database of the Public Healthcare System datacenter.
• The doctor will also have to mention in the SMS the PHC-ID the day’s report belongs to.
• The entire process will ensure on-ground reporting of diseases by the doctors themselves, instead of deploying a specialized workforce for this activity. 

Remote marginalized regions with no healthcare center –

• Remote areas suffer from lack of hospitals and clinics where people can go for checkup. Such places need regular visit of healthcare workers to track the health status of the residents.
• The national government and state governments will collaborate to assign Region IDs to such places for tracking purpose.
• Such healthcare workforce will first be trained on how to use the Reporting Template and will be sent to visit the remote areas at least once a week.
• With each diagnosed patient, the doctor will record the ailment details in the Template and will identify any disease that is on the verge of a major outbreak.
• By the end of day, once the doctor returns to the city/ village having moderate telecom network, the doctor will need to need to type in the Template details in a SMS using a predefined format, mention the Region ID and send to a specific number, which is connected to the database of the Public Healthcare System datacenter.
• Updates for remote regions will happen only once a week.

Small towns with limited connectivity –

• Doctors in small towns are expected to have relatively higher digital literacy accompanied with a sound telecom network and internet connectivity.
• Doctors in digitally enabled hospitals can be provided with tablets by the government in which the ailment records can be updated with each patient visit and can be stored temporarily over 24 hours.
• At the end of every working day, a single button can help to automatically upload all the records to the datacenter by either sending the data over web or by using an in-built GSM module to automatically prepare a SMS and send it over to the specified number provided by government.

Centralized data analytics –

• The data uploaded to data lakes through SMSs will be collated and cleaned by an automated system in the central datacenter locations.
• Microsoft Azure will be used as the Cloud platform for hosting the data and for performing predictive analytics.
• Datasets will be analyzed for identifying key trends in diseases across the population, predicting any major disease outbreak, identifying the gender and socioeconomic divide in incidence of diseases and informing the concerned stakeholders to prepare a disease response strategy in case of a major impending outbreak. 

Governance –

• The backend server will run a sanity check at sharp midnight daily to check if any PHC-ID has been missing in that day’s updates.
• The administrator or official corresponding to that PHC-ID will be alerted and the local administration will be alerted as well regarding the observed lack of discipline.
• Once a week, the Region ID updates will also be checked for regularity.
• Any quality issues will be highlighted to the concerned local administration and the doctor corresponding to the healthcare center.
• Quality of data, timeliness and regularity will be among the Key Performance Indicators (KPIs) for the doctors.

Outcomes –

• Disease incidence tracking, recording and analysis without reliance on internet network for regions with little to nil internet penetration.
• Reduced risks of erroneous data being fed to database since experienced doctors are responsible for feeding correct and validated data.
• Daily data analytics powered by predictive intelligence algorithms will keep the government and public healthcare institutions updated on any deviation, anomaly or red flags.
• Data sharing among government, WHO and international organizations can help the world stay prepared on any major disease outbreak and possibly equip the nation with knowledge, manpower, medicines and other resources to contain the spread early on.

Framework – 

The solution serves the most impoverished and marginalized communities of India who have low access to healthcare and whose data rarely gets recorded in national health database, as they are disconnected from the formal organized healthcare system. The solution will bring those people under the umbrella of universal data tracking and measurement. 

The solution also serves the resource-starved medical professionals who don’t have many avenues to share data with the government, except written applications or verbal warnings to government agencies. This solution will make sure that their voices are heard daily, on proactive basis through the data they upload on servers through pre-defined SMS format. 

It also serves the government, NGOs, civil society and institutions working for improvement of healthcare system in India, as they grow better prepared with regularly collected verified data and can take data-driven decisions to mitigate a disease outbreak, or even a pandemic, by formulating relevant strategies as quick & resilient response mechanism. 

My team carries significant experience in healthcare consulting, financial management, grassroot innovation and program management. We also carry 7 years of volunteering experience, serving in the marginalized communities of the impoverished regions of India. 

Moreover, we have a network of grassroot project sponsors, mentors from Jagriti Yatra project and social innovators from Engineering for Change organization. 

The ASME iSHOW event will be leveraged to pitch the project and seek funding & mentoring for the project, which will help implement and scale the project in pilot districts. Knowledge, experience, network and passion – we will build on these competencies. 

The motivation to apply to this Challenge is to get mentoring from industry experts and healthcare professionals that currently I lack access to, though my team carries consulting & market research experience in this sector. However, we will need partners, sponsors and grassroot innovation leaders to guide us on our journey. 

Moreover, we need legal support and technical resources for deploying the data analytics capability, for scaling the solution and for onboarding the public sector policymakers for making the solution viable for a pilot project. MIT Solve can help to bring access to such networks that can help us accelerate our solution's implementation. 

The solution is innovative due to its novel approach for data collection, easy to use technology, minimal reliance of internet and telecom infrastructure and the participative nature of the program. 

• Centralized data collection – Instead of health workers going door to door for data collection and relying on people’s unverified statements for recording health data, the solution leverages the data maintained by a doctor at his/her clinic which adds credibility and relevance to the collected data. Moreover, the details of disease and ailments is recorded by a doctor, which means the data will be accurate as a doctor can identify a disease better than another citizen. 
• Easy to use technology – The doctor simply needs to record the incidence of a disease for every patient in a printed sheet or a simple tablet interface, which simply requires clicking a button. Such basic technology is easy to teach to non-tech savvy doctors, nurses and medical professionals, and therefore the onboarding process for doctors will be quick and they will show higher readiness to use the solution.
• Minimal telecom infrastructure – Since SMS is to be sent only at the end of the day and not frequently over a single day, the process will consume very minimal telecom network and will not even need internet facilities. This makes it all the more suitable for remote areas where internet facilities may rarely exist.
• Community participation – The involvement of specialized healthcare professionals reaching out to the remotest of areas in Least Developed Countries and recording data along with treating patients helps citizens to be participants in the process and contribute to its success. 

Goals for:

• Next year – To secure funding for the project, meet public sector stakeholders and hire Azure Cloud consultants to define the centralized data analytics framework.
• 5 years – To run pilot project in select 5 districts as proof of concept and communicate the outcomes to the government for further assessment and expansion of the program with buy-in from government agencies.

The goals will be achieved through the following activities:

• On-ground primary and secondary research of healthcare landscape in low-income & remote regions of India
• Institutionalization of a program to lay out the guidelines, process and stakeholders for the program
• Identification of key accountable stakeholders and hiring of program team
• Support from Jagriti Yatra network for grassroot-level pilot in select districts of a partner province
• Establishment of Key Performance Indicators (KPIs) for meeting the program objectives
• Communication of incentives for stakeholders for meeting the objectives
• Hiring of grassroot project consultants and selection of fellows for driving the pilot
• Liaison with doctors, nurses and medica staff in pilot district for monitoring of program. 

The Key Performance Indicators for progress measurement are as follows:

1. Regularity of data uploaded from all health centers daily
2. Quality and accuracy of data format sent by SMS
3. Time taken by a doctor to send daily reports (gives clue about efficiency and ease of use of technology)
4. Time taken to analyze data and produce output
5. Number of potential disease outbreaks detected in advance
6. Number of diseases outbreaks gone unidentified
7. Number of doctors lagging in performance
8. Extent of regional and hospital coverage in pilot district
9. Growth in number of participating doctors and medical staff
10. Frequency of downtimes
11. Number of failed transmission of data by SMS
12. Time taken for government to acknowledge and respond to a potential disease outbreak 

Theory of Change –

• Inputs: Ailment details recorded by doctors, Region and time of record, Number of patients for same disease in a day/week, Frequency & regional concentration of disease, Epidemic threshold.
• Activities: Recording of patient’s ailment’s details anonymously, sharing of collected data daily through SMS to centralized datacenters, Data analytics over compiled datasets from over the country.
• Output: Trend analysis of different ailments, identification of disease(s) that cross tolerance threshold.
• Intermediate outcomes: Preparedness of healthcare workforce and concerned public sector agencies to mitigate any potential disease outbreak, procure medicines/vaccines in advance and train doctors on how to handle surge of patients during an outbreak.
• Impact: Inclusive healthcare through last mile health data tracking. 

GSM technology for SMS communication, data analytics, cloud, web-app development for tablet interface, Knowledge Management systems, Project management tools 

The primary health data is collected by the doctors at Public Health Centers, travelling medical staff in remotest areas, nurses in small towns & busy hospitals, and volunteers/ fellows assisting small health centers at grassroot level. 

Diversity will be ensured in the following ways:

• Diversity of doctors: Medical professionals from different practices (general physicians, pediatricians, nephrologists, etc.) will be uploading ailment-focused data which will help to increase coverage over a large pool of diseases and will not leave any kind of patient missing from the database.
• Diversity of regions: The robust system will work in towns, villages and remote areas, which will ensure that both the urban and rural landscape et covered and no particular region or ethnic community is left behind. Even the marginalized communities in remote areas and urban regions will get covered anonymously.
• Diversity of gender and age: People of all genders and age will be covered under this plan and this will ensure that no person goes untouched by the system.

Inclusivity: When people of all socioeconomic backgrounds get covered, regardless of their ethnicity, social status and location, inclusivity on all levels will be ensured.

Equity: All patients under tracking will be treated equally by the database and no discrimination will done in terms of comprehensiveness of metrics and process in any urban, rural or remote region. The incorporation of different methodologies for resource-challenged regions will ensure that we build inclusive systems for equitable outcomes. 

My business model is that of a market intermediary and public sector consultant to the government. I will offer a market assessment, program benchmarking, capability driven strategy, go-to-market strategy and Target Operating Model, using which the suggested idea can be scaled into a progressive and functional program for the healthcare sector of the target country. 

Consulting services usually earn from advisory fee and results in an outcome-based model. I plan to offer a partial fixed fee and partial outcome-based billing model. The fixed fee will cover the expenses of the team of consultants and the healthcare sector research activities. However, the variable component will depend on the magnitude of results generated. 

So far, financial sustainability has been planned to be achieved through fixed  or outcome-based consulting fee alone.