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Background: Delay in receiving care significantly contributes to maternal morbidity and mortality. Much has been studied about reducing delays prior to arrival to referral facilities, but the delays incurred upon arrival to the hospital have not been described in many low- and middle-income countries. Methods: We report on the obstetric referral process at Ridge Regional Hospital, Accra, Ghana, the largest referral hospital in the Ghana Health System. This study uses data from a prospectively-collected cohort of 1082 women presenting with pregnancy complications over a 10-week period. To characterize which factors lead to delays in receiving care, we analyzed wait times based on reason for referral, time and day of arrival, and concurrent volume of patients in the triage area. Results: The findings show that 108 facilities refer patients to Ridge Regional Hospital, and 52 facilities account for 90.5% of all transfers. The most common reason for referral was fetal-pelvic size disproportion (24.3%) followed by hypertensive disorders of pregnancy (9.8%) and prior uterine scar (9.1%). The median arrival-to-evaluation (wait) time was 40 min (IQR 15-100); 206 (22%) of women were evaluated within 10 min of arrival. Factors associated with longer wait times include presenting during the night shift, being in latent labour, and having a non-time-sensitive risk factor. The median time to be evaluated was 32 min (12-80) for women with hypertensive disorders of pregnancy and 37 min (10-66) for women with obstetric hemorrhage. In addition, the wait time for women in the second stage of labour was 30 min (12-79). Conclusions: Reducing delay upon arrival is imperative to improve the care at high-volume comprehensive emergency obstetric centers. Although women with time-sensitive risk factors such as hypertension, bleeding, fever, and second stage of labour were seen more quickly than the baseline population, all groups failed to be evaluated within the international standard of 10 min. This study emphasizes the need to improve hospital systems so that space and personnel are available to access high-risk pregnancy transfers rapidly.
RRH in Accra, Ghana was selected as the site for this study as the highest volume obstetric unit of 10 regional referral hospitals in the GHS. Regional hospitals primarily manage complicated pregnancies and as such, approximately 70% of deliveries at RRH are high-risk antenatal or peripartum referrals. The maternity unit at RRH has a 90-bed capacity and provides comprehensive services from antenatal care through postpartum discharge. In 2012, there were 10 labour and delivery beds, one obstetric operating room, and four general operating rooms shared among surgical services and located remotely from the labour ward. The obstetric triage area was an open hallway with a bench and a small adjacent examination room. Staffing consisted of only two obstetricians, an average of four medical officers/residents, and 22 midwives to manage the operating room and labour ward. Despite these challenges, the unit maintained an open-door policy of not turning away patients needing maternity care. Morning shifts were conducted from 0800 to 1400, afternoon shifts from 1400 to 2000 and night shifts from 2000 to 0800, during which there were typically 4 midwives scheduled during the day shifts and 3 midwives during the night shifts. Prior to this study, we conducted a small pilot survey among patients that identified waiting time as a significant modifiable factor that negatively affected patient experience and outcome [9]. We developed a data collection and analysis plan to further understand this issue. The a priori goal of the study was to document the wait time and triage time for women when they arrive. We also wanted to identify factors that led to prolonged delays so that an educational and systems-based intervention could be developed. Four non-staff nurses were hired and trained to collect data on obstetric patients admitted to RRH during a 10-week period from September 9 to November 11, 2012. This sample time represented a time of the year with intermediate patient volume based on monthly census data and was selected to reduce the potential influence of peak or low volume periods. Data collectors were scheduled to work throughout the day and night to gather time-sequence information at patient arrival and from patient records and logbooks within 24 h. Data included patient and labour characteristics, referral information, and the timeliness of triage. Timeliness was based on direct observation of patient-provider interactions by the data collection nurses and recorded on a data sheet. We defined wait time as the difference in minutes from arrival at the facility to the first interaction with a midwife. Triage time was defined as the time from first interaction with a midwife to departure from the triage area en route to a treatment area (women’s ward, labour ward, operating theatre, etc.). For variables that were normally distributed, Student’s t-test and one-way ANOVA was used for continuous variable, and Pearson chi-squared test was used for categorical variables. Results are shown with means and 95% confidence intervals (CI) where applicable. For variables, such as wait time, that are nonparametric, more appropriate tests were chosen. The Wilcox rank-sum (also known as Mann-Whitney U) test was used for continuous variables and Krukal-Wallis test for categorical variables. These results are reported using medians and interquartile ranges. Statistical analyses were done using STATA version 14.0 software (StataCorp, College Station, TX).
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