Chabikuli, Nzapfurundi O; Awi, Dorka D; Chukwujekwu, Ogo; Abubakar, Zubaida; Gwarzo, Usman; Ibrahim, Mohammed; Merrigan, Mike; Hamelmann, Christoph
The provision of a comprehensive package of reproductive health programme through integration with HIV services has received endorsement in several fora since the Cairo International Conference on Population and Development 15 years ago [1,2]. The implementation of this strategy has faced policy, structural, managerial and operational difficulties in many sub-Saharan countries [3,4]. A sustainable integration of reproductive health and HIV services must address these challenges.
The global interest and enormous resources available for the control of HIV has overshadowed the importance of reproductive health. However, investment in HIV offers an opportunity to strengthen other programmes, specifically reproductive health, because of synergies in HIV prevention. A recent review of benefits derived from reproductive health–HIV integration suggests a shift from an earlier trend of reproductive health services adding on HIV services towards more HIV programmes adding reproductive health services, and family planning in particular .
With the expansion of HIV treatment programmes, more people living with HIV (PLWH) intend to resume or are resuming sexually active lives and childbearing [6–9]. The unmet need for family planning among PLWH is significant in some countries. This represents an important missed opportunity as sexual activity and pregnancy among PLWH increases in the period after antiretroviral therapy (ART) initiation, even though the majority do not plan a pregnancy at the beginning of treatment [10–12]. The fear of disclosure of HIV status to male partners is an important contributing factor .
Family planning is an important component of HIV programmes to inform PLWH's reproductive decisions and decrease HIV transmission. Nigeria has approximately 3 million PLWH, the third largest number in the world after India and South Africa . HIV is transmitted predominantly through heterosexual encounters and still is a stigmatized epidemic in Nigeria [15–18]. Women constitute 58% of the adults infected with HIV in Nigeria . The estimated HIV seroprevalence among pregnant women in antenatal clinics (ANCs) is 4.6% . This ANC survey showed that HIV in Nigeria disproportionately affects those aged 15–24 years, with the number of infected young women almost double that of young men.
The reproductive health situation in Nigeria is poor. The unmet need for contraception in the general population is estimated at 17% and the contraceptive prevalence rate is low at 12.6% . Although access to HIV services has improved in the past 5 years, there has been no systematic effort to cater to the reproductive health needs of PLWH in the HIV programmes in public hospitals. By 2008, 215 ART sites in Nigeria served about 252 000 patients on ART .
The benefits of integrating family planning services are generally accepted. How to operationalize, monitor and evaluate integration efforts remains debatable. There is no blue print family planning–HIV integration model. More evidence on the effect of integrated services on utilization, coverage of services and quality of care is needed. The evaluation of family planning–HIV integration programmes seldom uses data from routine monitoring and evaluation (M&E) systems. The aim of this article is to assess the changes in service utilization in the Global HIV/AIDS Initiative Nigeria (GHAIN) supported public health facilities using data from routine M&E systems of family planning and three HIV service settings namely HCT, ART and PMTCT.
Setting and population
GHAIN is the largest U.S. President's Emergency Plan for AIDS Relief (PEPFAR) funded HIV programme worldwide, providing technical assistance to 115 comprehensive ART sites and over 300 feeder clinics in all the states of Nigeria. GHAIN has piloted the integration of family planning services in its HIV programme since 2007. This evaluation involved family planning, HCT, ART and PMTCT clinics in 71 public health facilities that serve low socioeconomic population groups in urban and rural areas. Prior to integration, the health facilities had HIV and family planning clinics co-located on the same premises, operating from different consultation rooms and waiting areas. These services had separate, vertical planning, management and implementation structures. In each state, there was a family planning coordinator and HIV coordinator overseeing the implementation of the programmes. HIV and family planning clinics used separate registers, parallel reporting structures, data flow and vertical supply chain management systems. Similar separations affected the human resources in HIV and family planning clinics. The traditional training of HIV and family planning providers was specialized. The isolated HIV service provider seldom initiated discussions about family planning methods with clients; similarly, clients in family planning clinics were not encouraged to know their HIV status. The service financing policy also differed between the two programmes within the same facility. Public hospitals providing both services had HIV services provided free of charge, but there was a charge for family planning commodities.
The intervention: a referral-based, co-located family planning–HIV integration model
GHAIN opted for a model that strengthened referral links in co-located family planning and HIV clinics to optimize the acceptability of the interventions by clients, service providers and programme managers. It offered confidentiality, and the providers were less reluctant to participate because changes to the scope of responsibility were not as pronounced as those in a one-provider/one-session model. The basic programmatic and service arrangements within the health facility were untouched: family planning and HIV services remained separated, they retained the same staff and used parallel supply chain management systems.
GHAIN's family planning–HIV integration intervention focussed on upgrading the skills of providers, supporting them on the job, formalizing referrals between family planning and HIV clinics and M&E by adding HIV data elements in the family planning register, and streamlined data flow from facility to the state and federal levels. Six providers per facility attended a 3-day integrated family planning–HIV training that emphasized the importance of dual protection for PLWH. Each family planning clinic received a package of four job aids: a checklist to screen clients for pregnancy; a checklist to screen clients who want to initiate the use of copper intrauterine contraceptive device (IUCD); a checklist to screen clients who want to initiate medroxyprogesterone acetate (DMPA); and a checklist to screen clients who want to initiate combined oral contraceptive. HIV clinics received one job aid: a reference chart for the WHO medical eligibility criteria for contraceptive use. Each facility identified a focal person who coordinated day-to-day integration activities in family planning and HIV clinics. In addition, a GHAIN reproductive health officer supervized each health facility monthly. She or he assisted the facility coordinator to check whether providers used the job aids, routinely counselled clients, assessed their family planning needs and completed data entry in the registers.
In this integration model, clients at the HIV clinics were routinely counselled on family planning methods; those who intended to use family planning methods were given a referral letter to a family planning clinic, irrespective of their HIV status. At the family planning clinic, clients received further counselling and assessment before an appropriate contraceptive method was dispensed. The client's referral source was then recorded in the family planning register but not the HIV status for confidentiality reasons. Similarly, clients at the family planning clinics were counselled on HIV and consenting clients were given a referral letter to a HCT clinic for testing.
Adaptation of the monitoring and evaluation system
The service integration model guided revisions to the national family planning register, which, in turn, informed the selection of HIV integration data elements and indicators used in Nigeria. Four columns were added to the existing family planning register to capture completed referrals from the three HIV clinics to family planning clinics, and referrals from family planning clinics to HCT. Adjustments were made to PMTCT and HCT registers to record family planning counselling at PMTCT clinics, and HIV counselling and testing at family planning clinics. Standard monthly summary forms were introduced to aggregate the combined family planning and HIV datasets, including the attendance at the family planning clinic (by sex), the number of clients taking up family planning commodities (by method of contraception) and the quantity of family planning commodities dispensed (by method of contraception). Integration-specific data elements included the number of:
1. clients referred from HIV clinics accessing family planning services (by referral point, i.e. HCT, ART or PMTCT) and the number of family planning clients referred for HCT;
2. family planning clients receiving HCT at the family planning clinics and;
3. HIV-positive pregnant women receiving family planning counselling at ANC services.
Key structural components of the HIV M&E system informed the nature of reproductive health–HIV integrated M&E system. Each facility used a trained M&E focal person, often a medical records officer, who oversaw the aggregation and onwards reporting of data from each service delivery point. Following reproductive health–HIV service integration, the facility M&E focal persons and family planning providers were trained on the use of the modified registers and monthly summary forms. Aggregated reproductive health–HIV integration data were subsequently transmitted to state level. M&E officers in each state added the family planning clinics to their schedule of monthly data verification visits. The verified data were computerized using the Ministry of Health's national platform, the District Health Information System (DHIS) software. Data analysis outputs were generated and discussed at monthly M&E meetings.
This was a cross-sectional review of service utilization registers of HIV and family planning clinics in four tertiary hospitals, 60 secondary hospitals and seven primary healthcare (PHC) centres between March 2007 and January 2009. The evaluation had two components. The first was a prepost retrospective survey of the utilization of family planning services and quantity of family planning commodities dispensed, comparing a 6-month period before family planning–HIV integration in participating health facilities with a 9-month period following integration of services. The outcome measures were the attendance at family planning clinics and the couple-years of protection (CYP). CYP was calculated by dividing the total quantity uptake of each family planning commodity by the duration of protection provided, assuming an average of 10 acts per month. The number of each commodity required to make up one CYP were as follows: 120 units for condoms or vaginal foaming tablets; four doses of DMPA injectable; six doses of Noristerat injectable; 0.29 implants or IUCD devices inserted (assuming 3.5 years coverage per implant or IUCD); 15 cycles of oral contraceptives; or 0.125 sterilizations (assuming 8 years of coverage per procedure). Only health facilities with a complete observation time of family planning service utilization 6 months prior to integration and at least 6 months after integration were included. The data were derived from the aggregated monthly service statistics from the adapted national registers.
The second component of the evaluation was an analysis of service ratios, derived from taking the ratio of completed referrals and the total client load at the referring HIV clinic. Because data were aggregated from routine service statistics, it was not possible to calculate referral completion rates, linking individual referrals issued in HIV clinics to those that complete referral at family planning. The total number of clients that attended the family planning clinic at each hospital in a given month was disaggregated by referral source for the postintegration period. For confidentiality reasons, these data were not available by HIV serostatus for clients referred from HCT and PMTCT clinics. All referrals from the ART clinic were considered HIV positive. Service ratios used the most relevant and available data element measuring service utilization at the respective HIV service point. For these routine data elements, only two age groups (<15 years, ≥15 years) were available. The following service ratios were selected using the ≥15 years age group for all denominators:
1. Service ratio for the referrals from HCT clinics calculated as the number of completed referrals from the HCT clinic to the family planning clinic divided by the number of clients who were counselled, tested for HIV and received their result at the HCT clinic.
2. Service ratio for the referrals from ART clinics calculated as the number of completed referrals from the ART clinic to the family planning clinic divided by the number of new HIV-positive clients in the pre-ART register at the ART clinic.
3. Service ratio for the referrals from PMTCT service points calculated as the number of completed referrals from the PMTCT service point to the family planning clinic divided by the number of first ANC visits.
Data on attendance at family planning clinics and CYP for 6 months preintegration and 9 months postintegration were exported from the DHIS and imported into Stata 10.0 for analysis. Only facilities with preintegration data and at least 6 months of postintegration data were included in the prepost analysis. Generalized estimating equation methods using an identity link function and exchangeable working correlation matrix were used to compare the mean attendance and mean CYP preintegration and postintegration. The P value from the Wald test was used to assess whether the difference in mean preintegration and postintegration was significant.
Frequencies were applied to calculate monthly service ratios of referrals from HIV clinics to family planning clinics. The number of completed referrals to the family planning clinic initiated by a particular HIV clinic each month postintegration was divided by the total attendance at that particular HIV clinic. Trends in service ratios were subsequently compared by HIV setting and facility type. The comparison of service ratios by facility type were carried out for the first 5 months postintegration only, since all the PHC facilities had implemented the intervention for only 5 months.
Preintegration and postintegration comparison of service utilization
Forty health facilities had a complete observation time of family planning service utilization 6 months prior to integration and at least 6 months after integration. Thirty-three, 25 and 23 sites had implemented the integration model for 7, 8 and 9 months, respectively. A total of 44 589 people attended family planning clinics in the 40 health facilities during the review period. Service utilization varied substantially between facilities. Attendance at family planning clinics ranged from an average of 1–261 consultations per facility per month preintegration. Post integration attendance at family planning clinics increased; attendance ranged from an average of 3 to 410 consultations per facility per month. The mean attendance at family planning clinics increased significantly from 67.6 preintegration to 87.0 postintegration (P < 0.0001) (Table 1).
Postintegration attendance at the 40 family planning clinics was 28 360. The majority, 81.9% (23 216), were nonreferred clients. Clients in family planning clinics were counselled for HIV and 12.4% (2869) were referred to HCT clinics for HIV testing. The proportion of family planning attendees referred from HIV clinics increased from 14.1 to 27.4% in months 1 and 9, respectively.
Interfacility variation in total CYP ranged from 1 to 109 preintegration and 1 to 163 postintegration. The monthly mean CYP increased significantly from 32.3 preintegration to 38.2 postintegration (P = 0.009). Many postintegration clients used methods with low CYP factor. Condoms accounted for 55.4% of all contraceptives dispensed, but only 2.0% of the total CYP. Eight types of contraceptive methods were dispensed. IUCD represented only 4% of the quantity of contraceptives dispensed but contributed the highest to CYP calculation (60.9%) followed by Depo-Provera (13.8% of total; 15.2% of total CYP), Noristerat (15.5% of total; 11.4% of total CYP) and combined oral contraceptives (11% of total; 3.2% of total CYP). Implants (0.3%), female sterilization (0.1%) and vaginal foaming tablets (<0.1%) were less frequently used.
Sixty-nine, 46 and 67 health facilities offered the HIV services relevant for the service ratios for referrals from HCT, ART and PMTCT clinics, respectively. None of the service ratios exceeded 100 referrals for every 1000 HIV service users ≥15 years. However, there was an improvement over 9 months with an increase of 4, 34 and 42 completed referrals per 1000 HCT, ART and PMTCT clinic users, respectively, between month 1 and 9 (Fig. 1).
None of the PHC facilities had ART clinics; the service ratio of referrals from ART clinics could, therefore, not be calculated for this service level. The service ratio of referrals from PMTCT clinics in PHC facilities increased from 100 completed referrals for every 1000 first ANC visit in the first month of integration to 260 by the fifth month.
The ratio for referrals from PMTCT clinics in PHC facilities was five times higher than that observed for hospitals. Furthermore, the increase in service ratio over time was greater for PHC facilities compared with hospitals. Similar differences between PHC facilities and hospitals were observed for the service ratio of referrals from HCT clinics (Figs. 2 and 3).
Postintegration utilization of family planning clinics by sex
Among the 23 216 nonreferred postintegration clients, only 3.0% were men. The proportion of men among the family planning clients referred from HCT and ART clinics was significantly higher with 23.8 and 18.3%, respectively. All 2469 clients referred from PMTCT clinics were women (Table 2).
This article demonstrates how routine health data from a strengthened government health information system in a developing country can be used successfully to evaluate a family planning–HIV integration programme. The evidence presented is limited by the unavailability of a control group, but provides useful insights into how integration improved family planning service outputs. There was no significant difference between excluded and included facilities in terms of the communities served and service output; key factors in service uptake. The potential to undertake this type of analysis is often missed in the scale up of large HIV programmes with substantial resources for routine data collection. These data are useful in generating hypotheses on service configuration that optimizes synergies when integrating vertical programmes. A key constraint in the use of routine data is the desire to limit the number of data elements, which might not provide the level of details required to isolate special groups or events. Examples in our setting were the lack of family planning data by HIV status due to confidentiality policies and the availability of only two age groups, which did not allow excluding HIV service clients older than 49 years.
Our findings show significant improvements of family planning attendance and uptake of contraceptives. The results suggest that referrals from the HIV service were the main contributing factor. These findings support the evidence of increased contraceptive use in integrated services, particularly with PMTCT, in other African settings [21,22].
In addition to output and outcome evaluation, this article has demonstrated the use of routine health facility data for process evaluation using service ratios. There are different options for the selection of the denominator of the ratios. The choice depends on the available routine data elements and the specific groups targeted for process improvement. For example, to evaluate interventions that might improve the referral of men, sex-specific service ratios can be calculated and trends over time analyzed against targets.
Only a small proportion of HIV clients completed referral to family planning clinics. Four contributing factors should be considered in the Nigerian setting. First, the utilization of family planning clinics and the use of contraceptives are low in Nigeria . Second, counselling alone is not sufficient to increase the uptake of contraception. Male partners must be involved and commodities must be available and accessible . It is encouraging that male participation was higher among clients referred from HIV clinics compared with the nonreferred group. Motivating men in the communities to attend family planning clinics is difficult. Our findings suggest that more effort should focus on men who are already attending a health facility, particularly for HIV services. In this way, scale up of HIV services with improvements in disclosure and partner involvement will have a positive impact on male participation in family planning. Third, user fees for contraceptives are a barrier particularly for clients used to receiving HIV-related commodities without charges. The negative impact of user fee policies on access to healthcare and equity is well established in Africa [23–25]. Fourth, the additional waiting time in the referral model of integration is a deterrent. Longer waiting times are associated with poor client satisfaction with health services [26,27].
The findings on the completion of referrals, especially for PMTCT, might be an underestimate. Clients referred from HIV clinics do not necessarily attend the family planning clinic the same day and may not come with their referral letter later. In this case, they are not identified and recorded as referred clients. A one-provider/one-session integration model would avoid this problem but is perceived as less confidential when the same provider cares for partners . This model also requires to break entrenched barriers of current service organization and of vertical programmes, which is difficult to achieve . PHC facilities had comparatively better service ratios for HCT and PMTCT than hospitals. This suggests that integration at PHC level with a relatively less complex service organization is more efficient. HIV programmes are increasingly decentralized to PHC level. The family planning–HIV integration agenda should be part of this process from the beginning.
In conclusion, the positive impact of integrated family planning–HIV services was demonstrated with routine health service data. This referral model of integration can be applied in most settings in developing countries as a minimum standard. A well designed, routine M&E system is adequate to evaluate process, output and outcome of the integration effort. Men attending HIV services seem to be approachable for family planning services; this opportunity for male involvement in family planning should be used more efficiently. Improvements of service organization within the facilities, accessibility of family planning–HIV services particularly on PHC level and the review of user fees for contraceptives will attract more clients in need. Considering the resources available for HIV services, family planning–HIV integration should become one of the core components of HIV programming.
The GHAIN project receives funding from USAID through the Cooperative Agreement number 620-A-00-04-00122-00.
Author contribution: Nzapfurundi O. Chabikuli, Dorka D. Awi, Ogo Chukwujekwu, Christoph Hamelmann, Zubaida Abubakar and Usman Gwarzo contributed to study conception, design, analysis and interpretation of data. Ogo Chukwujekwu and Dorka D. Awi designed the statistical tests and created all the visuals. Nzapfurundi O. Chabikuli, Dorka D. Awi and Ogo Chukwujekwu wrote the drafts of the publication. Mohammed Ibrahim, Mike Merrigan and Christoph Hamelmann contributed to the critical revision of the article.
Conflicts of interest: None.
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