Certified nurse midwives effects on catecholamine levels and maternal anxiety during labor

Studies of nurse midwifery care in the last twenty one years have reported excellent birth outcomes (Levy, Wilkenson and Marine, 1971; Platt et al. 1985; Stone et al. 1976). These outcomes are frequently attributed to the special support offered during labor and delivery by nurse midwives. This supportive style is thought to decrease catecholamine levels by reducing maternal anxiety. This prospective observational study evaluated catecholamine levels, anxiety levels, in-hospital costs, obstetrical practices and outcomes between low risk, term, labor and delivery primigravida patients managed by obstetrical residents (n = 55) or by certified nurse-midwives CNM (n = 59). The two groups were similar with regard to obstetrical risk factors present at admission. Each group was selected over the same period of time between March 23, 1994 and November 2, 1994. Specific catecholamines evaluated were epinephrine and norepinephrine. Obstetrical and newborn characteristics were also compared. This study did not prove that there is a decreased level in stress as indicated by lower levels of epinephrine and norepinephrine in nurse-midwife patients compared to obstetrical resident patients after adjusting for the use of epidural anesthesia. There was also no difference found in the perceived anxiety levels between the two groups. This study did confirm that nurse-midwives and obstetrical residents have different practice styles. Nurse-midwife patients had fewer augmented deliveries, fewer operative deliveries, less blood loss, fewer episiotomies and fewer third and fourth degree lacerations. The physician's choice to utilize more interventions such as continuous fetal monitoring and epidural anesthesia did not improve outcomes. The hospital cost of the nurse-midwife patients in this study was 35 percent lower than the physician patients. ^

A Time-Motion Study of Registered Nurses’ Workflow in Intensive Care Unit Remote Monitoring

Utilizing advanced information technology, Intensive Care Unit (ICU) remote monitoring allows highly trained specialists to oversee a large number of patients at multiple sites on a continuous basis. In the current research, we conducted a time-motion study of registered nurses’ work in an ICU remote monitoring facility. Data were collected on seven nurses through 40 hours of observation. The results showed that nurses’ essential tasks were centered on three themes: monitoring patients, maintaining patients’ health records, and managing technology use. In monitoring patients, nurses spent 52% of the time assimilating information embedded in a clinical information system and 15% on monitoring live vitals. System-generated alerts frequently interrupted nurses in their task performance and redirected them to manage suddenly appearing events. These findings provide insight into nurses’ workflow in a new, technology-driven critical care setting and have important implications for system design, work engineering, and personnel selection and training.

Continuous safety screens for randomized controlled clinical trials with blinded treatment information

Standard methods for testing safety data are needed to ensure the safe conduct of clinical trials. In particular, objective rules for reliably identifying unsafe treatments need to be put into place to help protect patients from unnecessary harm. DMCs are uniquely qualified to evaluate accumulating unblinded data and make recommendations about the continuing safe conduct of a trial. However, it is the trial leadership who must make the tough ethical decision about stopping a trial, and they could benefit from objective statistical rules that help them judge the strength of evidence contained in the blinded data. We design early stopping rules for harm that act as continuous safety screens for randomized controlled clinical trials with blinded treatment information, which could be used by anyone, including trial investigators (and trial leadership). A Bayesian framework, with emphasis on the likelihood function, is used to allow for continuous monitoring without adjusting for multiple comparisons. Close collaboration between the statistician and the clinical investigators will be needed in order to design safety screens with good operating characteristics. Though the math underlying this procedure may be computationally intensive, implementation of the statistical rules will be easy and the continuous screening provided will give suitably early warning when real problems were to emerge. Trial investigators and trial leadership need these safety screens to help them to effectively monitor the ongoing safe conduct of clinical trials with blinded data.^