Symptor

In most sub-Saharan countries' healthcare system, the individual patient and the aggregate patient’s recovery (in terms of responsiveness to medical treatment) data are unavailable or are lost to lack of its progressive documentation, monitoring and tracking. While this is more prevalent in primary healthcare centers (PHCs) due to inconsistent follow-up routines, facilities and consulting medical specialists, patients are observed to not prioritize follow-up care appointments which would have been the means of getting a closure on the health recovery status of patient. In the more than 30,000 PHCs in Nigeria for example, patient’s post-treatment recovery data is not explicitly documented. At scale, the almost non-existent record and the tracking of post-treatment recovery pattern and the metrics for healthcare responsiveness measures in healthcare service delivery process leaves healthcare outcomes and records with an unmonitored, untracked and an unaccountable system.

More specifically, the treatment of patients excludes them from assessment of healthcare experience report with the recovery data from patient perspective left undocumented in a systematic, progressive and cumulative structure for informed decision making on the effectiveness of treatment and associated healthcare services. These unavailable pre-requisite data has left the tracking of the patient’s responsiveness to healthcare treatment, assessment of correctness of diagnosis and the appropriateness/validity of medication to diagnosis unattended. Consequently, the monitoring and tracking of patient healthcare ends after diagnosis/medications without a means of confirming patient recovery, the recovery pattern, and the consequent validation of correctness of medications for a said diagnosis.

The Symptor (a Data Aid project) is a patient-centred mobile-based solution for progressive & systematic reporting of patient recovery for and beyond primary healthcare services. Symptor allows patients, caregivers, and caseworkers/health workers (on behalf of patient) to:

• Track post-treatment responsiveness in healthcare treatment from identified/common disease symptoms
• Define and track patient-defined symptoms that patients are exhibiting during & beyond the treatment period
  • Provide an AI-based prognosis to aid health worker decision & performance during the treatment period

Symptor further follows up with the patient medical condition and symptoms beyond the treatment period. For example, a patient diagnosed with and is treating Malaria, the patient/caregiver/health worker reports patient’s intuitive perception of the symptoms (say, headache, fatigue, vomiting, shivering, fever, cold, etc) on a predefined severity scale, say 0-5, 0 representing completely faded symptom and 5, strongly manifesting symptoms.

For proof of concept, Symptor will engage trained caseworkers to follow-up patients during the treatment period to track their recovery process. At scale, patients and caregivers can report the recovery data independent of health workers’ input. Together with frontline health/case workers and caregiver representatives, an all-inclusive process work flow is factored in the design of a seamless solution. This approach is broadened to extend Symptor use-cases across to a wide application domain based on disease symptoms and flexibility in collecting recovery/responsiveness data as a performance indicator for healthcare services delivered.

While existing eHealth systems like the DHIS2 provides aggregate treatment health records, it lacks patient level records and does not provide a record of recovery validation. Symptor complements with a post-treatment follow-up health record based on patient reported outcomes. Symptor’s solution is novel in that it engages patient views about outcome of health care provided as (1) an additional data source in triangulating healthcare data and (2) a complementary extension of indicators of healthcare performance measures beyond the orthodox facility records of administered medications and treatments served but also extended to patient progressive responsiveness to healthcare delivery.

From cumulative reported data, an AI-based prognosis dashboard for healthcare administrators/workers to display analytics for optimal level of improvement of predefined symptoms and the amount of time, requirement and predictions of levels of improvement needed to reach optimal recovery level in the least. This prognosis analytics will support healthcare workers with informed decision in improving patient care in their respective wards by learning from reported data and comparing current outcomes to services that were previously reported. The prognosis intelligence driven from reported outcomes can support healthcare administrators in assessing the performance of healthcare provider/caregiver and strengthen healthcare service delivery in narrowing the information gap between healthcare beneficiaries, providers and administrators/policy makers with increased healthcare indicators for validating & triangulating data from multiple sources.

Hence, PHC data will be collected by frontline workers, caseworkers or patients at ward-rounds or medication rounds using the Symptor application software online and offline. 

Adamawa State is one of 3 North-east Nigerian states that is affected by insurgency for over 10years. Its estimated population is about 4,864,404 with 924 established public primary health facilities spread across the 21 local government areas. 7 of the 21 LGAs are in the insurgency territory. The effect of insurgency in the region has crippled the full-fledge operations of PHCs in many of the agrarian communities resorting to use of mobile health post and/or temporary health facility that allocates rationed or routine medical visits to communities having little provisions and facilities for on-demand follow-up. In addition, the presence of resident medical specialists has been inconsistent in meeting the healthcare needs of the communities especially for follow-up care.

Considering the accessibility challenge in the communities, Symptor is primarily designed to complement and serve frontline health workers’ inadequacies and healthcare administrators in this region with ease of use by patients and caregivers as well. Since these PHCs primarily rely on frontline health workers with few or no resident consulting specialists in a given medical line. Patients and primary healthcare workers are underserved full-fledge consultancy support on their limited expertise. Consequently, Symptor will play a significant role in closing the specialist’s consultancy gap in the tracking of dispensed healthcare services as a representative follow up data. The knowledge base and derived intelligence will support workers with technical analysis that can improve patient treatment and consequently, their health outcome. This is achievable as the solution assists the PHC worker in providing tentative diagnosis from symptoms presented by the patient in the PHC. Once the diagnosis shows that the patient requires advanced treatment like surgical interventions beyond the PHC capacity, Symptor uses its referral network to the nearest Specialist hospitals, teaching hospitals and other higher health facilities for further treatment.  The patients’ additional post-treatment medical history is transferred where expert-based consultations and review can be made for full intervention.

The Data Aid project team comprises of experienced health informatician, health workers, administrators and a software engineer drawn from multi-sector organizations (Adamawa State Primary Healthcare Development Agency, Data Aid) that can influence and build necessary collaborations and engagements. The Symptor development team is located in Yola, at the target implementing community.

The aggregate experiences of the team members across healthcare projects has been rooted in a long community-level engagement with the benefiaries of the said solution and the understanding of patient need, healthworker’s support needs and technology needs in building usable partnerships.

Having worked in understanding health data requirements at different levels, the team has worked with caseworkers, frontline health workers and primary healthcare centres in the region to understand and integrate a suitable workflow into Symptor. In addition, we are engaging digital transformation principles in co-designing of Symptor with all stakeholders taking peculiarities of technological exposure of potential users, usability and familiarity of process flow with Symptor workflow.

The idea behind Symptor is great considering the anticipated impact it hopes to bring. Consequently, the team would like the best version of this solution which the WFP Incubator Accelerator program will enhance. The team considers the Challenge as a shaping ground for enhancing the potentials of our solutions to build visibility, partnership and scalability.

While it takes resources to advance and implement solutions our solution on a broad range of use cases and scales, it is our first step in mobilizing the right resource & partnerships for implementation.

While other primary healthcare measures track aggregate and likely asymptomatic test-based data, Symptor complements the existing aggregate data like DHIS2 and the patient-level test-based diagnostic record like in LAMIS with patient-centred progressive feedback within the treatment period. The former are solely frontline-worker-based while the latter provides for patient-feedback.

Symptor engages patient reported outcome measures as a measure in ascertaining recovery and indicative measure of efficiency of healthcare service delivery. The use of Symptor will strengthen healthcare efficiency especially where follow-up care is not prioritized.

This approach improves on data triangulation approaches with a symptomatic feedback and feedforward mechanism with the potential to impact symptom-based measures in tracking patient recovery, measures of medication appropriateness, healthcare delivery efficiency and drug variation responses in case treatment.

Symptor seeks to initiate a data-driven tracking of patient care in LMIC and the monitoring of healthcare service delivery through progressive stakeholder engagement uniquely in a patient-centred manner.

In the next year, Symptor will provide a progressive patient (caregiver) treatment response reporting technology in Nigeria that documents healthcare recovery (or otherwise) data for a specific medical condition (say Malaria). This data will provide in the least, metrics for improved healthcare through measures of-

• Specific drug-use effectiveness per diagnosis
• Specific drug-use effectiveness per demography
• Diagnosis response rate
• Identifying treatment outliers based on diagnosis and medications in their treatment progressions

In the next five years, Symptor will integrate AI in providing a prognosis dashboard as it scales its operation to other countries and several other symptomatic medical conditions. This feature will:

• Serve as a healthcare aid for healthcare workers in rural PHCs.
• Incorporate external support from expert consultants.

Therefore, Symptor will bring positive improvement in breaking the barriers of hard-to-reach PHCs that have experienced halted progress in universal health coverage and decreasing deaths from tropical ailments like Malaria and minimize disruptions in essential health services.

Some measurable indicators of progress for Symptor are:

• Number of follow-up interventions through Symptor
• Symptoms before/during treatment
• Number of treatments
• Number of resolved/cured cases
• Drugs dispensed per diagnosis
• Time taken to recover 

Wherever diagnosis & treatments are offered, whether hospitals, medicine store or just at home, there is need to track the effectiveness of the treatment by the patient/caregiver, health workers and administrators on the basis of patient symptoms.

Symptor will take steps in raising advocacy to adhere to follow-up appointments for enrolled patients, train users of symptoms reporting method and report symptoms-based treatment outcomes.

Symptor measures intermediate impact through access flexible follow-up tools, drug used/recovery, diagnosis correctness, recovery rate/diagnosis and recovery rate/medication. This impact will result to improved follow up response, track and support for inpatient and outpatient recovery during treatment period, support for health workers in monitoring the patient recovery process and improved measurable health outcomes.

Symptor will be using an app and SMS technology for reporting and a AI to drive the prognosis dashboard in the Symptor app.

Patient/caregiver

Caseworker

Health worker

Like with the principle of Data Aid, Our solution will insist on diversity, equity and  inclusion across social & cultural identities.

The business model for Symptor is the low-income client model. With this model, Symptor services will be sold directly to clinics or a any form of healthcare centre but focused also on providing access to those who cannot afford it. Symptor will provide the clients with a feedback and performance tracking metrics for assessing the effectiveness of healthcare service delivery. They will need Symptor’s new method in measuring efficiency of their services and increase patronage because of improvement in follow-up response.

To maintain financial sustainability, the business model for Symptor is the low-income client model. With this model, Symptor services will be sold directly to clinics or any form of healthcare centre but focused also on providing access to those who cannot afford it. Grants is an additional source of financial sustainability in assessing healthcare performance and improving response to follow-up.

Through our web-based EdTech solutions which over 5 schools have subscribed to, the system has sustained itself through an affordable termly subscription fee by the school based on the number of enrolled students on the system. The cost has been incorporated into the schools fees seemlessly.