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Objectives: To evaluate the effects of the implementation of a postabortion care (PAC) strategy in Kinshasa referral hospitals, this study analyzed the quality of postabortion care services, including postabortion contraception, and the duration of hospitalization. Methodology: We estimated the effects of the PAC strategy using a quasi-experimental study by evaluating the outcomes of 334 patients with the diagnosis of a complication of induced abortion admitted to 10 hospitals in which the PAC strategy was implemented compared to the same outcomes in 314 patients with the same diagnosis admitted to 10 control facilities from 01/01/2016 to 12/31/2018. In response to government policy, the PAC strategy included the treatment of abortion complications with recommended uterine evacuation technology, the family planning counseling and service provision, linkages with other reproductive health services, including STI evaluation and HIV counseling and/or referral for testing, and partnerships between providers and communities. The information was collected using a questionnaire and stored using open data kit software. We supplemented this information with data abstracted from patient records, facility registries of gynecological obstetrical emergencies, and family planning registries. We analyzed data and developed regression models using STATA15. Thus, we compared changes in use of specific treatments and duration of hospitalization using a “difference-in-differences” analysis. Results: The implementation of PAC strategy in Kinshasa referral hospitals has resulted in the utilization of WHO recommended uterine evacuation method MVA (29.3% more in the experimental structures, p = 0.025), a significant decline in sharp-curettage (19.3% less, p = 0.132), and a decline in the duration of hospitalization of patients admitted for PAC (1 day less, p = 0.020). We did not observe any change in the use of PAC services, mortality, and the provision of post abortion contraception. Conclusion: Despite significant improvement in the management of PAC, the uptake in WHO approved technology—namely MVA, and the duration of hospitalization, these outcomes while a significant improvement for DRC, indicate that additional quality improvement strategies for management of PAC and risk-mitigating strategies to reduce barriers to care are required.
This was a quasi-experimental study of the management of postabortion service delivery before and after the implementation of a PAC strategy in intervention hospitals compared to control hospitals. The period before the intervention was from January 1, 2016 to June 30, 2017, and after was from July 1, 2017 to December 31, 2018. This study was conducted in referral hospitals in Kinshasa. Hospitals are designated as referral hospitals by the DRC Ministry of Health based on the provision of certain services. Referral hospitals support and supervise primary care in health centers, train health professionals, and perform operational and implementation research. They typically have more than 100 inpatient beds which equates to about 100 beds for a population of 100,000 inhabitants [11]. The study population only included women presenting to referral hospitals with complications of induced abortion performed elsewhere. The intervention tested in this study was PAC, which includes the treatment of abortion complications with recommended uterine evacuation technology, the family planning counseling and service provision, linkages with other reproductive health services, including STI evaluation and HIV counseling and/or referral for testing, and partnerships between providers and communities. Table Table11 presents the activities of the implementation of the PAC intervention, including the main activities, the responsible persons, and the proposed devices. Summary of the implementation strategy for PAC Overview of PAC Learning objectives: How to conduct counseling after an abortion? How to assess the patient for complications? How to treat complications How to ensure preventive measures against infections Affix PAC wall posters in health facilities Provide PAC advice cards at all health-related activity (prenatal consultations days, vaccination, …) Inform the patient about her PAC rights Perform initial assessment to identify emergency conditions Perform a complete clinical examination Request additional examinations Stabilize the patient’s condition Deal urgently with the complications of abortions Explain to the patient how to take care of her health Psychologically support the patient Provide FP and HIV counseling Advise during follow-up consultations PAC postabortion care, NPRH National Program for Reproductive Health, EONC emergency obstetric and newborn care, FP family planning, HIV human immunodeficiency virus In December 2016, the National Program for Reproductive Health (NPRH) identified the health facilities eligible for PAC implementation in Kinshasa, including the 29 referral hospitals. In February 2017, an initial 6-day training was organized by the NPRH targeting two providers per eligible hospital. In June 2017, additional training sessions under the supervision of the NPRH were organized in the hospitals that participated in the initial training. Our hypothesis was that if the human, financial, and logistical resources are mobilized for the training of the providers in PAC, the sensitization of the population, and the care of the patients with complication of abortion, then the provider clinical skills will be increased, the population sensitized, and patients admitted for an abortion complication will be properly managed. With these achievements, the outcomes of PAC will be improved, the duration of hospitalization, and maternal deaths due to complications of induced abortion will be reduced. From the original 29 hospitals, ten intervention hospitals were selected because they had completed the entire PAC intervention. This included: (1) declared eligible for PAC implementation by the NPRH in December 2016; (2) represented at the initial training on PAC in February 2017; (3) performed hospital-based training PAC in June 2017 for all providers (midwives and doctors) in the maternity ward. In total, around 100 providers were reached by these trainings in the 10 intervention hospitals. The intervention hospitals were matched with ten control hospitals. These hospitals were offered the PAC intervention during the study period but did not respond to at least one of the three criterion for the intervention hospitals. Matching was based on type of employer (private, civil state, military state, catholic denominational, protestant denominational, or salvationist denominational) and the type of neighborhood of residence (semi-rural, eccentric, residential, old cities, and planned cities) [12]. Matching according to the type of employer is taken into account because of the difference that appears in the organization and functioning of the health facilities concerned. The state health facilities have an unlimited range of services, including family planning, they are all over-staffed in the city of Kinshasa, with dilapidated equipment, health care providers with little financial motivation and with several other jobs in order to survive. Faith-based health facilities have a range of services with restrictions in terms of modern contraception for some catholic health facilities, they have understaffed staff compared to the clientele, financially motivated and exhausted each time at the end of service, they are relatively well equipped. Private health facilities, on the other hand, have an unlimited range of services like those in the state, have an adequate number of staff in relation to the clientele, are financially motivated, and are relatively well equipped. And the matching by the type of neighborhood of residence aims at the similarity of the population benefiting from the services. The impact of implementation of the PAC intervention was estimated by examining the care and outcome of all women who were evaluated at study hospitals for complications of induced abortion. Data were abstracted from all medical records and registers for patients with the diagnosis of complications of induced abortion admitted from January 1, 2016 to December 31, 2018. Data were entered into a digital database installed in the smartphones of nurse and physician investigators. The database included sociodemographic, clinical, para-clinical analysis and therapeutic information, and patient outcomes. We measured the effects of the PAC intervention using variables potentially sensitive to the main activities of the implementation of this intervention (Table (Table22). Indicators measuring the effects of PAC A comparative description of characteristics was performed at both the individual level (sociodemographic and general clinical characteristics of patients admitted for an induced-abortion related complication) and the structure level to verify the balance between experimental and control structures. At the individual level, a robust standard error linear regression model for cluster sampling was used to compare the mean age of patients in both groups after verification of data normality and homoscedasticity, and logistic regression models with robust standard error for cluster sampling to compare proportions of other categorical variables. At the structure level, the median of percentages by structure accompanied by the minimum and maximum values was used for the “types of provider” and “location of uterine evacuation” variables that were not normally distributed. For analysis of the effects of the intervention, we generated linear regression models with Robust Standard Errors for cluster sampling (ES and p-values adjusted for clustering), and considered an intra-cluster correlation coefficient being different from 0 for all the variables to be significant. The regression models included the period for the “before” and “after” the intervention for each group. We compared changes in use of specific treatments and duration of hospitalization using a “difference-in-differences” analysis. The models included the group, the period, and the interaction between group and period. For the period of hospitalization which was not normally distributed, quantile regression models were used. An α = 0.05 threshold of significance was chosen. The data were processed and analyzed using STATA15. The study was approved by the National Ethics Committee of the Kinshasa School of Public Health (NCE-KSPH). We obtained consent for data collection from administrators at each health facility. The NCE-KSPH waived the need for consent of the participants because data were drawn from the medical records of patients who had either died or had been discharged from the hospital, and they insisted on the anonymity of patients in the collection and analysis of data. We maintained confidentiality by de-identifying all personal health data. The database was password protected, and access was limited to study personnel.
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