Original Research ArticleImproving cancer patient emergency room utilization: A New Jersey state assessment

- Our study examined the characteristics and outcomes of ED visits by cancer patients in the state of New Jersey.
- Comorbidities, age, race, insurance type and certain cancers were associated with increased utilization of the ED by cancer patients.
- Questionnaires, patient navigators, and clinical pathways can identify, guide and provide early initiation of treatment.
- These programs can improve cancer patient satisfaction, outcomes and decreasing health care costs.

IntroductionDue to its increasing incidence and its major contribution to healthcare costs, cancer is a major public health problem in the United States. The impact across different services is not well documented and utilization of emergency departments (ED) by cancer patients is not well characterized. The aim of our study was to identify factors that can be addressed to improve the appropriate delivery of quality cancer care thereby reducing ED utilization, decreasing hospitalizations and reducing the related healthcare costs.MethodsThe New Jersey State Inpatient and Emergency Department Databases were used to identify the primary outcome variables; patient disposition and readmission rates. The independent variables were demographics, payer and clinical characteristics. Multivariable unconditional logistic regression models using clinical and demographic data were used to predict hospital admission or emergency department return.ResultsA total of 37,080 emergency department visits were cancer related with the most common diagnosis attributed to lung cancer (30.0%) and the most common presentation was pain. The disposition of patients who visit the ED due to cancer related issues is significantly affected by the factors of race (African American OR = 0.6, p value = 0.02 and Hispanic OR = 0.5, p value = 0.02, respectively), age aged 65 to 75 years (SNF/ICF OR 2.35, p value = 0.00 and Home Healthcare Service OR 5.15, p value = 0.01, respectively), number of diagnoses (OR 1.26, p value = 0.00), insurance payer (SNF/ICF OR 2.2, p value = 0.02 and Home Healthcare Services OR 2.85, p value = 0.07, respectively) and type of cancer (breast OR 0.54, p value = 0.01, prostate OR 0.56, p value = 0.01, uterine OR 0.37, p value = 0.02, and other OR 0.62, p value = 0.05, respectively). In addition, comorbidities increased the likelihood of death, being transferred to SNF/ICF, or utilization of home healthcare services (OR 1.6, p value = 0.00, OR 1.18, p value = 0.00, and OR 1.16, p value = 0.04, respectively). Readmission is significantly affected by race (American Americans OR 0.41, standard error 0.08, p value = 0.001 and Hispanics OR 0.29, standard error 0.11, p value = 0.01, respectively), income (Quartile 2 OR 0.98, standard error 0.14, p value 0.01, Quartile 3 OR 1.07, standard error 0.13, p value 0.01, and Quartile 4 OR 0.88, standard error 0.12, p value 0.01, respectively), and type of cancer (prostate OR 0.25, standard error 0.09, p value = 0.001).ConclusionWeb based symptom questionnaires, patient navigators, end of life nursing and clinical cancer pathways can identify, guide and prompt early initiation of treat before progression of symptoms in cancer patients most likely to visit the ED. Thus, improving cancer patient satisfaction, outcomes and reduce health care costs.