Abstract: Background: Bangladesh has achieved remarkable progress in reducing maternal mortality, yet postpartum deaths remain a significant issue. Emphasis on quality postnatal care (qPNC) is crucial, as increased coverage alone has not sufficiently reduced maternal morbidity and mortality. Methods: This study included data from the Bangladesh Maternal Mortality Survey of 32,106 mothers who delivered within three years prior to the survey. Descriptive statistics were used to report coverage and components of postnatal care stratified by covariates. Log-linear regression models were used to assess the determinants of quality postnatal care among facility and home births. Results: From 2010 to 2016, postnatal care coverage within 48 hours of delivery by a qualified provider rose from 23% to 47%. 94% of facility births received timely PNC, contrasted with only 6% for home births. Despite the increased coverage, quality of care remained as low as 1% for home births and 13% for facility births. Key factors affecting qPNC utilization included socio-demographic factors, pregnancy complications, delivery method, financial readiness, and mobile ownership. Conclusion: Importantly, deliveries assisted by skilled birth attendants correlated with higher quality postnatal care. The study reveals a significant gap between the coverage and quality of postnatal care in rural Bangladesh, especially for home births. It underscores the need for targeted interventions to enhance qPNC.

A new model for international bed numbers is applied to local area populations for English Clinical Commissioning Groups (CCGs) where the Age Standardized Mortality Rate (ASMR) is used as a measure of population health and hence for total occupied hospital bed demand (elective plus emergency admission types, including acute, rehabilitation, mental health, and maternity), rather than simple bed availability. A 100-unit increase in ASMR (European Standard population) leads to a 15.3 – 30.7 (feasible range) unit increase in occupied beds per 1,000 deaths. ASMR shows why the Australian states of the Northern Territory and Tasmania have an intrinsic higher bed demand than the other states – although in both cases the bed planning methodologies failed to indicate this need and both states show a large bed deficit. Due to the high volatility in bed demand the average bed demand for 2019 was determined by a linear trend using data for 2014/15 to 2019/20 — as the pre-COVID-19 baseline. The slope of the relationship between occupied beds per 1,000 deaths and deaths per 1,000 population shows a power law function. As is to be expected there is scatter around the trend line which will partly arise from uncertainty in the expected occupied beds in 2019, fluctuations in both ASMR and deaths per 1,000 population from one year to another, changes in the number of persons on the elective, outpatient and diagnostic waiting lists, and local area variation in births and consequently upon maternity, neonatal and pediatric bed demand. Additional variation in bed demand will arise from differences in the level of funding for social care, especially elderly care, and to a lesser extent upon patients using private health care, and charitable hospices for palliative care. However, after including the change in bed demand arising from ASMR the model is sufficiently accurate to identify gross differences in bed demand as a prelude to further investigation. The model requires further extension to cover specialty-level demand, and perhaps segregation between elective and emergency types of inpatient demand. A method for benchmarking the whole hospital’s average bed occupancy is given which enables them to run at optimum efficiency and safety. Using this method English hospitals can be shown to operate at highly disruptive and unsafe levels of bed occupancy leading to deleterious ‘turn-away’. Turn-away implies bed unavailability for the next arriving patient. The problems associated with crafting effective bed planning are illustrated using the English NHS as an example.