Platform for Neonatal Sepsis Prediction & Antimicrobial resistance

PreSco is an Integrated Digital Health platform for rapid and affordable diagnosis of Neonatal Sepsis and Prevention of Antimicrobial Resistance. 

Dr. Hyma Goparaju PhD, Founder & CEO of Avyantra Health Technologies with vast experience in Data Analytics and Product Development and is the Program Manager.

Problem & Scale – Every year, 25 million babies are born in India and 10 million of them are at the bottom of pyramid. Six lakh babies die annually due to neonatal infections and 30% are due to Neonatal Sepsis. Neonatal mortality rate (NMR) is 25 while it is 1 or 2 in developed countries.

Causes – Primary factors for high neonatal mortality in India due to neonatal sepsis are delayed diagnosis (culture reports take between 48 and 72 hours), limitations of current blood and culture tests (non-specificity and non-sensitivity), low access to specialised healthcare in rural areas and low affordability. More than 40% neonatal deaths are reported to occur within the first 24 hours of birth chiefly due to low resources and time lost in transportation to urban centres.

A recent study also reveals that administration of antibiotics from the time of birth causes metabolic and immunological disorders in the long run. Additionally, mothers and babies have been reported to be the most affected during the COVID-91 pandemic across the globe.

Our Solution - Our integrated cloud-enabled platform uses machine learning algorithms for prediction of Neonatal Sepsis infections to address the shortfall of resources in rural areas. The platform has a referral system that connects urban health infrastructure with rural areas. It also provides a cost-effective electronic medical records platform that can be used by both practitioners and patients. 

Our platform primarily addresses a critical area of ‘maternal and child’ health which traditionally has been side-lined as a female issue. Child birth and child care are viewed as women’s issues. Additionally, most frontline volunteers working in the maternal and child space in India are women. They have limited access to advanced technologies and tools. We strongly believe that our platform has the potential to empower them and redefine the way their work and healthcare delivery at point of care.

 Primary Target – Mothers and Babies - Covid-19 crisis has severely impacted the delivery of health services and has reversed the progress made in the past few years w.r.t several health indicators listed in the UN sustainable development goals.

Secondary Target -

a. Rural Clinics and healthcare professionals

b. Tertiary hospitals were loaded due to increased Covid-19 patients’ occupancy.

c. Mother and Children – Young mothers and infants found it hard to commute to receive quality healthcare from an urban health centers.

d. Health Volunteers – Our application is designed for use with minimal training by a large force of frontline health volunteers (ASHAs). There are about 800,000 ASHA volunteers in India that serve the bottom pf pyramid segment.

Our project is implemented using open-source standards and tools. It follows ISO/IEC/IEEE 12207 Systems and software engineering – as international standard for Software life cycle processes.

Sustainability: The project is being undertaken with an objective of making diagnosis accurate, reliable, affordable, and sustainable with a well-defined business model.

Open-Source Technology:  Our application was built using open-source tools and technologies. The same have been made publicly available in GITHUB platform with the GNU license option. https://github.com/kvklrao/Avyantra_Presco_Project

Address privacy and security:  We are following strict data privacy protocols during collection, processing and storage of data. Anonymous data of patients has been collected to ensure privacy. The platform has been built with multi-tier security protocols to prevent unauthorized access to patient data. 

Collaborative: The platform has been built with open source standards and the code base was made publicly available in GITHUB for collaboration with the global community of developers and users for improving features as well as adoption of the globally. 

During our work at hospitals, we have noticed that culture test facilities are not available at most centres leading to empirical antibiotic administration. Our platform fills this critical gap through early assessments. Early diagnosis leads to reduced administration of empirical antibiotics and brings down antibiotic resistance.  A recent study has reported that extensive use of antibiotics from neonatal stage among babies can result in increased metabolic and immunological disorders among individuals across their life span. 

Health resources are constrained in developing countries like India. More than 40% of babies die during transit to urban centres in India. India also has the highest first 24-hour mortality of neonates. Digital and cloud platforms like ours have the ability to deliver quality health services to all nooks and corners. Our platform’s referral system to provide emergency treatments. 

Our platform addresses the existing gap of low health resources and facilitates early identification of babies with infections and aids in optimal decision making for timely diagnosis.

Clinical decision support system (CDSS) can bring down usage of antibiotics significantly by at least 50% upon its consistent use and reduce cost of treatment, antibiotic resistance and mortality. We plan to impact at least 50,000 babies post launch.

Digital health market is expected to go up to $150 billion by 2030 and save at least $50 billion in healthcare expenses in India.

SCALE THROUGH LARGE RURAL DEMAND – Rural market in India is very large with more than 60% of the population. The large size of the neonatal market (USD 10 to 15 billion) lends sustainability to our solution.

SCALE THROUGH PARTNERSHIPS – We have a signed LONG-TERM AGREEMENT (LTA) with Unicef in August 2020 for supplying our solution to their member countries. We are also exploring opportunities for partnering with large software and medical firms for distribution and hospitals for implementation.

SCALE THROUGH COST EFFECTIVENESS - Demand for quality healthcare services in rural India is extremely high. The large demand will help us sustain our model and scale it.

SCALE THROUGH OPERATIONAL AND FINANCIAL GROWTH BY PARTNERSHIPS - Our project is aligned with Universal health coverage programmes in India, and Sustainable Development Goals (SDGs) that together aim to reduce neonatal & infant mortality and provide universal health coverage to maternal and child health requirements in India and across the globe. We are in final rounds of a couple of Funding Initiatives by the Govt of India for Startups.

Processes – We have well defined processes in place for monitoring and evaluation such as setting Project Goals and Objectives, Defining Indicators, Data Collection Methods, Data Analysis and Reporting, Dissemination of Information through communication protocols agreed.

Data Quality Assurance Mechanisms – We follow data quality assurance plan with defined process for ensuring data validity, integrity, reliability, precision and timeliness.

Frequency of Appraisals – Daily basis for project operations, Monthly basis for comprehensive project review and quarterly for review of project goals and impact.

Results Framework – We follow a well-defined template & results framework in agreement with our funding partner. The results framework includes a comprehensive performance management plan for monitoring of key project goals and objectives as agreed with our funding partners.

Tools that project uses – We use several project tools for project execution and monitoring such as Github, Code Climate, MSP etc.

Measurable Indicators -

Percent of Target Data Collected from Collaborating Hospitals - We are targeting to collect at least 5000 data points from 3 collaborating hospitals in 24 – 36 months’ timeframe.

Percent Achievement of Key Indicators for Sepsis Score - We target to achieve 80 - 90% for key metrics such as Accuracy, Sensitivity, Specificity.

Financial Barrier – We are in need of consistent funding support to enhance the features of the product, complete testing and validation and to ready our product for commercialisation and launch. We are working with several funding agencies, both domestic as well as international ones, to meet our future funding requirements.

Technical Barrier - Data availability in required digital formats for retrospective study as well as conversion of unstructured medical data to structured data for analysis is a complex task. We are planning to overcome this challenge with advanced technical architecture for big data, image analysis and data mining techniques.

Legal & Policy Barrier - Data privacy laws are becoming stringent globally and we are taking steps to adhere to data privacy laws to ensure safety and privacy of patient data.

Infrastructure Barrier - Lack of required internet bandwidth in developing countries and less developed countries could be an issue in the short term. However, since telecom infrastructure is improving in many developing countries we expect it will support usage of digital products through mobile applications.

Resources Available - We are pursuing our project goals with support from international agencies like UNICEF and government support programmes for start-ups.  

We have a long-term agreement (LTA) with Unicef for supplying our solution to Unicef member countries.

We are collaborated with Data Centre & Analytics Lab, Indian Institute of Management, Bangalore, India for data analytics support.

Winning the Trinity Challenge will help us overcome several barriers that we have been facing in the recent times.

Financial Barrier – The fund will help us to meet our financial needs and provide the much required budgetary boost to support our team.

Technical Barrier – The fund will help us explore the technical innovations in the area.

Legal Barrier & Policy Barrier – Fund will help us to make our product and platform complaint with domestic as well as international regulations on data privacy and protection of patient data.

Cultural Barrier – Since we are working with several partners, the Trinity Fund would be able to help us overcome cultural barriers as we walk through our partnerships.

Market Barrier – Attention from various organisations and governments across the globe to help market our solution better.

Infrastructure Barrier - The fund will help us to enhance the technical capabilities of the product as well as platform, overcome infrastructural barriers and make the application responsive in low resource settings.

Resources Available – The fund will most certainly help us get access to better resources, be it manpower, infrastructure, collaborating partners and take us towards our scale-up and commercialization goals.

We have a Long-Term Agreement (LTA) with Unicef, signed in August 2020, to provide our solution to Unicef member countries.

We are collaborated with a reputed academic organisation in India for finetuning our algorithms. We are also seeking guidance from international academic organizations for machine learning and artificial intelligence technologies.

 We have tie-ups with reputed hospitals in India for development and validation of our platform.

We are working towards partnering with the Government of India organizations and are open to collaborations and partnerships with organizations for implementation of our platform.

 We are aligned with United Nations Sustainable Development Goals (SDGs) – SDG-3 for Good health and well-being; SDG-5 for Gender equality; SDG-10 for reduced inequalities and finally SDG-17 for Partnerships for the Goals.

 We are open to working with consortium partners and have begun to explore the same with our Indian and UK based academic partners.