E - Swasthya Saathi

In Uttar Pradesh which is the most populous state of India with a population of 230 million, around 6 million babies are born every year out of which, around 4 million are born in the public health facilities.  Around 17,OOO nurses are posted across 30,000 public health facilities offering primary, secondary and tertiary care across the state.  These staff nurses are the primary service providers during the intrapartum and post partum period as they conduct majority of deliveries, because most of the health facilities do not have qualified medical doctors providing round the clock  ( 24 hours) maternal and new born services. 

Insufficiency of doctors leads to lack of immediate and appropriate decision  taking process at the time of delivery, further affecting the timely identification and provision of basic management services to the mother and the newborn. Along with high case load, nurses are burdened with recording and reporting of cases in multiple registers and platforms which takes majority of their duty hours. This leads to poor quality of case sheets, hence affecting the timely identification and management of complications in the mother and the new born. This further causes compromised quality of care in public health settings, which may be one of the factors contributing to excess mortality across maternal and newborn conditions. 

The increased dual workload of offering standard clinical services as well undertaking  realtime recording and reporting across multiple formats may be a reason for reluctance among the staff nurses to effectively capture data on case sheets and other required portals. This renders data at source of collection to be duplicated, improperly formatted, non-standardised, non  interoperable and incorrectly analysed and projected, hampering program monitoring and evaluation and proper data based decisions. 

We are building a digital clinical case sheet with an inbuilt  clinical decision making tool with  algorithm driven processes. Through the prompts on the application once the digital case sheet is initiated realtime, it will act as a comprehensive job aid for the staff nurse delivering maternal and child health services at the public health facility. This will also aid in streamlining real-time data collection and ensuring that adequate quality of data is captured.

The technology is governed by  a workflow based platform with clinical decision support system, running on a tablet/mobile. 

The nurse will be the primary user whose work will be driven by guided steps through the clinical decision making support  system. 

The flow of the application will be as follows:-

 Pregnant women comes in facility —->  Nurse initiates digital case sheet on the application  —> If the pregnant woman is already registered —> Identifier, ANC, Past medical and obstetric history fetched from linked dataset,  If not, possibilty to fill manually on the application—> Nurse can start recording clinical information with time progression according to protocol —>will be Based on the standardised clinical algorithm —>if nurse forgets to fill any essential data they will be notified the application will suggest the steps of management and referral if required. 

Data will be stored locally on the device and will synced whenever internet connection is available. By this process data will be collected at the source which can be segregated in backend and various reports can be generated and viewed on dashboard, depending upon need of service provider/hospital manager/program manager at different levels for taking data based decisions

Once data are recorded on the system advanced tool like machine learning and artifical intelligence can be used for further improving clinical algorithms and  clinical outcomes. 

Primary beneficiary and user :  The nursing staff of delivery points in the public health settings who have to provide maternal and new born services  and have the primary responsibility of recording data at source. The digital tool  will reduce the workload of the nurse as they will be better equipped to manage case records in shorter duration of time. Additionally, this will decrease the cumbersome paper work, duplication of data  and aid in making  timely clinical decisions. 

It will instill motivation and encourage the staff to work efficiently, utilise  the resources offered to them, make their work easier and interesting as they will have opportunities to leverage new learnings and improve their performance. 

End beneficiary:- Pregnant women and newborn. They can be offered prompt and quality clinical care as the clinical decision  making tool will drive early detection of complications, prompt management and referral. This will contribute to reduction in maternal and infant mortality. \

Other beneficiaries :- Hospital and program managers, in monitoring and evaluation, inventory management and quality improvement of clinical service delivery at the facilities along with robust recording and reporting to drive evidence  and data based decision making, This will augment the implementation of health programs effectively. 

We are a team of diverse  public health professionals with a background in clinical medicine as well as research, working in  maternal and new born health across one of the states of india which has the largest cohort of pregnant women and newborn  6 million and one of the highest MMR  and IMR. We intend to work for both the service providers (nursing staff and doctors)  at the public health facilities and the communities ( beneficiaries - pregnant and new born).

The pilots of rolling out the digital tool  post development of the application will include feedback through operational/implementation research incorporating feedback  and inputs of our end users.

We are a group of professionals working in the health system in close contact with the beneficiaries and realise that the scale of the problem that the service providers face. An innovative solution meeting their needs, resolving their issues can act as aid their work on a daily basis. Eventually, prompt clinical decision making, timely referrals, undertaking correct procedures can ensure quality of continuum care at the facilities and reduce the mortality among mother and newborn, ultimately propel LMICs like India  to achieve SDG targets of maternal and infant mortality till 2030. Since we are  at a ideation to conception stage, we are looking for right guidance, mentorships, financial resources to build a low cost solution for capturing the data at the source and digitalisation of the records along with conducting an implementation research to test and correct the solution midcourse.

Our solution is innovative in its approach and addresses to solve the key problems faced by the staff nurses while clinical service delivery, in turn acting as a digital job aid facilitating and empowering them in the low resource public health settings. Through our solution, there is a dual benefit, the job aid will strengthen the staff nurses capacity effectively while improvement in their performance in a cascade manner will reflect on good quality of recording and reporting of clinical data as well timely delivery of  adequate clinical services thus giving our beneficiaries the pregnant women and newborn a positive birthing experience in the public health settings. 

The conventional methods of recording and reporting of clinical data at the facility is paper based, poses a problem of added workload and duplication of formats for the staff nurses. Most times, when they are performing clincial procedures in absence of medical doctors they are burdened and might be underconfident, a clincial decision making tool with case sheet displaying guided steps can assist them to enter the data realtime and aid in timely identification and management of complications, undertaking correct procedures and administration of required dosages to the mother or new born delievring quality care to the beneficiaries. This will eventually enable the nurses, motivate them as well as contribute to transparent seamless data based decision making. In the broader picture, we will be able to aid to accomplishment of reduction of maternal and infant mortality rates in the state and achieve SDG targets. 

Our solution aligns with the SDG 3 : Ensure healthy lives and promote well-being for all at all ages. In the coming years, we will contribute to reduce the global maternal mortality ratio to less than 70 per 100,000 live births. 

Additionally, we will aid in efforts to comply with the following goal -  By 2030, end preventable deaths of newborns and children under 5 years of age, with all countries aiming to reduce neonatal mortality to at least as low as 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live births.

Overall Progress can be  tracked by the indicators - maternal mortality ratio and proportion of deliveries attended by skilled birth attendant, inafnt mortality rate, under 5 mortality rate, neonatal mortality rate. 

Indicators to asssess the robustness of data adminstered on data portals like health management information systems will be tracked by evaluating its frequency, completeness, adequacy and quality. 

Additionally, proxy indicators to assess the knowledge, skills and practices of the staff nurses will be developed so that the impact of the digital case sheet and clinical decision making on the competency and quality of care can be tracked.

We are a digital application based solution and the technology is governed by  a workflow based platform with clinical decision support system, running on a tablet/mobile. The algorithm is driven by artificial intelligence /machine learning. 

The staff nurses will collect the data for the solution as it is her primary responsiblity in the public health settings. We are the replacing paper based tool ( case sheet)  to a digitalized version and the data will be filled through the application on the mobile/tablet.  Our solution will enable them and build a sense of accountability, since it is  part of their regular duties it doesn't require an additional incentive, 

Grant based project with implementation research - Non profit 

Grant based funding as per the need to develop the digital tool, conduct pilots and research 

Not applicable , in the ideation to conception stage