Chung Stephanie, Tumlinson Katherine, Bullington Brooke W, Goland Emilia, Onyango Dickens Otieno, Senderowicz Leigh, Mwanyiro Abigael, Wekesa Ben, Frizzelle Brian, Golub Ginger, Rothschild Claire W
Department of Maternal and Child Health, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
BMC Health Serv Res. 2025 Aug 30;25(1):1155. doi: 10.1186/s12913-025-13278-4.
Long wait times at health facilities negatively affect contraceptive access and cause dissatisfaction with care. Conventional data collection methods, such as population-based surveys and exit interviews, may not accurately capture wait times due to methodological challenges including recall and social desirability bias.
We compared mystery client observations conducted in all public facilities in Kisumu County, Kenya with data from a population-based sample of women of reproductive age (18-49, n = 744) in Kisumu County. We compared recalled wait times from women who used public facilities in the last year for their last contraceptive method with wait times recorded by mystery clients (n = 401) presenting as first-time family planning users, and analyzed quotes from mystery clients who mentioned long waits.
Most mystery clients reported wait times between 1-2 h (49%) or over 2 h (33%), whereas most women surveyed in their homes recalled being seen within 30 min at their most recent visit for family planning (74%). When stratified by facility type, mystery clients waited the longest at dispensaries and basic health centers (median wait time of 110 min) and the shortest wait times at primary and secondary care hospitals (median of 82.5 min). In the survey, women recalled waiting a median of 15 min at basic health centers, 20 min at dispensaries, and 30 min at hospitals. Common causes of long waits reported by mystery clients in qualitative data included late facility openings, late providers, or prioritization of other patients. More than half of mystery clients reported spending less than 5 min with providers (59%), compared to only 8% of women surveyed.
Triangulation of data between different sources can provide a more nuanced understanding of long wait times, their causes, and how they impact contraceptive seekers. We find that in comparison, these different methods of data collection answer distinct questions about wait times, time spent with provider, and their impacts on contraceptive seekers. Both forms of data are useful to policy makers and stakeholders. We recommend data collection efforts aimed at improving quality of services and adherence to national guidelines consider supplementing standard data collection methods with mystery clients.
医疗机构的长时间等待会对避孕服务的获取产生负面影响,并导致患者对医疗服务不满。传统的数据收集方法,如基于人群的调查和出院访谈,由于存在回忆偏差和社会期望偏差等方法学挑战,可能无法准确反映等待时间。
我们将在肯尼亚基苏木县所有公共医疗机构进行的神秘顾客观察结果,与基苏木县基于人群的育龄妇女样本(18 - 49岁,n = 744)的数据进行了比较。我们将过去一年使用公共医疗机构获取最后一种避孕方法的女性回忆的等待时间,与作为首次计划生育使用者的神秘顾客记录的等待时间(n = 401)进行了比较,并分析了提到长时间等待的神秘顾客的描述。
大多数神秘顾客报告等待时间在1 - 2小时(49%)或超过2小时(33%),而大多数在家中接受调查的女性回忆说,她们最近一次计划生育就诊时在30分钟内就得到了诊治(74%)。按医疗机构类型分层时,神秘顾客在诊所和基层医疗中心等待时间最长(中位等待时间为110分钟),在一级和二级护理医院等待时间最短(中位等待时间为82.5分钟)。在调查中,女性回忆在基层医疗中心中位等待时间为15分钟,在诊所为20分钟,在医院为30分钟。神秘顾客在定性数据中报告的长时间等待的常见原因包括医疗机构开业晚、医护人员迟到或优先诊治其他患者。超过一半的神秘顾客报告与医护人员相处时间少于5分钟(59%),而接受调查的女性中这一比例仅为8%。
不同来源数据的三角测量可以更细致地了解长时间等待、其原因以及它们如何影响避孕服务寻求者。我们发现,相比之下,这些不同的数据收集方法回答了关于等待时间、与医护人员相处时间及其对避孕服务寻求者影响的不同问题。这两种数据形式对政策制定者和利益相关者都有用。我们建议,旨在提高服务质量和遵守国家指南的数据收集工作,考虑用神秘顾客补充标准数据收集方法。