The health system costs of post abortion care in Tanzania

Background: Unsafe abortion is common in Tanzania. Currently, postabortion care (PAC) is legally provided, but there is little information on the national cost. We estimated the health system costs of offering PAC in Tanzania in 2018, at existing levels of care and when hypothetically expanded to meet all need. Methods: We employed a bottom-up costing methodology. Between October 2018 and February 2019, face-to-face interviews were conducted with facility administrators and PAC providers in a sample of 40 health facilities located across seven mainland regions and Zanzibar. We collected data on the direct and indirect cost of care, fees charged to patients, and costs incurred by patients for PAC supplies. Sensitivity analysis was used to explore the impact of uncertainty in the analysis. Results: Overall, 3850 women received PAC at the study facilities in 2018. At the national level, 77,814 women received PAC, and the cost per patient was $58. The national health system cost for PAC provision at current levels totaled nearly $4.5 million. Meeting all need for PAC would increase costs to over $11 million. Public facilities bore the majority of PAC costs, and facilities recovered just 1% of costs through charges to patients. On average PAC patients incurred $7 in costs ($6.17 for fees plus $1.35 in supplies). Conclusions: Resources for health care are limited. While working to scale up access to PAC services to meet women’s needs, Tanzanian policymakers should consider increasing access to contraception to prevent unintended pregnancies. We estimated PAC service provision costs from the health provider perspective using a cross-sectional study design and a pre-tested, bottom-up costing methodology: the Post-Abortion Care Costing Methodology (PACCM), which has been previously used in several settings [17, 18, 24–26]. We established our sampling frame with input from government sources. We compiled a list of all public and private health facilities (including faith-based and NGO providers) offering PAC services in Tanzania’s mainland (n = 1187) and in Zanzibar (n = 38) in 2017. To reduce recall bias, we used facilities’ reported manual vacuum aspiration (MVA) caseload as a proxy for PAC service provision and excluded 450 mainland facilities that offered MVA to fewer than five patients between January 1 and October 31, 2017. (MVA caseload information was not available for facilities in Zanzibar.) We also excluded eight maternity homes and nine military health facilities due to expectations about low PAC caseloads and restrictions with obtaining approval for research onsite. Finally, we removed one site known to have closed after the list was generated. After these exclusions, there were 757 mainland and Zanzibar health facilities eligible for selection. These facilities were grouped based on ownership (public/private) and facility level (e.g. national/regional hospital, health center, dispensary, etc.) to establish our proportional sampling targets in these categories. For sampling, we selected geographical regions and then facilities within selected regions. There are eight geographical zones in Tanzania, including Zanzibar, which are further divided into 31 regions. Due to their political importance locally, we purposively selected Dar es Salaam region and Zanzibar. Dar es Salaam region in the Eastern Zone is the country’s former capital and the most populated area in the country. It also has the largest number of health facilities per region (i.e. three regional hospitals compared to one hospital in other regions). Zanzibar is a semi-autonomous region of Tanzania, which united with the Tanzania mainland to form the United Republic of Tanzania in 1964. We then randomly selected six additional regions. There were 237 eligible health facilities in the selected regions, and we randomly selected 40 facilities using the pre-established ownership/facility-level targets noted above. After selection, a few facility replacements were necessary. Five sites were replaced due to concerns about the feasibility of accessing the location (n = 1) or reports of sites no longer offering PAC when the interviewer arrived (n = 4). The interviewing team in the field replaced the facilities by going to a neighboring facility within the same region, district and ownership level. One of these facilities reported an MVA caseload of fewer than five and thus was not in the original sampling universe. From October 2018 to February 2019, at each facility, trained interviewers used purposive methods to recruit staff members knowledgeable regarding PAC service provision and the costs of the resources used. The interviewers conducted face-to-face interviews using two electronic questionnaires, referred to as A and B (See supplementary files provided in five parts: A, B-1, B-2, B-3, and B-4). The questionnaires were designed in Survey CTO [27]. They were piloted and updated based on expert advice from individuals familiar with PAC services in Tanzania. Questionnaire A included questions about patient volumes, staff types employed and average salaries, the costs of constructing and equipping the facility, annual overhead costs, and patient fees charged. This questionnaire also asked for information on the family planning methods offered at the site and detailed information on PAC for management of abortion-related complications. This included the proportion of PAC patients managed as inpatients or outpatients, and within each group, the proportion of patients who were treated for five main complication types: incomplete abortion, shock, sepsis, lacerations, and perforations. Finally, for each of the five complication types, Questionnaire A also captured the proportion of PAC patients seen by each clinical personnel type employed at the facility, and the average amount of time spent per PAC patient during their entire stay at the facility. Questionnaire B asked about the resource requirements when treating PAC patients in the five complication categories noted above. The questionnaire was split into four components, each of which listed items commonly used for PAC services and prompted listing of other items if used. The four questionnaire components covered use of consumables, small equipment, laboratory tests, and medications. For each component, the respondents were requested to provide, for each of the five complication types separately, whether the item was used at the facility, the proportion of PAC patients who were treated with the item, and the volume used. Finally, if the item was used at the site for any PAC patient, we asked for the unit cost per item. Costs were collected with the year of purchase and the currency. Some sites were unable to report prices, and we used the Tanzania’s Medical Stores Department Price Catalog or in a few cases, prices from UNICEF’s Supply Catalog [28, 29]. After data collection, all data were exported to Stata (v 16) for cleaning and analysis. Cost results are presented in 2018 US dollars ($) (in the text and tables) and Tanzanian Shillings (TzSh) (in the text only). If required, we inflated costs to 2018 values using currency-specific consumer price indices [30], and then converted non-US dollar currencies to US dollars using the average annual exchange rate for 2018 (TzSh 2322: $ 1.00) [31]. Capital and equipment costs were annualized using the government’s discount rate of 8.17% [32]. We used 60 years of useful life for buildings as reported in local accounting guidelines [33] and replacement rates reported by the respondents for equipment. We generated descriptive service-level statistics by facility level, ownership category, and region. These include a summary of the components included in the PAC services and the family planning methods offered at the study facilities. These also include the average time spent per clinical staff type with each PAC patient (if seen by the staff type). The average time spent per patient is weighted by the proportion of complications within the outpatient and inpatient groups and the proportion in- versus outpatient. We also present patient volume information that includes all patients (PAC or not), all maternal and neonatal health (MNH) patients, all PAC patients, and the number of each of the five complications treated in the last year. Note that the number of PAC patients and complications treated are not the same at all sites because women could be treated for more than one complication. We then estimated the direct, indirect, and total costs for PAC provision at the study facilities, as well as fees paid by patients, for management of each of the five main PAC complication types. We defined direct costs as the sum of costs for clinical personnel time and medical supplies (i.e. consumables, small equipment, laboratory tests, and medications). Indirect costs included capital (buildings and large equipment), utilities, and administrative/support staff salaries plus administrative time spent by clinical staff administrative activities. Detail on how these components were calculated is provided below. To estimate clinical staff costs for PAC provision, we calculated the cost per minute for each staff type employed at each facility using reported annual salaries and monthly working hours. Then we created a set of average costs per minute per staff type at public or private facilities in the sample. Subsequently, for each facility and each PAC inpatient or outpatient complication type, we multiplied the site’s reported proportion of patients seen per staff type by the number of minutes spent when seen to obtain the average time spent per PAC complication type by each staff type. Then we multiplied that by the appropriate (i.e. public or private sector) average cost per minute per staff type to arrive at the average clinical cost per staff type per PAC complication type. These staff costs were then summed across the staff types to obtain the total direct personnel cost per PAC complication type at each facility. For medical supplies (i.e. consumables, small equipment, laboratory tests, and medications), we followed a similar approach as described for direct personnel costs. Each site was asked to report unit costs for all items used for PAC patients. For each facility and each PAC inpatient or outpatient complication type, we multiplied the proportion of PAC patients with whom the item was used by the volume used to obtain the average volume used per PAC complication type. That average volume was then multiplied by the unit cost to produce the average cost per item per PAC complication type, and costs were summed across all items to produce total costs for medical supplies per PAC complication type. Total direct costs are the sum of clinical personnel costs and medical supply costs. We present average direct costs per complication type and per patient. The latter are offered by facility type and region and reflect the reported frequency of patients having more than one complication. Total direct costs for all PAC patients seen at each site were calculated by multiplying the direct cost for management of each type of PAC complication by the number of women treated for the complication and then summing across complication types. Reported costs for building and equipping each facility were first annualized as noted above. Then we created an average capital cost per facility level (e.g. hospital, health center, etc.) for public and private facilities separately. For each facility, the appropriate average annualized capital cost was divided by the number of patients (PAC or not) seen in the last year to produce an average capital cost per patient. Annual overhead costs were also divided by the number of patients seen in the last year, and this was added to the capital costs to produce an average capital and overhead cost per patient at each site. Indirect personnel costs were handled in two ways. First, we summed the annual wage bill for all administrative and support staff at each facility. These included security guards, cleaners, clerks, receptionists, etc. As with the capital and overhead costs, this annual wage bill was divided by the total number of patients seen at the facility in the last year to produce a cost per patient. Second, we estimated the cost of administrative time spent by clinical staff. This involved multiplying the average cost per minute for each clinical staff type by the number of minutes reportedly spent by these staff in administrative tasks (e.g. department meetings, trainings, inventory, etc.) per year, and summing across clinical staff types. That was divided by the reported number of MNH patients (which included PAC patients) seen by the site per year to produce an average administrative time cost per patient. All per patient indirect personnel costs were then summed. Total indirect costs represent the sum of capital, overhead, and administrative personnel costs. We assumed that the average indirect cost would be the same for any PAC patient seen at a given site. We present these average costs per facility type and region. Note that these costs are constant per patient regardless of whether the patient had more than one complication type. Total indirect costs for all PAC patients seen at the site represent the indirect cost per patient multiplied by the number of PAC patients seen in the last year. Finally, we summed direct and indirect costs to produce estimates of the total costs for management of complications of induced abortion at all study facilities. Although delivery services should technically be free in public facilities in Tanzania [34], women must pay for some aspects of PAC services. Women who access care in private facilities also contribute to the costs of care—either out-of-pocket or through insurance premiums. To estimate the fees paid by PAC patients to the health facilities offering care, we used the study facilities’ reports of fees charged for PAC. Facilities were asked what proportion of PAC patients would be expected to pay for any portion of their care, and if expected to pay, how much they would pay in total. Not all facilities charged fees, so we present the fees per woman charged and per PAC patient in the sample in addition to the total fees charged across all the study facilities for a one-year period. We also asked the facilities what proportion of PAC patients would be expected to contribute supplies (e.g. food, medications, etc.) while receiving their PAC care, and if expected to contribute, what the total cost to the patient might be. Again, we present the results per women incurring a cost and per PAC patient. Keogh and colleagues estimated the number of women who received PAC for abortion complications nationally by facility type, and the number of women who needed but did not receive PAC in Tanzania in 2013 [8]. We distributed the group of women who needed but did not receive PAC across facility types using the reported distribution for women who did receive care. Then, we inflated the 2013 numbers to obtain a 2018 estimate, using an average annual population growth rate of 3.1% [35], assuming a constant abortion rate and similar patterns of service delivery over time. Finally, we multiplied the average facility-level cost per PAC patient as calculated in the study sample by the number of women estimated to receive PAC across all PAC facilities nationally, and repeated this for the group of women who needed but did not receive PAC. For both groups of women, the direct and indirect costs were calculated separately to allow for discussion of these components within the total cost. We extrapolated patient costs to the national level following the same steps. Estimating the resources and volumes required for bottom-up costing can be challenging for respondents. When necessary, we imputed values for missing responses in our data. Wherever possible, we imputed the mean of non-missing responses within a site’s facility level (for public facilities) or ownership category (for private facilities). However, there were some cases where there were no responses given within a facility level/category. For those cases, we used the next most similar facility level/category, or when required, the mean of all facilities in the sample. In addition, although some facilities reported a proportion of PAC patients being treated for a particular complication in the last year, when asked about the resources required for treatment, they noted that either no staff members saw the patient type or that no medical supplies were used (inferring that they thought the patient type was not seen at the site). This was the result of different staff being interviewed for the different parts of the costing interviews. For sites that lacked reported personnel costs or medical supply costs but did report seeing a particular patient type in the last year, we imputed the mean personnel or supply cost per patient using information provided by facilities in the same category. Finally, we conducted univariate and multivariate sensitivity analyses to explore the impact of uncertainty in the analysis inputs on the cost outcomes. Specifically, we varied our estimates of the number of PAC cases nationally in 2018, the average personnel cost per PAC patient, and certain indirect cost components. Each variable was adjusted over a pre-set range independently, and then all variables were adjusted at the same time. The results are presented in terms of the proportional impact on patient-level and national-level costs.