Evan S. Fieldston

Little is known about repeat testing for patients admitted to children's hospitals from the emergency department (ED). The objective of this study was to describe the trend of repeat laboratory testing from a children's hospital ED. Laboratory studies were analyzed for July 2002 to June 2010 for complete blood counts (CBCs; 7 years), basic metabolic panels (BMPs; 2.5 years), and coagulation studies (7 years) ordered and reordered in the ED within 8 hours for patients admitted to the hospital. Results for tests were generated and classified into high, low, and normal based on reference ranges. To reflect actual practice, we expanded the normal range from 95% of lower bound to 105% of upper bound. A total of 37,035 CBCs, 11,414 BMPs, and 3903 coagulation studies were ordered. Proportions of these tests repeated were 0.9%, 1.9%, and 1.9%, respectively. Mean time to repeat was 2 hours. For CBCs, 25% of repeats were for a missing component; 35% were for low platelet counts. Sixty-eight percent of initial BMPs were repeated for high potassium. Half of coagulation studies were repeated for high prothrombin time; 36% were repeated for a missing component. On repeat, 75% of BMPs with high potassium levels and 65% of CBCs with low platelet count returned normal values, but 16% of coagulation studies repeated for high prothrombin time returned normal values. Repeat ED laboratory testing occurs infrequently at a children's hospital, and a large proportion of repeats is attributed to missing results. When repeated, abnormal results on initial studies are often returned as normal.

*Address for correspondence: Evan Fieldston, MD, MBA, MS, Department of Pediatrics, Children’s Hospital of Philadelphia and Perelman School of Medicine at the U

*Address for correspondence and reprint requests: Evan S. Fieldston, MD, MBA, MSHP, Department of Pediatrics, The Children’s Hospital of Philadelphia, 34th & Ci

BACKGROUND: To develop the capacity for rapid-cycle improvement at the unit level, a large freestanding children’s hospital designated 2 inpatient units with normal patient loads and workforce as pilot “Innovation Units” where frontline staff was trained to lead rigorous improvement portfolios. METHODS: Frontline staff received improvement training, and interdisciplinary teams brainstormed ideas for tests of change. Ideas were prioritized using an impact-effort evaluation and an assessment of how they aligned with high-level goals. A template for each test summarized the following: the opportunity for improvement, the test being conducted, dates for the tests, driver diagrams, metrics to measure effects, baseline data, results, findings, and next steps. Successful interventions were implemented and disseminated to other units. RESULTS: Multidisciplinary staff generated 150 improvement ideas and Innovation Units collectively ran >40 plan-do-study-act cycles. Of the 10 distinct improvement projects, elements of all 10 were deemed “successful” and fully implemented on the unit, and elements from 8 were spread to other units. More than 3 years later, elements of all of the successful improvements are still in practice in some form on the units, and each unit has tested >20 additional improvement ideas, using multiple plan-do-study-act cycles to refine them. CONCLUSIONS: The Innovation Unit model successfully engaged frontline staff in improvement work and established a sustainable system and framework for managing rigorous improvement portfolios at the unit level. Other hospitals and health care delivery settings may find our quality improvement approach helpful, especially because it is rooted in the microsystem of care delivery.

OBJECTIVE: There is growing consensus that to ensure that health care dollars are spent efficiently, physicians need more training in how to provide high-value, cost-conscious care. Thus, in fiscal year 2014, The Children’s Hospital of Philadelphia piloted a 9-part curriculum on health care costs and value for faculty in the Division of General Pediatrics. This study uses baseline and postintervention surveys to gauge knowledge, perceptions, and views on these issues and to assess the efficacy of the pilot curriculum. METHODS: Faculty completed surveys about their knowledge and perceptions about health care costs and value and their views on the role physicians should play in containing costs and promoting value. Baseline and postintervention responses were compared and analyzed on the basis of how many of the sessions respondents attended. RESULTS: Sixty-two faculty members completed the baseline survey (71% response rate), and 45 faculty members completed the postintervention survey (63% response rate). Reported knowledge of health care costs and value increased significantly in the postintervention survey (P = .04 and P < .001). Odds of being knowledgeable about costs and value were 2.42 (confidence interval: 1.05–5.58) and 6.22 times greater (confidence interval: 2.29–16.90), respectively, postintervention. Reported knowledge of health care costs and value increased with number of sessions attended (P = .01 and P < .001). CONCLUSIONS: The pilot curriculum appeared to successfully introduce physicians to concepts around health care costs and value and initiated important discussions about the role physicians can play in containing costs and promoting value. Additional education, increased cost transparency, and more decision support tools are needed to help physicians translate knowledge into practice.

Background And Objective: Treating envenomation with antivenom is costly. Many patients being treated with antivenom are in observation status, a billing designation for patients considered to need care that is less resource-intensive, and less expensive, than inpatient care. Observation status is also associated with lower hospital reimbursements and higher patient cost-sharing. The goal of this study was to examine resource utilization for treatment of envenomation under observation and inpatient status, and to compare patients in observation status receiving antivenom with all other patients in observation status. Methods: This was a retrospective study of patients with a primary diagnosis of toxic effect of venom seen during 2009 at 33 freestanding children’s hospitals in the Pediatric Health Information System. Data on age, length of stay, adjusted costs (ratio cost to charges), ICU flags, and antivenom utilization were collected. Comparisons were conducted according to admission status (emergency department only, observation status, and inpatient status), and between patients in observation status receiving antivenom and patients in observation status with other diagnoses. Results: A total of 2755 patients had a primary diagnosis of toxic effect of venom. Of the 335 hospitalized, either under observation (n = 124) or inpatient (n = 211) status, 107 (31.9%) received antivenom. Of those hospitalized patients receiving antivenom, 24 (22.4%) were designated as observation status. Costs were substantially higher for patients who received antivenom and were driven by pharmacy costs (mean cost: $17 665 for observation status, $20 503 for inpatient status). Mean costs for the 47 162 patients in observation status with other diagnoses were $3001 compared with $17 665 for observation-status patients who received antivenom. Conclusions: Treatment of envenomation with antivenom represents a high-cost outlier within observation-status hospitalizations. Observation status can have financial consequences for hospitals and patients.

BACKGROUND Matching workforce to workload is particularly important in healthcare delivery, where an excess of workload for the available workforce may negatively impact processes and outcomes of patient care and resident learning. Hospitals currently lack a means to measure and match dynamic workload and workforce factors. OBJECTIVES This article describes our work to develop and obtain consensus for use of an objective tool to dynamically match the front‐line ordering clinician (FLOC) workforce to clinical workload in a variety of inpatient settings. METHODS We undertook development of a tool to represent hospital workload and workforce based on literature reviews, discussions with clinical leadership, and repeated validation sessions. We met with physicians and nurses from every clinical care area of our large, urban children's hospital at least twice. RESULTS We successfully created a tool in a matrix format that is objective and flexible and can be applied to a variety of settings. We presented the tool in 14 hospital divisions and received widespread acceptance among physician, nursing, and administrative leadership. The hospital uses the tool to identify gaps in FLOC coverage and guide staffing decisions. DISCUSSION Hospitals can better match workload to workforce if they can define and measure these elements. The Care Model Matrix is a flexible, objective tool that quantifies the multidimensional aspects of workload and workforce. The tool, which uses multiple variables that are easily modifiable, can be adapted to a variety of settings. Journal of Hospital Medicine 2014;9:457–462. © 2014 Society of Hospital Medicine