Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia
Background: Maternity waiting homes (MWH) allow pregnant women to stay in a residential facility close to a health center while awaiting delivery. This approach can improve health outcomes for women and children. Health planners need to consider many factors in deciding the number of beds needed for...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Ubiquity Press
2022-05-01
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| Series: | Annals of Global Health |
| Subjects: | |
| Online Access: | https://annalsofglobalhealth.org/articles/3691 |
| _version_ | 1817975302633029632 |
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| author | Taryn Vian Jeanette L. Kaiser Thandiwe Ngoma Allison Juntunen Kaluba K. Mataka Misheck Bwalya Viviane I. R. Sakanga Peter C. Rockers Davidson H. Hamer Godfrey Biemba Nancy A. Scott |
| author_facet | Taryn Vian Jeanette L. Kaiser Thandiwe Ngoma Allison Juntunen Kaluba K. Mataka Misheck Bwalya Viviane I. R. Sakanga Peter C. Rockers Davidson H. Hamer Godfrey Biemba Nancy A. Scott |
| author_sort | Taryn Vian |
| collection | DOAJ |
| description | Background: Maternity waiting homes (MWH) allow pregnant women to stay in a residential facility close to a health center while awaiting delivery. This approach can improve health outcomes for women and children. Health planners need to consider many factors in deciding the number of beds needed for an MWH. Objective: The objective of the study is to review experience in Zambia in planning and implementing MWHs, and consider lessons learned in determining optimal capacity. Methods: We conducted a study of 10 newly built MWH in Zambia over 12 months. For this case study analysis, data on beds, service volume, and catchment area population were examined, including women staying at the homes, bed occupancy, and average length of stay. We analyzed bed occupancy by location and health facility catchment area size, and categorized occupancy by month from very low to very high. Findings: Most study sites were rural, with 3 of the 10 study sites rural-remote. Four sites served small catchment areas (<9 000), 3 had medium (9 000–11 000), and 3 had large (>11 000) size populations. Annual occupancy was variable among the sites, ranging from 13% (a medium rural site) to 151% (a large rural-remote site). Occupancy higher than 100% was accommodated by repurposing the MWH postnatal beds and using extra mattresses. Most sites had between 26–69% annual occupancy, but monthly occupancy was highly variable for reasons that seem unrelated to catchment area size, rural or rural-remote location. Conclusion: Planning for MWH capacity is difficult due to high variability. Our analysis suggests planners should try to gather actual recent monthly birth data and estimate capacity using the highest expected utilization months, anticipating that facility-based deliveries may increase with introduction of a MWH. Further research is needed to document and share data on MWH operations, including utilization statistics like number of beds, mattresses, occupancy rates and average length of stay. |
| first_indexed | 2024-04-13T21:48:08Z |
| format | Article |
| id | doaj.art-92203fb9d53e4231b395e8ff47913d37 |
| institution | Directory Open Access Journal |
| issn | 2214-9996 |
| language | English |
| last_indexed | 2024-04-13T21:48:08Z |
| publishDate | 2022-05-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Annals of Global Health |
| spelling | doaj.art-92203fb9d53e4231b395e8ff47913d372022-12-22T02:28:30ZengUbiquity PressAnnals of Global Health2214-99962022-05-0188110.5334/aogh.36912747Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural ZambiaTaryn Vian0Jeanette L. Kaiser1Thandiwe Ngoma2Allison Juntunen3Kaluba K. Mataka4Misheck Bwalya5Viviane I. R. Sakanga6Peter C. Rockers7Davidson H. Hamer8Godfrey Biemba9Nancy A. Scott10School of Nursing and Health Professions, University of San Francisco, San Francisco, CA; WHO Collaborating Centre for Governance, Accountability, and Transparency in the Pharmaceutical Sector, University of TorontoDepartment of Global Health, Boston University School of Public Health, Boston, MADepartment of Research, Right to Care Zambia, LusakaDepartment of Global Health, Boston University School of Public Health, Boston, MAZenysis Technologies, LusakaMothers2mothers (m2m), LusakaAmref Health Africa, LusakaDepartment of Global Health, Boston University School of Public Health, Boston, MADepartment of Global Health, Boston University School of Public Health; Section of Infectious Diseases, Department of Medicine, Boston University School of Medicine, Boston, MANational Health Research Authority, Pediatric Centre of Excellence, LusakaDepartment of Global Health, Boston University School of Public Health, Boston, MABackground: Maternity waiting homes (MWH) allow pregnant women to stay in a residential facility close to a health center while awaiting delivery. This approach can improve health outcomes for women and children. Health planners need to consider many factors in deciding the number of beds needed for an MWH. Objective: The objective of the study is to review experience in Zambia in planning and implementing MWHs, and consider lessons learned in determining optimal capacity. Methods: We conducted a study of 10 newly built MWH in Zambia over 12 months. For this case study analysis, data on beds, service volume, and catchment area population were examined, including women staying at the homes, bed occupancy, and average length of stay. We analyzed bed occupancy by location and health facility catchment area size, and categorized occupancy by month from very low to very high. Findings: Most study sites were rural, with 3 of the 10 study sites rural-remote. Four sites served small catchment areas (<9 000), 3 had medium (9 000–11 000), and 3 had large (>11 000) size populations. Annual occupancy was variable among the sites, ranging from 13% (a medium rural site) to 151% (a large rural-remote site). Occupancy higher than 100% was accommodated by repurposing the MWH postnatal beds and using extra mattresses. Most sites had between 26–69% annual occupancy, but monthly occupancy was highly variable for reasons that seem unrelated to catchment area size, rural or rural-remote location. Conclusion: Planning for MWH capacity is difficult due to high variability. Our analysis suggests planners should try to gather actual recent monthly birth data and estimate capacity using the highest expected utilization months, anticipating that facility-based deliveries may increase with introduction of a MWH. Further research is needed to document and share data on MWH operations, including utilization statistics like number of beds, mattresses, occupancy rates and average length of stay.https://annalsofglobalhealth.org/articles/3691mothers’ sheltersmaternal healthfacility deliveryoccupancy rateaverage length of stayhealth system strengthening |
| spellingShingle | Taryn Vian Jeanette L. Kaiser Thandiwe Ngoma Allison Juntunen Kaluba K. Mataka Misheck Bwalya Viviane I. R. Sakanga Peter C. Rockers Davidson H. Hamer Godfrey Biemba Nancy A. Scott Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia Annals of Global Health mothers’ shelters maternal health facility delivery occupancy rate average length of stay health system strengthening |
| title | Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia |
| title_full | Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia |
| title_fullStr | Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia |
| title_full_unstemmed | Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia |
| title_short | Planning for Maternity Waiting Home Bed Capacity: Lessons from Rural Zambia |
| title_sort | planning for maternity waiting home bed capacity lessons from rural zambia |
| topic | mothers’ shelters maternal health facility delivery occupancy rate average length of stay health system strengthening |
| url | https://annalsofglobalhealth.org/articles/3691 |
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