Decision Making about Hospital Arrival among Low‐Risk Nulliparous Women after Spontaneous Labor Onset at Home

Joyce K. Edmonds, Kathleen Miley, Kimberly J. Angelini, Neel T. Shah

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. 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. 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. 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.