Characterization of neonatal personnel time inputs and prediction from clinical variables--a time and motion study.
OBJECTIVE
To characterize and predict personnel time inputs to neonatal intensive care using infant characteristics from chart review.


METHODS
For 12 hours each day, observers timed all direct care, charting, discussions, and procedures for 154 infants. Time inputs were correlated with 40 infant characteristics and resource markers, as well as the Score for Neonatal Acute Physiology (SNAP) for that day of care.


RESULTS
Nurses accounted for 76%, respiratory therapists 8%, fellows 5%, nurse practitioners 7% and attendings 5% of total time invested in patient care. Nurses and respiratory therapists spent proportionately more time in direct patient care. In regression models, a limited number of variables explained 36% of the variance in time input per patient for respiratory therapists (p<0.0001), 42% for nurses (p<0.0001), and 23% for physicians and nurse practitioners (p<0.0001).


CONCLUSIONS
Total labor inputs can be accurately predicted through the use of a limited number of clinical characteristics. This technique should be routinely employed to improve the accuracy of economic evaluations. Nursing accounts for the majority of time invested in neonatal care. Improved efficiency in neonatology is thus most likely to be generated by interventions that reduce direct nursing time.
Zupancic
John A F
JA
Department of Neonatology, Beth Israel Deaconess Medical Center, Boston, MA 02458, USA.
Richardson
Douglas K
DK
D006282:Health Personnel / Q000706:statistics & numerical data*; D006801:Humans; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D007232:Infant, Newborn, Diseases / Q000628:therapy*; D007363:Intensive Care Units, Neonatal / Q000706:statistics & numerical data*; D015931:Intensive Care, Neonatal / Q000706:statistics & numerical data*; D008499:Medical Records / Q000706:statistics & numerical data; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D013997:Time Factors; D013996:Time and Motion Studies; D016526:Workload / Q000706:statistics & numerical data