scholarly journals Best Practices for Reducing Unplanned Acute Care for Patients With Cancer

2018 ◽  
Vol 14 (5) ◽  
pp. 306-313 ◽  
Author(s):  
Nathan R. Handley ◽  
Lynn M. Schuchter ◽  
Justin E. Bekelman
Keyword(s):  
Emergency Department ◽  
Best Practices ◽  
Acute Care ◽  
Clinical Pathways ◽  
Optimal Strategies ◽  
Emergency Department Visits ◽  
Professional Organizations ◽  
Early Palliative Care ◽  
Patients With Cancer ◽  
Unplanned Admissions

Variation and cost in oncology care represent a large and growing burden for the US health care system, and acute hospital care is one of the single largest drivers. Reduction of unplanned acute care is a major priority for clinical transformation in oncology; proposed changes to Medicare reimbursement for patients with cancer who suffer unplanned admissions while receiving chemotherapy heighten the need. We conducted a review of best practices to reduce unplanned acute care for patients with cancer. We searched PubMed for articles published between 2000 and 2017 and reviewed guidelines published by professional organizations. We identified five strategies to reduce unplanned acute care for patients with cancer: (1) identify patients at high risk for unplanned acute care; (2) enhance access and care coordination; (3) standardize clinical pathways for symptom management; (4) develop new loci for urgent cancer care; and (5) use early palliative care. We assessed each strategy on the basis of specific outcomes: reduction in emergency department visits, reduction in hospitalizations, and reduction in rehospitalizations within 30 days. For each, we define gaps in knowledge and identify areas for future effort. These five strategies can be implemented separately or, with possibly more success, as an integrated program to reduce unplanned acute care for patients with cancer. Because of the large investment required and the limited data on effectiveness, there should be further research and evaluation to identify the optimal strategies to reduce emergency department visits, hospitalizations, and rehospitalizations. Proposed reimbursement changes amplify the need for cancer programs to focus on this issue.

Patterns and Results of Triage Advice Before Emergency Department Visits Made by Patients With Cancer

2021 ◽  
pp. OP.20.00617
Author(s):  
Arthur S. Hong ◽  
Hannah Chang ◽  
D. Mark Courtney ◽  
Hannah Fullington ◽  
Simon J. Craddock Lee ◽  
...  
Keyword(s):  
Emergency Department ◽  
Acute Care ◽  
Emergency Department Visits ◽  
University Hospital ◽  
Urgent Care ◽  
Telephone Triage ◽  
Patients With Cancer ◽  
Oncology Care ◽  
Ed Visits ◽  
The University

PURPOSE: Patients with cancer undergoing treatment frequently visit the emergency department (ED) for commonly anticipated complaints (eg, pain, nausea, and vomiting). Nearly all Medicare Oncology Care Model (OCM) participants prioritized ED use reduction, and the OCM requires that patients have 24-hour telephone access to a clinician, but actual reductions in ED visits have been mixed. Little is known about the use of telephone triage for acute care. METHODS: We identified adults aged 18+ years newly diagnosed with cancer, linked to ED visits from a single institution within 6 months after diagnosis, and then analyzed the telephone and secure electronic messages in the preceding 24 hours. We coded interactions to classify the reason for the call, the main ED referrer, and other attempted management. We compared the acuity of patient self-referred versus clinician-referred ED visits by modeling hospitalization and ED visit severity. RESULTS: From 2011 to 2018, 3,247 adults made 5,371 ED visits to the university hospital and self-referred to the ED 58.5% of the time. Clinicians referred to outpatient or oncology urgent care for 10.3% of calls but referred to the ED for 61.3%. Patient self-referred ED visits were likely to be hospitalized (adjusted Odds Ratio [aOR], 0.89, 95% CI, 0.64 to 1.22) and were not more severe (aOR, 0.75, 95% CI, 0.55 to 1.02) than clinician referred. CONCLUSION: Although patients self-referred for six of every 10 ED visits, self-referred visits were not more severe. When patients called for advice, clinicians regularly recommended the ED. More should be done to understand barriers that patients and clinicians experience when trying to access non-ED acute care.

Prospectively assessing risk of acute care utilization for patients with an active cancer diagnosis.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 208-208
Author(s):  
Valerie Pracilio Csik ◽  
Adam Binder ◽  
Michael Li ◽  
Nathan Handley
Keyword(s):  
Emergency Department ◽  
Acute Care ◽  
Cancer Diagnosis ◽  
Cohort Analysis ◽  
Emergency Department Visits ◽  
Care Utilization ◽  
Significant Variable ◽  
Patients With Cancer ◽  
Acute Care Utilization ◽  
Active Cancer

208 Background: Acute care utilization (ACU)--emergency department visits or hospitalizations--is common in patients with cancer. As many as 83% of all patients with cancer visit the emergency department annually; nearly three quarters of patients with advanced cancer are hospitalized in the year after diagnosis. Much of this ACU may be preventable. Identifying patients at risk for ACU using model-based approaches has shown potential for risk stratifying certain patient subgroups. However, a model applicable to any patient with an active cancer diagnosis is needed. We developed a real time clinical prediction model to assess risk for acute care utilization in patients with an active cancer diagnosis. Methods: We completed a retrospective cohort analysis of patients with an active cancer diagnosis (defined as at least one medical oncology encounter in a 12 month period) at one health system. Clinical factors with potential to impact disease progression and ACU were identified through a clinical review. Significant variables were defined by multivariate logistic regression. Risk of ACU was further characterized through the development of a point scoring system to define the upper decile of patients at highest risk. Results: We included 8,246 patient records in the analysis. Seven variables were determined to be statistically significant: An emergency department visit in the last 90 days, chronic obstructive pulmonary disease, congestive heart failure, chronic kidney disease, low hemoglobin, low albumin, and low absolute neutrophil count. The model produced an overall C-statistic of 0.726 Each significant variable was assigned a score of 0 or 1 (with the exception of ED visits, which were given one point for each visit, with three points maximum). Each patient received a total score, resulting from the summation of the individual variable scores. An evaluation of the distribution of points determined that 10% of the patients achieved a score of 2 or higher and contributed to 46% of ACU in the last 90 days. Patients receiving 0 points were defined as low risk (73% of patients contributing to 30% of ED/admissions). Patients receiving 1 point were deemed intermediate risk (17% of patients contributing to 24% of ED/admissions). Conclusions: Risk of acute care utilization for patients with an active cancer diagnosis can be prospectively assessed. This tool is currently integrated into our clinical practice and is updated every 14 days, or any time the chart is accessed. Assessment of efficacy is ongoing.

scholarly journals Emergency department visits for children with acute asthma: discharge instructions, parental plans, and follow-through of care—a prospective study

CJEM ◽  
2014 ◽  
Vol 16 (06) ◽  
pp. 467-476 ◽  
Author(s):  
Pat G. Camp ◽  
Seamus P. Norton ◽  
Ran D. Goldman ◽  
Salomeh Shajari ◽  
M. Anne Smith ◽  
...  
Keyword(s):  
Emergency Department ◽  
Acute Care ◽  
Family Doctor ◽  
Emergency Department Visits ◽  
Upper Respiratory Tract ◽  
Asthma Exacerbations ◽  
Initial Care ◽  
Children With Asthma ◽  
Tract Infections ◽  
The Impact

Abstract Objective: Communication between emergency department (ED) staff and parents of children with asthma may play a role in asthma exacerbation management. We investigated the extent to which parents of children with asthma implement recommendations provided by the ED staff. Method: We asked questions on asthma triggers, ED care (including education and discharge recommendations), and asthma management strategies used at home shortly after the ED visit and again at 6 months. Results: A total of 148 children with asthma were recruited. Thirty-two percent of children were not on inhaled corticosteroids prior to their ED visit. Eighty percent of parents identified upper respiratory tract infections (URTIs) as the primary trigger for their child’s asthma. No parent received or implemented any specific asthma strategies to reduce the impact of URTIs; 82% of parents did not receive any printed asthma education materials. Most (66%) parents received verbal instructions on how to manage their child’s future asthma exacerbations. Of those, one-third of families were told to return to the ED. Parents were rarely advised to bring their child to their family doctor in the event of a future exacerbation. At 6 months, parents continued to use the ED services for asthma exacerbations in their children, despite reporting feeling confident in managing their child’s asthma. Conclusion: Improvements are urgently needed in developing strategies to manage pediatric asthma exacerbations related to URTIs, communication with parents at discharge in acute care, and using alternate acute care services for parents who continue to rely on EDs for the initial care of mild asthma exacerbations.

Identification of patients at high risk for preventable emergency department visits and inpatient admissions after starting chemotherapy: Machine learning applied to comprehensive electronic health record data.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1511-1511
Author(s):  
Dylan J. Peterson ◽  
Nicolai P. Ostberg ◽  
Douglas W. Blayney ◽  
James D. Brooks ◽  
Tina Hernandez-Boussard
Keyword(s):  
Machine Learning ◽  
Emergency Department ◽  
Electronic Health Record ◽  
Acute Care ◽  
Cancer Care ◽  
Model Performance ◽  
Emergency Department Visits ◽  
Health Record ◽  
Patients At Risk ◽  
Ed Visits

1511 Background: Acute care use is one of the largest drivers of cancer care costs. OP-35: Admissions and Emergency Department Visits for Patients Receiving Outpatient Chemotherapy is a CMS quality measure that will affect reimbursement based on unplanned inpatient admissions (IP) and emergency department (ED) visits. Targeted measures can reduce preventable acute care use but identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data available in the Electronic Health Record (EHR). We hypothesized dense, structured EHR data could be used to train machine learning algorithms to predict risk of preventable ED and IP visits. Methods: Patients treated at Stanford Health Care and affiliated community care sites between 2013 and 2015 who met inclusion criteria for OP-35 were selected from our EHR. Preventable ED or IP visits were identified using OP-35 criteria. Demographic, diagnosis, procedure, medication, laboratory, vital sign, and healthcare utilization data generated prior to chemotherapy treatment were obtained. A random split of 80% of the cohort was used to train a logistic regression with least absolute shrinkage and selection operator regularization (LASSO) model to predict risk for acute care events within the first 180 days of chemotherapy. The remaining 20% were used to measure model performance by the Area Under the Receiver Operator Curve (AUROC). Results: 8,439 patients were included, of whom 35% had one or more preventable event within 180 days of starting chemotherapy. Our LASSO model classified patients at risk for preventable ED or IP visits with an AUROC of 0.783 (95% CI: 0.761-0.806). Model performance was better for identifying risk for IP visits than ED visits. LASSO selected 125 of 760 possible features to use when classifying patients. These included prior acute care visits, cancer stage, race, laboratory values, and a diagnosis of depression. Key features for the model are shown in the table. Conclusions: Machine learning models trained on a large number of routinely collected clinical variables can identify patients at risk for acute care events with promising accuracy. These models have the potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted preventative interventions. Future work will include prospective and external validation in other healthcare systems.[Table: see text]

Prior Frequent Emergency Department Use as a Predictor of Emergency Department Visits After a New Cancer Diagnosis

2021 ◽  
pp. OP.20.00889
Author(s):  
Arthur S. Hong ◽  
Danh Q. Nguyen ◽  
Simon Craddock Lee ◽  
D. Mark Courtney ◽  
John W. Sweetenham ◽  
...  
Keyword(s):  
Emergency Department ◽  
Cancer Diagnosis ◽  
Negative Binomial ◽  
Academic Medical Center ◽  
Safety Net ◽  
Emergency Department Visits ◽  
Patients With Cancer ◽  
Safety Net Hospital ◽  
Ed Visits ◽  
After Cancer

PURPOSE: To determine whether emergency department (ED) visit history prior to cancer diagnosis is associated with ED visit volume after cancer diagnosis. METHODS: This was a retrospective cohort study of adults (≥ 18 years) with an incident cancer diagnosis (excluding nonmelanoma skin cancers or leukemia) at an academic medical center between 2008 and 2018 and a safety-net hospital between 2012 and 2016. Our primary outcome was the number of ED visits in the first 6 months after cancer diagnosis, modeled using a multivariable negative binomial regression accounting for ED visit history in the 6-12 months preceding cancer diagnosis, electronic health record proxy social determinants of health, and clinical cancer-related characteristics. RESULTS: Among 35,090 patients with cancer (49% female and 50% non-White), 57% had ≥ 1 ED visit in the 6 months immediately following cancer diagnosis and 20% had ≥ 1 ED visit in the 6-12 months prior to cancer diagnosis. The strongest predictor of postdiagnosis ED visits was frequent (≥ 4) prediagnosis ED visits (adjusted incidence rate ratio [aIRR]: 3.68; 95% CI, 3.36 to 4.02). Other covariates associated with greater postdiagnosis ED use included having 1-3 prediagnosis ED visits (aIRR: 1.32; 95% CI, 1.28 to 1.36), Hispanic (aIRR: 1.12; 95% CI, 1.07 to 1.17) and Black (aIRR: 1.21; 95% CI, 1.17 to 1.25) race, homelessness (aIRR: 1.95; 95% CI, 1.73 to 2.20), advanced-stage cancer (aIRR: 1.30; 95% CI, 1.26 to 1.35), and treatment regimens including chemotherapy (aIRR: 1.44; 95% CI, 1.40 to 1.48). CONCLUSION: The strongest independent predictor for ED use after a new cancer diagnosis was frequent ED visits before cancer diagnosis. Efforts to reduce potentially avoidable ED visits among patients with cancer should consider educational initiatives that target heavy prior ED users and offer them alternative ways to seek urgent medical care.

scholarly journals Emergency Department Visits for Opioid Overdoses Among Patients With Cancer

2019 ◽  
Vol 112 (9) ◽  
pp. 938-943 ◽  
Author(s):  
Vikram Jairam ◽  
Daniel X Yang ◽  
James B Yu ◽  
Henry S Park
Keyword(s):  
At Risk ◽  
Emergency Department ◽  
Statistical Tests ◽  
Temporal Trends ◽  
The United States ◽  
Emergency Department Visits ◽  
Multivariable Logistic Regression Analysis ◽  
Opioid Overdose ◽  
Patients With Cancer ◽  
Ed Visits

Abstract Background Patients with cancer may be at risk of high opioid use due to physical and psychosocial factors, although little data exist to inform providers and policymakers. Our aim is to examine overdoses from opioids 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 was queried for all adult cancer-related patient visits with a primary diagnosis of opioid overdose between 2006 and 2015. Temporal trends and baseline differences between patients with and without opioid-related ED visits were evaluated. Multivariable logistic regression analysis was used to identify risk factors associated with opioid overdose. All statistical tests were two-sided. Results Between 2006 and 2015, there were a weighted total of 35 339 opioid-related ED visits among patients with cancer. During this time frame, the incidence of opioid-related ED visits for overdose increased twofold (P < .001). On multivariable regression (P < .001), comorbid diagnoses of chronic pain (odds ratio [OR] 4.51, 95% confidence interval [CI] = 4.13 to 4.93), substance use disorder (OR = 3.54, 95% CI = 3.28 to 3.82), and mood disorder (OR = 3.40, 95% CI = 3.16 to 3.65) were strongly associated with an opioid-related visit. Patients with head and neck cancer (OR = 2.04, 95% CI = 1.82 to 2.28) and multiple myeloma (OR = 1.73, 95% CI = 1.32 to 2.26) were also at risk for overdose. Conclusions Over the study period, the incidence of opioid-related ED visits in patients with cancer increased approximately twofold. Comorbid diagnoses and primary disease site may predict risk for opioid overdose.

Inpatient Palliative Care Consult: A Marker for High Risk of Readmission or Death in Discharged Oncology Inpatients

2019 ◽  
pp. 082585971986906
Author(s):  
Debbie Selby ◽  
Anita Chakraborty ◽  
Audrey Kim ◽  
Jeff Myers
Keyword(s):  
Emergency Department ◽  
Palliative Care ◽  
High Risk ◽  
Acute Care ◽  
Disease Process ◽  
Emergency Department Visits ◽  
Advanced Illness ◽  
Phone Calls ◽  
Palliative Care Teams ◽  
Advance Care

Background: Emergency department visits or readmission to hospital are common particularly among those with advanced illness. Little prospective data exist on early outcomes specifically for patients seen by a palliative care consult service during their acute care admission, who are subsequently discharged home. Methods: This study followed 62 oncology patients who had had a palliative care consult during their admission to acute care with weekly phone calls postdischarge for 4 weeks. Events recorded included death, readmission, emergency department visits, and admission to a palliative care unit. Results: By the end of the study, 32 (52%) of 62 had had at least 1 event, (readmission, emergency department visit, or death), with the majority of these occurring in the first 2 weeks postdischarge. The overall 4-week death rate was 14 (22.6%) of 62. Conclusions: These data suggest that the need for a palliative care consult identifies inpatients at very high risk for early deterioration and underlines the critical importance of advance care planning/goals-of-care discussions by the oncology and palliative care teams to ensure patients and families understand their disease process and have the opportunity to direct their care decisions.

From metrics to practice: identifying preventable emergency department visits for patients with cancer

2020 ◽  
Author(s):  
Mohana Roy ◽  
Brian Halbert ◽  
Scott Devlin ◽  
David Chiu ◽  
Ryan Graue ◽  
...  
Keyword(s):  
Emergency Department ◽  
Emergency Department Visits ◽  
Patients With Cancer
Sign in / Sign up

Export Citation Format

Share Document