Using mHealth Technology to Identify and Refer Surgical Site Infections in Rwanda
Phase: NA
Conditions: Surgical Site Infection
Sponsor: Brigham and Women's Hospital

 
1 
                                                            Partners Human Research Committee Detailed 
Protocol  
Protocol title: Using mHealth technology to identify and refer surgical site infections in 
Rwanda. 
Version Date:  9/20/2017 
BACKGROUND AND SIGNIFICANCE: 
Surgical site infections (SSI) are a major source of morbidity and mortality worldwide and the 
leading health-care-associated infection in the developing world. 1 The burden is 
disproportionately felt in low- and middle-income countries (LMICs)2 and especially in Africa, 
where the rate of post-operative SSI has been documented as high as 30.9%.3 In these settings, 
SSIs often develop after patients are discharged from care,2 and geographic and financial barriers 
can prevent patients from following up during the post-operative period. 4,5  One study from the 
Central African Republic reported that only 25% of surgical patients returned for their 30-day 
post-operative follow-up visit.6 Failure to return or a delayed return to care among patients with 
SSI is linked with poor health outcomes, including sepsis, need for re-operation, and death,7 and 
an increase in healthcare costs. 
In many LMICs, community health workers (CHWs) play a major role in delivering household-
based care to vulnerable populations who might otherwise be unable to access health facilities. 
These CHWs are typically lay individuals nominated by their communities with relatively low 
levels of education and training.8 In Rwanda, villages typically have three CHWs: two 
“binomes” who are trained to provide care for malaria, pneumonia, and diarrhea for children9 
and a third CHW responsible for maternal health.10 These CHWs are considered a critical 
component of the health system in a country that has seen a 59.5% decline in maternal mortality 
and 70.4% decline in under-five mortality since 2000.11 In some limited geographic areas, CHWs 
are engaged in other health activities. For example, CHWs provide support for HIV patients, 
leading to improved treatment adherence and patient outcomes.12,13 
The current Rwandan CHW network includes 45,000+ lay health workers who focus on basic 
health screening and education for pre- and post-partum women and children under-five years. 
The lack of professional training of the existing CHWs, combined with the large number of 
activities already included in their daily work, limits their ability to provide more complex care, 
such as monitoring post-operative patients. 
The greatest challenge that prevents the national expansion of CHWs into specialized care areas 
such as surgical follow-up is their pre-existing heavy workload and limited training.14 Globally, 
the range of responsibilities of CHWs vary by program,15 whether polyvalent or topic-focused 
such as the maternal and child health CHWs in Rwanda. Regardless of the range, the number of 
responsibilities is typically great and additional activities will require extensive pre- or post-
service training or provision of activity support aides. 
Recent advances in telecommunications infrastructure and technologies and the increasing access 
to mobile phones in LMICs create opportunities to use mobile health (mHealth) strategies to 

 
2 
support CHWs in the efficient follow-up of specialized patients. In Rwanda, 63% of the 
population in 2014 reportedly own a cell phone, with 99% having access to mobile networks.16 
We have shown that real-time use of mHealth technologies increases adherence to health 
protocols in rural Africa even with minimal provider training,17 and also improves the perceived 
quality of care.18 Point-of-care mHealth technologies can also support the supervision and 
reporting of activities,19 an existing challenge that we have identified for CHWs in Rwanda.20  
Members of this study team previously conducted a small pilot study in Haiti21 with sCHWs 
using mHealth tools to administer an SSI screening. Following the screening, the sCHWs used 
cell phones to photograph the surgical wound and record the GPS location of the visit. The 
mHealth tool was developed by Sana and administered on a Samsung Galaxy X-Cover 2 smart 
phone. Of the 33 surgical patients assessed, there was 85% agreement between the diagnoses of 
the CHW and a surgeon’s assessment based on a physical exam. 
 
Significance of this research: 
In order to address the challenges of overburdened CHWs and the demand for improved 
identification and referral of SSIs, we plan to leverage mHealth technology. The proposed CHW-
mHealth interventions could greatly improve the existing model for surgical patient follow-up in 
rural Rwanda. Under the current standard of care, post-operative patients are discharged from the 
hospital with verbal instructions to return to care if SSI symptoms develop. The interventions 
under investigation will allow routine contact with post-operative patients and support the 
delivery of a systematic protocol to identify and refer patients with SSI back to care. Since most 
operations at district hospitals in Rwanda are caesarian sections, this research will inform the 
way these mothers are followed after delivery, which is currently under the mandate of maternal 
CHWs. In addition, our findings will advance the research frontier by informing future studies 
employing CHWs equipped with mHealth tools to individually monitor other types of patients in 
their homes. 
This research will generate new knowledge related to the diagnosis of SSI and surgical patient 
follow-up in low- and middle-income countries. The screening protocol to be validated will 
lower barriers to diagnosis and extend diagnostic services to surgical patients that would not 
otherwise present for follow-up care. Further, the mHealth tools developed to deploy the 
screening protocol will serve as models for similar initiatives related to other disease areas, 
allowing for improved patient follow-up in rural resource-poor settings. Finally, the process 
measures documented in Aim 3 will help other implementers better understand the feasibility of 
mHealth tools to support community health workers. 
 
 
 
 
 

 
3 
SPECIFIC AIMS: 
The present study aims to examine whether or not the use of mobile Health (mHealth) by 
community health workers (CHWs) can improve the identification of surgical site infection (SSI) 
and a timely return to care among patients who undergo surgery at a rural hospital in Rwanda.  
With advances in mobile technology and telecommunications infrastructure in Rwanda, there is 
great potential to leverage mHealth strategies to support CHWs to identify SSI in the community 
and improve patient return to care. Here, we propose to optimize a simple screening protocol that 
can be implemented by CHWs with mHealth support to identify patients with SSI among 
surgical patients who return to the community following discharge from the hospital. We will 
then evaluate the impact of this intervention on appropriate return to care for patients with an 
SSI. We have previously piloted such strategies in rural Haiti where we found 85% agreement 
between the CHW diagnosis of SSI and the diagnosis of a surgeon.  
Specific Aim 1: In order to determine whether or not the use of mHealth by CHWs improves the 
identification of SSI and timely return to care among surgical patients in rural Rwanda, we aim 
to optimize a simple screening protocol that can be implemented by lay CHWs in Rwanda that 
will help them to correctly identify SSI ten days post-surgery.  
Specific Aim 2: We will assess the antibiotic prescribing practices during hospitalization and at 
discharge. 
Specific Aim 3: We will describe water, sanitation and hygiene (WASH) resources at the 
hospital and at the mothers’ homes. 
Specific Aim 4: After optimizing the SSI screening protocol, we will compare the efficacy of the 
protocol across two groups: 1) patients who are visited by a surgical CHW who administers the 
protocol using a mobile phone 2) patients who receive a phone call from surgical CHWs who 
administer the protocol via phone. These groups will be compared to patients who receive the 
standard of care in Rwanda, which is no special follow-up after discharge.  
Specific Aim 5: We aim to document process indicators measuring aspects of the CHW-
mHealth intervention implementation. These measures will evaluate for successful and timely 
completion or compliance with each step of the specific aim 2. 
Specific Aim 6: We will assess barriers to return to care, specifically in individuals in Arms 1 
and 2 that receive follow-up and are recommended to return to care for suspected SSI, but fail to 
return to Kirehe District Hospital. 
Specific Aim 7: We will determine standard post-operative follow-up care procedures for 
individuals who receive no additional follow-up (Arm 3). 
Specific Aim 8: We will assess the direct and indirect costs incurred by the mother and her 
family, stratified by whether or not she has a surgical site infection, and describe the burden of 
these costs relative to the overall financial expenditures of the household. 
 

 
4 
SUBJECT SELECTION AND ENROLLMENT:  
This study will follow patients who received cesarean-section surgery at KDH and reside in 
Kirehe District. KDH is a 145-bed facility operated by the Rwanda Ministry of Health (RMOH) 
and supported since 2005 by the medical non-profit organization Partners In Health (PIH). The 
hospital serves a catchment area of 364,000 people, primarily residing in rural, outlying villages. 
In preliminary work, we conducted a chart review that showed that 7.3% of obstetric surgical 
patients and 3.1% of non-obstetric surgical patients returned to the hospital with an SSI. Based 
on regional literature, we expect the true rate of SSI in patients receiving surgery KDH to be 10-
20%.22  
 
Phase 1 
Participants will be adult (≥18 years) patients receiving cesarean-section surgery at KDH over a 
seven-month enrollment window. All patients receiving a cesarean section (c-section) surgery at 
KDH who reside in Kirehe district will be eligible and will be invited to participate on post-
operative day 2. We anticipate enrolling 525 post-operative c-section patients who received 
surgery at KDH during the seven-month period. Patients will be enrolled consecutively. We will 
include patients from Mahama Refugee Camp when collecting information about the 
hospitalization and outcomes. However, these patients will not be asked to return for follow-up.  
Phase 2 
We will continue to consecutively enroll participants on post-operative day 2 from the adult 
female patient population receiving c-section surgery at KDH during a 14-month period. 
Randomization into the three study arms will take place at time of discharge. We will enroll 
1092 participants in this phase of the study, 364 per study arm. Once enrolled, there will be no 
special retention strategies so as not to interfere with the outcomes under investigation in Aim 4 
(return to care) or Aim 5 (process measures describing the CHW-mHealth intervention 
implementation). If the patient is still in the hospital 10 days following surgery, they will be 
excluded from the study given the inability to be randomized properly to the three arms of this 
phase. We will include patients from Mahama Refugee Camp when collecting information about 
the hospitalization and outcomes. However, these patients will not be asked to return for follow-
up.  
 
Sealed study packets, prepared in advance, will be available at KDH. Each study packet will 
have the arm assignment for the patient, which will be randomly assigned during the preparation 
of the materials using a random number generator. Both the research staff and the patient will be 
unaware of the arm assignment during the consent process and the assignment will be revealed 
only after the patient has agreed to participate. In this phase, no participants will receive travel 
vouchers, to ensure appropriate comparison between the intervention and standard of care 
groups. Per standard of care, all patients will receive information on the signs of SSI and will be 
instructed to return as soon as any of these present. (Appendix A). 
 
STUDY PROCEDURES: 

 
5 
This research includes two distinct phases. During the first phase, we will optimize the SSI 
screening protocol by piloting it among a cross-section of patients receiving surgery at KDH, 
Rwanda. In the second phase, we will randomize patients receiving surgery at KDH to one of 
three arms – standard of care and the two intervention arms. At the conclusion of the study, we 
will compare rates of return and severity of SSI at return among the three arms and report 
process indicators describing the implementation of the CHW-mHealth interventions in the two 
intervention arms. In this study, patients will be assessed at 10 days after their operation, as 
symptoms for SSI usually develop during the first 6-9 post-operative days.23  
 
Through PIH, we will hire four sCHWs with similar demographics to the existing CHWs 
specifically for this study. They will receive five days of training on the organization of the 
Rwandan health sector, post-operative follow-up, operation of the mHealth tools, best practices 
in wound photography, and basic SSI physiology and identification. The five-day training is 
similar in length to the specialized health trainings current CHWs receive and mirrors the 
training experience of sCHWs in the pilot project in Haiti. The mHealth tool was developed by 
Sana and is administered on a Samsung Galaxy X-Cover 2 smart phone. The tool prompts the 
CHW to evaluate the wound for 1) warmth, 2) increased pain, 3) swelling, 4) firmness of the 
wound, 5) wound opening, and 6) fluid drainage and quality. The phone also has the capability to 
take a photo of the wound and record GPS location.  
PHASE 1:  
During this phase, we will address Aim 1, optimization of the SSI screening protocol. The 
protocol will be piloted using the mHealth device among a cross-section of patients 
receiving surgery at Kirehe District Hospital (KDH), Rwanda. We will also embedded 
Specific Aims 2 and 3 (assessments of antibiotic prescribing practices and WASH 
resources) into this phase.  
Consenting participants will be screened for surgical site infection (SSI) 10 days’ post-operation. 
The screening window will be ± 3 days (7-13 days post-operation). During the screening visit, 
patients will be evaluated in two different steps. First, a GP will perform a clinical assessment. 
These data will be considered the gold standard against which to compare the SSI screening 
protocol. Secondly, the patient will be independently screened by a sCHW who will use the 
mHealth tool described above to administer the six basic screening questions. 
For consenting participants that are discharged prior to their 10-day post-operative screening, a 
study data collector will administer a simple self-report survey to collect basic patient 
demographic and socioeconomic characteristics on the day of discharge. They will be asked to 
return to the clinic for screening. In line with national policies, these participants will receive a 
voucher worth approximately US $10, to compensate for travel and time, to return to the clinic. 
The voucher will be redeemed when the patient arrives to their assigned screening day. If a 
participant misses his assigned screening day, the participant will be contacted via his local 
community health worker. 
Consenting patients that are not discharged prior to their 10-day post-operative screening will 
have demographic and socioeconomic data collected via self-report survey administered by the 

 
6 
study data collector as well as GPs and sCHW conducting the physical examination on the 
assigned screening day. These participants will not receive any voucher. Study staff will also 
extract clinical data from the patient files of all consenting participants.  
We anticipate enrolling a minimum of 525 post-operative patients during the five-month period. 
With an estimated overall SSI rate of 15% based on existing literature and 10% loss-to-follow-up 
(LTFU), we expect 71 patients will have a GP-diagnosed SSI and 402 patients will not have a 
GP-diagnosed SSI. 
PHASE 2:  
After the screening protocol has been optimized in phase 1, new patients receiving c-section 
surgery at KDH will be enrolled and randomized to one of three study arms. Rates of 
return and severity of SSI at return across the three arms will be compared (Aim 4). We 
will also report process indicators to describe the implementation of the CHW-mHealth 
interventions (Aim 5). For patients that have contact with a sCHW (Arms 1 and 2), and are 
suspected to have a SSI and referred back to care but fail to return, we will assess their 
barriers to care (Aim 6). For patients that have no special follow-up, we will assess their 
post-operative follow-up practices (Aim 7). Embedded in this study will be a small sub-
study on the costs of care and impact of these costs on family expenses (Aim 8). 
All consenting participants will have basic demographic and socioeconomic data collected by 
self-report via a survey administered by the study data collector at time of discharge. The study 
data collector will extract additional clinical data from the patient file. At time of discharge, 
participants will receive surgery follow-up instructions (Appendix A), including a set of warning 
signs for SSI and when to return to a health center, per standard of care. Additional human 
subjects contact will depend on study arm assignment. Individuals in Arm 1 will be visited at 
home by the sCHW who will administer the optimized SSI protocol via the mHealth device. 
Following the screening, the sCHWs will use the cell phone to photograph the surgical wound 
and record the GPS location of the visit. Individuals in Arm 2 will be phoned by the sCHW who 
will administer the SSI protocol over the phone. Individuals in Arm 3 will not have any 
additional contact beyond standard of care (Figure 1).  
 
 
 
 
 
 
 
 

 
7 
 
 
Figure 1: 
 
BIOSTATISTICAL AND QUALITATIVE ANALYSIS:  
Phase 1: 
At the time of enrollment, study staff will administer a basic survey to record self-reported data 
on patient demographics (gender, age, weight, height, education level, location of residence, 
distance to hospital) and socioeconomic status (monthly household income, land ownership, cost 
of transport as a barrier to receiving health care). Study staff will also extract data from clinical 
charts on past medical history, type of surgery, time from surgery recommendation to operation, 
pre-operative antibiotic use/time, wound class, and any documented surgical complications. 
Clinical information will continue to be collected up to 90 days for any patients who are never 
discharged or for any patient who is readmitted for a surgical complication. For patients that are 
transferred to Kigali for tertiary care, we will use data collected routinely collected by the Right 
to Health Care program to complete their follow up information.   
Specific Aim 1: During the follow-up screening visit, patients will be evaluated in two different 
steps. First, the patient will be screened by a CHW who will use the mHealth tool to administer 
the basic screening questions. The mHealth application will prompt the CHW to evaluate for 
warmth, increased pain, increased swelling, increased firmness of the wound, wound opening, 
and fluid drainage and quality. The CHW will take photo of the wound on the mHealth tool. 
Second, a GP will perform a clinical assessment and provide responses to two basic questions: 1) 
Do you diagnose the patient as having an SSI? And 2) Do you identify any other post-operative 
Recruitment
1092 Patients, 14 months
Randomize patients
Provide patients with discharge 
instructions
Arm 1: CHW visits 
home to deliver 
mHealth questions
364 patients
Arm 2: CHW delivers 
mHealth questions 
over the phone
364 patients
Arm 3: Standard of 
Care
364 patients

 
8 
complications that would warrant the patient’s return to the clinic for physician review? These 
data will be considered the gold standard against which to compare the SSI screening protocol. 
The GP will also comment on the 6 characteristics from the mHealth tool for comparison.  
Specific Aim 2: For one month of Phase 1, study nurses will observe the clinical interactions 
with patients during rounding and document in a case observation form (Appendix B) the 
prescription and taking of antibiotics during admission and at discharge.  
Specific Aim 3: To assess the WASH infrastructure at the hospital, data collectors will 
administer a hospital assessment form (Appendix C). To assess variability, the data collectors 
will administer an abbreviated version of this form every 4 hours over the course of one week. At 
the follow-up visits, mothers will be asked about the access to sanitation facilities at home. 
Analysis and Outcomes:  
Aim 1: 
Patients who are still admitted at the follow-up will be excluded from the developing of the 
screening algorithm. At 4 months into Phase 1, we will assess the validity of the SSI screening 
protocol. In this first assessment we will identify a cutoff (c) by optimizing the area under the 
receiver operating characteristic curve. We will consider the screen positive if the patient meets 
at least c of the 6 criteria. If the sensitivity of SSI screening protocol is less than 90% or the 
specificity is less than 80%, we will modify and optimize the screening protocol. Steps for 
modifying the algorithm include the following: 
1. Adding, removing or modifying questions. We will use a classification and regression tree 
(CART) analysis to determine the best set of individual or combined items from the initial 
screening questions. We will develop maximal trees with all six screening questions, and 
then apply reduced error pruning, removing questions that do not reduce predictive error by 
10%. We will choose optimal trees based on overall predictive properties of the pruned tree. 
If the optimal tree removes screening questions, we will propose new questions guided by a) 
Rwandan colleagues for contextual relevance and b) global surgery and infectious disease 
experts for subject matter input. 
 
2. Adding photo functionality with review by the GP. Email through the cellular network and 
uploading through the mHealth system could allow sCHWs to send a photo along with the 
screening question responses to a GP for their recommended diagnosis. If the SSI screening 
protocol is performing sub optimally, then we will explore the validity of the protocol with 
the photo and GP photo assessment added. 
 
After 3 additional months (7 months into Phase 1), we will identify a new cutoff and reassess the 
sensitivity and specificity, with 95% confidence intervals, of the SSI screening protocol. This 
final algorithm will be considered optimal for Phase 2. 

 
9 
 
Aim 2:  
We will describe the type of antibiotics prescribed, the median number of doses and amount of 
doses with interquartile ranges. 
 
Aim 3:  
We will describe the overall WASH infrastructure, variability in availability in WASH 
infrastructure and availability of WASH infrastructure in the mothers’ homes using frequency 
and proportions with 95% confidence intervals. 
Phase 2:  
Basic demographic and clinical data will be recorded at baseline by study staff, as described in 
phase 1. For Arms 1 and 2, addresses/phone numbers and availability will be documented for 
patient follow-up. At ten post-operative days (±3 days), sCHWs will visit patients in Arm 1 at 
the address provided. The sCHW will be assisted by a local village CHW to identify the patients’ 
homes. Once there, the sCHW will administer the SSI screening protocol with prompting from 
the phone, record responses into the phone, take a photo of the wound, and take GPS 
coordinates. Patients in Arm 2 will be phoned by the sCHW on the tenth post-operative day (±3 
days). The sCHW will administer the SSI screening protocol over the phone, prompted by the 
smartphone application to ask the appropriate questions. For both arms, patients identified as 
having an SSI will be referred back to KDH for care. These patients will also be asked a set of 
questions to assess for possible barriers to return of follow up. In this phase, patients will not 
receive financial support to return to the clinic. Patients not identified with SSI will be reminded 
of the warning signs and follow-up instructions. Patients still hospitalized at the hospitalized on 
their assigned screening day will be excluded from the study as they will not be eligible for the 
expected study follow up. 
A patient tracker log at the hospital will be used to document patient return for follow-up care. 
The log will also document patients that self-present with potential SSI. Study staff will extract 
from the clinical chart the presence of an SSI, severity, treatment obtained, need for operative 
intervention, hospitalization, and/ or complications as recorded by a KDH GP. During the study 
period, clinical charts will be audited for completeness and GPs will be trained in data quality to 
ensure the accuracy of this clinical data. In addition, study staff will track process measures 
related to Arms 1 and 2. 
Patients in Arms 1 and 2, who are determined by the sCHW to have a suspected SSI and referred 
back to care, but fail to return back to care within one week will be identified. Data collectors 
will return to these patients’ homes at 22-30 days post-operation to interview them on why they 
failed to return to care. The interviews will be semi-structured, including questions on 
established barriers to care and allowing for open-ended response. A random sample of patients 
in Arm 3 will be visited at home at 22-30 days post-operation by data collectors who will 

 
10
interview them on their follow-up care procedures. The interviews will be semi-structured, 
including questions on standard care paths and allowing for open-ended response. 
For a subset of 50 patients, we will administer at discharge a Financial Risk Protection Survey 
(Appendix D), an existing validated tool, to understand the total costs of care and the costs 
relative to normal household expenditures.  
 
Analysis and Outcomes:  
Aim 4: 
For Aim 4, we will compare the proportion of patients who return for follow-up with an SSI in 
Arms 1 and 2 to Arm 3 (standard of care) using a two-sided, two-sample test of proportions at 
the α=0.05 significance level. We will use a logistic regression model to assess the impact of 
study arm on measures of severity at presentation (for example, readmission to hospital), 
controlling for potential confounders collected at enrollment. All analyses will be completed as 
intention to treat, regardless of whether the patient had contact with the sCHW or was screened 
by the mHealth tool in Arms 1 and 2. For Aim 4, for Arms 1 and 2, we will report percent for 
each of the process measures (for example, percent of home visits or calls completed on time) 
with 95% confidence intervals. We will assess the impact of study arm on measures of severity 
at presentation, controlling for potential confounders collected at enrollment. We will describe 
standard of care patient follow-up behavior using results from Arm 3. We will also report 
surgery-related reasons for return to care beyond SSI. We will perform a sensitivity analysis to 
determine under what range of SSI rates the results are still valid.  
 
Aim 5: 
For Aim 5, we will report percent for each of the process measures with 95% confidence 
intervals. Process measures include: ability to find the patient’s home (Arm 1), willingness to 
allow sCHW into home (Arm 1), percent of home visits completed (Arm 1), successful use of 
GPS (Arm 1), availability of phone (Arm 2), availability of patient when called (Arm 2), visits or 
calls completed on-time (Arms 1 and 2), percent of reports successfully transmitted via the 
application (Arms 1 and 2) and presentation to care upon referral (Arms 1 and 2).  
Aim 6: 
For Aim 6, we will identify potential predictors for failure to return, comparing those who were 
recommended in Arms 1 and 2 to return and did return to those who failed to return using 
logistic regression. Demographic and clinical predictors collected at enrollment will be used as 
potential predictors. All factors significant at the α=0.2 significance level in the bivariate analysis 
will be considered for the multivariate analysis. We will build the final predictive model using 
backward stepwise regression, stopping when all factors remain significant at the α=0.05. For 
those that fail to return to care, we will report their barriers to care using proportions and 95% 
confidence intervals. Responses to open ended questions will be transcribed and translated, and 
we will identify any unaddressed themes using a general inductive approach.  

 
11
Aim 7:  
For Aim 7, we will evaluate patient post-operative care behaviors using proportions and 95% 
confidence intervals. Responses to open ended questions will be transcribed and translated, and 
we will identify any unaddressed themes using a general inductive approach. 
 
Aim 8: 
For Aim 8, we will describe the median and ranges of expenses incurred by patients, stratified by 
whether or not the patient had a surgical site infection. We will also describe the median and 
range for the normal household expenditures and compare the care expenses relative to normal 
household expenditures. 
 
Power Analysis: 
 
The sample size for Phase 2 of this study was driven by Aim 4. We assume that the rates of SSI 
in the three arms will be similar (due to randomization), and we anticipate more patients with 
SSI will return to care in Arms 1 and 2 than in Arm 3. In each arm, we will enroll 364 patients. 
Assuming a 15% SSI rate, this translates to 55 SSI cases per arm. In Arm 3, we expect 
approximately 6% of all surgical patients to return with an SSI corresponding to 40% of all SSI 
infections. In Arms 1 and 2, we hypothesize twice as many patients with SSI (80%, n=44) will 
return. We would have an 81% power to detect a difference between the rate of patients that 
returned with SSI in Arms 1 and 2 (12%) as compared to Arm 3 (6%) with a two-sided test at the 
α=0.05 significance level (Table 1). 
 
Table 1: Sample size calculation in Phase 2 
  
Arm 1 
Arm 2 
Arm 3 
Description 
Home visit 
on 10th post-
operative 
day (±3 
days) 
Phone call 
on 10th post-
operative 
day (±3 
days) 
Standard of 
care  
Number per arm 
364 
364 
364 
Anticipated 
number with SSI 
55 
55 
55 
Hypothesized 
number to return 
with SSI days 7-
14 
44 (80%) 
44 (80%) 
22 (40%) 
Overall 
hypothesized 
proportion that 
0.12 
0.12 
0.06 

 
12
 
 
 
 
 
 
 
 
 
 
 
 
 
 
RISKS AND DISCOMFORTS: 
The study does not alter the standard of care in any way that increases risk to the patient. Risks to 
privacy are minimized by accessing data on password protected mobile phones, storing data on 
HIPAA-compliant servers, and de-identifying the database as soon as is practicable after the 
conclusion of the study period.  
The primary risk associated with participation in this study is a breach in confidentiality, 
resulting in the disclosure of patient information. This risk is considered minimal; as unique 
codes will be used in place of participant names. All study staff will be trained in confidentiality. 
To further reduce the likelihood of a breach in confidentiality, all digital information will be 
stored in a password-protected document on an encrypted study computer, and all paper records 
will be stored in a locked file cabinet in a secure room at KDH. 
A second risk will be decreasing the likelihood of a patient return to care when needed under the 
CHW mHealth interventions. All patients will receive standard of care advice on surgical follow-
up and when to return to care. Patients who have contact with a sCHW (Arms 1 and 2 of Aim 2) 
will be referred back to care if evidence of an SSI is present or will otherwise be reminded of 
advice on when to return to care. It is possible that the sCHW will give the wrong SSI diagnosis 
or that a patient may delay return to care because of an expected visit from a sCHW. This risk is 
moderate and will be monitored. 
A third risk is exposure of patient’s location due to the collection of GPS coordinates. To 
will return on 
POD 7-14 with 
SSI 

 
13
minimize this, we will adopt the concept of geographic masking- the process of altering the 
coordinates of point location data to limit the risk of re-identification upon release of the data.24 
POTENTIAL BENEFITS:  
Participants likely will benefit from the research in that the intervention we hypothesize will lead 
to a timelier diagnosis of SSI. This in turn will lead to earlier presentation and faster treatment 
initiation. Diagnosis of SSI earlier will then prevent progression to sepsis, need for re-operation, 
and possibly death. 
In addition, this study will help identify barriers to follow up care and improve access through 
the use of CHWs. The patients enrolled in Aim 1 will benefit directly by receiving vouchers to 
compensate for transportation costs (a known barrier) to return to follow up who otherwise 
would not routinely see a clinician post-operatively.  Patients enrolled in both Arms 1 and 2 of 
Aim 2 will have additional contact with a health care provider (sCHW) beyond the current 
standard of care. While not all participants may need this earlier screening, as not all will have 
surgical complications, the risks and discomforts associated with the screening are minimal. 
The long term goal of the present study is to scale up our mHealth technology by providing the 
intervention to all surgical patients, particularly mothers who received a caesarian section, 
leveraging our collaboration with the Rwanda Ministry of Health (RMOH) eHealth lead. 
Furthermore, the results of this disease-agnostic platform will inform other mHealth approaches 
to support patient follow-up by CHWs, allowing CHWs to expand to other specialized healthcare 
needs and better link these patients to care in rural African settings. 
 
MONITORING AND QUALITY ASSURANCE:  
Data monitoring 
Data will be monitored for accuracy, completeness and appropriateness of evaluations by the 
surgical research fellow and study staff every 2 weeks. Consent procedures will be conducted by 
the research team. Adherence to the protocol will be reviewed with feedback given to study 
personnel on a weekly basis 
Data Safety 
Only study staff, sCHWs and investigators Evrard Nahimana, Caste Habiyakare and the surgical 
research fellow will have access to identifiable data. These individuals will receive training in 
data confidentiality and research ethics. The remaining co-investigators will only have access to 
de-identified data including data collection forms that only have a study ID captured or final 
databases with all identifiers removed. 
The following includes the specific data that will be collected for the purposes of this study and 
the study design to ensure patient confidentiality, randomization, and patient safety.  
1) Demographic and socio-economic data (Phase 1 and 2). This data will be collected by study 
staff at the time of study enrollment via a self-report questionnaire administered to the 

 
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participants. Responses will be recorded onto a paper data collection form that will be stored in a 
locked file cabinet in a secure room at KDH. A unique study ID will be recorded on the paper 
data collection form in place of participant names. The file linking study IDs to patient identifiers 
will be kept separately. Once this data is double entered into a password-protected electronic 
database by study staff, the paper data collection form will be destroyed. 
2) Clinical data from patient files (Phase 1 and 2). This data will be extracted by study staff at 
time of enrollment or after the patient’s return visit (Aim 2 only). Co-investigators Evrard 
Nahimana, Caste Habiyakare and the surgical research fellow may assist with data extraction 
from files. Data will be recorded onto a paper data collection form that will be stored in a locked 
file cabinet in a secure room at KDH. A unique study ID will be recorded on the paper data 
collection form in place of participants’ names. The file linking the study ID to patient identifiers 
will be kept separately. Once this data is double-entered into a password-protected electronic 
database by study staff, the paper data collection form will be destroyed.  
3) Screening assessments by GP and sCHW (Phase 1). This data will be captured on a paper data 
collection form by the GP for the GP screening and directly into the mHealth tool by the sCHW 
for the sCHW screening. GP responses will be recorded onto a paper data collection form that 
will be stored in a locked file cabinet in a secure room at KDH. Only a study ID will be captured 
on the paper data collection form and a file linking the study ID to patient identifiers will be kept 
separately. Once this data is double entered into a password-protected electronic database by 
study staff, the paper data collection form will be destroyed. Data/photos collected on mHealth 
devices will be stored locally on a password protected phone before uploaded into the research 
database. Only the study id will be captured in the phone at the time of screening. 
4) Patient tracking information (Phase 2). This data is needed to identify patients in Arm 1 and 
Arm 2 of the study for appropriate follow-up. For Arm 1, which requires follow-up in the 
patient’s home, study staff will record the location of the participant’s home and the name of the 
existing CHW. For Arm 2, which requires a call to the patient, the study staff will record a phone 
number that can be used to reach the patient (if available). Patient tracking information will only 
be used by the study staff and the sCHW responsible for the patient’s follow-up. This 
information will be stored on a paper form, separate from any patient data and will be destroyed 
at the end of the study. 
5) CHW-mHealth process measures data (Phase 2). Study staff and community health workers 
will document the ability to find the patient’s home (Arm 1), participants’ willingness to allow 
sCHWs into their homes (Arm 1), percent of home visits completed (Arm 1), successful use of 
GPS (Arm 1), availability of phone (Arm 2), availability of patient when called (Arm 2), visits or 
calls completed on time (Arms 1 and 2), percent of reports successfully transmitted via the 
mHealth application (Arms 1 and 2) and whether a patient referred back to care returned to care 
(Arms 1 and 2). This data will be collected on a paper form with only the study ID captured. 
Once this data is double-entered into a password-protected electronic database by study staff, the 
paper data collection form will be destroyed. 
Outcome Monitoring 

 
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To minimize the risk of a breach in confidentiality, unique codes will be used in place of 
participant names and all study staff will be trained in confidentiality. Personal health 
information will be coded and collected on password-protected mobile phones. All digital 
information will then be stored on an encrypted study computer. All paper records, including 
consent forms, will be stored in a locked filing cabinet at KDH. At the conclusion of the study 
period, all datasets for analysis will be de-identified and all identifiable information will be 
destroyed. 
Adverse Event Reporting 
A Data and Safety Monitoring Board (DSMB) will be designated to oversee the safety and 
effectiveness of the Aim 4 in this study. This committee will include one surgery expert, one 
global health delivery expert, one Rwandan health practitioner and one statistician. After seven 
months of accrual, we will compare rates of return between the three study arms. We anticipate 
600 patients (200 per arm) will be included in this interim analysis. If the proportion who have 
returned in Arms 1 and 2 (intervention arms) is significantly lower compared to standard of care, 
then the study will be stopped or one study arm will be dropped. Further, if there are 
significantly more complex cases at return (higher rates of readmission or reoperation) in Arms 1 
or 2, then the study will be stopped or one study arm will be dropped. The DSMB will meet 
once, immediately after the interim analysis, and the outcome of the DSMB review will be 
summarized in a letter to the IRBs of all participating institutions. 
 
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