Transforming reproductive healthcare delivery through telemedicine services expansion: evidence from a mixed-methods pilot evaluation in rural Ghana

Abstract

Background

In 2021, Ghana’s National Comprehensive Abortion Care Standards and Protocols recognised telemedicine as an approved delivery model for early medical abortion (EMA). Following a successful pilot in Accra, MSI Reproductive Choices Ghana expanded their telemedicine model to more rural areas and broadened their package of sexual and reproductive health (SRH) services to include fertility evaluation. This study evaluates the expanded model.

Methods

A mixed-methods evaluation (January 2024 to March 2025) drew on routine clinical data, courier and call centre tracking, client feedback surveys, and qualitative, individual in-depth interviews with telemedicine clients to assess clinical safety, service utilisation and user experience. Quantitative analysis included descriptive statistics and unadjusted logistic and ordinal regression. Qualitative interviews with clients explored feasibility, acceptability and implementation challenges. A deductive, thematic analysis was conducted with the support of Delve qualitative research software and guided by the Consolidated Framework for Implementation Research.

Results

A total of 2721 clients accessed telemedicine services, with 70.0% receiving EMA and 29.5% short-term contraceptive methods. Among EMA clients reached for follow-up, 96.9% reported complete abortion with no further intervention. Satisfaction was high: 89.4% would recommend the service, and 78.2% would use it again. Qualitative findings highlighted that clients valued privacy, convenience and autonomy, particularly in stigmatised or crowded spaces. Barriers to accessing services included unclear eligibility criteria, limited digital access and misperceptions that the service was for abortion only. Most clients contacted the service between 4 and 6 weeks’ gestation. Post-abortion contraception uptake was 24.8%, with no significant variation by age or location. Nearly half of clients reported having no other way to access care.

Conclusions

Telemedicine is a feasible, safe and acceptable model for SRH delivery in Ghana. Findings will inform national scale-up and strategies to strengthen equity, communication and service integration.

WHAT IS ALREADY KNOWN ON THIS TOPIC.

WHAT THIS STUDY ADDS

• This mixed-methods evaluation demonstrates that a scaled telemedicine model for SRH, including EMA and short-term contraception, is feasible, safe and highly acceptable when expanded to more rural regions of Ghana. Clients valued the model’s privacy, convenience and support for self-managed care, though barriers around digital access, service visibility and continuity of care remain.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• Findings support the national scale-up of telemedicine for sexual and reproductive health and rights (SRHR) in Ghana and provide practical insights for improving access, equity and service integration. This study also contributes to the global evidence base on designing client-centred telehealth models that extend beyond abortion to comprehensive SRH services in low-income and middle-income settings.

Introduction

Despite notable progress in healthcare delivery in Ghana over the last decade, significant disparities persist in access to sexual and reproductive health (SRH) services in Ghana, particularly in rural and other underserved populations.^{1 2} These disparities are driven by a range of structural and sociocultural factors, including limited healthcare infrastructure, workforce shortages, geographic isolation and stigma surrounding SRH, especially among adolescents and women seeking services such as contraception and abortion care.^{2 3} Ghana’s health system remains under strain: although physician and nursing densities have improved modestly in past decades, the maldistribution of health workers means many rural districts still experience severe shortages, exacerbating barriers to SRH service access.³

In this context, digital health has emerged as a transformative opportunity for Ghana’s healthcare system. The country’s ‘Policy and Strategy on Digital Health (2023–2027)’ underscores the government’s commitment to leveraging information and communication technology (ICT) to expand healthcare access and improve health outcomes, especially for remote and underserved populations.⁴ Ghana has seen increasing investment in teleconsultation platforms, multi-dimensional telemedicine solutions and mobile health initiatives that connect community health workers to medical professionals in real time.^{4 5} These efforts are designed to bridge the urban-rural divide and create more resilient, responsive health systems.

Among these innovations, telemedicine—the remote delivery of health services through digital platforms—has shown considerable promise in improving access to SRH services. Globally, SRH services provided via telemedicine have been demonstrated to overcome geographical barriers, support continuity of care and empower clients through increased autonomy and privacy.^{6 7} In sub-Saharan Africa, telemedicine use among women of reproductive age remains low but is growing, particularly among younger, urban and wealthier populations.⁸ The expansion of digital literacy and telecommunications infrastructure creates fertile ground for more equitable deployment of these services.

In Ghana, MSI Reproductive Choices Ghana (MSIG) launched a telemedicine pilot in July 2021, aimed at improving access to essential reproductive health services, including early medication abortion (EMA) up to 9 weeks of gestation, and short-term contraceptive methods (STMs) including emergency contraception, Sayana Press injectables, oral contraceptive pills and condoms. Sayana Press is a subcutaneous injectable contraceptive containing depot medroxyprogesterone acetate (DMPA-SC), developed to enable simplified administration, including delivery through community-based distribution and self-injection. This intervention leveraged MSIG’s existing contact centre (MarieCall) and was implemented in collaboration with national stakeholders from the Ghana Health Service (GHS). In the MSIG telemedicine pathway, clients initiate contact through MarieCall, a toll-free contact centre staffed by trained agents who provide information and referrals for sexual and reproductive health services. Callers interested in abortion are offered the telemedicine option and screened by the contact centre agents for legal, safeguarding and clinical eligibility. Eligible and consenting clients are scheduled for a remote consultation with a qualified provider, who conducts full counselling, confirms eligibility and provides detailed instructions for medication use. Following mobile money payment, clients receive their EMA pack, either by courier or clinic collection, which includes the medication regimen (mifepristone and misoprostol), pain relief, a pregnancy test, condoms and a short-term contraceptive method, if chosen by the client during the provider-led counselling. Ongoing support is available via the contact centre, and a routine follow-up call is conducted approximately 7 days after medication use to assess outcomes and manage any complications, with referrals made for in-person care if needed. The telemedicine pilot yielded positive outcomes, including 97% of clients having a successful self-managed EMA, high levels of user satisfaction and increased service accessibility.⁹

The safety and efficacy of medication abortion, particularly when self-managed with proper information and support, have been well-established in diverse global contexts.^{6 10} Studies from both high-income and low-income and middle-income countries (LMICs) have demonstrated that self-managed EMA via telemedicine can be safe, effective and acceptable to users.^{6 11} Evidence shows that when supported by remote consultation and clear guidance, rates of complications are low and comparable to in-clinic care.⁶ These findings, in combination with the MSIG telemedicine pilot results, provide a strong rationale for scaling up telemedicine EMA services in Ghana, especially in regions where in-person access is restricted.⁹

Given the potential demonstrated in the pilot, in 2024, MSIG expanded the telemedicine model, with the service scope growing to include fertility evaluation. The expansion also included new geographies, with a specific target of underserved, rural areas in Northern and Southwestern Ghana. Despite promising early findings from MSIG’s initial telemedicine pilot in more urban areas of the Greater Accra Region, key questions remained regarding the model’s scalability, safety, acceptability and cost-effectiveness when scaled to rural areas and with an expanded services scope.⁹

The current study aims to fill this evidence gap by evaluating the expanded telemedicine model in Ghana. Specifically, the study assessed service utilisation patterns, client preferences, satisfaction levels, safety outcomes and barriers to access in the expanded rural geography. In doing so, this study aimed to generate actionable, evidence-based recommendations to inform Ghana’s national telemedicine policy and enhance the delivery of reproductive health services in Ghana and comparable LMIC settings.

Methods

A mixed methods approach was chosen to provide a comprehensive evaluation of the expanded telemedicine model, combining quantitative and qualitative data to capture outcome and implementation processes and nuance the interpretation with more in-depth contextual understanding. Quantitative analysis drew on a range of existing routine health information system (RHIS) data to assess service uptake, user characteristics and key performance indicators following expansion, while qualitative data from in-depth interviews explored client experience, perceived acceptability and contextual factors influencing implementation. Together, these methods enabled a more nuanced interpretation of the results, linking observed service-level patterns to underlying experiences and contextual dynamics. The approach leveraged the quantitative methods and data collection tools used in the published pilot evaluation.⁹

Quantitative analysis

Data sources

Several existing electronic reproductive health information systems (RHIS) and telemedicine programme-specific operational monitoring data sources supported the telemedicine model’s monitoring framework. These systems, which drew primarily on MSI’s internal RHIS, electronic customer relationship management system (C3), clinical follow-up forms and client feedback surveys, captured service delivery data across all telemedicine touchpoints from January to December 2024 (table 1).

Table 1. Data collection procedure and sample size overview.

Method/source	Study population	Sample
IDIs	Women of reproductive age (15–49) who have used telemedicine for SRH services at MSI Reproductive Choices Ghana (MSIG) and consented to be recontacted for research purposes.	EMA: 13 Short-term contraceptives: 3 Fertility evaluation: 2 Total: 18 IDIs
FGDs	MSIG healthcare providers, centre managers and contact centre agents directly involved in telemedicine operations who consented to participate.	1 FGD: telemedicine staff—providers and contact centre agents (4) 1 FGD: centre managers (6) Total: 2 FGDs, 10 participants
KIIs	MISG staff directly involved in the planning or implementation of the expansion phase.	Total: 5 KIIs
C3	Electronic customer relationship management system (C3) which logs details of all outbound and inbound calls managed by the MSIG contact centre. Included: All potential clients who call the contact centre to inquire on telemedicine, or who are offered this option by the contact centre agent.	Full year 2024 data from MSIG’s electronic customer relationship management system (C3) for the telemedicine eligibility screening form. The telemedicine option is offered via the contact centre to clients enquiring about MSI services. If a caller expresses interest in this option, the contact centre agent completes an eligibility screening and documents this in C3.
EHR	Electronic health records capturing patient-level information on all services delivered in MSIG clinics and telemedicine services including patient registration, information, demographics and select reproductive history characteristics. Included: Clients accessing the MSIG telemedicine option.	Full year 2024 data from MSIG centres electronic health records (EHR).
Clinical follow-up	A secure online clinical follow-up form used to capture information from the clinical follow-up calls with each EMA patient. Included: Clients accessing the MSIG telemedicine option.	Full year 2024 clinical follow-up data collected by contact centre agents 7 days post consultation for EMA via telemedicine only.
Client feedback	A secure online client feedback form used to capture their experience and overall satisfaction with the telemedicine service. Included: Clients accessing the MSIG telemedicine option who consent to complete the feedback form.	Full year 2024 client feedback collected by contact centre agents 7 days post consultation for EMA via telemedicine via an opt-in feedback form sent by e-mail or WhatsApp.
Telemedicine delivery tracking	Excel-based courier tracker to monitor the details of all telemedicine deliveries. Included: All entered data with matching Telemedicine consultation in EHR.	Full year 2024 delivery tracking data captured in a password-protected excel-based courier log.

EMA, early medication abortion; FGDs, focus group discussions; IDIs, in-depth interviews; KIIs, key-informant interviews; MSIG, MSI Reproductive Choices Ghana (MSIG); SRH, sexual and reproductive health.

MSI’s RHIS was the primary clinical data source, containing routine electronic health records of all clients who accessed the telemedicine pathway during the evaluation period. Data were collected continuously throughout service delivery, and quality assurance checks were conducted monthly by the MSIG team to ensure completeness and consistency. Access to RHIS data was restricted to authorised MSI personnel with secure logins.

The C3 system is MSI Ghana’s electronic customer relationship management (CRM) platform, which logs all inbound and outbound calls managed by the MSIG contact centre. This dataset captures every potential client who contacts the centre to inquire about telemedicine or is offered the telemedicine option by a contact centre agent. When a caller expresses interest, the contact centre agent conducts a telemedicine eligibility screening, documenting the client’s demographic information, interest in services and screening outcomes directly in C3.

Complementary patient feedback data were collected during routine 7-day follow-up calls by contact centre agents. During the routine follow-up call, clients who reported a successful EMA were invited to complete a short electronic feedback survey assessing satisfaction with service quality, privacy and accessibility. Participation was voluntary, and responses were stored separately from medical records to preserve confidentiality. Participants received a secure link to the survey via their preferred communication platform (email or WhatsApp).

Collectively, these data sources enabled a multilayered analysis of telemedicine implementation, covering the full continuum from client inquiry and eligibility screening through to clinical outcomes and user satisfaction.

Outcomes of interest

Key process and outcome indicators were defined collaboratively by MSI, MSIG and the GHS prior to the telemedicine expansion. These indicators were detailed in the outcome mapping matrix and guided descriptive and inferential analyses.

Key outcomes of interest included:

• Service utilisation and access: Number of telemedicine clients, call volume and completion rates.

• Clinical outcomes: Gestational age at presentation and successful completion of EMA.

• Post-abortion family planning (PAFP): Uptake and method mix following EMA.

• Client experience: Satisfaction with information provision, confidentiality and convenience of telemedicine.

The outcome framework ensured alignment with both the programme’s operational monitoring and national RHIS indicators.

Analysis

A descriptive and inferential analytical approach was used to explore telemedicine service patterns and outcomes. Frequencies and percentages were used to summarise client demographics and service utilisation indicators, while cross-tabulations with column percentages and 95% CIs were used to describe the distribution of gestational age at presentation across age groups and geographic regions. Approximately 1% of missing data were excluded from analyses.

To explore factors associated with gestational age at presentation, unadjusted ordinal logistic regression models were fitted with gestational age (3 to 9 weeks) as the ordered dependent variable. Independent variables included age group and geographic location which was recategorised into three zones (Southeastern (including Accra), Central (including Kumasi) and Northern & Southwestern (covering rural expansion regions)) in line with the scaled telemedicine model geographic focus. To enhance interpretability and mitigate sparse cell issues in early gestation data, gestational age was grouped into three bands: <5 weeks, 5–6 weeks and 7+ weeks.

To assess predictors of PAFP uptake, unadjusted binary logistic regression models were used with PAFP uptake (yes/no) as the outcome. PAFP was offered to all telemedicine clients and uptake was captured as the selection of a PAFP method to be delivered as part of their EMA telemedicine package (not at or following initiation of the selected contraceptive method). Explanatory variables included age group, gestational age group and geographic location.

Unadjusted models were used due to the limited availability of consistently reported covariates across datasets and the exploratory nature of the analysis, which aimed to describe associations rather than infer causality. For all models, ORs, 95% CIs and p values were reported. Analyses were conducted in R (version 4.3.3).

Qualitative interviews & analysis

To enhance transparency and rigour, the qualitative methods have been reported in accordance with the COREQ (Consolidated Criteria for Reporting Qualitative Research) 32-item checklist.¹²

Research team

Authors MR and EM conducted the qualitative interviews, along with three trained local research assistants. All interviewers were female and held at minimum an advanced degree in public health, sociology or a related degree. MR and EM were employed by MSI at the time of data collection but not directly involved in the implementation of the telemedicine model. The three local research assistants were consultants who had previously worked with MSIG data collection for client exit interviews and so were familiar with MSIG’s service provision and had previously undergone a Values Clarification and Attitudes Transformation (VCAT) training.

Theoretical framework

The qualitative component of this study was guided by the Consolidated Framework for Implementation Research (CFIR).¹³ The CFIR provides a comprehensive structure for identifying contextual, organisational and individual factors that influence the implementation and uptake of health innovations. Its five domains (intervention characteristics, outer setting, inner setting, characteristics of individuals and implementation process) offered a theoretical lens through which to explore the feasibility, acceptability and contextual dynamics of the expanded telemedicine model for SRH services in Ghana. This framework was selected to ensure that the analysis captured both system-level and behavioural determinants relevant to scaling digital health interventions in resource-constrained settings.

Participant selection

Purposive sampling was used to select participants for the qualitative interviews, including clients, healthcare providers and key stakeholders, who could provide rich insights into telemedicine experiences and perspectives. Sampling criteria included a diversity in age and geographic location to capture a range of perspectives. In addition, for the subsample of telemedicine contraceptive services, we ensured a representation of all types of contraceptive services. A total of 18 in-depth interviews (IDIs) were completed with MSIG clients accessing EMA (n=13), contraceptive services (n=3) and fertility evaluation (n=2) through telemedicine. Of note, given the limited total number of fertility evaluation and Sayana Press contraceptive services via telemedicine in 2024, this IDI subsample was not geographically diverse as initially planned in the research protocol (Table 4).

A total of two (2) focus group discussions (FGDs) with MSIG telemedicine providers, contact centre agents were completed and centre providers. Contact centre agents manage the incoming contacts to MSIG’s hotline which is the first point of contact for telemedicine clients, as well as screen for eligibility for telemedicine, book the virtual provider consultation and administer the 7-day follow-up calls. Five (5) key-informant interviews (KIIs) with MSIG current and former staff who were directly involved in the planning and expansion of the telemedicine model were also completed.

This manuscript reports findings exclusively from the IDIs with telemedicine clients to provide a detailed examination of clients’ lived experiences and perceptions of telemedicine-delivered sexual and reproductive health services. Other components of the evaluation were designed primarily to inform operational learning and are not reported here.

Participant recruitment

All telemedicine clients who were successfully reached for their 7-day clinical follow-up call were asked if they would be willing to be contacted for research purposes. Those who agreed were later called by research assistants, who provided a full explanation of the study and were informed of the researcher’s institutional affiliation, purpose of the study and interest in understanding their experiences to improve public health practices. For those who verbally reported that they were interested in continuing with the interview, participants received an explanation of the study objectives, procedures, potential risks and benefits, confidentiality measures and their right to withdraw at any time. Informed consent to participate in the phone-based interview was then obtained verbally and recorded at the start of the interview. Among the selected list of clients to contact for interviews, 5 were not reachable (did not answer the call after 3 attempts) and for an additional one call was interrupted due to connectivity issues, and the patient did not respond to the callback.

Data collection

Data collection for the qualitative interviews was completed across all telemedicine service provision areas—Accra, Kumasi and Northern Region—between February and March 2025. A virtual interview appointment was scheduled with clients who agreed to take part in the study. They were given the option of a video interview via Teams or being contacted by telephone at an agreed time by a research assistant. All participants preferred to be interviewed via telephone and interviews were conducted in English and other local languages (mainly Twi), based on the patient’s preference. Participants were asked if they were in a private and comfortable place before continuing the interview. The participants were also assured that their responses would be kept confidential and that their participation would not affect the services they receive from the health facility.

A semistructured interview guide was used to guide everyone—in-depth interview. The guide covered the objectives of the interview, assurance of a private environment, background interview information, overall experience of telemedicine service use, accessibility and overall satisfaction of their telemedicine service, suggestions for improvements and final reflections. The interview guides were adapted to be relevant to each type of telemedicine service.

Interviews took on average 25–40 min and were audio recorded. Structured note-taking templates were also developed and used to capture notes during the interviews and support regular debrief sessions with the interviewers, including reflections on whether saturation was being reached. All participants were compensated 150 GHS (equivalent to approximately US$10) for their time, which was sent by Mobile Money following the interview.

Data analysis

Following data collection, interviews were transcribed verbatim and translated into English if conducted in Twi (one interview). The translated transcript was then back-translated to assure fidelity. Two researchers (MR, EM) conducted a thematic analysis, informed by the CFIR.¹³ The CFIR domains guided the development of the initial codebook and structured the analytic process, enabling systematic exploration of factors influencing the feasibility and acceptability of the telemedicine model. Transcripts were coded deductively using CFIR constructs while allowing for iterative inductive refinement of subcodes to capture emergent themes and contextual nuances (eg, courier communication, digital literacy barriers). This hybrid analytical approach grounded the interpretation in a well-established implementation science framework while remaining responsive to the data. The resulting themes were organised across the five CFIR domains to illustrate multilevel influences on service delivery and client experience, with a particular focus on implications of the expansion in service offering and to rural locations.

Qualitative data were managed and analysed using Delve (Delve Research Ltd, accessed January 2025, www.delvetool.com), a cloud-based qualitative data analysis platform designed to support collaborative coding, thematic analysis and framework-based qualitative approaches. Coding was performed by two independent research team members (MR, EM) with debriefs as needed to resolve discrepancies. Thematic validity was checked through reflection and validation with select operational stakeholders (see online supplemental file 1 for the author’s reflexivity statement).

Ethics

The independent Ethical Review Committee MSI Reproductive Choices, based in the UK, reviewed and approved the study protocol. The researchers also secured local ethical approval from the Ghana Health Service Ethics Review Committee.

All participants provided informed consent prior to participation. Participation was voluntary, and participants were informed of their right to decline or withdraw at any time without penalty or impact on access to services. Measures were taken to ensure privacy and confidentiality, including anonymisation of interview transcripts and secure storage of all data on password-protected systems accessible only to the research team. In-depth interview participants received modest compensation (equivalent to US$10) to reimburse time.

Patient and public involvement statement

No funding was available for the involvement of clients or the public in the design, conduct or manuscript development of our research. Nevertheless, we spoke to the clients directly as part of the qualitative data collection and asked them to input into our dissemination aims at the end of the interviews. Furthermore, results will be disseminated to the public through media and a report for the GHS. Findings will also be shared directly with patient research participants who provided their consent to be recontacted for sharing the research results.

Results

Quantitative analysis

Sample characteristics

A total of 2721 clients received a range of SRH services via telemedicine in 2024. The majority accessed EMA (70.0%; 1904/2721), followed by STMs (29.5%; 804/2721) such as injectables, emergency contraception (EC) and Sayana Press. Fertility consultations were low, with only 14 (0.5%) services recorded.

Clients accessing EMA via telemedicine were predominantly women aged 20–29 (66.2%; 1260/1904), though a meaningful number of women over 30 (31.5%; 600/1904) also engaged with the service, indicating its cross-age demographic appeal. However, only a minority of clients were adolescents less than 20 years of age (2.3%; 44/1904), likely reflective of the marketing to university-aged populations and older due to the minimum age limit of 18 years for accessing the service.

Safety outcomes

Just over half of EMA clients (55.1%; 1049/1904) were reached for their 7-day follow-up. Among these EMA clients, 96.9% (1016/1049) reported complete abortion with no additional clinical intervention required (table 2).

Table 2. Early medication abortion outcomes and follow-up completion rates.

	%	Base (n)
Total SRH telemedicine services	–	2721
EMA services	70.0	2721
Follow-up completed	55.1	1904
Decided not to take medication abortion pills	2.7	1049
Took medication abortion pills as instructed	99.7	1021
Able to effectively manage pain and bleeding	96.3	1021
Complete abortion, not requiring clinical intervention	96.9	1049
Referred for non-urgent follow-up care	0.2	1049
Referred for urgent follow-up care	0.1	1049

EMA, early medication abortion; SRH, sexual and reproductive health.

Service utilisation patterns

Utilisation has steadily increased since the launch of Telemedicine in 2021, with uptake accelerating following service optimisation efforts in the post-pilot scale-up phase. During the 2024 service expansion, overall, EMA service numbers remained relatively stable with limited uptake of services in the expansion locations of Northern and Southwestern Ghana (figure 1a). Short-term methods were the most accessed after EMA, particularly injectables (64.0%; 515/804) and emergency contraception (EC) (36.0%; 289/804). Notably, no clients used oral contraceptive pills as a standalone telemedicine service.

Figure 1. Telemedicine uptake by location and service type. EMA, early medication abortion; STM, short-term contraceptive method.

Most EMA clients contacted the service between 4 and 6 weeks’ gestation—26.3% (501/1904) at 4 weeks, 31.5% (600/1904) at 5 weeks, and 22.3% (425/1904) at 6 weeks. Fewer clients reached out at 7 weeks or more (15.7%; 299/1904), and very few engaged before 4 weeks (4.4%; 84/1904). In the unadjusted ordinal logistic regression models, age group was not significantly associated with gestational age at presentation. Similarly, no significant differences were observed in gestational age at presentation across different geographic locations (table 3).

Table 3. Telemedicine early medication abortion service uptake and post-abortion family planning rates by age, location and gestational age.

	OR (95% CI)	P value
Gestational age at EMA service uptake by client characteristics
Age group
<20 years (ref)	1.00	–
20–24	0.8 (0.5 to 1.4)	0.414
25–29	0.7 (0.4 to 1.2)	0.163
30+ years	0.7 (0.4 to 1.2)	0.162
Region
Southeastern (ref)	1.0	–
Central	1.5 (0.7 to 1.5)	0.818
Northern+Southwestern	0.7 (0.4 to 1.3)	0.308
PAFP uptake by client characteristics
Gestational age
<5 weeks (ref)	1.0	–
5–6	0.9 (0.7 to 1.1)	0.392
7+ weeks	0.8 (0.6 to 1.1)	0.228
Age group
<20 years (ref)	1.0	–
20–24	1.1 (0.6 to 2.4)	0.780
25–29	1.1 (0.5 to 2.3)	0.903
30+ years	0.8 (0.4 to 1.7)	0.491
Region
Southeastern	1.0
Central	1.4 (0.8 to 2.1)	0.219
Northern+Southwestern	1.7 (0.8 to 3.4)	0.120

EMA, early medication abortion; PAFP, post-abortion family planning.

Overall, PAFP uptake was 24.8% (472/1904). While uptake appeared higher among clients in more rural regions (Central (30.6%; 583/1904) and Northern+Southwestern (36.1%; 687/1904) compared with the Southeastern region including Accra (24.7%; 470/1904)), these differences were not statistically significant (figure 1b). Clients presenting at 7 weeks or later had lower odds of adopting PAFP compared with those presenting before 5 weeks, though this association was non-significant with uptake rates of 23.0% (438/1904) and 26.6% (506/1904) respectively. No significant association was found between age group and PAFP uptake in unadjusted models (table 3).

Conversion data highlighted opportunities to improve continuity of care. Of initial client inquiries, 46% (3107/6720) led to confirmed Telemedicine appointment, and 61% (1904/3107) of those proceeded to service completion. This funnel reflects strong interest in the model but also areas to enhance communication and support through the decision-making process.

Client preferences and service satisfaction

The Telemedicine model continues to expand access for clients who may otherwise have had limited or no options for care. In 2024, 48.8% (83/170) of users reported in the client feedback survey they did not know of another way to access the service—an increase from 42.0% (86/205) in 2023 (50/154) and 38.3% in 2022. This is potentially reflective of the expansion into more rural and underserved areas in Ghana.

Client satisfaction remained high. In follow-up surveys, 88.1% (151/170) of EMA clients rated the medication instructions as ‘very helpful,’ 89.4% (152/170) said they would recommend the service to others, and 78.2% (133/170) reported they would choose Telemedicine again for future EMA needs. An additional 9.4% (16/170) had no preference, and only 12.4% (21/170) said they would prefer in-person care.

Qualitative interviews

Eighteen (18) women aged 22–32 years who had accessed EMA (n=13), short-term contraceptives (n=3) and fertility evaluation (n=2) services through MSIG’s telemedicine platform participated in the IDIs.

Participants were geographically distributed across Greater Accra (n=7), Kumasi in the Ashanti Region (n=4) and the Northern Region (n=7). EMA users were represented in all three regions, with the largest proportion from the Northern Region. Short-term contraceptive users were recruited from Greater Accra and Kumasi, while fertility evaluation participants were recruited from Greater Accra only. Table 4 summarises the distribution of participants by service type and region.

Table 4. Distribution of IDI participants by service type and region (n=18).

Service type	Greater Accra	Ashanti region	Northern region	Total
Early medical abortion (EMA)	3	3	7	13
Short-term contraceptives	2	1	0	3
Fertility evaluation	2	0	0	2
Total	7	4	7	18

IDI, in-depth interview.

Perceived value and motivation for telemedicine use

Most clients viewed telemedicine as a convenient, safe and discreet alternative to in-person care. Across abortion, contraception and fertility services, telemedicine was valued for enabling care without needing to travel, reducing social stigma and facilitating privacy in sensitive decisions. Clients consistently emphasised the importance of being able to manage their SRH needs from home. One user remarked, “It was just about reaching out to make inquiries, go about the payment, and everything. I just like how seamless it was… someone calls you; they give you a specific time, and then it’s always on time. So, I found it stress-free.”—EMA client.

However, some clients expressed hesitance about self-managing care without face-to-face interaction, especially where previous experiences with healthcare had emphasised the role of direct provider oversight. These users often expressed a preference for provider reassurance, access to facility-based care for an ultrasound prior to using the EMA telemedicine service, or additional support.

Patient needs, privacy, and self-efficacy

Clients frequently linked their use of telemedicine to an unmet need for privacy, confidentiality and discretion. This was particularly pronounced among EMA clients, many of whom cited telemedicine as the only viable option to avoid stigma or judgement. Privacy was often described as non-negotiable: “I just didn’t want anyone to know. And with this, I could do it in my room.”—EMA client.

Others emphasised the need for discretion within their households: “I was in the village, and I didn’t want people to ask too many questions, so delivery was perfect.”

Self-efficacy also played a key role in client decision-making. Many users expressed confidence in their ability to follow instructions, manage pain and self-administer medications or injections. “I was prepared… she advised that I take the pain pills 30 minutes before, and I did that,” one EMA client respondent shared. However, this confidence was often contingent on clear instructions and perceived access to support. Where information was lacking or pain exceeded expectations, self-efficacy diminished, sometimes prompting facility visits or second opinions.

Communication and support experiences

Experiences with service communication were mixed. Some clients praised the empathy, clarity and patience of the consulting midwives, with comments such as: “It was relaxing, like talking to a friend.”—fertility evaluation client.

Others described missed calls, delivery miscommunication or frustration with slow WhatsApp response times. One EMA client shared, “The person I spoke to said they would call me… but they didn’t.” Another reflected, “When you send a message today, and the next day you have to explain everything again – that was something else.”—EMA client.

Delivery logistics and follow-up were similarly inconsistent. While some reported prompt delivery and clear packaging, others described delays, poor communication from riders or unexpectedly high delivery fees. “I didn’t know it would come from Accra. If I had known, I would have picked it up myself,” said one EMA client. Another added, “It took about three days… I was eager and felt it was delaying.”—EMA client.

Pain and side effects: expectations vs reality

Pain and side effects were under-recognised in the client education process. While some clients reported being adequately prepared and managing symptoms with painkillers, others experienced unexpected or severe pain, prolonged bleeding or confusion about what constituted a normal reaction. “The pain wasn’t necessarily abdominal… my gums were hurting. I was feverish,” an EMA client respondent shared. Another said, “I expected to go on with my normal activities… but I had chills, fever, and vomiting. It was not very comfortable.”—EMA client.

The absence of follow-up or real-time support in these cases contributed to anxiety and, in a few cases, emergency visits.

Digital divide and informal entry points

Telemedicine access was predominantly facilitated through smartphones and internet-based platforms. Users with digital literacy and strong self-navigation skills fared well. “I just went online, googled (the service provider), and reached out via WhatsApp,” one STM client explained. However, those with limited access to data, digital devices or familiarity with online health services may struggle to discover or engage with care.

Informal entry points were critical. Many users discovered the service via Google, social media (TikTok, Facebook) or word-of-mouth. Peer referrals, especially from friends who had previously used the service, were an important trust-building mechanism. “My cousin had a pregnancy test there and said it was good, so I tried it too,” one EMA client respondent shared.

Marketing, public awareness and service perceptions

Most participants knew of the telemedicine service for abortion care, with limited awareness of its broader reproductive health services. Despite social media efforts to promote the other service options, respondents consistently advocated for more diverse and targeted marketing approaches.

“Take advantage of the market centres. Use billboards and educate women with messages that speak to their needs,” one EMA client respondent suggested. Another added, “social media is good, but not everybody is on it. Use local information centres with megaphones – especially in the rural areas.”—EMA client.

Discussion

This mixed-methods evaluation highlights the feasibility, acceptability and clinical promise of a scaled telemedicine model for SRH services in Ghana. The telemedicine model continued to demonstrate strong safety performance, in line with the pilot evaluation.⁹ The findings also show encouraging levels of early engagement with the EMA service. Similar to experiences in Nepal, most users in Ghana sought telemedicine care within the first 6 weeks of gestation, suggesting that well-structured remote counselling can facilitate timely access despite geographic barriers and is an acceptable to users.¹⁴ In this telemedicine client population, there was moderate uptake of PAFP, with higher uptake observed among clients in more rural areas. However, no statistically significant associations were found between gestational age at presentation or PAFP uptake and key demographic characteristics such as age or location, suggesting the need to explore additional factors—such as client attitudes, counselling quality and social norms—in shaping outcomes. These findings support growing global evidence that clients can safely and effectively navigate EMA care independently and the utilisation patterns are broadly consistent with findings from other LMIC settings, where early gestational presentation and high acceptability have been observed following the introduction of telemedicine EMA services.610 14,16

Client-reported data point to the model’s effectiveness in delivering EMA services safely and acceptably, although this data was limited due to loss-to-follow-up (~45%). Importantly, a majority of clients felt confident in managing their care, with self-efficacy closely linked to the clarity of information and the quality of counselling received. These results mirror evidence from Kenya and South Africa, where remote consultation models improved client confidence, strengthened abortion seekers’ autonomy and agency and reduced perceived stigma compared with in-clinic care.^{17 18} These findings underscore the centrality of communication quality in digital SRH interventions. Strengthening recontact strategies remains a key area for further improvement and innovation to ensure that those clients who would benefit from a follow-up touchpoint or may require additional care can access this.

The qualitative analysis reinforces these conclusions and offers deeper insight into how telemedicine can advance reproductive autonomy. Clients repeatedly emphasised the model’s convenience, privacy and flexibility—particularly in contexts of stigma, interpersonal violence or limited mobility. For many, the ability to manage their abortion discreetly at home was described as empowering and transformative. These experiences echo broader literature on the role of telehealth in promoting client-led care and expanding access to safe abortion and contraception.^{6 16 18} The Ghana experience contributes to this growing body of evidence by demonstrating how a unified telemedicine platform can feasibly deliver multiple SRH services, while maintaining high levels of satisfaction and safety. However, further model adaptations are needed to ensure a higher scale of awareness and service provision in the more rural northern and southwestern region telemedicine sites.

Several implementation challenges emerged that require attention to ensure equitable and sustainable scale-up. First, the digital divide shaped access. Specifically, clients with higher digital literacy and access to devices navigated the service with ease, while others faced barriers related to connectivity, phone ownership or unfamiliarity with digital platforms. Offline engagement strategies—such as community health worker referrals, partnerships with local clinics or walk-in information points—may help close this access gap. These implementation barriers are not unique to Ghana. Across LMIC telemedicine studies, digital access and literacy consistently emerge as key determinants of service uptake and equity.6,819 20 Addressing these challenges through hybrid models that combine digital and community-based outreach may therefore be essential to ensuring that telemedicine enhances, rather than exacerbates, existing inequities.

Second, many clients continued to view the service as abortion-specific, limiting uptake of broader SRH services such as contraception and fertility counselling. In particular, the low uptake of fertility evaluation services may reflect limited awareness of their availability or uncertainty about their relevance within a telemedicine model. Clearer communication regarding the scope, benefits and appropriateness of fertility evaluation via telemedicine—integrated more prominently within service information and counselling pathways—may help improve awareness and utilisation of fertility-related services. Furthermore, despite ongoing social media efforts, the telemedicine model lacked unified branding and service visibility. Participants recommended expanding outreach through traditional media, community activations and peer influencer networks, with messaging tailored to different demographics and geographic contexts. Improving brand awareness and clarifying the full scope of services will be key to expanding engagement and normalising telehealth for SRHR.

Taken together, these findings demonstrate that key aspects of telemedicine service design-particularly discretion, responsiveness and flexibility-strongly influence uptake in Ghana’s SRHR context. The service’s ability to reduce stigma and logistical burdens for clients was repeatedly cited as a major advantage. In a context where facility-based care may feel unsafe or socially fraught, being able to “be in the comfort of your home and call; a nurse will attend to you” is transformative. Our findings align with global telehealth evidence showing that telemedicine can deliver safe, client-centred SRH care when supported by robust communication, privacy safeguards and responsive follow-up systems. This expanded SRH telemedicine model adds new insight by demonstrating how these principles can be applied in a multi-service platform within a lower-resource setting, offering lessons for scaling integrated telehealth interventions in sub-Saharan Africa and beyond.

Study limitations

This was an evaluation of a targeted, expanded telemedicine pilot intervention, geographically limited to three zones in Ghana, including two more rural regions. As such, findings may not be generalisable to national implementation or to different regional or demographic contexts. Any future scale-up should account for contextual factors such as local levels of digital literacy, mobile phone access and the availability of supporting infrastructure critical for the success of a telemedicine-based EMA service.

While this study focused on service feasibility and client outcomes, a formal cost-effectiveness analysis was beyond its scope. Future research should incorporate economic evaluation components to better assess the efficiency and sustainability of telemedicine models in resource-limited settings.

A substantial proportion (45%) of clients were unreachable during the post-service clinical follow-up attempt conducted 6–7 days after medication administration. The experiences and outcomes of these clients remain unknown, which introduces the potential for non-response bias. While we might expect that clients experiencing adverse outcomes would be more likely to engage in follow-up or initiate contact with the service, this assumption cannot be confirmed and may underestimate complications or dissatisfaction among non-responders.

The pilot also relied on the implementation of parallel monitoring tools—including a patient feedback form and a courier tracking system—which were not integrated into existing data systems. These separate data streams required additional human resources to maintain and posed challenges for data triangulation. At scale, such system fragmentation could increase reporting burdens and compromise data consistency. MSIG is actively exploring opportunities to integrate telemedicine monitoring within its routine health information systems to address this challenge.

An additional limitation is that outcome measures—such as abortion completion and PAFP uptake—were based on self-reported data collected during follow-up calls. These outcomes were not clinically validated or biologically confirmed, which may affect their accuracy. However, prior research indicates that individuals can reliably self-assess abortion completion, particularly when supported by structured questioning from a trained provider or counsellor.²¹ In the case of PAFP, the data reflect method acceptance at the time of service rather than verified uptake or sustained use, limiting the conclusions that can be drawn about longer-term contraceptive impact. Future research should incorporate mechanisms for tracking sustained use, method satisfaction and long-term outcomes.

Additionally, while unadjusted analyses provide useful exploratory insights, more robust multivariable models are needed to assess the independent effects of demographic, service-level and behavioural factors on outcomes. Potential confounding factors, such as socioeconomic status, parity or previous abortion experience, were not controlled for, and therefore, observed associations should be interpreted with caution.

Finally, given that several authors were affiliated with the implementing organisation, we recognise the potential for institutional perspectives to influence interpretation of findings. Efforts were made to ensure reflexivity throughout the research process, including independent data verification, joint interpretation with external collaborators and explicit consideration of researcher positionality during analysis and manuscript drafting.

Conclusions

Together, these findings demonstrate that telemedicine is a promising and client-centred model for delivering SRH services in Ghana. When designed around discretion, responsiveness and flexibility, telemedicine can expand access, reduce stigma and empower clients to manage their care on their own terms. To maximise its impact, future scale-up efforts must address remaining access inequities, strengthen communication systems and ensure integration into existing monitoring frameworks for health services in Ghana. Further research is needed to explore long-term outcomes, assess cost-effectiveness and evaluate the potential of telemedicine to deliver a broader package of SRH services beyond abortion care.

Data availability statement

Data are available upon reasonable request.