Improving Productivity Through Scheduling at the WMed Family Medicine Residency Clinic

INTRODUCTION: The Accreditation Council for Graduate Medical Education (ACGME) requires every family medicine residency program to have a practice site that supports, “continuous, comprehensive, convenient, accessible, and coordinated patient care”. The WMed Family Medicine Resident Clinic (Team Oakland), located within the Family Health Center (FHC) – Paterson location, has long been plagued by scheduling difficulties, as evidenced by high no-show rates, empty appointment slots, and frequent cancellations threatening the ability of our residents to achieve the required number of outpatient visits mandated by the Family Medicine Residency Review Committee (RRC) and the requirement for continuity from the ACGME. We believe many of these issues arise from the FHC’s open-access scheduling template, which heavily favors same day and walk in visits. PURPOSE: This quality improvement project aims to assess the productivity of the Western Michigan Family Medicine Clinic through a scheduling analysis to determine how we can better meet the needs of our patients while also meeting the visit numbers required of the RRC for our residents. STUDY DESIGN: This study is a retrospective scheduling analysis in which our no show rate and unfilled appointments will be considered. Scheduling data for Team Oakland was collected from December 1st, 2016 to January 31st, 2017 through customizable EPIC reports. RESULTS: Data shown below exhibits the total number of appointment slots for Team Oakland broken down by the number of appoints filled, unfilled appointment slots and no show appointments. Data was subsequently broken down by day of the week and hour of the day. The fill rate for the 8:00 hour is 51% compared to 80-90% for most other hours. Image Table 1. Scheduling data for Team Oakland December 2016 through January 2017 DISCUSSION: Literature review revealed conflicting evidence in support of open-access scheduling. We found limited alternative scheduling approaches and limited data specific to residency clinic productivity. Data analysis confirmed that we have a high proportion of appointments that go unfilled as well as a significant no-show rate. Proposed changes to the scheduling template include increasing the number of advanced scheduled appointments-particularly during early morning hours, obtaining an independent scheduler for the resident clinic, and a novel scheduling model targeted at filling no-show appointments with walk-in patients. CONCLUSION: The current scheduling model used at the FHC does not adequately meet the needs of the Family Medicine Residency clinic and data-driven alternative scheduling models should be explored

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society