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Background <p>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.</p> Methods <p>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, <i>n</i> = 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 (<i>n</i> = 401) presenting as first-time family planning users, and analyzed quotes from mystery clients who mentioned long waits.</p> Results <p>Most mystery clients reported wait times between 1-2&#xa0;h (49%) or over 2&#xa0;h (33%), whereas most women surveyed in their homes recalled being seen within 30&#xa0;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&#xa0;min) and the shortest wait times at primary and secondary care hospitals (median of 82.5&#xa0;min). In the survey, women recalled waiting a median of 15&#xa0;min at basic health centers, 20 min at dispensaries, and 30&#xa0;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&#xa0;min with providers (59%), compared to only 8% of women surveyed.</p> Conclusions <p>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.</p>

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Comparative perceptions of wait times for family planning services among contraceptive users and mystery clients in Kisumu, Kenya: a mixed methods analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年8月30日

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  • Stephanie Chung,
  • Katherine Tumlinson,
  • Brooke W. Bullington,
  • Emilia Goland,
  • Dickens Otieno Onyango,
  • Leigh Senderowicz,
  • Abigael Mwanyiro,
  • Ben Wekesa,
  • Brian Frizzelle,
  • Ginger Golub,
  • Claire W. Rothschild

摘要

Background

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.

Methods

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.

Results

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.

Conclusions

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.