INTRODUCTION: Postponing hospital admission until the active phase of labor is a recommended strategy to safely reduce the incidence of primary cesarean births. Success of this strategy depends on women's decisions about when to transfer from home to the hospital, a process that is largely absent from research about childbirth. This study aimed to determine the decision-making criteria used by women about when to go to the hospital after the self-identification of labor onset at home.
METHODS: A qualitative study was conducted at an academic medical center with a sample of 21 nulliparous women who went into spontaneous labor at home and had term, singleton, and vertex-presentation births. The purposive sample consisted of women who decided to stay at home or go to the hospital in early labor. Birth narratives from in-depth interviews conducted in the postpartum period using a semistructured interview guide were subjected to content analysis. The verbatim transcriptions of the interviews were coded and categorized into a set of decision criteria.
RESULTS: Criteria used by women in deciding to go to the hospital or stay at home in early labor included the degree of certainty with the self-identification of labor onset, ability to cope with labor pain, influence of social network members, health care provider advice, and concerns about travel to the hospital. Perception of childbirth risk and the need for reassurance about the normalcy of symptoms and fetal well-being also influenced women's decisions.
DISCUSSION: Women use a common set of criteria in deciding when to arrive at the hospital during labor. Antenatal education and telephone triage interventions that incorporate the considerations of women deciding to seek or delay hospital admission in childbirth may facilitate health seeking in more advanced labor. Symptom recognition education about early labor onset and progression could reduce decisional uncertainty.
OBJECTIVE: To demonstrate the association between increases in labor and delivery unit census and delays in patient care decisions using a computer simulation module.
METHODS: This was an observational cohort study of labor and delivery unit nurse managers. We developed a computer module that simulates the physical layout and clinical activity of the labor and delivery unit at our tertiary care academic medical center, in which players act as clinical managers in dynamically allocating nursing staff and beds as patients arrive, progress in labor, and undergo procedures. We exposed nurse managers to variation in patient census and measured the delays in resource decisions over the course of a simulated shift. We used mixed logistic and linear regression models to analyze the associations between patient census and delays in patient care.
RESULTS: Thirteen nurse managers participated in the study and completed 17 12-hour shifts, or 204 simulated hours of decision-making. All participants reported the simulation module reflected their real-life experiences at least somewhat well. We observed 1.47-increased odds (95% CI 1.18-1.82) of recommending a patient ambulate in early labor for every additional patient on the labor and delivery unit. For every additional patient on the labor and delivery unit, there was a 15.9-minute delay between delivery and transfer to the postpartum unit (95% CI 2.4-29.3). For every additional patient in the waiting room, we observed a 33.3-minute delay in the time patients spent in the waiting room (95% CI 23.2-43.5) and a 14.3-minute delay in moving a patient in need of a cesarean delivery to the operating room (95% CI 2.8-25.8).
CONCLUSION: Increasing labor and delivery unit census is associated with patient care delays in a computer simulation. Computer simulation is a feasible and valid method of demonstrating the sensitivity of care decisions to shifts in patient volume.
Many Medicaid programs and private health plans are implementing new models of maternity care reimbursement, and clinicians face mounting pressure to demonstrate high-quality care at a lower cost. Clinicians will be better prepared to meet these challenges with a fuller understanding of new payment models and the opportunities they present. We describe the structure of maternity care episode payments and recommend 4 ways that clinicians can prepare for success as value-based payment models are implemented: identify opportunities to improve outcomes and experience, measure quality, reduce waste, and work in teams across settings.
BACKGROUND: Managers of labor and delivery units need to ensure that their limited supply of beds and nursing staff are adequately available, despite uncertainty with respect to patient needs. The ability to address this challenge has been associated with patient outcomes; however, best practices have not been defined.
METHODS: We conducted a secondary analysis of 96 interviews with nurse and physician managers from 48 labor and delivery units across the United States. Included units represented a diverse range of characteristics, but skewed toward higher volume teaching hospitals. The prior study scored management practice based on their proactiveness (ability to mitigate challenges before they occur). Based on emerging themes, we identified common challenges in managing bed and staff availability and performed an analysis of positive deviants to identify an additional criterion for effective management performance.
RESULTS: We identified four key challenges common to all labor and delivery units, (1) scheduling planned cases, (2) tracking patient flow, (3) monitoring bed and staff availability in the moment, and (4) adjusting bed and staff availability in the moment. We also identified "systematicness" (ability to address challenges in a consistent and reliable manner) as an emerging criterion for effective management. We observed that being proactive and systematic represented distinct characteristics, and units with both proactive and systematic practices appeared best positioned to effectively manage limited beds and staffing.
DISCUSSION: Labor and delivery unit managers should distinctly assess both the proactiveness and systematicness of their existing management practices and consider how their practices could be modified to improve care.