Scaling Phone-Based PROM Collection Across Low-Resource Settings: Learnings From MomCare,a Digital Pregnancy Care Bundle

Abstract

Scalable approaches for collecting patient-reported outcome and experience measures (PROMs/PREMs) are essential to operationalize value-based healthcare (VBHC). This paper presents implementation insights from MomCare, a digital pregnancy care bundle in Kenya and Tanzania that scaled phone-based PROM/PREM collection to over 7000 women. It describes implications of its implementation approach on patient reach, data quality, and cost. It highlights how design choices, such as standardization, contextualization, and automation, contribute to enhancing feasibility and generating value. Transitioning from SMS surveys to computer-assisted telephone interviewing enabled increased patient reach and improved data quality, while costs lowered with scale. These findings indicate that phone-based PROM/PREM collection is scalable in resource-constrained health systems. Lessons from MomCare offer actionable insights for embedding patient voices into quality improvement and VBHC models, providing practical recommendations for strengthening patient-centered care in low- and middle-income countries.

Keywords

patient-reported outcome measures patient-reported experience measures quality improvement survey data value-based care/purchasing patient engagement

Introduction

Understanding patient needs is fundamental to the design of effective health interventions, particularly for vulnerable populations that face disproportionate health risks.¹ Across healthcare, data-based quality improvement efforts still prioritize the use of provider-reported data, often burdening an already strained healthcare workforce.² In maternal and child health, where care utilization remains fragmented across multiple providers, capturing comprehensive data across the full care journey presents significant challenges—yet remains critical for evaluating and improving care.^3,4

Patient-reported outcome measures (PROMs) and patient-reported experience measures (PREMs) make these needs measurable by capturing not only clinical outcomes, but also women's expectations, preferences, and experiences of care.⁵ Embedding these measures into maternal health programs enables a patient-centered approach to care quality. In value-based healthcare (VBHC), value is defined as health outcomes achieved per dollar spent.⁶ The objective of VBHC programs is to deliver value to patients, as generated by outcomes and experiences across the care continuum, offset by its costs. Therefore, as VBHC frameworks gain traction, PROM/PREM implementation models are needed that do not only demonstrate how this patient-reported data can be collected across different contexts, but also consider its costs.

PROM/PREM Collection in MomCare

In MomCare, a digital, value-based care program implemented across Kenya and Tanzania, patient-reported outcome collection was introduced to steer patient-centric improvements across the pregnancy care continuum.^7,8 PROMs/PREMs were selected from the International Consortium of Health Outcomes Measurement (ICHOM) Pregnancy and Childbirth Standard Set, reviewed by stakeholders and iterated across implementation cohorts.⁹ PROMs included pregnancy and neonatal complications, maternal mental health, and newborn outcomes, while PREMs captured satisfaction with care, adequacy of information, support received, and confidence in services. These measures were chosen not only to make patient-reported outcomes visible, but to ensure patient-centric design of linked care quality improvement efforts. Across MomCare, patient-reported measures informed facility quality-improvement plans, shaped performance-based financing schemes, and guided adherence reward structures, demonstrating how patient voices were systematically embedded into program decision-making.¹⁰

MomCare evaluated a phone-based PROM/PREM implementation approach in 2017, by testing the feasibility of using short message service (SMS)-based technology to collect selected measures in a pilot. The pilot demonstrated that low-cost mobile technologies could capture PROMs/PREMs in hard-to-reach populations, highlighting the potential to operationalize phone-based PROM/PREM collection as part of VBHC implementation in low-resource settings.⁸

This early survey designs emphasized open-ended formats to allow patients to freely express their experiences. However, as the program scaled, this approach introduced analytical complexity due to multilingual, ambiguous, or incomplete responses. With MomCare continuing to enroll thousands of pregnant women a year, these limitations necessitated a shift to a more standardized yet substantive mode of data collection: computer-assisted telephone interviewing (CATI). CATI systems combine automation (scheduling, call tracking, reminders) with interviewer-administered surveys, thereby enhancing engagement, standardization, and data quality. This new PROM/PREM implementation approach has currently reached over 7000 pregnant women across Kenya and Tanzania. Over its implementation period, the program refined its phone-based survey approach to improve both the accuracy of outcome measurement and the efficiency of implementation, achieving progressively lower per-patient costs.

This paper summarizes key lessons from MomCare's phone-based PROM/PREM implementation process, offering insights into how design choices, such as standardization, contextualization, and automation, can strengthen feasibility, data quality, and value generation in resource-constrained environments.

Actionable Insights

Phone-Based Surveys Enable High Reach

While PROM/PREM implementation via SMS frequently yielded no or one-time responses to surveys, transitioning to phone-based surveys using CATI substantially improved participant engagement, achieving reach rates between 61% and 85%. This success was dependent on several factors, including increased mobile phone ownership and availability of contact information at registration (rising from 79% in Version 1 to 95% in Version 3.1 of MomCare; see Supplemental Materials).

Moreover, sustained engagement required multiple outreach attempts: an average of 4.1 to 6.7 calls were placed per participant per survey round. CATI systems supported automated dialing and follow-up scheduling, enabling up to 10 call attempts per respondent. Calling patients within 20 weeks post-delivery enhanced response rates compared to < 26 weeks (85% and 80%, respectively), and utilizing trusted data collection partners further contributed to improved participation.

While consent was already obtained for broader program participation, it was reconfirmed verbally at the start of each phone interview. Participants were given an explicit opportunity to opt out of sensitive topics (eg, questions on child loss). To protect data confidentiality, results were anonymized using tokenization and scrambled birth dates.

Conversational Data Collection Increases Quality of Patient Input

The shift to voice-based, interviewer-administered surveys enabled richer and more nuanced patient input. Compared to SMS responses, conversational interviews allowed for clarification of questions, immediate probing, and empathetic engagement: Noted especially critical in the MomCare implementation context marked by variable literacy and language diversity. These dynamics enhanced both the relevance and interpretability of responses.

Refusal rates declined markedly (to ∼1%) in later program versions, attributed to improved communication strategies and use of Community Health Promoters (CHPs) as interviewers. CHPs’ familiarity with maternal health and local customs helped to build rapport and elicit more candid feedback. In cases of adverse events, CHPs offered condolences and referred women for follow-up care, creating service feedback loops that extended beyond data collection.

Cost-Effectiveness of Phone-Based Surveys Increases With Scale

Across implementation rounds, the average cost per completed interview ranged from $3.05 to $4.14 (see Supplemental Materials), assuming response rates of ≥65%. Direct data collection costs, including interviewer compensation, mobile airtime, and translation services, accounted for 60% to 84% of total expenditures. Setup costs such as training, scripting, and software licensing varied by cohort (6%-30%).

Targeted cost-reduction strategies were implemented over time. These included shifting from annual to daily software licenses, batching contacts to optimize field team utilization, and limiting costly customizations to survey tools. Programmatic efficiency was further enhanced by longer implementation cycles and cross-program infrastructure sharing. Most importantly, as respondent volume increased (>2000 participants), marginal costs dropped below $2.00 per interview, demonstrating the scalability of this approach.

Role of Automation in Efficiencies

Automated CATI systems can reduce labor costs and increase response rates through automated scheduling, reminders, and call tracking. However, infrastructure, local workforce capacity, and national data protection regulations all influence the feasibility and design of automated systems. In MomCare, interviewers clinical backgrounds allowed immediate interpretation of patient-reported outcomes and appropriate follow-up. This human-mediated approach increased costs but was deemed essential for data validity and care linkage.

Design Standardization Contributes to Scalability

Early survey versions emphasized open-ended formats, while later iterations adopted more structured question formats such as Likert scales, multiple-choice questions, and targeted prompts, enabling more efficient data processing and analysis. Despite these implementation changes, the surveys core thematic domains remained consistent (components further outlined in the Supplemental Materials). This consistency enabled longitudinal tracking and aggregation across program sites. Future PROM tools should embed validation checks and follow structured formats to ensure data completeness and comparability. Advances in natural language processing and artificial intelligence may eventually enhance the analysis of open responses but remain secondary to structured question design in resource-limited contexts.

Practical Recommendations

Drawing on MomCare's operational insights, Table 1 summarizes practical strategies for phone-based PROM/PREM collection in low-resource settings. Recommendations are structured around common barriers to PROM/PREM implementation, spanning patient burden, literacy and cultural adaptation, provider engagement, cost, scalability, data quality, and system-level governance.¹¹

Table 1.

Practical Recommendations to Address PROM/PREM Implementation Barriers Identified by Bull et al (2022), with MomCare Implementation Examples.

Barriers	Recommendation	Implementation examples in MomCare
Low literacy, language, and cultural appropriateness	1) Adapt and co-design with community stakeholders	Train and deploy established, trusted parties as interviewers Co-design survey tools with local partners Clearly communicate data collection intent to participants Adapt language and structure based on user feedback
Burden of participation	2) Standardize and minimize tools	Define a core set of outcome/experience indicators Use structured formats (such as rating scales)
Integration into workflows and provider engagement	3) Use non-clinical workflows and tools available for automation	Outsource PROM/PREM collection Use automation to time calls close to care events and tracking to identify optimal contact windows for SMS or call reminders
Cost, staffing, and resource burden	4) Minimize variable costs for increased cost-effectiveness	Optimize time and number of call attempts per respondent (4-6 as observed) Shift from one-off projects to routine data collection for optimal use of workforce Re-use platforms and training tools across projects
Scalability and sustainability	5) Invest in scalable infrastructure where possible	Implement cloud-based CATI platforms Use virtual phone numbers and automated dialing Centralize quality control through supervisors
Data quality and validity	6) Embed data validation methods	Use built-in input constraints Train interviewers for real-time data quality checks Explore AI-assisted screening
System-level policy, governance, and use	7) Link data to service improvement	Enable PROMs/PREMs use in quality improvement plans, payment schemes and incentives

As Table 1 illustrates, MomCare's design systematically addressed many of the barriers identified in the literature. For example, using CHPs as interviewers overcame literacy and trust barriers, while automation and structured indicators reduced provider workload and data processing burdens. At the service level, cost efficiencies were achieved through reuse of platforms and workforce optimization, while cloud-based CATI infrastructure enabled scalability. Importantly, PROM/PREM results were embedded into performance-based financing and quality-improvement cycles, ensuring that patient voices shaped service delivery. Remaining system-level challenges include institutionalizing PROM/PREM within national health information systems, standardizing validation protocols, and creating sustainable budget lines for outcome collection.

Conclusion

Implementing patient-reported outcome collection in low-resource settings requires a strategic blend of mobile technology, local engagement, and iterative learning. The experiences from MomCare's scaling efforts, from a small-scale SMS pilot with 204 women to over 7000 phone-based surveys across Kenya and Tanzania, highlight both the opportunities and challenges of leveraging mobile technologies for PROM/PREM collection in maternal healthcare.

Insights from MomCare indicate that barriers commonly identified in the literature, such as cultural fit, provider workload, cost and data quality, can be addressed through a combination of contextual adaptation and automation. It underlines that while phone-based technologies offer a powerful tool for expanding patient engagement, their effectiveness hinges on continuous iteration, stakeholder collaboration, while also integrating standardization in design. While improvements in cost efficiency are noted across MomCare's implementations, rigorous cost-effectiveness evaluations remain a critical area for future research. Ultimately, these lessons from MomCare provide practical considerations to further integrate PROM/PREM in low-resource healthcare systems, thereby embedding patient voices in the design of effective health interventions.

Supplemental Material

sj-docx-1-jpx-10.1177_23743735251415087 - Supplemental material for Scaling Phone-Based PROM Collection Across Low-Resource Settings: Learnings From MomCare, a Digital Pregnancy Care Bundle

Supplemental material, sj-docx-1-jpx-10.1177_23743735251415087 for Scaling Phone-Based PROM Collection Across Low-Resource Settings: Learnings From MomCare, a Digital Pregnancy Care Bundle by Femke Heddema, Elizabeth Opondo, Nkirote Kalaine, Joel Lehmann, Julie Fleischer and Spencer Connell in Journal of Patient Experience

Footnotes

Acknowledgments

We want to thank all those involved across the MomCare program for their engagement and invaluable feedback across its implementation.

Author Contributions

FH led the conceptualization, writing, methodology, data curation, and formal analysis. EO contributed to the conceptualization, writing, data curation, and formal analysis. NK contributed to the conceptualization. JL, JF, and SC contributed to the review and editing.

Data Availability

The data supporting this manuscript is provided in the Supplemental materials. Further operational data can be shared upon request.

Declaration of Conflicting Interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval and Informed Consent

Ethical approval was not required for this manuscript as the study does not report on human participants.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: PharmAccess is structurally supported by a grant from the Netherlands Ministry of Foreign Affairs.

Supplemental Material

Supplemental material for this article is available online.

ORCID iDs

Femke Heddema, MS

Elizabeth Opondo, MPharm, MS

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Supplementary Material

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