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  • br Moher D Liberati A Tetzlaff J

    2020-08-18


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    Contents lists available at ScienceDirect
    Oral Oncology
    journal homepage: www.elsevier.com/locate/oraloncology
    Associations between pre-, post-, and peri-operative variables and health resource use following surgery for head and neck cancer 
    T
    Hoda Badra, , Maximiliano Sobrerob, Joshua Chena,c, Tamar Kotzd, Eric Gendend, Andrew G. Sikorae, Brett Milesd
    a Department of Medicine, Section of Health Services Research, Baylor College of Medicine, Houston, TX, USA
    b Department of Emergency Medicine, Alameda Health System, Oakland, CA, USA
    c Department of Psychology, University of St Thomas, Houston, TX, USA
    d Department of Otolaryngology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
    e Department of Otolaryngology-Head and Neck Surgery, Baylor College of Medicine, Houston, TX, USA
    Keywords:
    Quality of life
    Health resource use
    Head and neck cancer
    Surgery
    M D Anderson Dysphagia Inventory 
    Objective: We examined associations between pre-, post-, and peri-operative variables and health resource use in head and neck cancer patients.
    Methods: Patients (N = 183) who were seen for a pre-surgical consult between January 2012 and December 2014 completed surveys that SB 203580 assessed medical history, a patient-reported outcome measure (PROM) of dys-phagia, and quality of life (QOL). After surgery, peri-operative (e.g., tracheostomy, feeding tube) and post-operative (e.g., complications) variables were abstracted from patients’ medical records.
    Results: Multivariate regression models using backward elimination showed that pre-surgical University of Washington Quality of Life (UW-QOL) Inventory and M.D. Anderson Dysphagia Inventory (MDADI) composite scores, documented surgical complications, and having a tracheostomy, were all significant predictors of hos-pital length of stay, explaining 57% of the total variance (F(5, 160) = 18.71, p < .001). Male gender, psy-chiatric history, and lower pre-surgical MDADI scores significantly predicted thirty-day unplanned readmissions (30dUR). Pre-surgical MDADI composite scores also significantly predicted emergencey department (ED) visits within 30 days of initial hospital discharge (p = .02).
    Conclusions: Assessment of PROMs and QOL in the pre-surgical setting may assist providers in identifying pa-tients at risk for prolonged LOS and increased health resource use after hospital discharge.
    Introduction
    Head and neck cancer (HNC) is the sixth most common malignancy in the world, and its incidence is rising rapidly worldwide [1]. Most HNC tumors (90%) are squamous cell carcinomas occurring in the oral cavity, pharynx, and larynx [1]. Treatments for HNC have changed dramatically over the past few decades, owing largely to the advance-ments in multimodality therapy and improvements in radiotherapeutic and surgical techniques [2]. For HNC patients diagnosed with early stage disease, surgical excision is considered a standard treatment [3]. For locally advanced disease (stages III, IVA, IVB), which makes up more than 50% of HNC cases, patients typically undergo surgery either before or after chemoradiation (or radiation) [2]. However, patients undergoing surgery are at increased risk for significant complications
    and health resource use [4,5]. Measures of health resource use such as hospital length of stay (LOS), readmissions, and emergency department (ED) visits, are considered markers of surgical quality of care, and are increasingly tied to hospital reimbursements in the age of affordable care [6–9]. In HNC, the average LOS after surgery is 5–9 days [10,11], rates of hospital readmission after initial discharge range from 3.1% to 16% [12–16], and almost one-third of patients have at least one visit to the ED [17]. These high rates of health resource utilization make HNC one of the most costly cancers to treat [18,19], and contribute to in-creased patient morbidity and mortality [10,14,20,21]. A clearer un-derstanding of factors that contribute to increased health resource use could help clinicians identify “at risk” patients and identify appropriate benchmarks and targets for future quality improvement efforts.