Association Between Hospitals’ Risk-Adjusted Emergency Department Visits and Survival and Costs in Kidney Cancer Patients Undergoing Nephrectomy

2019 ◽  
Vol 17 (3) ◽  
pp. e650-e657
Author(s):  
Joel E. Segel ◽  
Eric W. Schaefer ◽  
Jay D. Raman ◽  
Christopher S. Hollenbeak
Keyword(s):  
Emergency Department ◽  
Cancer Patients ◽  
Kidney Cancer ◽  
Emergency Department Visits

The association between hospitals’ risk-adjusted emergency department visits and survival and costs in kidney cancer patients.

2019 ◽  
Vol 37 (7_suppl) ◽  
pp. 609-609
Author(s):  
Joel E Segel ◽  
Eric W. Schaefer ◽  
Jay D. Raman ◽  
Christopher S. Hollenbeak
Keyword(s):  
Emergency Department ◽  
Cancer Patients ◽  
Kidney Cancer ◽  
Mortality Rates ◽  
Emergency Department Visits ◽  
Medicare Data ◽  
Initial Surgery ◽  
Oncology Care ◽  
Ed Visits ◽  
The Cost

609 Background: As payers turn to alternative payment models, including the CMS Oncology Care Model, risk-adjusted emergency department (ED) visits are being incorporated as a quality. Yet little is know about this metric compares to existing metrics such as risk-adjusted mortality rates and costs. Methods: Using 2007-2012 SEER-Medicare data, we used logistic regression to model occurrence of an ED visit within 30 and 365 days for all kidney cancer patients receiving initial surgery. Our model controlled for demographics, stage, histology, systemic targeted therapy, and comorbidities. Based on model predictions, we created a ratio of actual versus predicted ED visits for hospitals to identify hospitals with higher and lower than predicted ED visit rates. We estimated the association between the hospitals’ ED visit ratio and hospitals’ risk-adjusted 365-day mortality rates, and 6- and 12-month total costs and total costs (less ED visits). Results: In our sample of 6,078 patients, 15.5% had an ED visit within 30 days of surgery and 43.5% within 365 days. For hospitals with ≥10 patients, we found no statistically significant association between 30-day or 365-day risk-adjusted ED visit rate and their 365-day risk-adjusted mortality rate. While hospitals’ 30-day ED visit rates were significantly associated with 6- and 12-month costs, the association was largely driven by the cost of the ED visit itself. Conversely, hospitals’ 365-day ED visit rates were significantly associated with 12-month costs after excluding the cost of the ED visit. Conclusions: Our results suggest hospitals’ risk-adjusted ED visit rates capture a qualitatively different measure of quality than the more commonly reported mortality rates and is significantly associated with patient cost.

scholarly journals Emergency department visits by head-and-neck cancer patients

2019 ◽  
Vol 25 (4) ◽  
pp. 535
Author(s):  
Pankaj Chaturvedi ◽  
Akshat Malik ◽  
Vivek Sukumar ◽  
Ameya Pai ◽  
Aseem Mishra ◽  
...  
Keyword(s):  
Emergency Department ◽  
Head And Neck Cancer ◽  
Head And Neck ◽  
Cancer Patients ◽  
Neck Cancer ◽  
Emergency Department Visits

Emergency department visits for prescription and synthetic opioid overdoses among patients with cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 6579-6579
Author(s):  
Vikram Jairam ◽  
Daniel X. Yang ◽  
James B. Yu ◽  
Henry S. Park
Keyword(s):  
Cervical Cancer ◽  
Emergency Department ◽  
Cancer Patients ◽  
The United States ◽  
Emergency Department Visits ◽  
Cancer Site ◽  
Opioid Overdose ◽  
Patients With Cancer ◽  
Rate Of Increase ◽  
Ed Visits

6579 Background: Patients with cancer may be at high risk of opioid dependence due to physical and psychosocial factors, although little data exists to inform providers and policymakers. Our aim is to examine overdoses from prescription and synthetic opiates leading to emergency department (ED) visits among patients with cancer in the United States. Methods: The Healthcare Cost and Utilization Project Nationwide Emergency Department Sample (HCUP-NEDS) was queried for all patient visits with a primary diagnosis of prescription or synthetic opioid overdose between 2006 and 2015. Baseline differences between patients with and without cancer were assessed using chi-square and ANOVA testing. Overdose rates by primary cancer site were normalized using prevalence data from the Surveillance, Epidemiology, and End Results (SEER) Program. Weighted frequencies were used to create national estimates for all data analyses. Results: There were 682,820 weighted ED visits for synthetic opioid overdose, among which 34,547 (5.1%) visits were also associated with a diagnosis of cancer. During this timeframe, ED visits for opioid overdose among patients with cancer increased 2.5-fold, compared to 1.7-fold among those without cancer. 16.5% of patients with cancer had metastatic disease. Patients with cancer presenting for opioid overdose had higher risk of hospital admission (74.8% vs 49.6%), respiratory intubation (13.2% vs 12.2%), mortality (2.1% vs 1.1%), and cost-of-hospital-stay ($32,665 vs $31,824) compared to their non-cancer counterparts (all P < 0.05). Primary cancers with the highest normalized overdose rates (ED visits per 10,000 patients) were esophagus (134), liver & intrahepatic bile duct (124), and cervical cancer (124). Other common cancers had the following normalized overdose rates: lung (105), head and neck (70), and breast (26). Conclusions: Approximately 5% of all ED visits due to prescription and synthetic opioid overdose are among patients with cancer. The rate of increase in ED visits due to opioid overdose from cancer patients was nearly 50% higher than that from non-cancer patients over the 10-year study period. Patients with esophageal, liver, and cervical cancer may be at highest risk.

scholarly journals P1.01-032 Emergency Department Visits by Lung Cancer Patients in Korea

2017 ◽  
Vol 12 (1) ◽  
pp. S468
Author(s):  
Dong Won Park ◽  
Gun Woo Koo ◽  
Tai Sun Park ◽  
Ji-Yong Moon ◽  
Sang-Heon Kim ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Emergency Department ◽  
Cancer Patients ◽  
Emergency Department Visits ◽  
Lung Cancer Patients

Frontline oncology care team primary palliative symptom guideline education, the oncology care model, and emergency department visits.

2018 ◽  
Vol 36 (34_suppl) ◽  
pp. 143-143 ◽  
Author(s):  
Susan McInnes ◽  
Cheryl M Carrino ◽  
Laura Shoemaker
Keyword(s):  
Emergency Department ◽  
Cancer Patients ◽  
Cleveland Clinic ◽  
Care Quality ◽  
Emergency Department Visits ◽  
Care Model ◽  
Main Campus ◽  
Palliative Care Teams ◽  
Oncology Care ◽  
Ed Visits

143 Background: The Oncology Care Model (OCM) is a novel 5-year quality-based Oncology payment and care delivery program established by the Centers for Medicare & Medicaid Service in 2016. OCM prioritizes high-quality, coordinated care for patients undergoing chemotherapy (chemo pts.) Participating centers provide augmented services to enhance care and meet quality goals. Challenging symptoms (sxs) are common among chemo pts and may lead to hospitalization and decreased quality of life. Specialist palliative care teams are not able to see all chemo pts with active sxs. Front line oncology care teams (FLC) need education on primary palliative sx management. Methods: Cleveland Clinic Taussig Cancer Institute is one of 181 practices voluntarily participating in OCM. Locations include main campus and 5 regional cancer offices with 100 oncologists caring for about 4,000 chemotherapy patients annually. Our OCM team engaged Oncology (Onc) and Palliative Medicine (PM) providers to standardize sx management. Education was provided to FLC of all disciplines. Electronic record analytics were used to determine emergency department (ED) utilization. Results: A multidisciplinary team of Onc and PM experts developed guidelines for 4 common sxs (chemotherapy-induced neuropathy, persistent cancer pain, nausea/vomiting and constipation. Guidelines were approved by key Onc and PM staff and made available to all providers online. There were 4 educational sessions for FLCs to all sites in 2017. Urgent sx outpatient appointment slots were created in oncology offices to address uncontrolled sx. From Dec 2017 to May 2018, ED visits for all cancer patients at main campus decreased from 500/month to 453/month (9.4%.) Reductions in ED visits were also seen at 2 hospitals adjacent to regional cancer centers (16% and 6%.) Conclusions: OCM participation provided an opportunity to improve care quality at our institution. Primary palliative sx guidelines were successfully developed by an interdisciplinary team and disseminated to FLC. Urgent sx management appointments were made available in oncology offices. These interventions coincided with a reduction in ED visits for all cancer patients.

Using a chatbot to reduce emergency department visits and unscheduled hospitalizations among patients with gynecologic malignancies during chemotherapy: a pilot study (Preprint)

2021 ◽  
Author(s):  
Ming-Yuan Huang ◽  
Chia-Sui Weng ◽  
Hsiao-Li Kuo ◽  
Yung-Cheng Su
Keyword(s):  
Emergency Department ◽  
Pilot Study ◽  
Usual Care ◽  
Cancer Patients ◽  
Text Messaging ◽  
Emergency Department Visits ◽  
Control Group ◽  
Gynecologic Malignancies ◽  
Patient Reported ◽  
Ed Visits

BACKGROUND A chatbot is an automatic text-messaging tool that creates a dynamic interaction and simulates a human conversation through text or voice via smartphones or computers. A chatbot could be an effective solution for cancer patients’ follow-up during treatment, and could save time for healthcare providers. OBJECTIVE We conducted a retrospective cohort pilot study to evaluate whether a chatbot-based collection of patient-reported symptoms during chemotherapy, with automated alerts to clinicians, could decrease emergency department (ED) visits and hospitalizations. A control group received usual care. METHODS Self-reporting symptoms were communicated via the chatbot, a Facebook Messenger-based interface for patients with gynecologic malignancies. The chatbot included questions about common symptoms experienced during chemotherapy. Patients could also use the text-messaging feature to speak directly to the chatbot, and all reported outcomes were monitored by a cancer manager. The primary and secondary outcomes of the study were emergency department visits and unscheduled hospitalizations after initiation of chemotherapy after diagnosis of gynecologic malignancies. Multivariate Poisson regression models were applied to assess the adjusted incidence rate ratios (aIRRs) for chatbot use for ED visits and unscheduled hospitalizations after controlling for age, cancer stage, type of malignancy, diabetes, hypertension, chronic renal insufficiency, and coronary heart disease. RESULTS Twenty patients were included in the chatbot group, and 43 in the usual-care group. Significantly lower aIRRs for chatbot use for ED visits (0.27; 95% CI 0.11–0.65; p=0.003) and unscheduled hospitalizations (0.31; 95% CI 0.11–0.88; p=0.028) were noted. Patients using the chatbot approach had lower aIRRs of ED visits and unscheduled hospitalizations compared to usual-care patients. CONCLUSIONS The chatbot was helpful for reducing ED visits and unscheduled hospitalizations in patients with gynecologic malignancies who were receiving chemotherapy. These findings are valuable for inspiring the future design of digital health interventions for cancer patients.

EPR19-069: Opioid Use Among Cancer Patients Undergoing Surgery and Their Associated Risk of Re-admissions and Emergency Department Visits in the 1-Year Postsurgical Period

2019 ◽  
Vol 17 (3.5) ◽  
pp. EPR19-069 ◽  
Author(s):  
Siyana Kurteva ◽  
Robyn Tamblyn ◽  
Ari Meguerditchian
Keyword(s):  
Emergency Department ◽  
Cancer Patients ◽  
Healthcare System ◽  
Emergency Department Visits ◽  
Administrative Claims ◽  
Opioid Use ◽  
Opioid Prescription ◽  
Ed Visits ◽  
Opioid Users ◽  
The Impact

Background: Prescription opioid use and overdose has steadily increased over the past years, resulting in a dramatic increase in opioid-related emergency department (ED) visits and hospitalizations. Methods: This study used a prospective cohort of cancer patients having undergone surgery in Montreal (Quebec) to describe their post-discharge opioid use and identify potential patterns of unplanned health service use (ED visits, hospitalizations). Provincial health administrative claims were used to measure opioid dispensation as well as hospital re-admissions and ED visits. The hospital warehouse, patient chart and patient interview will be used to further describe patient’s medical profile. Marginal structural models will be used to model the association between use of opioids and risk of ED visits and hospitalizations. Inverse probability of treatment and censoring weights will be constructed to properly adjust for confounders that may be unbalanced between the opioid and non–opioid users as well as to account for competing risk due to mortality. Reasons for the re-admissions will also be presented as part of the analyses. Covariates will include patient comorbidities, medication history, and healthcare system characteristics such as nurse-to-patient and attending physician-to-patient ratios. Results (interim): A total of 821 were included in the study; of these, 73% (n=597) were admitted for a cancer procedure. At postoperative discharge, 605 (74%) of patients had at least one opioid dispensation, of which the majority (67%) were oxycodone with hydromorphone being the second most prescribed (28%). Among those who filled a prescription, mean age was 66 (13.4), 68% had no previous history of opioid use, and 10% have had 3 or more dispensing pharmacies in the year prior to admission, compared to less than 1% for the non–opioid users. Overall, 343 people refilled their opioid prescription at least once and 128 at least twice during the 1-year postoperative period. Among cancer patients who were opioid users, 214 ED visits occurred in the 1 year after surgery compared to only 40 for the non-cancer opioid users. Conclusion: This study will help to identify the risk profile of cancer patients who are most likely to continue using opioids for prolonged periods following surgical procedures as well as quantify the impact of opioid use and its associated burden on the healthcare system in order to identify areas for possible interventions.

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