| 11 th Annual Pediatric Critical Care Colloquium |
| Session/Time | Poster/Thu, 4:30 - 6:30 PM |
| Title | An Outcomes Analysis to Measure the Impact of a Management Model to Optimize Nursing Supply and Market Demands in a Pediatric Intensive Care Unit (PICU) |
| Author | R Sachdeva, S McElligott, A Garson, S Distefano, D Nicholson, N Ward, R Feigin, L Jefferson |
| Affiliation | From the Critical Care Section, Departments of Pediatrics and Nursing, and Centerfor Health Care Management Research, Texas Children's Hospital, Baylor College of Medicine, Houston, TX |
| Introduction | Nursing salaries in the PICU comprise a significant component of hospital expenses. Although nursing demand in the PICU varies based upon census and acuity, nursing departments do not generally use "flexible" schedules for nurses. The purpose of this study was: 1) to develop a quantitative management model to facilitate implementation of "flexible'. nursing schedules to minimize discrepancies in supply and demand for nurses in thfi PICU; 2) measure the outcomes of this initiative. |
| Method | This study was performed in the PICU at Texas Children's Hospital. Phase I (Aug-Sep 19.97) included developing a forecasting model based upon historical trends to predict nursing needs (in hours) during Phase 11 and using these estimates in a linear programming model to facilitate management decisions for developing flexible nursing schedules, recruitment, and initiating financial incentive programs. Linear programming involves quantitative management sciences modeling to mathematically identify the optimal cost effective solution using predicted demand (forecasting estimates) and available supply (# nursing hours) after adjusting for differences in salary and benefits. Phase I/ (Sep 1997-Feb 1998) included measuring outcomes of the implementation of flexible scheduling and financial incentives for nurses in the PICU. Outcomes measured included - 1) Patient outcomes - identified by collecting demographic and quality of care data on all patients during the study period and after severity adjustment using the PRISM score. 2) Nursing outcomes - identified by using a specific, validated 42 item nursing satisfaction survey and daily measures of nursing .efficiency" and nursing behavior (absences, transfer requests, tardies, sick calls, overtime, float pool). 3) Management outcomes - identified by measuring denials in transport requpsts, and impact on revenue and expenses. |
| Result | Linear programming models w,-re successfully developed during Phase 1. Results from Phase 11 include: 1) Patient outcomes - there were no differences (p>0.05) in quality of care or severity adjusted patient outcomes during the study period. 2) Nursing outcomes - there were no differences (p>0.05) in estimates of nursing satisfaction and efficiency during the study period. 3) Management outcomes - there was a decrease in transport denials (by 26.6%:p<0.05) and an increase in 17.2 % of gross revenue during the study period. |
| Conclusion | Linear programming models and incentive programs can be used in the PICU to optimize nursing scheduling to minimize short term mismatch in nursing supply and demand without any measurable adverse effects on parient or nursing outcome. |
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