Sahyog, a tech-enabled system support for health workers

Improving the quality of primary healthcare (PHC) delivered in community settings during service delivery contacts for antenatal care (ANC), postnatal care (PNC) and immunization (EPI or expanded program on immunization) or during home visits is critical to improve health outcomes in low- and middle-income countries. Evidence is mounting that transforming the way community health workers (CHWs) are supervised is associated with improvement in quality of services. That’s the goal of the solution.

Improving quality of PHC services is being recognized as a priority for governments in India, Bangladesh and globally.

• Poor access to quality healthcare is one of the most important reasons for high maternal and neonatal mortality in India, particularly in poor states like Bihar (Kaur J. et al., 2019).
• Coverage is not sufficient. In India, increased institutional delivery is associated with significant mortality reduction only in districts where quality of care is high (Lee, HY., Leslie, H.H., Oh, J. et al., 2022).
• “As the maternal, newborn, and child health community recognizes the importance of quality of care (QoC) to reaching population health goals, there is a shifting focus on improving and therefore measuring and monitoring service quality” (King 2021).
• Point of Care Quality Improvement techniques have been developed and are starting to be piloted and rolled out across South Asia to improve PHC QoC in health facilities (World Health Organization, 2020).

However, while the number of initiatives to improve the quality of service delivery in health facilities is growing fast, there remain important gaps.

• For key PHC preventative services such as nutrition, quality is only starting to be defined and remains to be prioritized (King, 2021).
• Improving the quality of community-based services remains underprioritized. A report by Lancet Global Health Commission on High Quality Health Care System recommends four actions: governing for quality, redesigning service delivery to maximize quality, transforming the health workforce to provide high-quality, respectful care, and igniting people’s demand for high-quality care (Kruk, 2018).
• The stakes are high in Indian states such as Gujarat, Uttar Pradesh (UP), Bihar and Jharkhand. These states have a higher under-five mortality rate than the national average with a peak at close to 60 per 1,000 live births in UP (Government of India). Access to government community healthcare services also remains a concern in Bangladesh (NIPORT & ICF, 2017).

Evidence on what does and doesn’t work to sustainably improve the quality of community-based PHC activities is mounting.

• While building the capacity of CHWs is critical to improve QoC, it is not sufficient. Data from large scale trials suggest that training, supervision and communication may be of similar importance to improve CHW QoC and coverage (Nguyen et al., 2019).
• Qualitative studies in India suggest that effective interventions to improve QoC in community settings require interventions that overcome the key barriers to effective service delivery by CHWs: 1) poor knowledge and skills, 2) limited beliefs, self-efficacy and motivation, and 3) systemic barriers, such as lack of adequate supplies, competing priorities, etc. (John, Lewis & Srinivasan, 2019).
• Large scale assessment programs in the field suggest that the root causes of most of those barriers must be addressed at the local or sub-district level (USAID, 2014).
• A mounting body of evidence suggests that interventions that aim at institutionalizing supportive supervision, defined as an approach to better balance supervisors’ administrative duties (that currently make up the bulk of their responsibilities) and their on-the-job coaching and problem-solving support roles may improve CHW job satisfaction and performance (Bailey et al., 2016; Biemba et al., 2020; Desta et al., 2022).

A lack of focus on quality of services, coupled with low CHW motivation levels and poor support mechanism for decision making at lower levels in the health system leads to poor service quality and beneficiary experience.

• Quality of community-based services is generally not measured and often poorly defined in India and Bangladeshi PHC systems.
• Systems lack structured and sustained mechanism to support CHWs by which a relationship of trust and faith can be established between the supervisor and the supervisee. The concepts of ‘coaching’ and ‘mentoring’ are non-existent (FHI 360, 2021; FHI 360, 2022; WeCaN, 2021; IFPRI, 2019).
• Due to the fear of admonishment, CHWs and often lower-level supervisors don’t make decisions to address service delivery challenges. In addition, the flow of information is mostly top-down, which means that higher authorities don’t know what barriers need to be addressed on an ongoing basis (FHI 360, 2021; FHI 360, 2022; WeCaN, 2021; IFPRI, 2019).

References:

Bailey C, Blake C, Schriver M, Cubaka VK, Thomas T, Martin Hilber A. A systematic review of supportive supervision as a strategy to improve primary healthcare services in Sub-Saharan Africa. Int J Gynaecol Obstet. 2016 Jan;132(1):117-25. doi: 10.1016/j.ijgo.2015.10.004. Epub 2015 Nov 6. PMID: 26653397.

Biemba G, Chiluba B, Yeboah-Antwi K, Silavwe V, Lunze K, Mwale RK, Hamer DH, MacLeod WB. Impact of mobile health-enhanced supportive supervision and supply chain management on appropriate integrated community case management of malaria, diarrhoea, and pneumonia in children 2-59 months: A cluster randomised trial in Eastern Province, Zambia. J Glob Health. 2020 Jun;10(1):010425. doi: 10.7189/jogh.10.010425. PMID: 32509293; PMCID: PMC7243069.

Desta BF, Beshir IA, Tefera BB, Argaw MD, Demeke HZ, Kibret MA (2020) Does frequency of supportive supervisory visits influence health service delivery?—Dose and response study. PLoS ONE 15(6): e0234819. https://doi-org.ezproxyberklee.flo.org/10.1371/ journal.pone.0234819

Government of India.  Family Health Survey 5. (2019-21). http://rchiips.org/nfhs/

Government of India.  Family Health Survey 5. (2019-21). http://rchiips.org/nfhs/

John A, Newton-Lewis T, Srinivasan S. Means, Motives and Opportunity: determinants of community health worker performance. BMJ Global Health 2019;4:e001790. doi:10.1136/ bmjgh-2019-001790

Kaur J, Franzen SRP, Newton-Lewis T, et al Readiness of public health facilities to provide quality maternal and newborn care across the state of Bihar, India: a cross-sectional study of district hospitals and primary health centres BMJOpen 2019;9:e028370. doi: 10.1136/bmjopen-2018-028370

King, Shannon., Sheffel, Ashley., Heidkamp, Rebecca., Xu, Yuvonne., Walton, Shelley., Munos, Melinda K. Advancing nutrition measurement: Developing quantitative measures of nutrition service quality for pregnant women and children in low- and middle-income country health systems. Maternal and Child Nutrition. 18 (1). Wiley 2022. https://onlinelibrary-wiley-com.ezproxyberklee.flo.org/doi/10.1111/mcn.13279

Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, Adeyi O, Barker P, Daelmans B, Doubova SV, English M, García-Elorrio E, Guanais F, Gureje O, Hirschhorn LR, Jiang L, Kelley E, Lemango ET, Liljestrand J, Malata A, Marchant T, Matsoso MP, Meara JG, Mohanan M, Ndiaye Y, Norheim OF, Reddy KS, Rowe AK, Salomon JA, Thapa G, Twum-Danso NAY, Pate M. High-quality health systems in the Sustainable Development Goals era: time for a revolution. Lancet Glob Health. 2018 Nov;6(11):e1196-e1252. doi: 10.1016/S2214-109X(18)30386-3. Epub 2018 Sep 5. Erratum in: Lancet Glob Health. 2018 Sep 18;: Erratum in: Lancet Glob Health. 2018 Nov;6(11):e1162. Erratum in: Lancet Glob Health. 2021 Aug;9(8):e1067. PMID: 30196093; PMCID: PMC7734391.

Lee, HY., Leslie, H.H., Oh, J. et al. The association between institutional delivery and neonatal mortality based on the quality of maternal and newborn health system in India. Sci Rep 12, 6220 (2022). https://doi-org.ezproxyberklee.flo.org/10.1038/s41598-022-10214-y

Nguyen, Phuong Hong, Sunny S Kim, Lan Mai Tran, Purnima Menon, Edward A Frongillo, Intervention Design Elements Are Associated with Frontline Health Workers’ Performance to Deliver Infant and Young Child Nutrition Services in Bangladesh and Vietnam, Current Developments in Nutrition, Volume 3, Issue 8, August 2019, nzz070, https://doi-org.ezproxyberklee.flo.org/10.1093/cdn/nzz070

National Institute of Population Research and Training (NIPORT), and ICF. 2020. Bangladesh Demographic and Health Survey 2017-18. Dhaka, Bangladesh, and Rockville, Maryland, USA: NIPORT and ICF.

World Health Organization. Regional Office for South-East Asia. (‎2020)‎. Towards maternal and newborn survival in the WHO South-East Asia Region: Implementation experience of the WHO SEARO model of point-of-care quality improvement (‎POCQI)‎. World Health Organization. Regional Office for South-East Asia. https://apps.who.int/iris/handle/10665/337921

USAID ASSIST. Improving essential newborn care through quality improvement interventions in Regional Hospital Chamba, Himachal Pradesh, India. 2013. https://pdf.usaid.gov/pdf_docs/PA00KXRP.pdf

The goal of the solution is primarily to improve the quality of maternal, newborn and child healthcare and nutrition services delivered by government CHWs in community settings such as ANC, PNC and EPI service delivery contacts, courtyard sessions and home visits, and secondarily to empower (mostly female) CHWs. The solution will deliver those benefits through two behavior change interventions targeted at system supervisors:

• Supportive Supervision, understood as an improved method to supervise government CHWs that better balances the administrative, coaching/on-the-job training and support roles of frontline supervisors and their managers, and
• Strategic Use of Data, understood as a new way to run monthly review meetings that focuses on reviewing data on service coverage and quality, understanding, resolving/escalating for resolution and tracking the issues precluding effective service delivery in the field.

The solution was developed using a Human-Centric Design approach adapted from the CREATE and DECIDE methods (O’Reilly, 2013, Designing for Behavior Change). Each step of the process, from “Defining the problem”, “Exploring the context” and “Crafting the solution” involved structured and unstructured consultations with stakeholders (supervisors, CHWs and beneficiaries) to refine our understanding of the root causes of issues, identify probable solutions and stress test solution design options.

The solution includes five components: 1) new processes, 2) training, 3) supporting mobile app, 4) change management and 5) monitoring.

1-New processes

Supportive Supervision: New processes require frontline supervisors and their managers to regularly go to the field to observe CHW service quality, conduct structured Debrief Sessions with CHWs, and track the resolution of issues in the field or escalation to higher authorities. Every month each supervisor defines, executes and documents her field visit plan. Each visit involves the observation of service quality using structured checklists. Supervisors are to reinforce the positive findings and discuss potential root causes and solutions to quality issues with CHWs. Those issues are then captured (in audio format), acted upon or escalated, and tracked. Solutions can involve addressing supply bottlenecks, jointly consulting job aids/capsule training materials on specific knowledge or skill gaps, advocating with community stakeholders to get needed support, etc.

Strategic Use of Data: New processes change the way monthly review meetings are structured at the local, sub-district and district levels. The solution tracks meeting execution, attendance, workflow and issue resolution or escalation. Supervisors in charge of facilitating those meetings are provided with a problem-solving focused dashboard, prompted to review data on service coverage (from other management information systems) and quality (from Supportive Supervision observations) to identify where performance improvement may be needed, simple triangulations of data points common across systems to identify what steps are required to increase data quality, as well as the compilation of issues identified during Supportive Supervision visits. Armed with this information, supervisors are requested to facilitate structured review meetings focused not on data, but on the resolution of the key issues resulting from the partially automated data review conducted during meeting preparation. The core of review meeting agendas is dedicated to discussion of issues precluding effective service delivery in the field, potential solutions and, when relevant, on capsule training focused on common knowledge or skill gaps. Corrective actions are then planned and tracked or issues further escalated.

2-Training

A two-day supervisory training involves strengthening the supervisory skills of supervisory cadres from PHC and nutrition services to ensure their renewed focus on listening and addressing issues from the field and improving service quality.

3- Mobile app

The solution contains a simple, easy-to-use, mobile-based application or app. The app functions as a guided tool for supervisory cadres to make supportive supervision effective and easy. Features of the app enable observation of service quality, on-the-job training, discussion of issues between supervisors and their subordinates, and data-driven resolution of issues. The app’s features and underlying technologies are described in the section on Core Technologies. 

4- Change management

The solution involves structured change management to counter and mitigate barriers to adoption of change and achieve desired outcomes, which involves targeted and repeat communication on the case for change and early wins, identification and activation of champions amongst supervisors to act as peer-to-peer trainers, and non-financial incentives.

5- Monitoring

To drive accountability, the solution tracks supervisors’ Supportive Supervision and Strategic Use of Data responsibilities such as joint field visits, monthly review meetings and associated workflows. To support quality improvement (QI), the solution measures service delivery quality and automates simple triangulation of field workers’ and supervisor data to improve data quality. To prevent Supportive Supervision features from turning into simple monitoring, the solution enables CHWs to provide anonymous feedback on supervisory visits.

Table: Key indicators included in checklists for community-based ANC events (multiple indicators in each row)

Percentage of pregnant women (PW) registered within 1st trimester, received 4 or more ANC check-ups

Percentage of PW detected with hypertension, hemoglobin (Hb) level less than 11, less than 7, severe anemia

Percentage of PW receiving tetanus typhoid vaccination (TT), Albendazole, 180 iron folic acid (IFA) tablets, 360 calcium (Ca) tablets

Percentage of sufficient stock of TT, IFA, Ca injections available

Percentage of events where functional blood pressure (BP) instrument, hemoglobinometer and strips, functional weighing scale, urine strips, oral glucose tolerance test, stadiometer, fetoscope, examination table, curtain for privacy available

Percentage of events where measures BP, Hb, weight, test urine, abdominal checkup, oral glucose tolerance of pregnant women are taken

Percentage of events where measures BP, Hb, weight, test urine, determination of pregnancy danger signs of PW are taken correctly

Percentage of events where CHW able to identify the high risk pregnancy

Percentage of events where High Risk Pregnancy referrals are done

Percentage of events where counselling is done (20 theme specific indicators including nutrition)

Percentage of CHW explained importance of regular ANC at events

The solution is meant to impact two categories of populations, providers of government community-based healthcare services and the pregnant and lactating women (PLW) and under 5 children eligible to their services.

• Service Providers: This category includes CHWs such as Accredited Social Health Activists (ASHAs) and Anganwadi Workers (AWWs) in India and Health Assistants (HAs) and Family Welfare Assistants (FWAs) in Bangladesh and their supervisors. The solution is aimed at supporting service providers by:
  • Building the capacity of supervisors to assess the quality of services and not just coverage, thus improving their performance and help in opening pathways for career progression,
  • Capacitating and empowering CHWs and their supervisors to identify, resolve and escalate systemic challenges in service delivery,
  • Improving interpersonal communication skills of CHWs and their supervisors while enabling an environment that encourages asking fundamental questions for better service delivery,
  • Improving data quality to enable effective decision making
  • Lessening operational issues that supervisory cadres have to deal with, especially at higher levels, thus opening up their time to engage more with strategic issues.
• Beneficiaries of government-run services: This category includes PLWs and children under five years of age. The solution aims at supporting service beneficiaries by:
  • Improving patient service experience so that in turn demand for services and adherence to preventive and treatment regimens improve,
  • Ensuring that beneficiaries receive complete sets of essential healthcare and nutrition services during ANC, PNC and EPI,
  • Improving the quality of services, notably preventive ones such as nutrition counseling, so that self-care and nutrition behaviors improve,
  • Thus, leading to improved maternal, newborn and child health and nutrition outcomes.

To deliver Sahyog, FHI 360 benefits from access to a 1) packaged solution and app, 2), strong technical capabilities, 3) policy, program advocacy and collaboration capabilities, and 4) momentum towards replication and scaleup of the solution with government and donor partners in various states of India and in Bangladesh.

1. Packaged solution and app: The Sahyog solution has been tested and packaged. Multiple adaptations of the technical content have been developed across geographies and government departments (e.g., Gujarat, UP, Bihar, Jharkhand, Bangladesh). The app has been developed in such a way that further adaptation to new contexts is relatively inexpensive.

2. Technical capabilities: During past design, development, piloting and advocacy for scaleup of Sahyog, the solution team at FHI 360 has developed a unique understanding of unmet needs, solution alternatives, technology and solution development issues, and barriers to adoption and implementation in the areas of Supportive Supervision and Strategic Use of Data. Global literature in the area was reviewed and synthesized. Multiple targeted formative research studies were conducted in Gujarat, UP, Bihar, Jharkhand in India and in Bangladesh. The solution team is comprised of public health professionals each with between 10 and >20 years of experience located in South Asia. To complement its capabilities, the solution team regularly consults with global experts within FHI 360’s Digital Development, Design Lab, Social Behavior Change and Health Systems Strengthening units based in the US and globally.

3. Policy, program advocacy and collaboration capabilities: As important as its technical acumen in the areas of Supportive Supervision, Strategic Use of Data and technology, the Sahyog solution team has the ability to interface with government and development partners to advocate and support scaleup. In both India and Bangladesh, the team has been advising the Ministry of Health and Family Welfare on maternal, newborn and child health (MNCH) and nutrition policy and program operationalization issues either directly or as a member of multiple technical working groups. The solution team has presence in Gujarat, UP and Bihar in India and in Bangladesh, where it has been supporting government with the adaptation, piloting and scaleup planning for the solution. The Sahyog team also has demonstrated the unique ability to collaborate with other development partners present in the states to support the rollout of the solution.

4. Momentum with governments and donor partners: The Sahyog team benefits from good momentum towards adoption, adaptation and scaleup of the solution across Indian states and in Bangladesh. In India, the Ministry of Health and Family Welfare has expressed interest in seeing the solution rolled out across states. Scaleup planning of the ASHA solution is complete in UP and scaleup has started. In Gujarat, scaleup planning is ongoing. Interest for the solution has been expressed in multiple other states including Bihar and in Bangladesh. Funding to support scaleup in UP and Bihar and implementation research in Bangladesh is expected in the coming months.

Getting Sahyog recognized in the MIT Solve challenge would 1) support advocacy with governments as we promote the adaptation and scaleup of the solution, and 2) enable the team to provide technical assistance to the government of Gujarat, India as they conduct the scale up the solution across the state. 

The solution integrates people, process and technology to improve quality of PHC and nutrition service delivery in community settings. It innovates in 1) its target outcome - improving the quality of community-based service delivery, 2) its core approach – decentralizing problem identification and problem solving and empowering the bottom of the PHC system pyramid, 3) the way it handles data and technology – centered on facilitating use of data by data collectors, and 4) the way it pursues change – by transforming government supervisors’ change architecture from within the system. In addition, the solution’s scale up strategy innovates by providing flexibility to government to integrate the solution with their system or to replicate its technology component within their own technology stack with FHI 360 support (see Core Technology section).

• Community-Based Service Quality: The solution aims at improving the quality of services provided by government CHWs in community settings such as ANC, PNC and EPI service delivery contacts, courtyard sessions and home visits with an integrated and digitally enabled systems strengthening solution. This is an area that is largely untouched globally. While many system strengthening efforts utilize QI methods to enhance service delivery in health facilities, very few try to apply QI principles in community settings. Improvement initiatives are typically limited to improving the training and job aids of CHWs. The solution has a built-in mechanism to drive observation and measurement of service quality in community settings, promote review of quality indicators to set accountability and ensure that service quality receives the focus it deserves. The focus on quality at the last mile is expected to drive improved public healthcare and nutrition services, increased service uptake, and ultimately improved outcomes.
• Bottom-Up Problem Solving: Recognizing that the majority of implementation challenges are best solved at the local level, the solution aims at institutionalizing decentralized problem solving by empowering government CHWs and frontline supervisors to identify, act on and escalate the issues the preclude quality service delivery. The intent to address problems at the last mile is not new, but few initiatives have tried to operationalize it at scale. Current systems remain largely top down, and thus often fail to understand and address the root causes of issues. Most “supportive supervision” initiatives focus exclusively on monitoring. The solution focuses on modifying existing system coping behaviors through the implementation of new ‘people centric’ processes, tools and communication that structure the joint identification of service delivery issues by CHWs and their supervisors and encourage and empower them to jointly identify their causes and take action. By putting the power of decision-making in the hands of service providers at the ground level, the solution accelerates issue resolution.
• Strategic Use of Data: The solution focuses on driving data usage at the local level to improve service quality and enable problem solving. There are hundreds of digital applications in public health. Most record lots of data that is being reviewed by senior officials to inform program action. Few make data useful for app users. Even fewer capacitate, motivate and require app users to utilize data for decision making, which often results in poor understanding of indicators and low data quality, in addition to lost problem-solving opportunities. The Sahyog solution attempts to make data core to supervisors’ daily supervisory interactions with CHWs and monthly review meetings. In each case, the data supervisors captured is played back to them in a way that supports decision making. In addition, the solution includes automated basic triangulation between Sahyog service quality data and similar information captured in government management information systems (MIS) to drive improved data literacy and supports interactions between supervisors and CHWs to improve capture of MIS data.
• Behavioral Science: The solution aims at nudging supervisory cadres and CHWs to change their behaviors towards openly discussing service delivery challenges, problem solving and issue escalation by changing key components of their choice architecture: management expectations, behavioral triggers along 1:1 and collective supervisory processes, measures of success, ease of changing, risk of not adapting, and perception of the personal and collective potential of change. As such, it is at the forefront of global efforts to improve supportive supervision and scale up methods, which often focus on addressing single or a limited number of obstacles to behavior change. Based on learnings from behavioral science and corporate change management practices, the solution’s 360 approach is required to enable the evolution of supervisory cultures in South Asia and globally.

The ultimate impact goal of Sahyog is to improve families’ maternal, newborn and child healthcare and nutrition outcomes (e.g., maternal mortality and morbidity, stunting, anemia) in key states of India, in Bangladesh and globally by bringing about improvement in the coverage and quality of community-based PHC services through enhancement in CHW supervisory practices.  Our key impact areas and pathways to achieve outcomes in this area includes:

Over the next year and the next five years, major process steps on the pathway towards impact goals are expected to be achieved by scaling up the Sahyog solution across three states in India (Gujarat, UP and Bihar) and advocating for full adoption and scaleup of the solution in other states, Bangladesh and globally.

In Gujarat, the solution has been endorsed by the government and is being piloted across three districts to enhance the supervision of AWWs and ASHAs. The government is considering scaling up the intervention across the state in the coming financial year. A scaleup strategy is currently being worked out. Over the coming year, FHI 360 will complete its pilot and associated implementation research and provide technical assistance to the government to organize a quality rollout across the state over 2023-24.

In UP, piloting of the solution to supervise AWWs was completed in two districts, a scaleup plan agreed upon with the government, and a three-way Memorandum of Understanding (MoU) signed with the government and its main implementation partner to roll out the solution over 2022-23.  In parallel, FHI 360 will continue to advocate for the adoption of the solution to supervise ASHA, through deployment of its functionalities within the new information system being deployed by the government.

In Bihar, the government expressed initial interest in deploying the solution’s functionalities to improve the supervision of AWWs and ASHAs. The technical content of the solution (e.g., checklists) was adapted to suit the needs of AWW management in the state. Discussions are ongoing on the best approach to adapt and deploy the technology components of the solution within the state’s evolving technology stack.

Upon review of the solution, the Indian Ministry of Health and Family Welfare expressed interest in supporting the rollout of the solution across five states (Odisha, Jharkhand, Assam, Chhattisgarh and Bihar). FHI 360 will continue to advocate for formal endorsement of the solution to help with cross-state replication.

In Bangladesh, the core elements of the solution’s Supportive Supervision and Strategic Use of Data were piloted in four sub-districts with a focus on improving the coverage and quality of nutrition interventions. Key components of the solution were then integrated into the national Comprehensive Competency Training on Nutrition and the checklists of health supervisors. The solution was then mainstreamed to cover the full set of community-based MNCH and family planning services in addition to nutrition and reviewed by the various involved government departments. The piloting of this mainstreamed supervision package, excluding technology enablement, is expected to start late 2023 and to inform decision to scale up. Discussions are ongoing on next steps to develop the supporting app.

At the global level, discussions are ongoing regarding funding of adjustments of the solution and its technology backbone to automate many of the steps required for its adaptation to country requirements, translation in new languages and advocacy for replication and scale up.  

Progress towards impact goals will be measured through 1) implementation research, 2) monitoring of solution rollout and usage, and 3) review of national health surveys.

1- Implementation research

Implementation research will demonstrate the feasibility of integration of the solution with the government community-based PHC system and the association between solution implementation, improved supervisory practices, improved coverage and quality of key MNCH and nutrition interventions and improved maternal, infant and young child nutrition behaviors. In Gujarat, results from a clustered randomized study across three districts covering those indicators will be available by mid-2023. In Bangladesh, a mixed-method evaluation of the solution covering supervision processes and intervention coverage and quality is expected to be conducted over 2023-24.  

2- Monitoring

Monitoring of solution scale up and analysis of Sahyog app data will be used to measure the extent of solution adoption and usage, and the impact of the solution on supervisory practices and reported service coverage and quality. Advocacy and scale up process information will be collected across geographies by the team. App data is expected to be available for analysis in Gujarat and UP.

3- Review of national health survey data

The team does not expect to be able to demonstrate contribution of the solution to ultimate impact goals (e.g., stunting) as the pathway from supervision to service effectiveness and beneficiary level outcomes is long and complex. However, the team will continue to track the evolution of service coverage and outcome indicators in Demographic and Health Surveys (DHS) to see if associations can be observed.   

Our theory of change (TOC) assumes that improvements in MNCH and nutrition outcomes can be achieved as a result of higher coverage and quality of community-based PHC services resulting from improved Supportive Supervision of CHWs by their supervisors and more Strategic Use of Data for problem solving during monthly review meetings, enabled by new processes, training, technology, change management and monitoring. Our ToC is anchored in extended reviews of the literature, formative research and implementation research suggesting associations between service coverage/quality and MNCH and nutrition outcomes, and associations between training, Supportive Supervision and communication and service coverage and quality (see Problem section).

A brief overview of our TOC is presented below. It lists interventions inputs, desired outputs, as well expected outcomes and impact:

A. Inputs

As described above, the Sahyog solution includes the following inputs:

• New processes for Supportive Supervision and Strategic Use of Data
• Trainings of supervisors on those processes, associated skills and technical content
• Provision to supervisors of an easy-to-use app to facilitate new processes
• Provision of a package of change management interventions in the form of communication, peer-to-peer interactions and non-financial incentives
• Monitoring of service quality, Supportive Supervision and Strategic Use of Data
• Advocacy and technical assistance to the state and district governments (and their implementation partners when relevant) to plan and manage the rollout of the intervention, accompanied when possible of light technical support subdistrict cadres to maximize the quality of the rollout

B. Immediate outputs

The following immediate outputs are expected from the inputs:

• Standard processes for Supportive Supervision and Strategic Use of Data are rolled out 
• Supervisors get trained and receive technical support on Supportive Supervision and Strategic Use of Data
• Technical and skill training for supervisors are rolled out
• Supportive Supervision field visits are mandated and monitored
• Local decision making to solve issues identified by CHWs is mandated and monitored
• Communication support is rolled out
• Non-financial incentives are rolled out

B. Intermediary outcomes:

 We expect the following outcomes to be facilitated by the interventions and their immediate outputs:

• Improved knowledge and skills of CHWs and their supervisors 
• Supervisors go to the field to coach and help CHWs to resolve issues with PHC and nutrition services
• Review meetings focus more on data informed action and capacity building happens regularly
• Data quality improves with a focus on correct and complete data
• Problem solving is more decentralized, leading to faster problem solving
• CHWs and supervisors take pride in their work with increased motivation levels

C. Impact:

• Improvements in the coverage and quality of primary healthcare services in terms of maternal and child health and nutrition lead to better health and nutrition outcomes
  • Reduction in stunting (height for age) and underweight (weight for age) in children under 2 years of age is expected through Improved essential newborn care practices, breastfeeding practices, complementary feeding practices and regular growth monitoring
  • Reduction in maternal mortality and morbidity is expected through counselling on family planning services available and maternal health and nutrition counselling
  • Reduction in anemia in pregnant women, children under 2 years of age and adolescent girls is expected through Iron and Folic Acid supplementation coverage and compliance
• Often female CHW and lower-level supervisors feel empowered and their empowerment is emulated by village women who takes them as role models

The core technology that powers the solution is a mobile app for supervisors (A). It was designed to be cost effective to adapt and scale up across geographies and systems (B). However, recognizing that governments increasingly want to decide their technology stacks, FHI 360 also provides technical assistance for inclusion of the solution within governments’ existing information systems (C).

A- Overview of the Sahyog support app

The solution’s supportive supervision and strategic use of data processes are supported by a simple Android-based mobile app for CHW supervisors and their own managers that can be operated both in an online and offline mode. At a macro level, the app enables supervisors to capture data on the quality of community-based PHC services, to conduct structured 1:1 interactions with their supervisees in the field, to access and triangulate data from service observations and government MIS, and to facilitate monthly review meetings focused on problem solving. It involves six components or tabs: an assigned worker dashboard (1), a monthly planner (2), service and supervision observation checklists (3), workflows to support debrief sessions and action planning with supervisees (4), anonymous feedback submission by supervisees (5) and workflows and dashboards to support effective facilitation of monthly review meetings (6).

• Assigned Workers: This tab gives access to a list of all the supervisees assigned to each supervisory cadre for health and nutrition programs. Supervisors can see information for each CHW under them and review their performance to inform prioritization of CHWs for support and capacity building.
• Monthly Planner: The Monthly Planner allows supervisors to select a particular CHW under their purview, and plan joint field visits along with the CHWs to assess service quality and provide them with on-the-job coaching and support to improve their performance. Supervisors can also use this feature to plan specific dates for conducting review meetings and comes with provisions to send reminders and notifications. 
• Checklists: The App contains Checklists to support supervisors’ observation of the quality-of-service delivery by CHW (or of supportive supervision by CHW supervisors) and capture beneficiary feedback on service quality. Checklists are structured as a series of multiple-choice questions.
• Debrief Sessions: The app has an in-built mechanism to aid supervisors to conduct Debrief Sessions with supervisees on service or supportive supervision activities. Once all observations are recorded, the app prompts users to discuss the activities with their supervisees based on a pre-defined set of instructions. The app summarizes observations of service delivery (or supportive supervision activities) recorded in the checklists in positive feedback to be given to supervisees and issues to jointly address. It then allows supervisors to mark an issue as resolved or to be escalated based on the actions taken
• Anonymous Feedback: Once visits are over, supervisees can give feedback on the session with their supervisors anonymously through web-link automatically sent to them by SMS.
• Review Meeting Workflow and Dashboard: The app includes a Review Meeting Workflow and Dashboard for each level of CHWs. It is meant to guide supervisors while conducting monthly review meetings with groups of supervisees. Features include: prompts for pre-meeting actions, data visualization, simple triangulation of service quality data from the checklists and other government MIS data, steps to conduct the meeting and record proceedings, issues to be discussed during the meeting based on data quality issues selected when reviewing data triangulation, MIS and service quality data, and prompts for post-meeting follow-ups on action points.
• Job Aids: The app is equipped with Job Aids. These Job Aids contain summary points to help supervisory cadres perform necessary actions for supportive supervision and capsule technical information on primary healthcare and nutrition services to be shared during Debrief Sessions and Review Meetings.

B- Sahyog support app underlying technology

The Sahyog mobile app uses an advanced technology stack that has been chosen based on the parameters of ease of use, ease of adaptation, cost-effectiveness and scalability by governments. Key underlying technologies are as follows:

• User interface (UI) – The app uses Flutter for UI because it is one of the most effective cross-platform frameworks. Flutter is Google's portable UI toolkit for crafting user-friendly natively compiled applications for mobile, web, and desktop from a single codebase. Flutter works with existing code, used by developers and organizations around the world, and is free and open source, and therefore well suited for technology-based solutions for primary health care and nutrition services in developing countries.
• Backend – The code for backend is written in Node.js, an open-source, cross-platform model. Node.js is apt for building fast, scalable network applications, offers benefits in performance and development speed. Today's requirements for processing and consuming real-time information are paramount, and Node.js is exceptionally fast for multi-user real-time data situations.
• Database: The database uses is MongoDB, an open-source NoSQL document-oriented database available across-platforms.
• Server: Initially, all app content was hosted on Amazon Web Service/Cloud servers, a solution that is secure, easy to use, flexible, cost-effective, reliable, scalable and high-performance. As governments move from pilot to scaleup, app content is being shifted to government servers.
• Dashboard & administrative panel were written in the open-source technologies Angular, CSS, and HTML. Angular is a Google-released JavaScript open-source front-end framework mainly used to develop single-page web applications (SPAs) and dynamic web applications. 

 C- Sahyog technology scaleup strategy

While the Sahyog app was designed to enable easy adoption and scaling by governments, FHI 360 also supports governments to incorporate Sahyog’s functionalities within their own technology stack. Experience across geographies and government departments suggests that the best technology can be a barrier to adoption. National and state governments increasingly make long term digital strategies, which involve selecting specific sets of technologies, and IT partners and staff equipped to govern, maintain and upgrade them. Governments therefore increasingly require digital innovation to be developed within their own technology stack, and not only integrated with it. As a result, in addition to providing governments with the technology to enable its Supportive Supervision & Strategic Use of Data solution like in Gujarat or UP (for AWW supervisors) in India, FHI 360 also supports replication of the Sahyog app functionalities within governments’ technology stacks as planned in Bihar, India for AWW or Bangladesh.

Solution primary health care data is being collected by frontline supervisors and their managers as they observe delivery of MNCH and maternal, infant and young child nutrition services and conduct monthly meetings to discuss program performance and required supportive actions.

The solution incorporates diversity, equity and inclusivity  in three ways: 1) by consulting with prospective solution beneficiaries and users as we develop and refine the solution, 2) by empowering often female CHWs within the PHC system, 3) by collecting feedback on supervision and services from CHW and beneficiaries, 4) and by taking steps to improve the quality of services delivered to key vulnerable groups. More broadly, FHI 360 is an equal opportunity organization.

1. Consulting with beneficiaries and users: The Sahyog solution was developed and is being refined using Human-Centric Desgin approaches that put the beneficiaries and users at the center of the design process. In addition to formal research and landscaping studies, beneficiaires and users are consulted at all steps of the problem definition, solution design and refinement approach in formal and informal meetings. For example, qualitative consultations with beneficiaries and users to explore the root causes of issues and probable solutions are core to our quarterly monitoring process.

2. Empowering female CHW: The core intervention of the Sayhog solution is to strengthen Supportive Supervision of often female CHW by their first line supervisors and second line managers. A critical part of Supportive Supervision is to enable female supervisees to freely report, discuss and have escalated the challenges that prevent them from effectively delivering services to female beneficiaries. The solution monitors the progress in those female supervisees in actually raising their challenges and having those challenges acted upon within the system. It is expected that progress in female CHW and supervisors being heard by the system may have impact on the self perception of women in the community, as female frontline workers are very numerous, present across villages, and often looked up to by other women in the community.

3. Collecting CHW and beneficiary feedback: The solution recognizes that CHW and beneficiary feedbacks are critical to improve adoption of new processes, ensure that CHWs get the support they need and improve service quality. As part of the Change Management of the package, stories from the field are systematically collected and communicated across the system to drive a sense of inclusion and ownership of the solution. Upon completion of Supportive Supervision visits, CHWs are provided with the opportunity to rate their experience through rapid SMS surveys. During the home visits they participate into, supervisors are prompted to have 1:1 conversations with beneficiaries and to collect resulting feedback on quality and respectful care in the app.

4. Improving quality for key vulnerable groups: The solution specifically identifies underweight children and high risk pregnant women, collects supplementary information on the quality of services delivered to those vulnerable groups and fosters discussions on how to improve it.

5. Operating as an equal opportunity organization: FHI 360 has clear criteria on diversity, equity and inclusion (DEI) for the organization as well as program teams. Our hiring process for the program team takes diversity as one of the key criteria. We are an equal opportunity employer. Diversity in backgrounds, identity, ideas and opinions are respected. Our program participants are given an equal voice in implementing solutions and their stories are given voice at every possible platform. We ensure that solutions incorporate voices from the beneficiary communities at the grassroots and involve stakeholders that are an integral part of these communities. 

FHI 360 typically operates with grant or contract funding from governments or private donors. In our support of the Sahyog solution, we typically operate in two ways: by provide technology solution and services directly to the government, and by supporting other development partners to integrate the Sahyog solution or components of it in the support they in turn provide to the government.

The scaleup and sustainability of the solution is to be achieved through adoption, hosting, management, maintenance and financing of the solution by the government. FHI 360 supports the research and development of the solution, advocates for its adoption and supports its piloting, implementation preparation and transition to the government and initial inclusion into government’s budgets. In specific geographies, FHI 360 may help other development partners ramp up their capabilities to provide scaleup and implementation support to the government. Once those objectives achieved, day-to-day involvement of FHI 360 is typically discontinued and the government takes over.

Sustainability of the solution will be achieved by transitioning its rollout, hosting, management, maintenance and financing to the government. Each of those steps need to be achieved to ensure sustainability. Implementation in the states of Gujarat and UP, in India, illustrate how the first three-four steps were achieved.

Gujarat, India: The plan to roll out the solution across the state is being defined jointly with the government. It involves execution of training and initial rollout activities by government cadres supported, based on government request, by the Non-Governmental Organizations (NGOs) present in part of the state. The solution is being owned and hosted on a government server. Plans to include maintenance of the app into government’s budget are being developed.

Uttar Pradesh (UP), India: A plan to scale up the solution across the 75 districts of UP was developed in collaboration with the government and the UP Technical Support Unit (TSU). It involves rollout of the solution by government cadres, supported by the UP TSU and other large NGOs operating in the state. FHI 360’s role is to provide state-level technical assistance for planning, monitoring and data analysis. Based on government request, hosting of the solution moved from FHI 360 to the UP TSU server as a transitory measure before transition to the government.