Chronic pain clinic efficiency analysis: optimization through use of the Gantt diagram and visit diagnoses.

OBJECTIVE: The aim of this study is to identify scheduling inefficiencies and to develop a personalized schedule based on diagnosis, service time (face-to-face time between the patient and the provider), and patient wait time using a Gantt diagram in a chronic pain clinic. DESIGN: This is an observational prospective cohort quality improvement (QI) study. SETTING: This study was carried out at a single outpatient multidisciplinary pain management clinic in a university teaching hospital. SUBJECTS: New and established chronic pain patients at the University of Pittsburgh Medical Center (UPMC) Montefiore Chronic Pain Clinic were recruited for this study. METHODS: Time tracking data for each phase of clinic visit and pain-related diagnoses were collected from 81 patients on 5 clinic days in March 2016 for patient flow analysis. RESULTS: A Gantt diagram was created using Microsoft Excel® software. Areas of overbooking and underbooking were identified. Median service times (minutes) differed dramatically based on the diagnosis and were highest for facial pain (23 [IQR, 15-31]) and chronic abdominal and/or pelvic pain (21.5 [IQR, 16-27]) and lowest for myalgia. Abdominal and/or pelvic pain and facial pain median service times consistently exceeded the 15-minute allocation for return visits. CONCLUSION: Schedule efficiency analysis using the Gantt diagram identified trends of overbooking and underbooking and inefficiencies in examination room utilization. A 15-minute appointment for all return patients is unrealistic due to variation of service times for some diagnoses. Scheduling appointments based on the diagnosis is an innovative approach that may reduce scheduling inefficiencies and improve patient satisfaction and the overall quality of care. To the best of our knowledge, this type of scheduling diagram has not been used in a chronic pain clinic.

Fluid overload and mortality are associated with acute kidney injury in sick near-term/term neonate.

BACKGROUND: Acute kidney injury (AKI) is common and portends mortality in several neonatal cohorts. Fluid overload is independently associated with poor outcomes in children and adults but has not been extensively studied in neonates. METHODS: Between February 2010 and May 2011, we followed 58 neonates who met the following criteria: birth weight >2,000 g, gestational age ≥ 34 weeks, 5-min Apgar ≤ 7, and parental consent. Serum creatinine (SCr) was measured daily for first 4 days of life. AKI was defined as a rise in SCr of > 0.3 mg/dl or persistent SCr above 1.5 mg/dl. RESULTS: AKI was present in 9/58 (15.6 %) neonates and was associated with higher birth weight, being male, lower 5-min Apgar scores, lower cord pH, delivery room intubation, and absence of maternal pre-eclampsia. Percent weight accumulation at day 3 of life was higher in those with AKI [median=8.2, interquartile range (IQR) =4.4-21.6)] than without AKI (median= -4 (IQR= -6.5 to 0.0) (p<0.001). Infants with AKI had lower survival rates than those without AKI [7/9 (72 %) vs. 49/49 (100 %) (p<0.02)]. CONCLUSIONS: AKI incidence in this neonatal population is similar to other neonatal cohorts. Near-term/term infants with AKI have a higher mortality rate and a net positive fluid balance over the first few days of life.

Urine biomarkers predict acute kidney injury in newborns.

OBJECTIVE: To identify urine biomarkers predictive of acute kidney injury (AKI) in infants admitted to level 2 and 3 neonatal intensive care units with birth weight >2000 g and 5-minute Apgar score ≤ 7. STUDY DESIGN: A nested case-control study was performed comparing 8 candidate urine AKI biomarkers in infants with AKI (defined as a rise in serum creatinine of at least 0.3 mg/dL or a serum creatinine elevation ≥ 1.7 mg/dL persisting for 3 days) and 24 infants from the described cohort without AKI. Urine was analyzed for neutrophil gelatinase-associated lipocalin, osteopontin, cystatin C, albumin, ß(2) microglobulin, epithelial growth factor, uromodulin (UMOD), and kidney injury molecule 1. RESULTS: Compared with the infants without AKI, those with AKI had higher levels of urine cystatin C (1123 pg/mL [95% CI, 272-4635 pg/mL] vs 90 pg/mL [95% CI, 39-205 pg/mL]; P < .004; area under the receiver operating characteristic curve [AUC] = 0.82), lower levels of UMOD (11.0 pg/mL [95% CI, 5.7-21.4 pg/mL] vs 26.2 pg/mL [95% CI, 17.4-39.4 pg/mL]; P < .03; AUC = 0.77), and lower levels of epithelial growth factor (6.7 pg/mL [95% CI, 4.0-11.3 pg/mL] vs 17.4 pg/mL [95% CI, 12.7-23.8 pg/mL; P = .003; AUC = 0.82). Although the differences were not statistically significant, levels of urine neutrophil-associated gelatinase lipocalin, kidney injury molecule 1, and osteopontin trended higher in infants with AKI. CONCLUSION: Urinary biomarkers can predict AKI in neonates admitted to level 2 and 3 neonatal intensive care units.