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Despite progress over the last decade, there is a continuing unmet need for contraception in Cambodia. Interventions delivered by mobile phone could help increase uptake and continuation of contraception, particularly among hard-to-reach populations, by providing interactive personalized support inexpensively wherever the person is located and whenever needed.
The objective of this study was to evaluate the cost-effectiveness of mobile phone–based support added to standard postabortion family planning care in Cambodia, according to the results of the MOTIF (MObile Technology for Improved Family planning) trial.
A model was created to estimate the costs and effects of the intervention versus standard care. We adopted a societal perspective when estimating costs, including direct and indirect costs for users. The incremental cost-effectiveness ratio was calculated for the base case, as well as a deterministic and probabilistic sensitivity analysis, which we compared against a range of likely cost-effectiveness thresholds.
The incremental cost of mobile phone–based support was estimated to be an additional US $8160.49 per 1000 clients, leading to an estimated 518 couple-years of protection (CYPs) gained per 1000 clients and 99 disability-adjusted life-years (DALYs) averted. The incremental cost-effectiveness ratio was US $15.75 per additional CYP and US $82.57 per DALY averted. The model was most sensitive to personnel and mobile service costs. Assuming a range of cost-effectiveness thresholds from US $58 to US $176 for Cambodia, the probability of the intervention being cost-effective ranged from 11% to 95%.
This study demonstrates that the cost-effectiveness of the intervention delivered by mobile phone assessed in the MOTIF trial lies within the estimated range of the cost-effectiveness threshold for Cambodia. When assessing value in interventions to improve the uptake and adherence of family planning services, the use of interactive mobile phone messaging and counselling for women who have had an abortion should be considered as an option by policy makers.
ClinicalTrials.gov NCT01823861; https://clinicaltrials.gov/ct2/show/NCT01823861
Contraception provides significant benefits for the health of women and children, as well as substantial social and economic benefits [
In Cambodia, over the last decade, progress has been made in reducing an unmet need for contraception. This has coincided with a reduction in maternal, infant, and under-5 mortality [
Interventions delivered by mobile phone could help increase uptake and continuation of contraception, particularly among hard-to-reach populations [
The MOTIF (MObile Technology for Improved Family planning) trial evaluated an intervention delivered by mobile phone to provide postabortion family planning support to women who received safe abortion at Marie Stopes International Cambodia (MSIC) clinics [
The MOTIF intervention was effective at increasing uptake of long-acting reversible contraceptive methods (subdermal implant and intrauterine device [IUD]), which are associated with lower discontinuation rates compared with those of short-acting hormonal methods [
We conducted a cost-effectiveness evaluation comparing a mobile phone–based intervention in addition to standard postabortion family planning care with standard care alone, using the results of the MOTIF trial. The methods and results of this trial have been previously published [
Conceptual framework for the service provision model based on the MOTIF trial. Inputs from the MOTIF trial are shown in green. Models used to derive costs and effects are shown in yellow. IUD: intrauterine device; MOTIF: MObile Technology for Improved Family planning; OCP: oral contraceptive pill.
We constructed a model to simulate total contraceptive and abortion services obtained for a single cohort of 1000 women after abortion in the intervention and control arms, using Excel 2016 (Microsoft Corp, Redmond, Washington). This design was chosen to link the empirical service usage data from the MOTIF trial (monthly services per user) to the Impact2 model (annual services per 1000 users). No discounting was applied to costs, because these were modelled to occur during 1 year.
Monthly service provision parameters were taken from 66% (328/500) of participants remaining in the study at the end of the 12-month follow-up period. Previously published MOTIF findings showed that missing data had a negligible effect on the contraceptive method mix at 12 months [
Service provision model parameters.
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Base | Deterministic range (95% CI) | Probabilistic distribution | ||||
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Oral contraceptive pill | 2172 | 2013-2330 | Lognormal | |||
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Injectable | 558 | 512-604 | Lognormal | |||
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Implant | 172 | 123-220 | Lognormal | |||
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IUDb | 112 | 72-153 | Lognormal | |||
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Repeat abortion | 47 | 21-91 | Beta | |||
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Oral contraceptive pill | 3308 | 3112-3499 | Lognormal | |||
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Injectable | 325 | 291-358 | Lognormal | |||
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Implant | 75 | 42-109 | Lognormal | |||
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IUD | 63 | 32-93 | Lognormal | |||
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Repeat abortion | 69 | 35-120 | Beta |
aPer 1000 participants per year.
bIUD: intrauterine device.
Effects were estimated using the Marie Stopes Impact2 (version 4) modelling tool (illustrated in
Marie Stopes International Impact2 model framework. Inputs, outputs, and processes used in the Impact2 model are illustrated, as they apply to this study. Green: inputs to the model from the MOTIF trial. Yellow: effects reported in this study. Adapted from Weinberger et al [
The base case analysis was performed from a societal perspective. Costs were collected in 2014 in US dollars (commonly used in Cambodia) and were expressed in constant 2011 purchasing power parity-adjusted US dollars.
For MSIC clinics, provider costs included medical consumables, personnel, and estimates of the time taken to provide each service. To account for overheads, 20% was added to personnel costs. For non-MSIC clinics, costs for personnel and overheads were not available, and commodity costs were assumed to be the same as those at MSIC clinics. Costs attributable to the intervention included airtime to deliver the mobile phone–based intervention and a proportion of fixed costs (computers and phones). MSIC personnel costs for training and delivery of the intervention were estimated from hourly wages and time spent on the intervention.
User costs included direct medical costs (service fees), direct nonmedical costs, and indirect costs of attending postabortion family planning services for the proportion of women who attended a separate appointment after their initial abortion. The average home-clinic round trip distance was multiplied by the per kilometer average price of motorcycle transport to obtain transport costs. If the client visited a different clinic, the estimated distance was reduced by one-third. Indirect costs to users were attributed to all women irrespective of formal employment status [
Unit costs.
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Base | Deterministic rangea | Probabilistic distribution | Comment/source | ||
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Airtime: voice messages | 0.79 | 0.39-1.18 | Gamma | Actual costs from the MOTIF study | |
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Airtime: outgoing phone calls | 2.16 | 1.08-3.25 | Gamma | Actual costs from the MOTIF study | |
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Computer | 1.34 | 0.67-2.01 | Gamma | Actual costs from the MOTIF study | |
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Phone | 0.2 | 0.1-0.3 | Gamma | Actual costs from the MOTIF study | |
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Oral contraceptive pill (one cycle) | 0.29 | 0.15-0.44 | Gamma | Direct cost reported by an MSICe clinic | |
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IUDd | 0.4 | 0.2-0.6 | Gamma | Direct cost reported by an MSIC clinic | |
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Medical abortion (Mariprist) | 0.7 | 0.35-1.05 | Gamma | Direct cost reported by an MSIC clinic | |
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Surgical abortion | 5 | 2.5-7.5 | Gamma | Personal communication with MOTIF trial authors | |
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Injectable contraceptive (one dose) | 0.5 | 0.25-0.75 | Gamma | Direct cost reported by an MSIC clinic | |
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Implanted subdermal contraceptive (Femplant) | 8 | 4-12 | Gamma | Direct cost reported by an MSIC clinic | |
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Long-acting contraceptive device removal | 3 | 1.5-4.5 | Gamma | Personal communication with MOTIF trial authors | |
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Midwife/health care service provider | 2.36 | 1.18-3.54 | Gamma | Direct cost reported by an MSIC clinic | |
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Counsellor | 2.52 | 1.26-3.78 | Gamma | Direct cost reported by an MSIC clinic | |
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IUDd insertion | 5 | 2.5-7.5 | Gamma | Direct price to users reported by an MSIC clinic | |
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Implant insertion | 25 | 12.5-37.5 | Gamma | Direct price to users reported by an MSIC clinic | |
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Injectable (MSIC clinic) | 1 | 0.5-1.5 | Gamma | Direct price to users reported by an MSIC clinic | |
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Injectable (pharmacy) | 0.73 | 0.37-1.1 | Gamma | Direct price to users reported by a local pharmacy | |
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Oral contraceptive pill (MSIC clinic) | 0.4 | 0.2-0.6 | Gamma | Direct price to users reported by an MSIC clinic | |
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Oral contraceptive pill (pharmacy) | 0.37 | 0.19-0.56 | Gamma | Direct price to users reported by a local pharmacy | |
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IUD removal | 2 | 1-3 | Gamma | Direct price to users reported by an MSIC clinic | |
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Implant removal | 3.75 | 1.8-5.63 | Gamma | Direct price to users reported by an MSIC clinic | |
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Repeat abortion (surgical) | 25 | 12.5-37.5 | Gamma | Direct price to users reported by an MSIC clinic | |
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Repeat abortion (medical) | 20 | 10-30 | Gamma | Direct price to users reported by an MSIC clinic | |
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Airtime to call a clinic/hotline (per min) | 0.07 | 0.04-0.11 | Gamma | Advertised cross-network charge in Cambodia | |
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Motorbike travel (per km) | 0.22 | 0.11-0.33 | Gamma | Data from Rozemuller et al [ |
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Average distance from clinic to home (km) | 38.2 | 30.1-46.3f | Gamma | Data from the MOTIF study | |
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Gross national income per capita | 2534 | 2280.6-2787.4g | Gamma | World Bank development data [ |
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Gross daily income per capita | 6.9 | 6.2-7.6g | Gamma | World Bank development data [ |
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Repeat abortion (total household indirect cost) | 5.07 | 2.54-7.61 | Gamma | Data from Potdar et al [ |
aThe range used for deterministic analysis was 50% above and below the base case estimate unless otherwise indicated. This range was then assumed to represent the 95% confidence interval of the distribution indicated for probabilistic sensitivity analysis.
bUnit costs were combined to calculate the service level costs used in the model.
cMOTIF: MObile Technology for Improved Family planning.
dIUD: intrauterine device.
eMSIC: Marie Stopes International Cambodia.
fRange used is the 95% confidence interval from MOTIF data.
gRange used is 10% above and below the base case estimate.
Incremental cost and utility per 1000 participants were calculated by subtracting the estimated cost and each of the measures of effect (CYPs, pregnancies averted, abortions averted, under-5 mortality, maternal mortality, and DALYs) in the MOTIF intervention arm from those in the standard care arm. The incremental cost-effectiveness ratio (ICER) for each measure of effect was calculated by dividing incremental cost by incremental effect.
To estimate the effect of uncertainty, the model was subjected to deterministic and probabilistic sensitivity analyses [
The probabilistic sensitivity analysis consisted of a Monte-Carlo simulation with 1000 iterations randomized according to the probability distribution of each parameter. Contraceptive use outcomes for each iteration were inputted to the Impact2 model to produce the joint probability distribution for effects. Uncertainty introduced through the Impact2 model itself was not included, because information about parameters used in the Impact2 model was not available. Simulation results for ICERs assessed using CYPs and DALYs were plotted on the cost-effectiveness plane, and the cumulative probability for cost-effectiveness across a range of cost-effectiveness thresholds was visualized as a cost-effectiveness acceptability curve (CEAC) [
To understand the relevance of the cost-effectiveness analysis to decision makers, the results of the base case and sensitivity analyses were compared with the likely range of cost-effectiveness thresholds. Ochalek et al have described a method for empirically deriving cost-effectiveness thresholds in low- and middle-income countries, along with their estimate for a list of countries. The estimated cost-effectiveness threshold for Cambodia using this method ranged from US $58 to US $176 or 12%–35% of the gross domestic product per capita [
To understand the health financing implications of reducing or removing user fees, two scenario analyses were conducted to model the effect on costs from user and provider perspectives. Because user fees represent a transfer from users to providers, from a societal perspective, the net direct effect on costs is zero. For users, we calculated the average estimated cost per client in each scenario. For providers interested in the effect of user fees on cost-effectiveness, we calculated the estimated ICER from the provider perspective.
The incremental cost of mobile phone–based support from a societal perspective over a 12-month period was an additional US $8160.49 per 1000 clients, and it is reported along with costs to providers and users in
Base case cost and effect results for the MOTIF (MObile Technology for Improved Family planning) intervention versus standard of care.
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Intervention | Standard care | Incremental value | |
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Provider | 4079.74 | −1625.20 | 5704.94 |
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User | 15,906.83 | 13,451.28 | 2455.55 |
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Total | 19,986.56 | 11,826.07 | 8160.49 |
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Couple-years of protection | 1350.6 | 832.6 | 518.0 |
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Pregnancies avertedb | 441 | 260 | 180 |
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Abortions avertedb | 251 | 148 | 103 |
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U5c mortalities avertedb | 3 | 2 | 1 |
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Maternal mortalities avertedb | 0 | 0 | 0 |
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DALYsd averted | 241.6 | 142.8 | 98.8 |
aCosts and effects are calculated per 1000 users.
bRounded to the nearest whole.
cU5: under five.
dDALYs: disability-adjusted life-years.
Base case incremental cost-effectiveness ratio (ICER) results for the MOTIF (MObile Technology for Improved Family planning) intervention.
Effect | ICER (US $ per unit of effect) |
Couple-years of protection | 15.75 |
Pregnancies averted | 45.22 |
Abortions averted | 79.33 |
U5a mortalities averted | 7659.96 |
Maternal mortalities averted | —b |
DALYsc averted | 82.57 |
aU5: under five.
bNo maternal mortalities were estimated to have been averted in either arm; therefore, no ICER calculation is possible.
cDALYs: disability-adjusted life-years.
Results of the deterministic sensitivity analysis are presented as a tornado plot in
Tornado plot of deterministic sensitivity analysis using MOTIF intervention model parameters. For each parameter, the ICER was recalculated taking the upper and then lower deterministic range value. ICER ranges are centered on the ICER point estimate of US $82.57 per DALY averted. DALYs: disability-adjusted life-years; ICER: incremental cost-effectiveness ratio; IUD: intrauterine device; MOTIF: MObile Technology for Improved Family planning; MSIC: Marie Stopes International Cambodia; OC: oral contraceptive.
Simulations recorded for probabilistic sensitivity analysis are presented on the cost-effectiveness plane for DALYs averted and CYPs in
Monte-Carlo simulation results plotted on the cost-effectiveness plane, with effects measured in DALYs averted. Linear demarcations of the upper and lower bounds for the cost-effectiveness threshold for DALYs averted are included for comparison. DALYs: disability-adjusted life-years; MOTIF: MObile Technology for Improved Family planning.
Monte-Carlo simulation results plotted on the cost-effectiveness plane, with effects measured in CYPs. CYPs: couple-years of protection.
Cost-effectiveness acceptability curve derived from Monte-Carlo simulations of MOTIF intervention results, with effects measured in DALYs averted. DALYs: disability-adjusted life-years; MOTIF: MObile Technology for Improved Family planning.
Cost-effectiveness acceptability curve derived from Monte-Carlo simulations of MOTIF intervention results, with effects measured in CYPs averted. CYPs: couple-years of protection; MOTIF: MObile Technology for Improved Family planning.
Average costs from a user perspective and cost-effectiveness from a provider perspective, with either 50% or no user fees, are compared with costs and cost-effectiveness from a societal perspective in
Costs for users and providers in scenarios involving variable user fees.
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Base case | Scenario 1 (50% user fees) | Scenario 2 (no user fees) | Societal perspectivea | |
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Intervention | 15,906.83 | 12,339.41 | 8772.00 | 19,986.56 | |
Standard care | 13,451.28c | 10,864.97 | 8278.66 | 11,826.07 | |
Incremental | 2455.55 | 1474.44 | 493.34 | 8160.49 | |
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Couple-years of protection | 11.01 | 12.91 | 14.80 | 15.75 | |
Pregnancies averted | 31.61 | 37.05 | 42.49 | 45.22 | |
Abortions averted | 55.46 | 65.00 | 74.54 | 79.33 | |
U5e mortalities averted | 5355.02 | 6275.95 | 7196.88 | 7659.96 | |
Maternal mortalities averted | —f | — | — | — | |
DALYsg averted | 57.72 | 67.65 | 77.58 | 82.57 |
aCosts and ICERs from a societal perspective are included for reference. These results remain constant in each scenario, as the user fee represents a transfer from users to providers, but a net zero change from a societal perspective.
bResults are presented as total cost (direct and indirect) from a user perspective and ICER from a provider perspective to reflect the outcome of interest for the respective groups. Changes in demand resultant from the imposition of user fees have not been modelled as part of the scenario analysis.
cUnder standard care with 100% user fees, the program provides income to providers.
dICER: incremental cost-effectiveness ratio.
eU5: under five.
fNo maternal mortalities were estimated to have been averted in either arm; therefore, no ICER calculation is possible.
gDALYs: disability-adjusted life-years.
This study demonstrates that the cost-effectiveness of the intervention delivered by mobile phone assessed in the MOTIF trial lies within the estimated range of the cost-effectiveness threshold for Cambodia. When assessing value in interventions to improve the uptake and adherence of family planning services, the use of interactive mobile phone messaging and counselling for women who have had an abortion should be considered as an option by policy makers. The MOTIF trial demonstrated that women randomized to an intervention delivered by a mobile phone were more likely to use long-acting contraceptive methods. Although these methods are known to be more cost-effective, the results of this study extend the evidence to show that an intervention delivered by a mobile phone favoring these methods is itself cost-effective.
This study has several strengths. Many of the cost and effect parameters are derived from trial and intervention delivery data rather than estimates from the literature, therefore improving the external validity of cost-effectiveness estimates within the Cambodian context. The use of the Impact2 model allows for replicable measurements of effects and comparison across studies. The cost-effectiveness estimates of the base case, the deterministic sensitivity analysis, and 96% of the probabilistic simulations fell within the chosen range of cost-effectiveness thresholds, and the threshold range was drawn from empirically derived cost-effectiveness threshold ranges, which are intended to realistically reflect what health systems are willing to pay [
Another strength of the study lies in the timely and important contribution to the literature linking innovations in mobile phone–based delivery with the delivery of family planning services. With the proliferation of mobile technology in the most rural and remote areas of the globe, there is great opportunity for harnessing mobile technology to reach women with life-saving health information. This study adds to the emerging body of knowledge about how to most effectively and efficiently achieve this aspect.
Deterministic testing indicated that estimated ICERs were particularly sensitive to counsellor personnel costs, estimated as a product of salary and time. However, these time estimates were not collected systematically, and they do not account for a run-in period of lower efficiency. Our estimates are therefore most relevant to a scaled-up intervention or a scenario where support by mobile phone is added to existing activities, for example, an established call center, where run-in time is reduced to a minimum. Process evaluations (unpublished) of the MOTIF trial intervention suggested that the link to a counsellor who could make an appointment if requested was a key to the success of the intervention, so programmatic implementation of a similar intervention should include these components. Although a component of training time was included in costs to deliver the intervention, the cost of ongoing technical support and training was not included. Sensitivity testing also indicated that the proportion of overheads attached to personnel costs produced a large change in ICER in comparison with other parameters. Overheads were not estimated as individual unit costs as part of the study, and thus, the approximation of overheads as a proportion of personnel costs could be improved.
Many of the cost parameters were estimated by personal communication with MOTIF study authors and staff, limiting the external validity of our results in other regions of Cambodia. Further, a range of 50% above and below the point estimate was used for sensitivity analyses. This was intended to capture a broad range of uncertainty in estimated costs, although it still may not accurately represent the cost of family planning services elsewhere in the country.
In the MOTIF trial, contraceptive use outcomes were self-reported by participants. Although this is the standard in family planning research, self-reported measures have been shown to overestimate contraceptive use and are susceptible to recall bias [
The Impact2 modelling tool is based on a number of assumptions linking contraceptive service provision to health outcomes. Although these assumptions are founded in a strong evidence base, the evidence is drawn from the survey data of all women of reproductive age, and it is possible that patterns of contraceptive use and decision-making behavior might differ in a postabortion population. Although the model settings for Cambodia were used and the modelled population was adjusted to match the age distribution of participants in the MOTIF trial, it is possible that differences between the trial population and the population used to inform the Impact2 model, for example, the socioeconomic distribution, might result in errors. The authors of the Impact2 methodology note that estimates of under-5 mortality may be particularly unreliable owing to limited data on linkages among contraception use, birth spacing, and child mortality [
There is extensive related literature in the areas of mobile health (mHealth) and economic evaluation [
With the proliferation of cheap and accessible mobile phones and network access, even in rural and remote locations, there is substantial interest in taking advantage of mobile innovations to aid the delivery of family planning programs. The MOTIF trial intervention, which was recently included as a digital high-impact practice in family planning behavior change, is an example of a scalable mobile innovation [
The sensitivity and scenario analyses included in this study provide useful details for health policy makers. Personnel costs and mobile phone costs have the greatest effects on the cost-effectiveness of the intervention and provide a useful focus for the business case that would accompany a scaled-up mHealth intervention. The cost and effect parameters used in this analysis were collected in a trial environment, whereas modest economies of scale could be achieved with wider implementation, for example, through automation of some call center tasks and bulk pricing agreements with network operators. From a user perspective, removal of user fees for services almost halved the average cost per participant in the intervention group. The effect of user fees on participation in family planning services was assumed to be zero in this study. Although there is likely to be some effect in practice, evidence from low- and middle-income countries suggests that contraceptive services are inelastic with respect to price [
Although this study provides useful evidence to support the cost-effectiveness of the MOTIF intervention, research to test and compare the cost-effectiveness of other interventions for improving the uptake of postabortion family planning services would improve the generalizability of this study to other settings.
This study demonstrates that the use of an intervention delivered by a mobile phone to provide postabortion family planning counselling was cost-effective for increasing CYPs and for preventing pregnancy and abortion. It also provides a basis for further research on how this emerging technology can improve access to family planning services.
Detailed description of the MOTIF intervention.
cost-effectiveness acceptability curve
couple-years of protection
disability-adjusted life-years
incremental cost-effectiveness ratio
intrauterine device
MObile Technology for Improved Family planning
Marie Stopes International Cambodia
We thank all clients and clinic staff who participated in the study. We thank Ly Sokhey, Uk Vannak, Kathryn Church, Anisa Berdellima, and Aisha Dasgupta at Marie Stopes International and Ties Hoomans at LSHTM for comments on previous versions and collecting cost data during the trial.
CS, JM, and JC conceptualized the study; JM and JH performed formal analysis; CS, JM, JH, and JC were responsible for the methodology; JC, CF, and CS supervised the study; JM, JH, and CS prepared the original draft; and JM, JH, JC, CF, and CS reviewed and edited the manuscript.
None declared.