Network analysis: a novel method for mapping neonatal acute transport patterns in California.

OBJECTIVE: The objectives of this study are to use network analysis to describe the pattern of neonatal transfers in California, to compare empirical sub-networks with established referral regions and to determine factors associated with transport outside the originating sub-network. STUDY DESIGN: This cross-sectional database study included 6546 infants <28 days old transported within California in 2012. After generating a graph representing acute transfers between hospitals (n=6696), we used community detection techniques to identify more tightly connected sub-networks. These empirically derived sub-networks were compared with state-defined regional referral networks. Reasons for transfer between empirical sub-networks were assessed using logistic regression. RESULTS: Empirical sub-networks showed significant overlap with regulatory regions (P<0.001). Transfer outside the empirical sub-network was associated with major congenital anomalies (P<0.001), need for surgery (P=0.01) and insurance as the reason for transfer (P<0.001). CONCLUSION: Network analysis accurately reflected empirical neonatal transfer patterns, potentially facilitating quantitative, rather than qualitative, analysis of regionalized health care delivery systems.

Burnout in the neonatal intensive care unit and its relation to healthcare-associated infections.

OBJECTIVE: To examine burnout prevalence among California neonatal intensive care units (NICUs) and to test the relation between burnout and healthcare-associated infection (HAI) rates in very low birth weight (VLBW) neonates. STUDY DESIGN: Retrospective observational study of provider perceptions of burnout from 2073 nurse practitioners, physicians, registered nurses and respiratory therapists, using a validated four-item questionnaire based on the Maslach Burnout Inventory. The relation between burnout and HAI rates among VLBW (<1500 g) neonates from each NICU was evaluated using multi-level logistic regression analysis with patient-level factors as fixed effects. RESULTS: We found variable prevalence of burnout across the NICUs surveyed (mean 25.2±10.1%). Healthcare-associated infection rates were 8.3±5.1% during the study period. Highest burnout prevalence was found among nurses, nurse practitioners and respiratory therapists (non-physicians, 28±11% vs 17±19% physicians), day shift workers (30±3% vs 25±4% night shift) and workers with 5 or more years of service (29±2% vs 16±6% in fewer than 3 years group). Overall burnout rates showed no correlation with risk-adjusted rates of HAIs (r=-0.133). Item-level analysis showed positive association between HAIs and perceptions of working too hard (odds ratio 1.15, 95% confidence interval 1.04-1.28). Sensitivity analysis of high-volume NICUs suggested a moderate correlation between burnout prevalence and HAIs (r=0.34). CONCLUSION: Burnout is most prevalent among non-physicians, daytime workers and experienced workers. Perceptions of working too hard associate with increased HAIs in this cohort of VLBW infants, but overall burnout prevalence is not predictive.

Percent free prostate specific antigen and cancer detection in black and white men with total prostate specific antigen 2.5 to 9.9 ng./ml.

PURPOSE: The ratio of free-to-total prostate specific antigen (PSA), or percent free PSA, is a useful adjunct to total PSA for estimating the risk of prostate cancer when total PSA is 2.5 to 9.9 ng./ml. Relationships between cancer detection and total PSA are influenced by race but to our knowledge relationships between cancer detection and percent free PSA have not been studied. MATERIALS AND METHODS: A total of 222 black and 298 white consecutive and evaluable men with total PSA 2.5 to 9.9 ng./ml. underwent prostate biopsy for suspected cancer at a Veterans Affairs Medical Center. Clinical measurements included digital rectal examination, total and free serum PSA, prostate volume, PSA density and Gleason score of malignant biopsy specimens. RESULTS: Median percent free PSA was 14.1 (range 3.6 to 49.2) in 201 men with prostate cancer and 21.9 (range 5.7 to 83.3) in 319 without detectable cancer (p <0.0001). Significant racial differences in demographic characteristics and clinical measurements were limited to total PSA, which was higher in black men (p = 0.03). Cancer was detected in 156 black (47%) and 206 white (33%) men (p = 0.001). Areas under receiver operating characteristics curves for percent free PSA and total PSA were 0.66 and 0.58, respectively, for black men (p = 0.15), and 0.76 and 0.58, respectively, for white men (p <0.00001). Percent free PSA was 35.2 in black men and 29.2 in white men, and specificity was 9.1% and 28.7%, respectively, when sensitivity for percent free PSA was set at 95%. Of 156 black and 206 white men with percent free PSA less than 25, 83 (53%) and 85 (41%), respectively, had detectable cancer (p = 0.03). Of 66 black and 92 white men with percent free PSA 25 or greater 21 (32%) and 12 (13%), respectively, had detectable cancer (p = 0.005). CONCLUSIONS: Our study demonstrates racial differences in relationships between percent free PSA and cancer detection in men with suspected prostatic carcinoma and total PSA 2.5 to 9.9 ng./ml. Clinical application of the commonly used percent free PSA cutoff of less than 25 to determine the advisability of prostate biopsy may lead to under diagnosis of early stage prostate cancer in black men, who are at greater risk of morbidity and mortality from disease than white men.