Search

Guidelines recommend surveillance after resection of colorectal cancer (CRC), but rates of adherence to surveillance are variable and have not been studied at National Cancer Institute (NCI)‐designated Comprehensive Cancer Centers. The aim of this study was to determine rates of adherence to standard postresection CRC surveillance recommendations including physician visits, carcinoembryonic antigen (CEA), computed tomography (CT), and colonoscopy after CRC resection at three NCI‐designated centers. Data on patients with resected CRC from 2010 to 2017 were reviewed. Adherence to physician visits was defined as having at least two visits within 14 months after surgical resection. CEA adherence was defined as having at least four CEA levels drawn within 14 months. CT and colonoscopy adherence were defined as completing each between 10 and 14 months from surgical resection. Chi‐square test and logistic regression analyses were performed for overall adherence and adherence to individual components. A total of 241 CRC patients were included. Overall adherence was 23%. While adherence to physician visits was over 98%, adherence to CEA levels, CT, and colonoscopy were each less than 50%. Center was an independent predictor of adherence to CEA, CT, and/or colonoscopy. Stage III disease predicted CT adherence, while distance traveled of 40 miles or less predicted colonoscopy adherence. Overall adherence to postresection CRC guideline‐recommended care is low at NCI‐designated centers. Adherence rates to surveillance vary by center, stage, and distance traveled for care. Understanding factors associated with adherence is critical to ensure CRC patients benefit from postresection surveillance.

Bevacizumab (BEV) is a common treatment for recurrent glioblastoma (GBM). After progression on BEV, there is no consensus on subsequent therapy, as multiple chemotherapy trials have failed to demonstrate discernible activity for salvage. A previous review (995 patients) estimated a progression free survival (PFS) on BEV of 4.2 months (SD±2.1) with an overall survival (OS) after progression on BEV at 3.8 months (SD +/− 1). We endeavored to establish a more rigorous historical control, both as a benchmark for efficacy, and a prognostic tool for clinical practice. A comprehensive literature review was performed utilizing PubMed and societal presentation abstracts. A total 2388 patients from 53 arms of 42 studies were analyzed in three groups: 1) thirty-two studies in which survival post-BEV was determined by subtracting PFS from OS (2045 patients): PFS on BEV =4.38 months (95% CI 4.09–4.68); OS post-BEV =3.36 months (95% CI 3.12–3.66); 2) two studies (94 patients) in which OS post-BEV is reported: OS= 3.26 (95% CI 2.39–4.42); 3) eight studies of salvage therapy after progression on BEV (249 patients): of OS post-BEV =4.46 months (95% CI 3.68–5.54). These estimates provide a firm historical control for PFS on BEV, as well as OS after disease progression on BEV therapy.

Among 4164 patients, those with type 2 diabetes mellitus (DM) had lower lung diffusion capacity (DLCO) compared with those without DM (DLCO mean±SE: 15.7±0.3 vs. 17.0±0.2 mL/min/mm Hg, p0.01). Reduced DLCO predicted hospitalization for pneumonia independent of diabetes control, severity and co-morbidities (OR=2.4, CI 1.08-5.31).

BACKGROUND: Time studies, first developed in the late 19th century, are now being used to evaluate and improve worker efficiency in the hospital setting. This is the first review of hospital time study literature of which we are aware. PURPOSE: We performed a systematic review of the literature to better understand the available time study literature describing the activities of hospital physicians. DATA SOURCES: We searched MEDLINE, EMBASE, EMBASE Classic, PsycINFO, Cochrane Library, CINAHL, and Web of Science. We also manually reviewed the reference lists of retrieved articles and consulted experts in the field to identify additional articles for review. STUDY SELECTION: We selected studies that used time-motion or work-sampling performed via direct observation, included physicians, medical residents, or interns in their study population, and were performed on an inpatient hospital ward. DATA EXTRACTION: We abstracted data on subject population, study site, collection tools, and percentage of time spent on key categories of activity. DATA SYNTHESIS: Our search produced 11 time-motion and 2 work-sampling studies that met our criteria. These studies focused primarily on academic hospitals (92%) and the activities of physicians in training (69%). Other results varied widely. A lack of methodological standardization and dissimilar activity categorizations inhibited our efforts to summarize detailed findings across studies. However, we consistently found that activities indirectly related to a patient's care took more of hospital physicians' time than direct interaction with hospitalized patients. CONCLUSIONS: Time studies, when properly performed, have a great deal to offer in helping us understand and reengineer hospital care. Journal of Hospital Medicine 2010;5:353–359. © 2010 Society of Hospital Medicine.

BACKGROUND: Within the last decade hospitalists have become an integral part of inpatient care in the United States and now care for about half of all Medicare patients requiring hospitalization. However, little data exists describing hospitalist workflow and their activities in daily patient care. OBJECTIVE: To clarify how hospitalists spend their time and how patient volumes affect their workflow. DESIGN: Observers continuously shadowed each of 24 hospitalists for two complete shifts. Observations were recorded using a handheld computer device with customized data collection software. SETTING: Urban, tertiary care, academic medical center. RESULTS: Hospitalists spent 17% of their time on direct patient contact, and 64% on indirect patient care. For 16% of all time recorded, more than one activity was occurring simultaneously (i.e., multitasking). Professional development, personal time, and travel each accounted for about 6% of their time. Communication and electronic medical record (EMR) use, two components of indirect care, occupied 25% and 34% of recorded time respectively. Hospitalists with above average patient loads spent less time per patient communicating with others and working with the EMR than those hospitalists with below average patient loads, but reported delaying documentation until later in the evening or next day. Patient load did not change the amount of time hospitalists spent with each patient. CONCLUSIONS: Hospitalists spend more time reviewing the EMR and documenting in it, than directly with the patient. Multi-tasking occurred frequently and occupied a significant portion of each shift. Journal of Hospital Medicine 2010;5:323–328. © 2010 Society of Hospital Medicine.