Composition Vendor Newgen KnowledgeWorks (P) Ltd. PLoS One plos plosone PLOS One 1932-6203 Public Library of Science San Francisco, CA USA 10.1371/journal.pone.0321265 PONE-D-24-09524 Research Article Medicine and health sciencesHealth careHealth care facilities Medicine and health sciencesMental health and psychiatry People and placesPopulation groupingsAge groupsChildrenAdolescents People and placesPopulation groupingsFamiliesChildrenAdolescents People and placesGeographical locationsAfricaGhana Social sciencesEconomicsHealth economicsHealth insurance Medicine and health sciencesHealth careHealth economicsHealth insurance Ecology and environmental sciencesNatural resourcesWater resources Physical sciencesPhysicsElectricity Social sciencesEconomicsMacroeconomicsProduction functions Technical efficiency of primary health care facilities in providing adolescent mental, sexual and reproductive health services in Ghana: A case study of selected districts in the Greater Accra Region Technical efficiency of primary health facilities in Ghana Novignon Jacob Conceptualization Data curation Formal analysis Investigation Methodology Validation Visualization Writing – original draft Writing – review & editing 1 https://orcid.org/0000-0001-9367-1265 Fenny Ama Pokuaa Data curation Funding acquisition Investigation Methodology Project administration Validation Visualization Writing – original draft Writing – review & editing Conceptualization 2 * Amenah Michel Adurayi Data curation Formal analysis Investigation Methodology Validation Visualization Writing – original draft Writing – review & editing 3 4 Addom Selasie Conceptualization Methodology Supervision Validation Visualization Writing – original draft Writing – review & editing 3 Gladzah Annick Conceptualization Data curation Formal analysis Methodology Supervision Validation Visualization Writing – review & editing 3 5 Ibrahim Nassirou Conceptualization Methodology Validation Visualization Writing – review & editing 6 7 Tapsoba Ludovic Deo Gracias Visualization Conceptualization Methodology Validation Writing – review & editing 7 8 Agyepong Irene A. Conceptualization Funding acquisition Methodology Project administration Supervision Validation Writing – review & editing 3 5 da Silva Roxanne Borges Conceptualization Funding acquisition Methodology Supervision Validation Writing – review & editing 7 Ensor Tim Conceptualization Funding acquisition Methodology Supervision Validation Visualization Writing – review & editing 9 Centre for Social Policy Studies, University of Ghana, Legon, Ghana Institute of Statistical Social and Economic Research, University of Ghana, Legon, Ghana Faculty of Public Health, Ghana College of Physicians and Surgeons, Accra, Ghana Division of Health Research, Lancaster University, Lancaster, United Kingdom Dodowa Heath Research Centre, Ghana Health Service, Dodowa, Ghana Laboratory for Studies and Research on Social Dynamics and Local Development, Niamey, Niger School of Public Health, University of Montreal, Montreal, Canada Laboratory of Public Health, University of Joseph KI Zerbo, Ouagadougou, Burkina Faso  School of Medicine, University of Leeds, Leeds, United Kingdom Habtu Aweke Yitagesu Editor Addis Ababa University, ETHIOPIA * E-mail: apfenny@ug.edu.gh

The authors have declared that no competing interests exist.

 362025 2025 20 6 e0321265 2332024 432025 2025 Novignon et al This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Primary healthcare (PHC) facilities have become essential in promoting adolescent healthcare, yet they face resource limitations that hinder their effectiveness. Ensuring the efficient use of available resources has therefore become pertinent. This study assessed the technical efficiency of primary health care facilities in providing adolescent mental sexual and reproductive health (AMSRH) services. Data was collected from 53 PHC facilities drawn from rural and urban locations in four districts in the Greater Accra region using a multi-stage sampling design. Stochastic Frontier Analysis (SFA) was employed to estimate the technical efficiency of each facility in optimizing outputs given available inputs. The findings revealed significant variation in efficiency, ranging from 0.91 to 0.04 with an average score of 0.60. Rural facilities and government-owned health facilities were more efficient compared to their urban and private counterparts. Facilities offering a wider scope of services to adolescents were also more efficient. However, the provision of adolescent mental health services was limited. Efforts should improve efficiency in the use of AMSRH services by properly aligning resource allocation to needs while expanding the range of services available to adolescents.

 http://dx.doi.org/10.13039/501100000265 Medical Research Council MR/T040203/1 AgyepongIrene A. This research with grant number [MR/T040203/1] is jointly funded by the UK Medical Research Council (MRC) and the Foreign Commonwealth and Development Office (FCDO) under the MRC/FCDO Concordat agreement, together with the Department of Health and Social Care (DHSC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data Availability All relevant data are within the manuscript and its Supporting Information files. 1. Introduction

Adolescence marks a transition phase of human development from childhood to adulthood. This phase of life has been shown to be associated with physical, cognitive and psychosocial transformations that may determine the ultimate health state of an individual in adulthood. In this regard, adolescent mental, sexual, and reproductive health (AMSRH) services play a crucial role in addressing the global burden of disease in this population and improving general wellbeing, with mental health conditions like suicide being a leading cause of death among adolescents worldwide, including in sub-Saharan Africa [1,2]. Globally, while adolescent mortality has decreased, morbidity has increased due to persistent issues like injuries, mental health disorders, and chronic diseases [2]. For instance, mental health conditions like suicide have been reported to be among the leading causes of death among adolescents worldwide, including sub-Saharan Africa [1,2].

In Ghana, the recent population and housing census reports that about 20% of the population are adolescents between the ages of 10 and 19 [3]. Despite their substantial population, access to health care remains challenging, posing threats to their health and wellbeing. For example, only 18% of sexually active adolescents aged 15–19 use modern contraceptive methods, and 31% received information about STIs Furthermore, about 14% of adolescent girls aged 15–19 had begun childbearing, with more than half of these pregnancies being unintended [4]. Moreover, while current policies emphasize sexual and reproductive health (SRH), there is a notable lack of focus on adolescent mental health [5]. This gap persists despite evidence linking SRH and mental health, which underscores the need for integrated care.

The poor access to AMSRH services has been attributed to several factors including the lack of diagnostic tools tailored for adolescents, financial constraints (particularly for mental health services), and pervasive stigma surrounding AMSRH [6,7]. Primary healthcare facilities have been identified as a potential enabler of improved healthcare access as they reach a wider population with relatively less resources [9]. Ghana’s PHC strategy emphasizes the importance of universal access to essential healthcare services including AMSRH [8]. The strategy aims to provide accessible, affordable, and quality healthcare to all Ghanaians, especially those living in rural and underserved communities.

PHC in Ghana includes health facilities at different levels starting from Community-based Health Planning and Services (CHPS) which are the lowest level of care, health centers, and accredited private clinics. According to the Ghana Health Service (GHS), there are approximately 4,800 health facilities in Ghana, including hospitals, health centers, clinics, and CHPS compounds [4]. Of these, there are about 2,300 CHPS compounds with coverage estimated at 60% of the country’s population [4]. By their design, PHC facilities in Ghana have the potential to fill the healthcare delivery gap for adolescents [9,10]. However effective service delivery at this level will require sufficient resource allocation and reforms to address current resource constraint challenges that hinder PHC service delivery [11,12]. While additional resources can be committed, ensuring that the available resources are used efficiently has been showed to improve resource availability [13,14]. Studies have shown that improving efficiency has potential to free up additional resources within the existing resource envelope while improving health outcomes [14,15]. Yet, there is currently no evidence that assesses how technically efficient these primary health facilities use available resources for AMSRH services. Most of the studies on health system efficiency focus on health facilities with a mix of services. Very few studies have focus on technical efficiency in the delivery of specific health services such as malaria [13,14,16–18].

Against this backdrop, the objective of this paper is twofold; (i) to estimate the technical efficiency of primary health facilities in providing adolescent mental, sexual and reproductive health services and (ii) to identify environmental factors that explain the level of technical efficiency. The rest of the paper is organized into four sections with sections two and three presenting the methods and results, respectively, while the last two sections cover the discussion of results and conclusion.

 2. Materials and methods 2.1 Data

AMSRH services are provided by both public and private healthcare facilities and therefore the study sampled both categories of providers. The services included are adolescent sexual and reproductive health services, such as contraception, pregnancy testing and counselling, maternal and child health services, STI testing and treatment, reproductive health education, and safe abortion services, as well as adolescent mental health services.

Primary data was collected from PHC facilities in four districts in the Greater Accra Region of Ghana. This data included information on inputs and outputs related to both ASRH and AMH services provided by the facilities, such as human resources, equipment, and service delivery statistics. The facilities were contacted through the District Health Directorate in each district, which provided a list of all functional primary healthcare facilities. The directorate also supplied the addresses and contact information of the heads of each health facility. Informed written consent was obtained from the heads of the healthcare facilities or their designated representatives before data collection commenced. All participants received comprehensive information about the study’s objectives and procedures.

 2.2 Sampling

We used a multi-stage sampling design to determine the sample size for this study. First, the Greater Accra region was purposefully selected as it contains a combination of urban and rural districts, as well as a diverse population that is representative of the country. Four districts were then purposively selected from the Greater Accra region. Specifically, two rural districts (Ningo Prampram and Shai Osudoku) with rapid urbanization in the periphery bordering the Accra and Tema metropolitan districts and two urban districts (Ga East and La Kwantemang) were included in the sample to allow for differences in service provision between rural and urban areas. In the third and final phase, all functional PHC facilities in the four selected districts were included in the study. Data was collected from a total of 78 facilities (including school-based sick bays) across all four districts. A sub-sample of 53 PHC facilities were included in the efficiency analysis after removing sick bays that did not meet the classification of PHC facilities in Ghana. Of these facilities, 28 (53%) were in rural areas while 25 (47%) were in urban areas.

 2.3 The stochastic frontier analysis (SFA) model

To measure technical efficiency, we used stochastic frontier analysis (SFA) which was simultaneously proposed by Aigner et al. [19] and Meeusen et al. [20]. The SFA is a parametric approach to assessing efficiency as opposed to nonparametric approaches like data envelopment analysis (DEA) [21]. The analysis begins with the estimation of a production function specified as follows.

yi=xi'β+υi−ui

Where yi represents the output of the ith decision-making unit (DMUs);xi is a vector of inputs; υi is the random disturbance term that accounts for random variations in the production functions of the DMUs. ui is a non-negative random disturbance term that measures the inefficiency of the DMUs. Both υi and ui are assumed to be independent and identically distributed across observations. uimeasures the shortfall of output from its potential maximum frontier given by

lnyi*=xi'β+υi.

Thus;

ui=xi'β+υi−(xi'β+υi−ui)=(lnyi*−lnyi)

Therefore, ui × 100% shows the percentage of output lost due to technical inefficiency where a value closer to 100% indicates high inefficiency (this is termed as technical inefficiency index).

Therefore, the expression to obtain the technical efficiency (TE) index of a DMU is arrived at by rearranging equation (3) as follows:

TEi=exp−ui=xi'β+υi−uixi'β+υi≥0

Equation (4) defines technical efficiency as the ratio of the observed output of the ith DMU to the potential maximum output produced by a completely efficient DMU using the same input mix [21]. The value of technical efficiency is between 0 and 1. This implies that the observed output always lies on or below the efficient frontier. A technical efficiency index closer to 1 indicates high technical efficiency while a value closer to zero means less technical efficiency.

The production function is an important component of the SFA as it determines the accuracy of the frontier from which technical efficiency estimates will be computed. While several forms of the production function exist, the Cobb-Douglas and Translog functions are popular in the efficiency literature [22,23]. In this paper, we used the translog function due to its flexibility as it, among others, allows for cross-product terms between inputs hence capturing complementary and substitution effects. The function is specified in this study as follows.

lnyi=a+αlnki+βlnli+δlnqi+αβlnkilnli+αδlnkilnqi+βδlnlilnqi+ααlnki2+ββlnli2+δδlnqi2+εi

Where yi is the output of the i-th DMU (health facilities), k represents capital of the DMUs (number of beds in the facility), l represents labour inputs of the DMUs (time spent by clinical staff, time spent by nonclinical staff), and q represents other potential determinants of output of the facilities (such as facility type, gender of head of the facility among others) whiles α, β and δ are estimable parameter. ε is the composite error term made of v(the random disturbance term) and u (the inefficiency term). The production function reports Lamda (λ) which is the ratio of the standard deviation of the inefficiency component (u) to the standard deviation of the idiosyncratic component v, and represents the technical efficiency of the production process. Lamda greater than 1 means the standard deviation of the inefficiency component is higher than the standard deviation of the random disturbance term, suggesting the presence of inefficiency in the production process.

Technical efficiency can be computed from the output or input orientations. The output orientation holds inputs constant and determines how outputs could potentially be expanded while input orientation keeps outputs fixed and explores possible reduction in inputs [24–27]. In this study, we used the output orientation given that the health facilities only receive a set of resources and the decision under their control is usually how much outputs can be produced with the available resources. Moreover, the ultimate objective of health facilities is to expand output rather than limiting available resources.

In the second stage analysis, we estimate how health facility and environmental factors are associated with the levels of technical efficiency estimated in the first stage. We used the Tobit regression technique which belongs to the family of limited variable models. The Tobit model was appropriate as it allows for continuous dependent variables that are observable only within an interval. In our case, the technical efficiency scores are limited within a 0–1 interval [28]. The estimated equation is presented in equation (6).

tei=α0+α1hfi+α2commi+εi

Where te is the estimated technical efficiency scores, hf is health facility characteristics and comm is community factors.

 2.6 Variable description

Table 1 presents a description of output, input, and other environmental variables included in the analysis.

10.1371/journal.pone.0321265.t001Summary of input and output variables.
Variable Measurement Definition
Outputs
Outpatient attendance Total number of adolescent outpatients receiving Adolescent Sexual and Reproductive Health (ASRH) services multiplied by the average time spent by clinical staff on an adolescent. Number of adolescent patients receiving ASRH services, adjusted by the average time spent by clinical staff to account for the severity of outpatient care in the facility.
Inputs
Clinical staff time Total number of clinical staff in the health facility multiplied by the average clinical time (in minutes) spent on an adolescent per week This variable is defined as the amount of time committed by clinical staff to providing ASRH services in a health facility. It also serves a key input in the production of adolescent healthcare services.
Non-clinical staff time Total number of non-clinical staff in the health facility multiplied by the average time (in minutes) spent per week on adolescents by non-clinical staff. The variable captures the amount of time devoted to adolescent healthcare services by non-clinical staff
Beds Total number of beds in the facility. Total number of beds in the facility adjusted by the proportion of adolescent visits.
Laboratory tests Total number of laboratory tests administered to adolescents in health facilities multiplied by the proportion of OPD cases that are related to ASRH. Total number of laboratory tests performed for adolescent patients seeking ASRH-specific services.
Medicines Total number of medicine packs disbursed to adolescents in health facilities multiplied by the proportion of OPD cases that are ASRH. Total number of medicine packs dispensed to adolescents seeking ASRH services.
Environmental factors
Computer availability Dummy variable: 1 = facility has a functional computer, 0 = otherwise. Indicates whether the facility has a functional computer.
Time spent by nurses on adolescents Average time spent by a nurse on an adolescent per visit to the facility. Represents the average time a nurse spends with an adolescent patient per visit.
Ratio of clinical staff to non-clinical staff Number of clinical staff in the health facility divided by the number of non-clinical staff in 2021. Represents the ratio of clinical staff to non-clinical staff in the facility.
Ratio of clinical staff to total staff Number of clinical staff in the health facility divided by the total staff in the health facility in 2021. Represents the ratio of clinical staff to the total number of staff in the facility.
Facility has a laboratory Dummy variable: 1 = facility has a functional laboratory, 0 = otherwise. Indicates whether the health facility has a functional laboratory.
Facility has a pharmacy Dummy variable: 1 = facility has a functional pharmacy, 0 = otherwise. Indicates whether the health facility has a functional pharmacy.
Facility has running vehicles Dummy variable: 1 = facility has a running vehicle, 0 = otherwise. Indicates whether the health facility has a running vehicle.
Availability of consultation rooms Total number of consultation rooms in the facility. Total number of consultation rooms available in the facility.
Access to electricity Dummy variable: 1 = facility has electricity, 0 = no electricity. Indicates whether the facility has an electricity supply.
Availability of water supply Dummy variable: 1 = facility has regular water supply, 0 = no regular water supply. Indicates whether the facility has a regular water supply.
Insurance coverage Proportion of the district population with health insurance coverage. Represents the proportion of the district population that is covered by health insurance.
Percentage of adolescent population Percentage of the population of the catchment area of the health facility who are adolescents. Indicates the percentage of the adolescent population within the facility’s catchment area.
Location of facility (Urban/Rural) Dummy variable: 1 = urban facility, 0 = rural facility. Indicates whether the facility is located in an urban or rural area.
Facility type (public/private) Dummy variable: 1 = public facility, 0 = private facility. Indicates whether the facility is public or private.
Gender of facility head Dummy variable: 1 = male head, 0 = female head. Indicates the gender of the facility head.
Gini coefficient District-level Gini coefficient for facilities located in that district. Measures economic inequality within the district where the facility is located.
Literacy rate Average literacy rate in the district allocated to all facilities within the district. Represents the average literacy rate in the district, applied to all facilities within that district.

The variables included in the model were selected based on their relevance to ASRH services and their use in analogous studies on healthcare facility efficiency. Key inputs like clinical and non-clinical staff time, beds, lab tests, and medicines reflect resource allocation, while outputs such as outpatient attendance measure service utilization [26,29]. Environmental variables like facility location, type (public vs. private), and leadership gender help account for external factors influencing efficiency. Additionally, economic factors such as the Gini coefficient and health insurance coverage provide context for disparities in healthcare access, drawing from similar studies that analyse health system performance.

 2.7 Estimation issues

An important concern with efficiency analysis that focuses on a sub-set of services produced by a given organization is the attribution of inputs to these services. In the case of SRH services in Ghana, health workers in PHC facilities are also involved in providing services across different disease conditions. In this regard, for the key inputs, we either adjust them with the average time spent per patient in providing AMSRH services or we use the variables as a proportion of AMSRH services delivered at the facility. The output variable we used is also subject to bias relating to the mix of services used by an adolescent reporting for OPD and the severity of service. For example, while two facilities may have the same number of SRH OPD patients each year, the intensity or quantity of the services they seek may be different, and therefore resource needs will not be the same. Some authors have recommended that outputs used in efficiency analysis of this nature be adjusted to reflect these nuances [30]. In practice, this is a difficult undertaking as data is typically limited. In this paper, we used the average time spent on adolescents in the facility to adjust the outcome variable. We consider this a reasonable way to account for service intensity (Service intensity refers to the complexity and resource demands of a health service. It accounts for variations in time, personnel, and equipment required, ensuring fair comparisons of facility efficiency). We, however, do acknowledge that our approach does not completely purge the variable of this potential bias.

 2.8 Ethics

Ethical approvals for this study were obtained from the Ghana Health Service Ethics Review Committee (GHS ERC 021/05/21) and the University of Leeds Medical Research Ethics Committee (MREC 21–010 External - AdoWA project). Written informed consent was obtained from the heads of the healthcare facilities or their designated representatives prior to data collection. All participants were provided with detailed information regarding the study’s objectives and procedures. The interviews were conducted to gather institutional-level data, and no personal data from patients were collected. Data were anonymized to ensure confidentiality, and all procedures adhered to the ethical standards set forth by the approving committees

 3. Results

Descriptive statistics of key variables included in the analysis are presented in Table 2. The results show that approximately 87% of the health facilities had laboratories, 66% of them had a functional computer and 53% were in rural areas. While 55% of the DMUs were government facilities, 72% had female heads. About 64% were health centers and CHPS compounds while the other 36% were primary-level clinics and hospitals. The table reports that facilities had 8 beds on average. On average, about 26 percent of the population in a catchment area are adolescents. About 94 percent of the facilities have a pharmacy, 30 percent of them have running vehicles while 79 percent of them have regular supply of water.

10.1371/journal.pone.0321265.t002Descriptive statistics.
Variable Mean Std. Dev. Minimum Maximum
Clinical staff time (minutes per week) 248.94 577.94 5.83 3819.14
Non-clinical staff time (minutes per week) 7.07 13.61 .91 92.65
Total beds 8 6.66 1 39
Medicines (number of packs) 201.90 612.84 .15 3686.64
Laboratory tests (number of tests) 73.99 303.48 .012 1768.23
OPD service for ASRH (number of OPD attendance) 242.98 637.17 4 4381
Number of OPD services for AMH 0.71 1.25 0 12
Number of Services provided per clinical staff 22.64 23.60 .44 110
Location of facility (urban) .47 .50 0 1
Facility type (public) .55 .50 0 1
Gender of facility head (Male) .28 .46 0 1
Gini coefficient 37.31 1.97 35.5 40.1
Health center/CHPS .64 .48 0 1
Facility has a computer .66 .48 0 1
Literacy rate .82 .08 .75 .92
Ratio of clinical staff to non-clinical staff .57 .44 .06 2.02
Facility has a laboratory .87 .34 0 1
Number of consultation room 1.64 1.09 1 7
Services provide per non-clinical staff 55.7 71.09 1.25 335.4
Health insurance coverage .63 .07 .55 .71
Percentage of adolescent population 25.84 8.26 10 67
Does facility have electricity supply .98 .14 0 1
Does facility have a Pharmacy .94 .23 0 1
Does the facility have running vehicles (Yes=1) .30 .46 0 1
Is there regular supply of water at this facility (Yes =1) .79 .41 0 1

Each facility provided approximately 243 ASRH services on average in 2021. Also, there are approximately 2 non-clinical staff per facility. Clinical staff spend about 4 hours and 15 minutes on adolescents per week and each clinical staff provides about 23 ASRH services per year while non-clinical staff spends about 7 minutes per adolescents per week.

While the study set out to assess both AMH and sexual and ASRH services, the data reveal a stark gap in the provision of AMH services. On average, the number of OPD services provided for adolescent mental health was just 0.71 per facility, compared to 243 ASRH services. This finding highlights the limited availability of mental health services, with few primary care facilities having mental health professionals specifically oriented to provide adolescent mental health services. The limited provision of AMH services is consistent with previous findings that mental health care in these facilities is marginalized, and even when available, is not specialized for adolescent needs.

Table 3 shows the estimated production frontier for the DMUs. The estimated parameters are acceptable for the model. Lambda is reasonably high and significant in the model indicating the presence of inefficiency in the estimated production function (thus inefficiency among the DMUs in the study). The variance, which is decomposed into sigma_u (inefficiency term) and sigma_v (random error term), shows that the inefficiency term dominates the random error term with a Lamda (λ) value greater than 1 and statistically significant.

10.1371/journal.pone.0321265.t003SFA translog production function regression results.
Coefficients
Clinical staff time per adolescent 1.009**
(0.512)
Non-clinical staff time per adolescent −0.273
(0.788)
Total beds 1.975**
(0.856)
AMSRH medicines disbursed to adolescent 0.282
(0.297)
AMSRH lab tests conducted for adolescent 0.682
(0.494)
Clinical staff time X non-clinical staff time 0.280
(0.181)
Clinical staff time X total beds 0.173
(0.220)
Clinical staff time X AMSRH medicines disbursed 0.017
(0.053)
Clinical staff time X AMSRH lab tests conducted 0.031
(0.063)
Non-clinical staff time X by total beds −0.385**
(0.173)
Non-clinical staff time X AMSRH medicines disbursed −0.086
(0.081)
Non-clinical staff time X AMSRH lab tests 0.159*
(0.088)
Total beds X AMSRH medicines disbursed 0.001
(0.101)
Total beds X AMSRH lab tests −0.197
(0.139)
AMSRH medicines disbursed X total lab tests −0.233***
(0.087)
Clinical staff time per adolescent square −0.107
(0.073)
Non-clinical staff time per adolescent square −0.219*
(0.133)
Total beds square −0.456**
(0.226)
AMSRH medicines disbursed to adolescent square 0.078
(0.048)
AMSRH lab tests conducted for adolescent square 0.112***
(0.037)
Constant 0.090
(1.661)
Sigma_U 0. 693***
(0.202)
Sigma_V 0.405***
(0.145)
Lamda 1.711***
(0.323)
N 53

Note:

*p<0.10,

**p<0.05,

***p<0.01. Standard errors are reported in parenthesis.

Table 4 presents the mean efficiency scores of the facilities across facility characteristics. Overall, average technical efficiency was estimated to be about 0.6 suggesting that on average, about 40% of health facility resources could have been saved while producing the observed levels of output. The disaggregated results show that primary healthcare facilities in rural (0.63) areas are more efficient than their counterparts in urban (0.56). Government health facilities are more efficient (0.63) than private healthcare facilities (0.56). There is relatively marginal difference in efficiency between female (0.60) and male (0.59) -headed facilities. Health centers and CHPS compounds are more efficient (0.63) than clinics (0.55). Facilities in the Shai Osudoku and Ningo Prampram districts lead in terms of efficiency (0.62) followed by Ga East district (0.56) and La Kwantanang (0.55). Moreover, facilities that have a laboratory (0.60) are slightly more efficient than facilities that do not have a laboratory (0.59). The reported differences across facility characteristics were all statistically significant as indicated by the 95% confidence interval.

10.1371/journal.pone.0321265.t004Mean of efficiency scores by facility characteristics.
Mean Standard error 95% confidence interval
Location of facility
 Rural 0.630 0.040 0.550 0.709
 Urban 0.561 0.045 0.471 0.651
Type of facility
 Private 0.561 0.048 0.465 0.657
 Government 0.627 0.037 0.553 0.702
Facility has a computer
 No 0.631 0.050 0.532 0.731
 Yes 0.580 0.037 0.505 0.655
Facility has a laboratory
 No 0.593 0.105 0.383 0.804
 Yes 0.598 0.031 0.536 0.660
Clinic or Health center
 Clinic/hospitals 0.548 0.057 0.434 0.662
 Health center/CHPS 0.625 0.034 0.557 0.692
Gender of facility head
 Female 0.602 0.036 0.530 0.675
 Male 0.585 0.054 0.477 0.693
District
 Ga East 0.560 0.080 0.399 0.721
 Shia Osudoku 0.622 0.058 0.506 0.738
 Ningo Prampram 0.615 0.045 0.525 0.704
 La Kwantanang 0.553 0.074 0.404 0.702
 Total average 0.593 0.052 0.489 0.697

Table 5 presents regression results on the environmental determinants of technical efficiency. A positive association suggests the variable is an enabler of efficiency while a negative association suggests reduction in efficiency. The regression results show that the number of ASRH services provided per clinical staff, number of consultation rooms in a facility and proportion of the district population with health insurance all have a positive and statistically significant association with technical efficiency in using ASRH resources. While the log of Gini index and literacy rate at the district level have significant negative effects on technical efficiency. The other determinants of efficiency in the model are not statistically significant at the 5% conventional level.

10.1371/journal.pone.0321265.t005Determinants of technical efficiency.
Variables Coefficients
Services provided per clinical staff 0.005*
(0.002)
Location of facility (Urban=1) −0.112
(0.082)
Facility type (Government=1) −0.137
(0.111)
Gender of head of facility (Male=1) 0.051
(0.058)
Log of Gini index −43.340*
(19.305)
Facility is a health center 0.191
(0.096)
Facility has a computer 0.024
(0.063)
Literacy rate −21.119*
(9.423)
Ratio of clinical staff to non-clinical staff −0.040
(0.077)
Number of consulting rooms in your facility 0.074*
(0.026)
Services provided per non-clinical staff 0.000
(0.001)
Insurance 18.852*
(8.582)
Percentage of the population that are adolescent −0.000
(0.004)
Does facility have electricity supply 0.165
(0.239)
Does the facility have a functional pharmacy −0.271
(0.141)
Does the facility have running vehicles 0.027
(0.076)
Is there regular supply of water at this facility? −0.114
(0.067)
Constant 162.906*
(72.250)
N 53.000
r2_p −2.611

Note:

*indicate statistical significance at 5%. Standard errors in parenthesis.

 3.4 Discussion

The study aimed to assess the technical efficiency of primary health facilities in providing AMH and ASRH services. The findings show a notable lack of AMH services, with primary care services largely focused on ASRH. The average technical efficiency score of facilities was 0.60, meaning that with current input levels, output can be expanded by an average of 40%. The average efficiency score was higher among rural facilities compared to their urban counterparts. Government facilities were also more efficient relative to private facilities. These findings echo prior research that confirm the presence of inefficiency across health facilities in general health service delivery [13,14,18] and specific disease conditions like malaria [16]. Our results also confirm previous findings by Novignon & Nonvignon [31] suggesting that countries like Ghana could greatly enhance primary healthcare delivery and utilization by increasing technical efficiency. These findings have broader implications for resource efficiency in low-resource settings. The presence of inefficiency suggests that there is significant potential to optimize the use of existing resources. By improving efficiency, cost savings can be achieved, enabling additional outputs to be generated within the same resource envelope. This is particularly important in resource-constrained environments, where optimizing and reallocating limited inputs can enhance healthcare delivery.

The results imply that there is the possibility of producing more outputs within the existing resource envelope. This may be achieved by reviewing the input mix at PHC facilities to ensure that the productivity of these inputs is improved by deploying them where they are most needed. The gains from improved efficiency could result in generating additional resources within existing envelope that could be repurposed within the health sector [15]. Observations from the fieldwork also underscore the estimated level of inefficiencies. We heard from health workers that due to the sensitive nature of sexual and reproductive health services provided at the facilities, adolescents find it difficult to seek care at these facilities. Consequently, some adolescents prefer to self-medicate or avoid seeking care altogether. This means existing resources may be under-utilized as fewer adolescents seek services from formal facilities.

In the second stage where we evaluate the potential association between facility characteristics, external environmental factors and inefficiency, we find some interesting results that could guide policy reforms to improve technical efficiency. For instance, the findings suggest that providing a wider range of ASRH services is associated with higher technical efficiency. This is justifiable as facilities that have more services can provide more comprehensive services and save resources. Resource use may not be optimal in cases where patients seek care for different services across different facilities. The findings also confirm that having more consulting rooms in the facility reduced inefficiency. Indeed, the availability of relatively more consulting rooms has the potential to reduce waiting time and, ultimately, improve efficiency. While PHC facilities are mostly designed as small structures with few consulting rooms, dedicated spaces could be created to meet the peculiar needs of adolescents and improve efficiency in resource use.

With regards to environmental factors external to the health facility, the results show that better economic environment (measured with the level of economic inequality) and reduced financial barriers to health care (measured with health insurance coverage) are associated with improved technical efficiency. Several studies have shown how poverty and inequality limit health care seeking and the role of insurance in enhancing health care utilization [32–36]. The findings support government efforts to improve livelihood and reduce financial barriers to health care through programmes like the Livelihood Empowerment Against Poverty (LEAP) and the National health Insurance Scheme (NHIS). Scaling up these interventions to ensure they are effective and reach the poor and vulnerable adolescents will encourage health seeking at formal facilities, thereby reducing resource redundancy at health facilities.

There are important strengths and limitations of the study worth discussing. The key strength of this study lies in its attempt to apply technical efficiency techniques to ASRH services. As mentioned earlier, technical efficiency is typically applied to health facilities as a whole and does not single out specific services. This is mostly due to the lack of data or difficulty in separating inputs and outputs for specific services within health facilities that provide a mix of services. To the best of our knowledge, this is the first effort to estimate the technical efficiency of PHC facilities in providing ASRH services in Ghana. Despite its strength, the study was limited in scope as it was confined to four districts in the Greater Accra Region, which may limit the generalizability of the findings to other regions in Ghana or other countries. Also, while the study included different types of health facilities, other influential factors such as staff qualifications, workload, or patient satisfaction were not accounted for in the analysis. Finally, our inability to include mental health services in our measure of efficiency is a limitation of the study. Future studies on technical efficiency of AMSRH resource use should consider addressing these limitations.

 4 Conclusion

This study provides critical insights into the efficiency of primary healthcare (PHC) facilities in delivering adolescent sexual and reproductive health (ASRH) services in the Greater Accra Region of Ghana. Our findings show significant inefficiencies, with about 40% of resources being underutilized in ASRH service delivery. In contrast, adolescent mental health services are minimally provided, highlighting a significant gap in comprehensive adolescent care.

The results suggest that facilities with a broader scope of ASRH services and more consulting rooms are more efficient. External factors, such as reducing financial barriers through health insurance coverage and addressing economic inequality, are also associated with better technical efficiency in health facilities.

These findings highlight the potential to improve adolescent health service delivery by optimizing resource allocation and addressing both internal facility characteristics and external environmental factors. Future interventions should focus on creating more adolescent-friendly spaces, integrating mental health services, and expanding financial access to healthcare to improve overall efficiency in primary health facilities.

 Appendix 10.1371/journal.pone.0321265.t006Summary of Input, Output, and Environmental Variables.
Category Variable Definition
Inputs Clinical staff time Total time spent by clinical staff (doctors, nurses) attending to adolescents, calculated as staff count multiplied by average time spent per adolescent.
Non-clinical staff time Total time spent by non-clinical staff (administrative/support staff) attending to adolescent-related services.
Beds Total number of beds available for adolescent patients in the facility.
Laboratory tests Total number of laboratory tests performed for adolescent patients, adjusted for AMSRH-specific services.
Medicines Total number of medications dispensed to adolescents, adjusted for AMSRH-specific services.
Outputs Outpatient attendance Number of adolescent patients receiving AMSRH services, adjusted by the average time spent by clinical staff.
Environmental Factors Location of facility (Urban/Rural) Dummy variable: 1 = urban facility, 0 = rural facility.
Facility type (Public/Private) Dummy variable: 1 = public facility, 0 = private facility.
Gender of facility head Dummy variable: 1 = male head, 0 = female head.
Gini coefficient Measure of economic inequality within the district where the facility is located.
Literacy rate Average literacy rate in the district, applied to the facilities within that district.
Availability of consultation rooms Total number of consultation rooms in the facility.
Access to electricity Dummy variable: 1 = facility has electricity, 0 = no electricity.
Availability of water supply Dummy variable: 1 = facility has regular water supply, 0 = no regular water supply.
Insurance coverage Proportion of the district population covered by health insurance.
Percentage of adolescent population Percentage of the facility’s catchment area population that is adolescent.

Note: This appendix summarizes the key input, output, and environmental variables used in the study to assess the technical efficiency of primary healthcare facilities in providing Adolescent Mental, Sexual, and Reproductive Health (AMSRH) services.

 Supporting information Adowa.

(XLS)

Not applicable.

 References Hanifiha M, Ghanbari A, Keykhaei M, Saeedi Moghaddam S, Rezaei N, Pasha Zanous M. Global, regional, and national burden and quality of care index in children and adolescents: A systematic analysis for the global burden of disease study 1990–2017. PLoS One. 2022;17(4):e0267596. Reiner RC, Olsen HE, Ikeda CT, Echko MM, Ballestreros KE, Manguerra H, et al. Diseases, injuries, and risk factors in child and adolescent health, 1990 to 2017. JAMA Pediatr. 2019;173(6):e190337. Ghana Statistical Service. Ghana 2021 Population And Housing Census General Report. 2021. Ghana Statistical Service. Ghana maternal health survey 2017. 2021. Vanderkruik R, Gonsalves L, Kapustianyk G, Allen T, Say L. Mental health of adolescents associated with sexual and reproductive outcomes: A systematic review. Bull World Health Organ. 2021;99(5):359–73. Abuosi AA, Anaba EA. Barriers on access to and use of adolescent health services in Ghana. J Health Res. 2019;33(3):197–207. doi: 10.1108/jhr-10-2018-0119 Ae-Ngibise KA, Sakyi L, Adwan-Kamara L, Lund C, Weobong B. Prevalence of probable mental, neurological and substance use conditions and case detection at primary healthcare facilities across three districts in Ghana: Findings from a cross-sectional health facility survey. BMC Psychiatry. 2023;23(1):280. Ayanore M, Asampong R, Akazili J, Awoonor-Williams JK, Akweongo P. Sub-national variations in general service readiness of primary health care facilities in Ghana: Health policy and equity implications towards the attainment of Universal Health Coverage. PLoS One. 2022;17(6):e0269546. doi: 10.1371/journal.pone.0269546 35657970 Doyle AM, Mchunu L, Koole O, Mthembu S, Dlamini S, Ngwenya N, et al. Primary healthcare and school health service utilisation by adolescents and young adults in KwaZulu-Natal, South Africa. BMC Health Serv Res. 2019;19(1):905. doi: 10.1186/s12913-019-4559-2 31779631 James S, Pisa PT, Imrie J, Beery MP, Martin C, Skosana C, et al. Assessment of adolescent and youth friendly services in primary healthcare facilities in two provinces in South Africa. BMC Health Serv Res. 2018;18(1):809. doi: 10.1186/s12913-018-3623-7 30348166 Moosa S. Building primary health care teams for universal health coverage in Africa. Afr J Prim Health Care Fam Med. 2022;14(1). cited 2023 Oct 7 /pmc/articles/PMC9082256/ Oleribe OO, Momoh J, Uzochukwu BSC, Mbofana F, Adebiyi A, Barbera T, et al. Identifying key challenges facing healthcare systems in Africa and potential solutions. Int J Gen Med. 2019;12:395. 2023 Oct 7 /pmc/articles/PMC6844097/ Jehu-Appiah C, Sekidde S, Adjuik M, Akazili J, Almeida SD, Nyonator F, et al. Ownership and technical efficiency of hospitals: Evidence from Ghana using data envelopment analysis. Cost Eff Resour Alloc. 2014;12(1):9. doi: 10.1186/1478-7547-12-9 24708886 Novignon J, Nonvignon J. Improving primary health care facility performance in Ghana: Efficiency analysis and fiscal space implications. BMC Health Serv Res. 2017 Dec 12;17(1):399. doi: 10.1186/s12913-017-2347-4 28606131 Barroy H, Cylus J, Patcharanarumol W, Novignon J, Evetovits T, Gupta S. Do efficiency gains really translate into more budget for health? An assessment framework and country applications. Health Policy Plan. 2021;36(8):1307–15. doi: 10.1093/heapol/czab040 33855342 Shretta R, Silal SP, Malm K, Mohammed W, Narh J, Piccinini D, et al. Estimating the risk of declining funding for malaria in Ghana: The case for continued investment in the malaria response. Malar J. 2020;19(1):1–15. doi: 10.1186/s12936-020-03267-9 32487148 Akazili J, Adjuik M, Jehu-Appiah C, Zere E. Using data envelopment analysis to measure the extent of technical efficiency of public health centres in Ghana. BMC Int Health Hum Rights. 2008;8(1):1–12. doi: 10.1186/1472-698X-8-11 19021906 Alhassan RK, Nketiah-Amponsah E, Akazili J, Spieker N, Arhinful DK, Rinke de Wit TF. Efficiency of private and public primary health facilities accredited by the National Health Insurance Authority in Ghana. Cost Eff Resour Alloc. 2015;13(1):23. doi: 10.1186/s12962-015-0050-z 26709349 Aigner D, Lovell CAK, Schmidt P. Formulation and estimation of stochastic frontier production function models. J Econometrics. 1977;6(1):21–37. Meeusen W, van Den Broeck J. Efficiency estimation from Cobb-Douglas production functions with composed error. Int Econ Rev. 1977;18(2):435. Cullinane K, Song DW. Estimating the relative efficiency of European container ports: A stochastic frontier analysis. Res Transp Econ. 2006;16:85–115. doi: 10.1016/s0739-8859(06)16005-9 Colther C, Doussoulin JP. Recent applications and developments of the Cobb–Douglas function: From productivity to sustainability. J Knowl Econ. 2024 May 16. Hung Chiang Y, Cheng EWL. Estimating contractors’ efficiency with panel data. Constr Innov. 2014;14(3):274–91. doi: 10.1108/ci-07-2013-0033 Alatawi A, Ahmed S, Niessen L, Khan J. Systematic review and meta-analysis of public hospital efficiency studies in Gulf region and selected countries in similar settings. Cost Eff Resour Alloc. 2019;17(1):17. doi: 10.1186/s12962-019-0185-4 31406487 Gonçalves PD, Hagenbeek ML, Vissers JMH. Hospital process orientation from an operations management perspective: Development of a measurement tool and practical testing in three ophthalmic practices. BMC Health Serv Res. 2013;13(1):475. doi: 10.1186/1472-6963-13-475 24219362 Ngobeni V, Breitenbach MC, Aye GC. Technical efficiency of provincial public healthcare in South Africa. Cost Eff Resour Alloc. 2020;18(1):3. doi: 10.1186/s12962-020-0199-y 32002018 González-de-Julián S, Vivas-Consuelo D, Barrachina-Martínez I. Modelling efficiency in primary healthcare using the DEA methodology: An empirical analysis in a healthcare district. BMC Health Serv Res. 2024;24(1):982. doi: 10.1186/s12913-024-11420-2 39182078 Amemiya T. Tobit models: A survey. J Econom. 1984 Jan;24(1–2):3–61. Achoki T, Hovels A, Masiye F, Lesego A, Leufkens H, Kinfu Y. Technical and scale efficiency in the delivery of child health services in Zambia: Results from data envelopment analysis. BMJ Open. 2017;7(1):e012321. doi: 10.1136/bmjopen-2016-012321 28057650 Ferreira DC, Marques RC. Malmquist and Hicks–Moorsteen productivity indexes for clusters performance evaluation. Int J Inf Technol Decis Mak. 2016;15(05):1015–53. Novignon J, Nonvignon J. Improving primary health care facility performance in Ghana: Efficiency analysis and fiscal space implications. BMC Health Serv Res. 2017;17(1):399. doi: 10.1186/s12913-017-2347-4 28606131 Peters DH, Garg A, Bloom G, Walker DG, Brieger WR, Hafizur Rahman M. Poverty and access to health care in developing countries. Ann N Y Acad Sci. 2008 Jun 25;1136(1):161–71. Chukwudozie A. Inequalities in health: The role of health insurance in Nigeria. J Public Health Afr. 2015 Mar 31. Devaux M. Income-related inequalities and inequities in health care services utilisation in 18 selected OECD countries. Eur J Health Econ. 2015 Jan 14;16(1):21–33. doi: 10.1007/s10198-013-0546-4 24337894 Dickman SL, Himmelstein DU, Woolhandler S. Inequality and the health-care system in the USA. Lancet. 2017 Apr;389(10077):1431–41. doi: 10.1016/S0140-6736(17)30398-7 28402825 Ilinca S, Di Giorgio L, Salari P, Chuma J. Socio-economic inequality and inequity in use of health care services in Kenya: Evidence from the fourth Kenya household health expenditure and utilization survey. Int J Equity Health. 2019 Dec;18(1):196. doi: 10.1186/s12939-019-1070-5 10.1371/journal.pone.0321265.r001 Author response to Decision Letter 0 Submission Version 0

23 Mar 2024

 10.1371/journal.pone.0321265.r002 Decision Letter 0 Habtu Aweke Yitagesu Academic Editor 2025 Yitagesu Habtu Aweke This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 0

18 Sep 2024

PONE-D-24-09524Technical Efficiency of Primary Health Facilities in Providing Adolescent Mental, Sexual and Reproductive Health Services in Ghana: a case study of selected districts in the Greater Accra RegionPLOS ONE

Dear Dr.  Fenny,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Nov 02 2024 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Yitagesu Habtu Aweke, Ph.D

Academic Editor

PLOS ONE

Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. We suggest you thoroughly copyedit your manuscript for language usage, spelling, and grammar. If you do not know anyone who can help you do this, you may wish to consider employing a professional scientific editing service.  The American Journal Experts (AJE) (https://www.aje.com/) is one such service that has extensive experience helping authors meet PLOS guidelines and can provide language editing, translation, manuscript formatting, and figure formatting to ensure your manuscript meets our submission guidelines. Please note that having the manuscript copyedited by AJE or any other editing services does not guarantee selection for peer review or acceptance for publication.  Upon resubmission, please provide the following: The name of the colleague or the details of the professional service that edited your manuscript A copy of your manuscript showing your changes by either highlighting them or using track changes (uploaded as a *supporting information* file) A clean copy of the edited manuscript (uploaded as the new *manuscript* file)” 3. Thank you for stating the following financial disclosure: "This research with grant number [MR/T040203/1] is jointly funded by the UK Medical Research Council (MRC) and the Foreign Commonwealth and Development Office (FCDO) under the MRC/FCDO Concordat agreement, together with the Department of Health and Social Care (DHSC). " Please state what role the funders took in the study.  If the funders had no role, please state: ""The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript."" If this statement is not correct you must amend it as needed. Please include this amended Role of Funder statement in your cover letter; we will change the online submission form on your behalf. 4. We note that your Data Availability Statement is currently as follows: All relevant data are within the manuscript and its Supporting Information files. Please confirm at this time whether or not your submission contains all raw data required to replicate the results of your study. Authors must share the “minimal data set” for their submission. PLOS defines the minimal data set to consist of the data required to replicate all study findings reported in the article, as well as related metadata and methods (https://journals.plos.org/plosone/s/data-availability#loc-minimal-data-set-definition). For example, authors should submit the following data: - The values behind the means, standard deviations and other measures reported;- The values used to build graphs;- The points extracted from images for analysis. Authors do not need to submit their entire data set if only a portion of the data was used in the reported study. If your submission does not contain these data, please either upload them as Supporting Information files or deposit them to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. For a list of recommended repositories, please see https://journals.plos.org/plosone/s/recommended-repositories. If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially sensitive information, data are owned by a third-party organization, etc.) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. If data are owned by a third party, please indicate how others may request data access. 5. Please include your full ethics statement in the ‘Methods’ section of your manuscript file. In your statement, please include the full name of the IRB or ethics committee who approved or waived your study, as well as whether or not you obtained informed written or verbal consent. If consent was waived for your study, please include this information in your statement as well.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Title need to be coincide more and easily understandable. In title it is mentioned Primary Health Facilities, rather it is better to mention Primary Health Care Facilities. Title might be "Efficiency of Primary Health Care Facilities in Providing Adolescent Health Services in Greater Accra, Ghana: a case study"

Abstract section can be more shorter. In abstract the background portion is large enough. It is better to prepare one sentence like " There are gaps in access to and use of AMSRH services, as well as in the quality and efficiency of care provided in many low- and middle-income countries like Ghana." The objective need to be rephrase. To assess is better to mention rather to estimate.

Introduction: This section is also very large. Please avoid to provide similar information in several sentences. Rather provide more references with one sentence. In objective there is mentioned the environmental factor, which can be inserted in title also.

Methodology: How many private facilities and public facilities are selected. How many facilities are selected from urban areas and rural areas need to be mentioned. The process of data collection need to be mentioned more elaborately. Who collect data from whom, and how the consent was taken, who provide permission to assess data need to be added in methodology.

Result: p value need to be added in Table 2. There in huge differences in services providing in different health facilities. So how many facilities providing - the best services, good services, Average services, poor services, and very poor services (Likert scale) can be incorporated. There are some abbreviation used without mentioning their elaboration like OPD, SRH, STIs etc.

Conclusion: This section will more to be reflected from the findings. The conclusion is more generic rather specific. So it could be improved based on the specific findings of the paper.

Reviewer #2: This article has the potential to contribute both strategy and knowledge to future efforts to evaluate and improve health system technical efficiency, especially in low-resource settings. However, as it stands, the work fails to frame the study methods and findings with this potential impact in mind. While I am interested in the “possibility of producing more outputs within the existing resource envelope”, I do not feel that this paper provides a path towards this goal.

In revising this manuscript, I urge the authors to consider the following:

1) Refocus the Introduction to center around resource limitations and the need to maximize AMSRH resources given the demand/burden of disease (draw data from GBD).

2) Define inputs and outputs earlier in the methods and use them to define the analysis in layman’s terms. I am not familiar with SFA so I will defer to the other reviewers on this analysis.

3) Do not discuss the paucity of mental health care in Methods; that is Results.

4) Start the discussion with one paragraph summary of results then describe i) how the methods may be used to evaluate technical efficiency in other low-resource settings and/or other specializations and ii) how the results may be used to improve technical efficiency, in other words, advise where efforts to improve resource efficiency should be focused. Be specific.

5) De-emphasize privacy from the Discussion unless you have additional data on privacy to contribute to the Results.

I thank the authors for their efforts and wish them the best of luck in future submissions.

Reviewer #3: Please see additional file for comments.

This study estimates the technical efficiency of adolescent sexual and reproductive health services among healthcare facilities in Greater Accra Region, Ghana and their environmental determinants. The authors use stochastic frontier analysis to estimate the technical efficiency of each healthcare facility, then multivariable regression analysis to assess the statistical relationships between environmental characteristics and technical efficiency. The authors find that healthcare facilities provide adolescent sexual and reproductive health services at approximately 60% efficiency, but with significant heterogeneity across the sample. Services covered by clinical staff, insurance coverage, the Gini Index, and the literacy rate were all statistically significant. This research provides an assessment of technical efficiency of specific services that are vital for the growing youth population in Ghana, as well as evidence for future policies that could improve the efficiency of those services if implemented.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

Submitted filename: PONE-D-24-09524_Review.pdf

 10.1371/journal.pone.0321265.r003 Author response to Decision Letter 0 Submission Version 1

30 Oct 2024

The response to reviewers has been attached as a separate document.

Submitted filename: Response to Reviewers.docx

 10.1371/journal.pone.0321265.r004 Decision Letter 1 Habtu Aweke Yitagesu Academic Editor 2025 Yitagesu Habtu Aweke This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 1

17 Jan 2025

PONE-D-24-09524R1Technical Efficiency of Primary Health Facilities in Providing Adolescent Mental, Sexual and Reproductive Health Services in Ghana: a case study of selected districts in the Greater Accra RegionPLOS ONE

Dear Dr. Fenny,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invited you to submit the revised version. Please submit your revised manuscript by Mar 03 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Yitagesu Habtu Aweke, Ph.D

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

 In addition to the reviewer's minor issues, you may consider the following comments: 

In your abstract section, "Primary healthcare (PHC) facilities have become essential in promoting adolescent healthcare, yet they face resource limitations that hinder their effectiveness. Ensuring the efficient use of available resources has therefore become pertinent.” Yes, it is important, but what was your research questions?  Describing the research question (gaps) that led you to assess the technical efficiency of primary health care facilities benefits the clarity before you state your objective (i.e., This study assessed.....)

Numbering headings, and sub-heading adds minimal benefits to the clarity of your content in some sections. So, it’s important to think over removing numbering of headings and subheadings  or  collapsing some third-level headings into second level, and succinctly describing them benefit the clarity and organization of the manuscript. e.g. collapse "2.3.1 "  in your method section into  2.3, and do the same thing in your result section, eg. 3.2.1.... Finally, avoid the sub-sectioning, and continue as “Introduction”, “methods”, “results”, Discussion”, “conclusion”...

Break your  "3.0 Results and discussion" into separate levels  as " Results", " Discussion"

Your discussion seems to lack depth. Please first, summarize what you learned from the results, and discuss and compare your findings with other studies in Ghana. There are studies within Ghana, and other countries with nearly similar contexts,  possible bias, limitations, policy implications etc

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: No

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: Dear authors,

Thank you for the opportunity to review this new submission, and for your detailed responses to my comments and those of the other reviewers. As I wrote earlier, I enjoyed reading this article for your study on the technical efficiency of adolescent health services in Ghana.

In the introduction, please carefully review the formatting for citations, since several are outside of the sentences to which they belong.

In the materials and methods section, please define DEA (line 126) and add some context to what "flexibility" means for the translog function (line 151).

For the results, in Table 2, please clarify what "Insurance" as a characteristic means. Also, I want to reiterate that, for lines 262-273, for many of the facility characteristics, the differences in mean efficiency scores is very small and the confidence intervals overlap. For example, the mean score for rural facilities is 0.630, but that score is fits in the confidence interval for urban facilities. Therefore, I am unsure if you can say that they differences are statistically significant, as you do in lines 272-273. This is even more pronounced--that the mean scores are very narrowly different--for characteristics like facility laboratory or gender of facility head.

Finally, for the discussion, I saw that you revised the writing around fieldwork observations. I suggest adding some language to couch the statements as from your or the data collection team's perspectives. For example, "We heard from adolescent patients that they would prefer to self-medicate..." While I saw that you addressed my comment about sample size, I recommend that you discuss this as a limitation to the study. I am not familiar with the SFA, but I wonder whether ~50 firms in the analytic sample is sufficient, especially with the 20 covariates in the final models. I looked around and found some studies that simulate SFA models under different sample sizes, like Cheng et al. (2024): https://www.sciencedirect.com/science/article/pii/S0304407622000677.

Throughout the paper, there are still grammatical errors and formatting issues that need to be addressed, including extra spaces, missing periods, incomplete sentences, etc.

Thank you!

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #3: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step.

 10.1371/journal.pone.0321265.r005 Author response to Decision Letter 1 Submission Version 2

3 Mar 2025

This has been attached as a separate document.

Submitted filename: Response_to_Reviewers_auresp_2.docx

 10.1371/journal.pone.0321265.r006 Decision Letter 2 Habtu Aweke Yitagesu Academic Editor 2025 Yitagesu Habtu Aweke This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Submission Version 2

4 Mar 2025

Technical Efficiency of Primary Health Facilities in Providing Adolescent Mental, Sexual and Reproductive Health Services in Ghana: a case study of selected districts in the Greater Accra Region

PONE-D-24-09524R2

Dear Dr. Ama Pokuaa Fenny,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager®  and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Yitagesu Habtu Aweke, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Although they don't have much impact on the scientific content, and readability effect, it is good if you are able to:

  avoid numbering of  "headings" and "subheading"  because you have a maximum of two headings

avoid "Materials" from the "Materials and Methods"

remove "Acknowledgements"  if you don't have anybody to acknowledge,  instead of writing "Not applicable".

 10.1371/journal.pone.0321265.r007 Acceptance letter Habtu Aweke Yitagesu Academic Editor 2025 Yitagesu Habtu Aweke This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PONE-D-24-09524R2

PLOS ONE

Dear Dr. Fenny,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

* All references, tables, and figures are properly cited

* All relevant supporting information is included in the manuscript submission,

* There are no issues that prevent the paper from being properly typeset

If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps.

Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

If we can help with anything else, please email us at customercare@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

PhD Candidate Yitagesu Habtu Aweke

Academic Editor

PLOS ONE