# Expanding and Scaling Two-way Texting to Reduce Unnecessary Follow-Up and Improve Adverse Event Identification Among Voluntary Medical Male Circumcision Clients in the Republic of South Africa

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2021 · $575,667

## Abstract

Male circumcision (MC) is a critical HIV prevention intervention with global support for expansion across sub-
Saharan Africa (SSA). MC is safe: routine programs in SSA report adverse event (AE) rates well under 2%.
Nevertheless, global MC guidelines require one or more follow-up visits within 14 days for AE detection. With
low AE rates, overstretched clinic staff waste invaluable resources conducting unnecessary routine reviews for
MC clients without complications. Men healing well needlessly pay for transport, miss work, and wait for reviews,
discouraging MC uptake. In weak healthcare systems in SSA, MC quality is buckling under pressure to provide
quality MC services and meet ambitious global targets of 5 million annual MCs. Our prior research in Zimbabwe
employed two-way texting (2wT) between patients and providers to focus follow-up on men with potential AEs,
allowing men healing without complication to opt-out of routine post-operative visits. 2wT safely reduced client
visits by 85%, suggesting that 2wT can make MC services dramatically more efficient while maintaining safety.
Whether 2wT can be replicated and scaled in other routine program settings is now a critical implementation
research question. The Republic of South Africa’s (RSA) MC context of high-volume urban clinics, remote service
delivery, and low AE identification threaten quality at scale. Across more than 500,000 annual MCs performed,
up to 1 million multi-stage, unnecessary MC reviews are likely conducted. In urban sites, this causes service
delivery bottlenecks; in rural areas, follow-up requires multiple, multi-hour trips, curtailing productivity. RSA
pressure for MC expansion and severe health system constraints, combined with good cell coverage, suggest
2wT’s impact would be significant for MC care quality and efficiency, especially in rural areas. Therefore, we
seek to develop an adaptable 2wT dissemination and implementation model at scale (2wT-2-SCALE) delivered
by routine MC teams, not research teams. First, a randomized control trial (RCT) (phase 1: test) will rigorously
evaluate how 2wT improves AE ascertainment and follow-up efficiency in urban and rural clinics. Then (phase
2: intensive), we scale (2wT-2-SCALE) via a one-year, quasi-experimental, step-wedge design with insights
gained from one additional year of 2wT with routine MC teams (phase 3: maintain). Guided by implementation
science, we employ mixed-methods to evaluate 2wT-2-SCALE’s impact on VMMC service quality. Our specific
aims are to 1) conduct an RCT to determine how 2wT increases AE ascertainment while reducing workload in
the RSA implementation context; 2) develop an effective dissemination and implementation strategy at scale
(2WT-2-SCALE) using RE-AIM to evaluate program reach, effectiveness, adoption, implementation, and
maintenance; and 3) use activity based micro-costing to estimate the payer-perspective budget and program
impact from 2wT scale-up compared to routine care. This implementatio...

## Key facts

- **NIH application ID:** 10191053
- **Project number:** 5R01NR019229-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Caryl Feldacker
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $575,667
- **Award type:** 5
- **Project period:** 2020-06-12 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10191053

## Citation

> US National Institutes of Health, RePORTER application 10191053, Expanding and Scaling Two-way Texting to Reduce Unnecessary Follow-Up and Improve Adverse Event Identification Among Voluntary Medical Male Circumcision Clients in the Republic of South Africa (5R01NR019229-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10191053. Licensed CC0.

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