Identification of potentially avoidable hospitalizations in patients with GI cancer

Studying Guaranteed Income in Oncology: Lessons Learned From Launching the Guaranteed Income and Financial Treatment Trial

By targeting income and financial stress as key social determinants of health, unconditional cash transfers (UCTs) may improve cancer health outcomes and reduce cancer health disparities. Described in policy circles as guaranteed or basic income, UCTs have been shown to improve a range of health outcomes in low-income populations but have not yet been examined as a targeted intervention for people with cancer. This article describes some of the lessons learned from launching the Guaranteed Income and Financial Treatment trial, a two-arm randomized controlled trial of UCTs in oncology, along with a rationale for studying UCTs in people with cancer who have low incomes, and presents an introductory primer on UCT research for oncology clinicians and researchers and future directions for research.

Unplanned Hospital Admissions in Patients With Solid Tumors in Brazil: Causes and Progressive Disease's Impact on Outcomes

PURPOSE

Most patients with cancer will be hospitalized throughout the disease course. However, most evidence on the causes and outcomes of these hospitalizations comes from administrative data or small retrospective studies from high-income countries.

METHODS

This study is a retrospective cohort of patients with solid tumors hospitalized from February 1, 2021, to December 31, 2021, in a tertiary cancer center in São Paulo, Brazil. We collected data on cancer diagnosis, symptoms at admission, hospitalization diagnosis, and survival clinical outcomes during in-hospital stay (in-hospital mortality) and after discharge (readmission rates and overall survival [OS]). Progressive disease (PD) diagnosis during admission was retrieved from manual chart review if explicitly stated by the attending physician. We modeled in-hospital mortality and postdischarge OS with logistic regression and Cox proportional hazards models, respectively.

RESULTS

A total of 3,726 unique unplanned admissions were identified. The most common symptoms at admission were pain (40.6%), nausea (16.8%), and dyspnea (16.1%). PD (34.0%), infection (31.1%), and cancer pain (13.4%) were the most frequent reasons for admission. The in-hospital mortality rate was 18.9%. Patients with PD had a high in-hospital mortality rate across all tumor groups and higher odds of in-hospital death (odds ratio, 3.5 [95% CI, 3.0 to 4.2]). The 7-, 30-, and 90-day readmission rates were 11.9%, 33.5%, and 54%, respectively. The postdischarge median OS (mOS) was 12.6 months (95% CI, 11.6 to 13.7). Poorer postdischarge survival was observed among patients with PD (mOS, 5 months v 18 months; P < .001; hazard ratio, 2.4 [95% CI, 2.1 to 2.6]).

CONCLUSION

PD is a common diagnosis during unplanned hospitalizations and is associated with higher in-hospital mortality rates and poorer OS after discharge. Oncologists should be aware of the prognostic implications of PD during admission and align goals of care with their patients.

Patterns of acute hospital and specialist palliative care use among people with non-curative upper gastrointestinal cancer

PURPOSE

Upper gastrointestinal (GI) cancers contribute to 16.7% of UK cancer deaths. These patients make high use of acute hospital services, but detail about palliative care use is lacking. We aimed to determine the patterns of use of acute hospital and hospital specialist palliative care services in patients with advanced non-curative upper GI cancer.

METHODS

We conducted a service evaluation of hospital use and palliative care for all patients with non-curative upper GI cancer seen in one large hospital, using routinely collected data (2019-2022). We report and characterise hospital admissions and palliative care within the study time period, using descriptive statistics, and multivariable Poisson regression to estimate the unadjusted and adjusted incidence rate ratio of hospital admissions.

RESULTS

The total with non-curative upper GI cancer was 960. 86.7% had at least one hospital admission, with 1239 admissions in total. Patients had a higher risk of admission to hospital if: aged ≤ 65 (IRR for 66-75 years 0.71, IRR 76-85 years 0.68; IRR > 85 years 0.53; p < 0.05), or lived in an area of lower socioeconomic status (IMD Deciles 1-5) (IRR 0.90; p < 0.05). Over the 4-year period, the rate of re-admission was higher in patients not referred to palliative care (rate 0.52 readmissions/patient versus rate 1.47 readmissions/patient).

CONCLUSION

People with advanced non-curative gastrointestinal cancer have frequent hospital admissions, especially if younger or from areas of lower socioeconomic status. There is clear association between specialist palliative care referral and reduced risk of hospitalisation. This evidence supports referral to specialist palliative care.

Impact of Electronic Patient-Reported Outcomes on Unplanned Consultations and Hospitalizations in Patients With Cancer Undergoing Systemic Therapy: Results of a Patient-Reported Outcome Study Compared With Matched Retrospective Data

BACKGROUND

The evaluation of electronic patient-reported outcomes (ePROs) is increasingly being used in clinical studies of patients with cancer and enables structured and standardized data collection in patients' everyday lives. So far, few studies or analyses have focused on the medical benefit of ePROs for patients.

OBJECTIVE

The current exploratory analysis aimed to obtain an initial indication of whether the use of the Consilium Care app (recently renamed medidux; mobile Health AG) for structured and regular self-assessment of side effects by ePROs had a recognizable effect on incidences of unplanned consultations and hospitalizations of patients with cancer compared to a control group in a real-world care setting without app use. To analyze this, the incidences of unplanned consultations and hospitalizations of patients with cancer using the Consilium Care app that were recorded by the treating physicians as part of the patient reported outcome (PRO) study were compared retrospectively to corresponding data from a comparable population of patients with cancer collected at 2 Swiss oncology centers during standard-of-care treatment.

METHODS

Patients with cancer in the PRO study (178 included in this analysis) receiving systemic therapy in a neoadjuvant or noncurative setting performed a self-assessment of side effects via the Consilium Care app over an observational period of 90 days. In this period, unplanned (emergency) consultations and hospitalizations were documented by the participating physicians. The incidence of these events was compared with retrospective data obtained from 2 Swiss tumor centers for a matched cohort of patients with cancer.

RESULTS

Both patient groups were comparable in terms of age and gender ratio, as well as the distribution of cancer entities and Joint Committee on Cancer stages. In total, 139 patients from each group were treated with chemotherapy and 39 with other therapies. Looking at all patients, no significant difference in events per patient was found between the Consilium group and the control group (odds ratio 0.742, 90% CI 0.455-1.206). However, a multivariate regression model revealed that the interaction term between the Consilium group and the factor "chemotherapy" was significant at the 5% level (P=.048). This motivated a corresponding subgroup analysis that indicated a relevant reduction of the risk for the intervention group in the subgroup of patients who underwent chemotherapy. The corresponding odds ratio of 0.53, 90% CI 0.288-0.957 is equivalent to a halving of the risk for patients in the Consilium group and suggests a clinically relevant effect that is significant at a 2-sided 10% level (P=.08, Fisher exact test).

CONCLUSIONS

A comparison of unplanned consultations and hospitalizations from the PRO study with retrospective data from a comparable cohort of patients with cancer suggests a positive effect of regular app-based ePROs for patients receiving chemotherapy. These data are to be verified in the ongoing randomized PRO2 study (registered on ClinicalTrials.gov; NCT05425550).

TRIAL REGISTRATION

ClinicalTrials.gov NCT03578731; https://www.clinicaltrials.gov/ct2/show/NCT03578731.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/29271.

Digitally Enabled Transitional Care Management in Oncology

PURPOSE

Improving care transitions for patients with cancer discharged from the hospital is considered an important component of quality care. Digital monitoring has the potential to better the delivery of transitional care through improved patient-provider communication and enhanced symptom management. However, remote patient monitoring (RPM) interventions have not been widely implemented for oncology patients after discharge, an innovative setting in which to apply this technology.

METHODS

We implemented a RPM intervention which identifies medical oncology patients at discharge, monitors their symptoms for 10 days, and intervenes as necessary to manage symptoms. We evaluated the feasibility (>50% patient engagement with symptom assessment), appropriateness (symptom alerts), and acceptability (net promoter score >0.7) of the intervention and the initial effect on acute care visits and return on investment.

RESULTS

During the study period, January 1, 2021, to December 31, 2022, we evaluated 2,257 medical oncology discharges representing 1,857 unique patients. We found that 65.9% of patients discharged (N = 1,489) completed at least one symptom assessment postdischarge and of them, 45.5% (n = 678) generated a severe symptom alert that we helped to manage. Patients expressed high satisfaction with the intervention with a net promoter score of 84%. In preliminary analysis of patients with GI malignancies (n = 449), we found a nonsignificant decrease in 30-day readmissions for the intervention cohort (n = 269) by 5.8% as compared with the control (n = 180; from 33.3% to 27.5%; P = .22).

CONCLUSION

Digital transitional care management was feasible and demonstrated that patients transitioning from the hospital to home have a substantial symptom burden. The intervention was associated with high patient satisfaction but will require further refinement and evaluation to increase its impact on 30-day readmission.

The impact of an oncology urgent care center on health-care utilization

INTRODUCTION

Studies suggest that many emergency department (ED) visits and hospitalizations for patients with cancer may be preventable. The Centers for Medicare & Medicaid Services has implemented changes to the hospital outpatient reporting program that targets acute care in-treatment patients for preventable conditions. Oncology urgent care centers aim to streamline patient care. Our cancer center developed an urgent care center called the direct referral unit in 2011.

METHODS

We abstracted visits to our adjacent hospital ED and direct referral unit from January 2014 to June 2018. Patient demographics, cancer and visit diagnoses, visit charges, and 30-day therapy utilization were assessed.

RESULTS

An analysis of 13 114 visits demonstrated that increased direct referral unit utilization was associated with decreased monthly ED visits (P < .001). Common direct referral unit visit diagnoses were dehydration, nausea and vomiting, abdominal pain, and fever. Patients receiving active cancer treatment more frequently presented to the direct referral unit (P < .001). The average charges were $2221 for the direct referral unit and $10 261 for the ED.

CONCLUSION

The association of decreased ED visits with increased direct referral unit utilization demonstrates the potential for urgent care centers to reduce acute care visits. Many patients presented to our direct referral unit with preventable conditions, and these visits were associated with considerable cost savings, supporting its use as a cost-effective method to reduce acute care costs.

Understanding Potentially Preventable 7-day Readmission Rates in Hospital Medicine Patients at a Comprehensive Cancer Center

This study aimed to describe the potentially preventable 7-day unplanned readmission (PPR) rate in medical oncology patients. A retrospective analysis of all unplanned 7-day readmissions within Hospital Medicine at MD Anderson Cancer Center from September 1, 2020 to February 28, 2021, was performed. Readmissions were independently analyzed by 2 randomly selected individuals to determine preventability. Discordant reviews were resolved by a third reviewer to reach a consensus. Statistical analysis included 138 unplanned readmissions. The estimated PPR rate was 15.94%. The median age was 62.50 years; 52.90% were female. The most common type of cancer was noncolon GI malignancy (34.06%). Most patients had stage 4 cancer (69.57%) and were discharged home (64.93%). Premature discharge followed by missed opportunities for goals of care discussions were the most cited reasons for potential preventability. These findings highlight areas where care delivery can be improved to mitigate the risk of readmission within the medical oncology population.

Advance Directives for Patients With Breast Cancer: Applying the Right Info/Right Care/Right Patient/Right Time Oncology Model

Background Advance directives (AD) are an important component of life care planning for patients undergoing treatment for cancer; however, there are few effective interventions to increase AD rates. In this quality improvement project, the authors integrated AD counseling into a novel right info/right care/right patient/right time (4R) sequence of care oncology delivery intervention for breast cancer patients in an integrated health care delivery system. Methods The authors studied two groups of patients with newly diagnosed breast cancer who attended a multidisciplinary clinic and underwent definitive surgery at a single facility. The usual care (UC) cohort (N = 139) received care from October 1, 2019 to September 30, 2020. The 4R cohort (N = 141) received care from October 1, 2020 to September 30, 2121 that included discussing AD completion with a health educator prior to surgery. The authors used bivariate analyses to assess whether the AD intervention increased AD completion rates and to identify factors influencing AD completion. Results The UC and 4R cohorts were similar in age, gender, race/ethnicity, interpreter need, Elixhauser comorbidity index, National Comprehensive Cancer Network distress score ≥ 5, surgery type, stage, histology, grade, and Estrogen receptor/Progesterone receptor/ human epidermal growth factor receptor 2 (ER/PR/HER2) status. AD completion rates prior to surgery were significantly higher for the 4R vs UC cohort (73.8%, 95% confidence interval [CI] [66.5%-81.0%] vs 15.1%, 95% CI [9.2%-21.1%], p < .01) and did not significantly differ by age, race, need for interpreter, or distress scores. Conclusion Incorporation of a health educator discussion into a 4R care sequence plan significantly increased rates of time-sensitive AD completion.

Predictors of frequent emergency department visits among hospitalized cancer patients: a comparative cohort study using integrated clinical and administrative data to improve care delivery

BACKGROUND

Frequent emergency department (FED) visits by cancer patients represent a significant burden to the health system. This study identified determinants of FED in recently hospitalized cancer patients, with a particular focus on opioid use.

METHODS

A prospective cohort discharged from surgical/medical units of the McGill University Health Centre was assembled. The outcome was FED use (≥ 4 ED visits) within one year of discharge. Data retrieved from the universal health insurance system was analyzed using Cox Proportional Hazards (PH) model, adopting the Lunn-McNeil approach for competing risk of death.

RESULTS

Of 1253 patients, 14.5% became FED users. FED use was associated with chemotherapy one-year pre-admission (adjusted hazard ratio (aHR) 2.60, 95% CI: 1.80-3.70), ≥1 ED visit in the previous year (aHR: 1.80, 95% CI 1.20-2.80), ≥15 pre-admission ambulatory visits (aHR 1.54, 95% CI 1.06-2.34), previous opioid and benzodiazepine use (aHR: 1.40, 95% CI: 1.10-1.90 and aHR: 1.70, 95% CI: 1.10-2.40), Charlson Comorbidity Index ≥ 3 (aHR: 2.0, 95% CI: 1.2-3.4), diabetes (aHR: 1.60, 95% CI: 1.10-2.20), heart disease (aHR: 1.50, 95% CI: 1.10-2.20) and lung cancer (aHR: 1.70, 95% CI: 1.10-2.40). Surgery (cardiac (aHR: 0.33, 95% CI: 0.16-0.66), gastrointestinal (aHR: 0.34, 95% CI: 0.14-0.82) and thoracic (aHR: 0.45, 95% CI: 0.30-0.67) led to a decreased risk of FED use.

CONCLUSIONS

Cancer patients with higher co-morbidity, frequent use of the healthcare system, and opioid use were at increased risk of FED use. High-risk patients should be flagged for preventive intervention.

Potentially Avoidable Admissions and Prolonged Hospitalization in Patients with Suspected Colon Cancer

BACKGROUND

Suspicion of cancer in the Emergency Department (ED) may lead to potentially avoidable and prolonged admissions. We aimed to examine the reasons for potentially avoidable and prolonged hospitalizations after admissions from the ED for new colon cancer diagnoses (ED-dx).

METHODS

A retrospective, single-institution analysis was conducted of patients with ED-dx between 2017 and 2018. Defined criteria were used to identify potentially avoidable admissions. Patients without avoidable admissions were examined for ideal length of stay (iLOS), using separate defined criteria. Prolonged length of stay (pLOS) was defined as actual length of stay (aLOS) being greater than 1 day longer than iLOS.

RESULTS

Of 97 patients with ED-dx, 12% had potentially avoidable admissions, most often (58%) for cancer workup. Very little difference in demographic, tumor characteristics, or symptoms were found, except patients with potentially avoidable admissions were more functional (Eastern Cooperative Oncology Group [ECOG] score 0-1: 83% vs. 46%; p = 0.049) and had longer symptom duration prior to ED presentation {24 days (interquartile range [IQR] 7-75) vs. 7 days (IQR 2-21)}. Among the 60 patients who had necessary admissions but did not require urgent intervention, 78% had pLOS, most often for non-urgent surgery (60%) and further oncologic workup. The median difference between iLOS and aLOS was 12 days (IQR 8-16) for pLOS.

CONCLUSIONS

Potentially avoidable admissions following Ed-dx were uncommon but were mostly for oncologic workup. Once admitted, the majority of patients had pLOS, most often for definitive surgery and further oncologic workup. This suggests a lack of systems to safely transition to outpatient cancer management.

Thirty-Day Unplanned Hospital Readmissions in Patients With Cancer and the Impact of Social Determinants of Health: A Machine Learning Approach

PURPOSE

Develop a cancer-specific machine learning (ML) model that accurately predicts 30-day unplanned readmissions in patients with solid tumors.

METHODS

The initial cohort included patients 18 years or older diagnosed with a solid tumor. Two distinct cohorts were generated: one with and one without detailed social determinants of health (SDOHs) data. For each cohort, data were temporally partitioned in 70% (training), 20% (validation), and 10% (testing). Tree-based ML models were developed and validated on each cohort. The metrics used to evaluate the model's performance were receiver operating characteristic curve (ROC), area under the ROC curve, precision, recall (R), accuracy, and area under the precision-recall curve.

RESULTS

We included 13,717 patients in this study in two cohorts (5,059 without SDOH data and 8,658 with SDOH data). Unplanned 30-day readmission occurred in 21.3% of the cases overall. The five main non-SDOH factors most highly associated with an unplanned 30-day readmission (R, 0.74; IQR, 0.58-0.76) were: number of previous unplanned readmissions; higher Charlson comorbidity score; nonelective index admission; discharge to anywhere other than home, hospice, or nursing facility; and higher anion gap during the admission. Neighborhood crime index, neighborhood median home values, annual income, neighborhood median household income, and wealth index were the main five SDOH factors important for predicting a high risk for an unplanned hospital readmission (R, 0.66; IQR, 0.56-0.72). The models were not directly comparable.

CONCLUSION

Key drivers of unplanned readmissions in patients with cancer are complex and involve both clinical factors and SDOH. We developed a cancer-specific ML model that with reasonable accuracy identified patients with cancer at high risk for an unplanned hospital readmission.

Retrospective study of cancer patients' predictive factors of care in a large, Hungarian tertiary care centre

OBJECTIVES

To identify predictive factors of multiple emergency department (ED) visits, hospitalisation and potentially preventable ED visits made by patients with cancer in a Hungarian tertiary care centre.

DESIGN

Observational, retrospective study.

SETTING

A large, public tertiary hospital, in Somogy County, Hungary, with a level 3 emergency and trauma centre and a dedicated cancer centre.

PARTICIPANTS

Patients above 18 years with a cancer diagnosis (International Classification of Diseases, 10th Revision codes of C0000-C9670) who visited the ED in 2018, who had received their diagnosis of cancer within 5 years of their first ED visit in 2018 or received their diagnosis of cancer latest within the study year. Cases diagnosed with cancer at the ED (new cancer diagnosis-related ED visits) were also included, constituting 7.9% of visits.

PRIMARY OUTCOME MEASURES

Demographic and clinical characteristics were collected and the predictors of multiple (≥2) ED visits within the study year, admission to inpatient care following the ED visit (hospitalisation), potentially preventable ED visits and death within 36 months were determined.

RESULTS

2383 ED visits made by 1512 patients with cancer were registered. Predictive factors of multiple (≥2) ED visits were residing in a nursing home (OR 3.09, 95% CI 1.88 to 5.07) and prior hospice care (OR 1.87, 95% CI 1.05 to 3.31). Predictive factors for hospitalisation following an ED visit included a new cancer diagnosis-related visit (OR 1.86, 95% CI 1.30 to 2.66) and complaint of dyspnoea (OR 1.61, 95% CI 1.22 to 2.12).

CONCLUSIONS

Being a resident of a nursing home and receiving prior hospice care significantly increased the odds of multiple ED visits, while new cancer-related ED visits independently increased the odds of hospitalisation of patients with cancer. This is the first study to report these associations from a Central-Eastern European country. Our study may shed light on the specific challenges of EDs in general and particularly faced by countries in the region.

Risk Factors for Return to the Emergency Department and Readmission in Patients With Hospital-Diagnosed Advanced Lung Cancer

BACKGROUND

Advanced lung cancer (ALC) is a symptomatic disease often diagnosed in the context of hospitalization. The index hospitalization may be a window of opportunity to improve care delivery.

OBJECTIVES

We examined the patterns of care and risk factors for subsequent acute care utilization among patients with hospital-diagnosed ALC.

RESEARCH DESIGN, SUBJECTS, AND MEASURES

In Surveillance, Epidemiology, and End Results-Medicare, we identified patients with incident ALC (stage IIIB-IV small cell or non-small cell) from 2007 to 2013 and an index hospitalization within 7 days of diagnosis. We used a time-to-event model with multivariable regression to identify risk factors for 30-day acute care utilization (emergency department use or readmission).

RESULTS

More than half of incident ALC patients were hospitalized around the time of diagnosis. Among 25,627 patients with hospital-diagnosed ALC who survived to discharge, only 37% ever received systemic cancer treatment. Within 6 months, 53% had been readmitted, 50% had enrolled in hospice, and 70% had died. The 30-day acute care utilization was 38%.Small cell histology, greater comorbidity, precancer acute care use, length of index stay >8 days, and prescription of a wheelchair were associated with higher risk of 30-day acute care utilization. Age >85 years, female sex, residence in South or West regions, palliative care consultation, and discharge to hospice or a facility were associated with lower risk.

CONCLUSIONS

Many patients with hospital-diagnosed ALC experience an early return to the hospital and most die within 6 months. These patients may benefit from increased access to palliative and other supportive care during index hospitalization to prevent subsequent health care utilization.

Comparison of Oncologist and Model Estimates of Risk for Hospitalization During Systemic Therapy for Advanced Cancer

PURPOSE

A validated risk model with inputs of pretreatment sodium and albumin can identify patients at risk for hospitalization during cancer treatment. We evaluated how the model compares with risk estimates from treating oncologists.

METHODS

We evaluated the 30-day risk of hospitalization or death in patients starting palliative-intent systemic therapy for solid tumor malignancy. For each patient, we prospectively recorded categorical estimates of 30-day hospitalization risk (bottom third, middle third, top third) generated by a treating oncologist and by the two-variable model; a third hybrid risk estimate represented a composite of the oncologist and model risk assessments. We analyzed the agreement of oncologist and model-based risk estimates and compared discrimination, sensitivity, and specificity of each risk assessment method.

RESULTS

We collected oncologist, model, and hybrid estimates of hospitalization risk for 120 patients. The 30-day rate of hospitalization or death was 20%. There was minimal agreement between oncologist and model risk estimates (weighted kappa = 0.27). The c-statistic (a measure of discrimination) was 0.69 (95% CI, 0.57 to 0.81) for the clinician assessment, 0.77 for the model assessment (CI, 0.67 to 0.86; P = .24 compared with the oncologist assessment), and 0.79 for the hybrid assessment (CI, 0.69 to 0.90; P = .007 compared with the oncologist assessment). Sensitivity and specificity of the high-risk categorization did not differ significantly between the oncologist and model assessments; the hybrid assessment was significantly more sensitive (P = .02) and less specific (P = .03) than the oncologist assessment.

CONCLUSION

A model with inputs of pretreatment sodium and albumin improves oncologists' predictions of hospitalization risk during cancer treatment.

Variation in hospital utilization of palliative interventions for patients with advanced gastrointestinal cancer near end of life

BACKGROUND

Patients with advanced gastrointestinal (GI) cancer often undergo noncurative interventions with palliative intent to relieve high symptom burden near end of life. Hospital-level variation in intervention utilization remains unclear.

METHODS

National cohort study of 142 304 patients with stage III or IV GI cancer within the National Cancer Database (2004-2014) who died within 1-year of diagnosis. Hospitals were stratified by palliative intervention utilization (surgery, chemotherapy, radiation, pain management). Multivariable, multinomial regression evaluated the association between patient/hospital factors and palliative intervention utilization.

RESULTS

Across 1322 hospitals, median hospital palliative intervention utilization was 12.0% [interquartile range: 0.0%-26.1%]. Utilization increased over time in all but lowest utilizing hospitals. Relative to lowest utilizing hospitals, factors associated with a lower likelihood of care at highest utilizing hospitals included: race (White [ref]; Black-Relative Risk Ratio [RRR] 0.81, 95% confidence interval [0.77-0.85]) and lower income (RRR 0.81 [0.78-0.84]). Factors associated with a higher likelihood included: lower education level (RRR 1.62 [1.55-1.69]) and hospital type (community program [ref]; comprehensive community-RRR 1.33 [1.26-1.41]; academic-RRR 1.88 [1.77-1.99]; integrated network-RRR 1.79 [1.66-1.93]).

CONCLUSION

Hospital variation in palliative intervention use is substantial and potentially associated with sociodemographic and hospital characteristics. Future work can examine how differences in hospital care processes translate to quantity/quality of life for cancer patients.

Patient-Reported Symptom Complexity and Acute Care Utilization Among Patients With Cancer: A Population-Based Study Using a Novel Symptom Complexity Algorithm and Observational Data

BACKGROUND

Patients with cancer in Canada are often effectively managed in ambulatory settings; however, patients with unmanaged or complex symptoms may turn to the emergency department (ED) for additional support. These unplanned visits can be costly to the healthcare system and distressing for patients. This study used a novel patient-reported outcomes (PROs)-derived symptom complexity algorithm to understand characteristics of patients who use acute care, which may help clinicians identify patients who would benefit from additional support.

PATIENTS AND METHODS

This retrospective observational cohort study used population-based linked administrative healthcare data. All patients with cancer in Alberta, Canada, who completed at least one PRO symptom-reporting questionnaire between October 1, 2019, and April 1, 2020, were included. The algorithm used ratings of 9 symptoms to assign a complexity score of low, medium, or high. Multivariable binary logistic regressions were used to evaluate factors associated with a higher likelihood of having an ED visit or hospital admission (HA) within 7 days of completing a PRO questionnaire.

RESULTS

Of the 29,133 patients in the cohort, 738 had an ED visit and 452 had an HA within 7 days of completing the PRO questionnaire. Patients with high symptom complexity had significantly higher odds of having an ED visit (OR, 3.10; 95% CI, 2.59-3.70) or HA (OR, 4.20; 95% CI, 3.36-5.26) compared with low complexity patients, controlling for demographic covariates.

CONCLUSIONS

Given that patients with higher symptom complexity scores were more likely to use acute care, clinicians should monitor these more complex patients closely, because they may benefit from additional support or symptom management in ambulatory settings. A symptom complexity algorithm can help clinicians easily identify patients who may require additional support. Using an algorithm to guide care can enhance patient experiences, while reducing use of acute care services and the accompanying cost and burden.

Toward Predicting 30-Day Readmission Among Oncology Patients: Identifying Timely and Actionable Risk Factors

PURPOSE

Predicting 30-day readmission risk is paramount to improving the quality of patient care. In this study, we compare sets of patient-, provider-, and community-level variables that are available at two different points of a patient's inpatient encounter (first 48 hours and the full encounter) to train readmission prediction models and identify possible targets for appropriate interventions that can potentially reduce avoidable readmissions.

METHODS

Using electronic health record data from a retrospective cohort of 2,460 oncology patients and a comprehensive machine learning analysis pipeline, we trained and tested models predicting 30-day readmission on the basis of data available within the first 48 hours of admission and from the entire hospital encounter.

RESULTS

Leveraging all features, the light gradient boosting model produced higher, but comparable performance (area under receiver operating characteristic curve [AUROC]: 0.711) with the Epic model (AUROC: 0.697). Given features in the first 48 hours, the random forest model produces higher AUROC (0.684) than the Epic model (AUROC: 0.676). Both models flagged patients with a similar distribution of race and sex; however, our light gradient boosting and random forest models were more inclusive, flagging more patients among younger age groups. The Epic models were more sensitive to identifying patients with an average lower zip income. Our 48-hour models were powered by novel features at various levels: patient (weight change over 365 days, depression symptoms, laboratory values, and cancer type), hospital (winter discharge and hospital admission type), and community (zip income and marital status of partner).

CONCLUSION

We developed and validated models comparable with the existing Epic 30-day readmission models with several novel actionable insights that could create service interventions deployed by the case management or discharge planning teams that may decrease readmission rates over time.

Trends and Characteristics of Potentially Preventable Emergency Department Visits Among Patients With Cancer in the US

IMPORTANCE

An initial step to reducing emergency department (ED) visits among patients with cancer is to identify the characteristics of patients visiting the ED and examine which of those visits could be prevented.

OBJECTIVE

To explore nationwide trends and characteristics of ED visits and examine factors associated with potentially preventable ED visits and unplanned hospitalizations among patients with cancer in the US.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data on ED visits from the National Hospital Ambulatory Medical Care Survey from January 1, 2012, to December 31, 2019; US Cancer Statistics reports were used to estimate new cancer cases each year. Frequencies and trends among 35 510 014 ED visits by adult patients (aged ≥18 years) with cancer were calculated.

MAIN OUTCOMES AND MEASURES

The primary outcome was potentially preventable ED visits, and secondary outcomes were unplanned hospitalizations and the immediacy of the ED visits. Potentially preventable ED visits were identified using the Centers for Medicare & Medicaid Services definition. The Emergency Severity Index, a triage algorithm that ranks patients based on the urgency of their health care condition, was used to measure the immediacy of ED visits (immediate [most urgent], emergent, urgent, less urgent, and nonurgent), with the categories of immediate and emergent classified as high acuity. The Wilcoxon rank sum test was used to calculate trends in ED visits among patients with cancer over time. Multivariable logistic regression analyses were performed to examine the associations of patient, hospital, and temporal factors with potentially preventable ED use and ED use resulting in hospitalization.

RESULTS

Among 854 911 106 ED visits, 35 510 014 (4.2%) were made by patients with cancer (mean [SD] age, 66.2 [16.2] years); of those, 55.2% of visits were among women, 73.2% were among non-Hispanic White individuals, 89.8% were among patients living in a private residence, and 54.3% were among Medicare enrollees. A total of 18 316 373 ED visits (51.6%) were identified as potentially preventable, and 5 770 571 visits (21.3%) were classified as high acuity. From 2012 to 2019, potentially preventable ED visits increased from 1 851 692 to 3 214 276. Pain (36.9%) was the most common reason for potentially preventable ED visits. The number of patients who visited an ED because of pain increased from 1 192 197 in 2012 to 2 405 849 in 2019 (a 101.8% increase). Overall, 28.9% of ED visits resulted in unplanned hospitalizations, which did not change significantly over time (from 32.2% in 2012 to 26.6% in 2019; P = .78 for trend). Factors such as residence in a nursing home (odds ratio, 1.73; 95% CI, 1.25-2.41) were positively associated with having a potentially preventable ED visit, and factors such as the presence of more than 1 comorbidity (odds ratio, 1.82; 95% CI, 1.43-2.32) were positively associated with having an unplanned hospitalization.

CONCLUSIONS AND RELEVANCE

In this study, 51.6% of ED visits among patients with cancer were identified as potentially preventable, and the absolute number of potentially preventable ED visits increased substantially between 2012 and 2019. These findings highlight the need for cancer care programs to implement evidence-based interventions to better manage cancer treatment complications, such as uncontrolled pain, in outpatient and ambulatory settings.

Presentation Patterns and Outcomes in Patients with Colorectal Cancer Seeking the Emergency Department for Consultation

Background Patients with colorectal cancer may seek the emergency department for symptoms related to chemotherapy and radiotherapy side effects as well as those from the disease itself and from surgery complications.

Objectives To establish the epidemiological and clinical profile of colorectal cancer patients that look for consultations in the emergency department.

Methods Retrospective study of emergency room charts from colorectal cancer patients that consulted in a single oncological hospital for the period of 1 year.

Results Four hundred and forty-six consultations were identified (49.5% males and 50.5% females) with a mean age of 63 years and with advanced disease (most with tumor, node, metastases [TNM] stages III and IV). The most common complaint was abdominal pain (27.5%), followed by nausea (4.7%; more commonly seen in females with p = 0.03) and bladder symptoms (4.7%; more commonly seen in males, with p = 0.003). Infections (10.3%) and acute abdominal pain (9.1%) were the most frequent diagnoses. About 18% of them were admitted to the hospital and 80% were discharged home.

Conclusion The profile of patients with colorectal cancer seeking the emergency department comprises patients with advanced disease and a similar proportion of males and females. Symptom-driven complaints were the most frequent reason for consultations.

Cancer-related emergency and urgent care: expanding the research agenda

Purpose of review

Cancer-related emergency department (ED) visits often result in higher hospital admission rates than non-cancer visits. It has been estimated many of these costly hospital admissions can be prevented, yet urgent care clinics and EDs lack cancer-specific care resources to support the needs of this complex population. Implementing effective approaches across different care settings and populations to minimize ED and urgent care visits improves oncologic complication management, and coordinating follow-up care will be particularly important as the population of cancer patients and survivors continues to increase. The National Cancer Institute (NCI) and the Office of Emergency Care (OECR) convened a workshop in December 2021, “Cancer-related Emergency and Urgent Care: Prevention, Management, and Care Coordination” to highlight progress, knowledge gaps, and research opportunities. This report describes the current landscape of cancer-related urgent and emergency care and includes research recommendations from workshop participants to decrease the risk of oncologic complications, improve their management, and enhance coordination of care.

Recent findings

Since 2014, NCI and OECR have collaborated to support research in cancer-related emergency care. Workshop participants recommended a number of promising research opportunities, as well as key considerations for designing and conducting research in this area. Opportunities included better characterizing unscheduled care services, identifying those at higher risk for such care, developing care delivery models to minimize unplanned events and enhance their care, recognizing cancer prevention and screening opportunities in the ED, improving management of specific cancer-related presentations, and conducting goals of care conversations.

Summary

Significant progress has been made over the past 7 years with the creation of the Comprehensive Oncologic Emergency Research Network, broad involvement of the emergency medicine and oncology communities, establishing a proof-of-concept observational study, and NCI and OECR’s efforts to support this area of research. However, critical gaps remain.

Study protocol for a randomized trial of bridge: Person-centered collaborative care for serious mental illness and cancer

BACKGROUND

Individuals with serious mental illness (SMI) experience inequities in cancer care that contribute to increased cancer mortality. Involving mental health at the time of cancer diagnosis may improve cancer care delivery for patients with SMI yet access to care remains challenging. Collaborative care is a promising approach to integrate mental health and cancer care that has not yet been studied in this marginalized population.

METHODS/DESIGN

We describe a 24-week, two-arm, single-site randomized trial of person-centered collaborative care (Bridge) for patients with SMI (schizophrenia, bipolar disorder, or major depression with psychiatric hospitalization) and their caregivers. 120 patients are randomized 1:1 to Bridge or Enhanced Usual Care (EUC) along with their caregivers. Researchers proactively identify individuals with SMI and a new breast, lung, gastrointestinal, or head and neck cancer that can be treated with curative intent. EUC includes informing oncologists about the patient's psychiatric diagnosis, notifying patients about available psychosocial services, and tracking patient and caregiver outcomes. Bridge includes a proactive assessment by psychiatry and social work, a person-centered, team approach including collaboration between mental health and oncology, and increased access to evidence-based psycho-oncology care. The primary outcome is cancer care disruptions evaluated by a blinded panel of oncologists. Secondary outcomes include patient and caregiver-reported outcomes and healthcare utilization. Barriers to Bridge implementation and dissemination are assessed using mixed methods.

DISCUSSION

This trial will inform efforts to systematically identify individuals with SMI and cancer and generate the first experimental evidence for the impact of person-centered collaborative care on cancer care for this underserved population.

Interprofessional Interventions to Improve Serious Illness Communication in the Intensive Care Unit: A Scoping Review

Serious illness communication is fundamental to the provision of quality care for patients in the intensive care unit (ICU). Evidence suggests that including interprofessional team members in such communication is beneficial. This scoping review--conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines-maps existing evidence regarding interprofessional interventions to improve serious illness communication in the ICU. The review yielded 14 studies for inclusion, which were organized by 3 thematic categories of strategies implemented: training curriculum, scheduled meetings, and liaison role. Most used a combination of intervention strategies. Outcome measures varied across the studies but could be broadly categorized as patient/family-focused, provider-focused, or systems-focused. Great heterogeneity between studies exists. More research is needed.

End-of-life care of patients with esophageal or gastric cancer: decision making and the goal of care

BACKGROUND

Overall survival (OS) with advanced esophageal or gastric cancer is poor. To avoid overly aggressive treatments at the end-of-life and assure adequate end-of-life quality, the decision to focus on symptom-centered palliative care (PC) and terminate anticancer treatments, i.e., the PC decision, should be made in time.

MATERIAL AND METHODS

We reviewed the charts of patients (N = 160) with esophageal or gastric cancer treated at the Department of Oncology at Helsinki University Central Hospital in 2013 and deceased by December 2014. The use of acute services (Emergency department (ED) visits and hospitalizations) and places of death were compared according to the timing of the PC decision. Reasons for ED visits and hospitalizations were collected.

RESULTS

The median OS from diagnosis of advanced cancer was 6 months. Anti-cancer treatments were never started for 34% of the patients. The PC decision was made early (>30 days before death) for 54% of the patients and late (≤30 days before death) or not at all for 46%. Patients with late or no PC decision died more often in tertiary/secondary hospital (29 versus 7%, p = 0.001) and had more ED visits (49 versus 29%, p < 0.001) and hospitalizations (53 versus 28%, p = 0.001) in their last month, and visited the PC unit less often (18 versus 69%, p < 0.001), than the patients with early PC decision. The ED visits were most commonly related to cancer progression, and clinical deterioration (17%), fever (16%), and dysphagia (15%) were the most common symptoms.

CONCLUSION

The decision to focus on PC and terminate anticancer treatments, i.e., the PC decision, was made late or not at all in every other patient, leading to increased tertiary/secondary hospital service use and deaths at tertiary/secondary hospital. Early decision-making increased end-of-life care at specialized PC services or at home, implying better end-of-life care.

Use of Palliative Interventions at End of Life for Advanced Gastrointestinal Cancer

BACKGROUND

Despite the well-established benefits of palliative care, little is known about the use of palliative interventions among patients with advanced gastrointestinal (GI) cancer near the end of life (EOL).

METHODS

A national cohort study analyzed 142,304 patients with advanced GI cancers (stage 3 or 4) near EOL (death within 1 year of diagnosis) in the National Cancer Database (2004-2014) who received palliative interventions (defined as treatment to relieve symptoms: surgery, radiation, chemotherapy, and/or pain management). The study used multivariable hierarchical regression evaluate the association between the use of palliative interventions, temporal trends, and patient and hospital factors.

RESULTS

Overall, 16.5% of the patients were treated with a palliative intervention, and use increased over time (13.4% in 2004 vs 19.8% in 2014; trend test, p < 0.001). Palliative interventions were used most frequently for esophageal cancer (20.6%) and least frequently for gallbladder cancer (13.3%). Palliative interventions were associated with younger age (odds ratio [OR], 0.99; 95% confidence interval [CI], 0.98-0.99), recent diagnosis year (OR, 1.05; 95% CI, 1.04-1.06), black race (white [ref]; OR, 1.07; 95% CI, 1.01-1.12), insurance status (no insurance [ref]; private: OR, 0.92; 95% CI ,0.95-0.99), hospital type (community cancer program [ref]; integrated network cancer programs: OR, 1.37; 95% CI ,1.07-1.75), and stage 4 disease (OR, 2.17; 95% CI, 2.07-2.27). Patients in southern and western regions were less likely to receive palliative intervention (Northeast [ref]; OR, 0.76; 95% CI, 0.62-0.94 and OR 0.46; 95% CI, 0.37-0.57, respectively).

CONCLUSION

Increased palliative intervention use over time suggests ongoing changes in how care is delivered to GI cancer patients toward EOL. However, sociodemographic and geographic variation suggests opportunities to address barriers to optimal EOL care.

Implementation of patient-reported outcomes for symptom management in oncology practice through the SIMPRO research consortium: a protocol for a pragmatic type II hybrid effectiveness-implementation multi-center cluster-randomized stepped wedge trial

Background

Many cancer patients experience high symptom burden. Healthcare in the USA is reactive, not proactive, and doctor-patient communication is often suboptimal. As a result, symptomatic patients may suffer between clinic visits. In research settings, systematic assessment of electronic patient-reported outcomes (ePROs), coupled with clinical responses to severe symptoms, has eased this symptom burden, improved health-related quality of life, reduced acute care needs, and extended survival. Implementing ePRO-based symptom management programs in routine care is challenging. To study methods to overcome the implementation gap and improve symptom control for cancer patients, the National Cancer Institute created the Cancer-Moonshot funded Improving the Management of symPtoms during And following Cancer Treatment (IMPACT) Consortium.

Methods

Symptom Management IMplementation of Patient Reported Outcomes in Oncology (SIMPRO) is one of three research centers that make up the IMPACT Consortium. SIMPRO, a multi-disciplinary team of investigators from six US health systems, seeks to develop, test, and integrate an electronic symptom management program (eSyM) for medical oncology and surgery patients into the Epic electronic health record (EHR) system and associated patient portal. eSyM supports real-time symptom tracking for patients, automated clinician alerts for severe symptoms, and specialized reports to facilitate population management. To rigorously evaluate its impact, eSyM is deployed through a pragmatic stepped wedge cluster-randomized trial. The primary study outcome is the occurrence of an emergency department treat-and-release event within 30 days of starting chemotherapy or being discharged following surgery. Secondary outcomes include hospitalization rates, chemotherapy use (time to initiation and duration of therapy), and patient quality of life and satisfaction. As a type II hybrid effectiveness-implementation study, facilitators and barriers to implementation are assessed throughout the project.

Discussion

Creating and deploying eSyM requires collaboration between dozens of staff across diverse health systems, dedicated engagement of patient advocates, and robust support from Epic. This trial will evaluate eSyM in routine care settings across academic and community-based healthcare systems serving patients in rural and metropolitan locations. This trial’s pragmatic design will promote generalizable results about the uptake, acceptability, and impact of an EHR-integrated, ePRO-based symptom management program.

Trial registration

ClinicalTrials.gov NCT03850912. Registered on February 22, 2019. Last updated on November 9, 2021.

Supportive oncology care at home interventions: protocols for clinical trials to shift the paradigm of care for patients with cancer

BACKGROUND

Patients with cancer often endure substantial symptoms and treatment toxicities leading to high healthcare utilization, including hospitalizations and emergency department visits, throughout the continuum of their illness. Innovative oncology care models are needed to improve patient outcomes and reduce their healthcare utilization. Using a novel hospital at home care platform, we developed a Supportive Oncology Care at Home intervention to address the needs of patients with cancer.

METHODS

We are conducting three trials to delineate the role of Supportive Oncology Care at Home for patients with cancer. The Supportive Oncology Care at Home intervention includes: (1) a hospital at home care model for symptom assessment and management; (2) remote monitoring of daily patient-reported symptoms, vital signs, and body weight; and (3) structured communication with the oncology team. Our first study is a randomized controlled trial to test the efficacy of Supportive Oncology Care at Home versus standard oncology care for improving healthcare utilization, cancer treatment interruptions, and patient-reported outcomes in patients with cancer receiving definitive treatment of their cancer. Participants include adult patients with gastrointestinal and head and neck cancer, as well as lymphoma, receiving definitive treatment (e.g., treatment with curative intent). The second study is a single-arm trial assessing the feasibility and acceptability of the Supportive Oncology Care at Home intervention for hospitalized patients with advanced cancer. Eligible participants include adult patients with incurable cancer who are admitted with an unplanned hospitalization. The third study is a single-arm trial assessing the feasibility and acceptability of the Supportive Oncology Care at Home intervention to enhance the end-of-life care for patients with advanced hematologic malignancies. Eligible participants include adult patients with relapsed or refractory hematologic malignancy receiving palliative therapy or supportive care alone.

DISCUSSION

These studies are approved by the Dana-Farber/Harvard Cancer Center Institutional Review Board and are being conducted in accordance with the Consolidated Standards of Reporting Trials statement for non-pharmacological trials. This work has the potential to transform the paradigm of care for patients with cancer by providing them with the necessary support at home to improve their health outcomes and care delivery.

TRIAL REGISTRATIONS

NCT04544046, NCT04637035, NCT04690205.

Effect of a Symptom Monitoring Intervention for Patients Hospitalized With Advanced Cancer: A Randomized Clinical Trial

IMPORTANCE

Symptom monitoring interventions are increasingly becoming the standard of care in oncology, but studies assessing these interventions in the hospital setting are lacking.

OBJECTIVE

To evaluate the effect of a symptom monitoring intervention on symptom burden and health care use among hospitalized patients with advanced cancer.

DESIGN, SETTING, AND PARTICIPANTS

This nonblinded randomized clinical trial conducted from February 12, 2018, to October 30, 2019, assessed 321 hospitalized adult patients with advanced cancer and admitted to the inpatient oncology services of an academic hospital. Data obtained through November 13, 2020, were included in analyses, and all analyses assessed the intent-to-treat population.

INTERVENTIONS

Patients in both the intervention and usual care groups reported their symptoms using the Edmonton Symptom Assessment System (ESAS) and the 4-item Patient Health Questionnaire-4 (PHQ-4) daily via tablet computers. Patients assigned to the intervention had their symptom reports displayed during daily oncology rounds, with alerts for moderate, severe, or worsening symptoms. Patients assigned to usual care did not have their symptom reports displayed to their clinical teams.

MAIN OUTCOMES AND MEASURES

The primary outcome was the proportion of days with improved symptoms, and the secondary outcomes were hospital length of stay and readmission rates. Linear regression was used to evaluate differences in hospital length of stay. Competing-risk regression (with death treated as a competing event) was used to compare differences in time to first unplanned readmission within 30 days.

RESULTS

From February 12, 2018, to October 30, 2019, 390 patients (76.2% enrollment rate) were randomized. Study analyses to assess change in symptom burden included 321 of 390 patients (82.3%) who had 2 or more days of symptom reports completed (usual care, 161 of 193; intervention, 160 of 197). Participants had a mean (SD) age of 63.6 (12.8) years and were mostly male (180; 56.1%), self-reported as White (291; 90.7%), and married (230; 71.7%). The most common cancer type was gastrointestinal (118 patients; 36.8%), followed by lung (60 patients; 18.7%), genitourinary (39 patients; 12.1%), and breast (29 patients; 9.0%). No significant differences were detected between the intervention and usual care for the proportion of days with improved ESAS-physical (unstandardized coefficient [B] = -0.02; 95% CI, -0.10 to 0.05; P = .56), ESAS-total (B = -0.05; 95% CI, -0.12 to 0.02; P = .17), PHQ-4-depression (B = -0.02; 95% CI, -0.08 to 0.04; P = .55), and PHQ-4-anxiety (B = -0.04; 95% CI, -0.10 to 0.03; P = .29) symptoms. Intervention patients also did not differ significantly from patients receiving usual care for the secondary end points of hospital length of stay (7.59 vs 7.47 days; B = 0.13; 95% CI, -1.04 to 1.29; P = .83) and 30-day readmission rates (26.5% vs 33.8%; hazard ratio, 0.73; 95% CI, 0.48-1.09; P = .12).

CONCLUSIONS AND RELEVANCE

This randomized clinical trial found that for hospitalized patients with advanced cancer, the assessed symptom monitoring intervention did not have a significant effect on patients' symptom burden or health care use. These findings do not support the routine integration of this type of symptom monitoring intervention for hospitalized patients with advanced cancer.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03396510.

Cost evaluation of an exercise oncology intervention: The exercise in all chemotherapy trial

BACKGROUND

There is strong evidence supporting the efficacy of exercise oncology programs to improve physical and psychosocial outcomes during active treatment. However, there is a paucity of evidence on the effect of exercise on healthcare utilization and cost analyzes of exercise oncology programs.

AIMS

Our objective was to assess the effects of a pragmatic exercise oncology program (ENACT) during active chemotherapy treatment on healthcare utilization and associated costs.

METHODS

We conducted post-hoc analyzes on 160 ENACT participants and 75 comparison participants matched on cancer site, stage, age range, and gender. We obtained complete healthcare utilization histories for each patient (specific to emergency department [ED] visits and hospital admissions) coinciding with their participation in ENACT. A sub-analysis was conducted for advanced stage breast, gastrointestinal, and pancreatic cancer patients.

RESULTS

Healthcare costs for patients who participated in the ENACT exercise oncology intervention were numerically lower than healthcare costs for the comparison group, even after accounting for the cost of the intervention. However, the differences were not statistically significant.

CONCLUSION

Our findings suggest that an exercise oncology program during active chemotherapy treatment are at least cost neutral for all cancer patients, including advanced stage cancers. Additional research is warranted to evaluate the potential for exercise oncology programs to reduce healthcare utilization, particularly in advanced cancer patients.

Accountable care in oncology: Where do we go from here?

The study by Erfani et al. confirms that ACOs did not achieve the promise of cancer care cost reduction, but leaves open important questions about the impacts of accountable care on the quality, coordination, and equity of cancer care delivery. While the inability of ACOs to deliver cost reductions for patients with cancer may feel like a step backwards for accountable care in oncology, the work of Erfani et al. actually represents an important step forward in the field, settling the important cost question in order to open a broader conversation on the goals of ACOs and value-based care delivery models in oncology, the means to evaluate them in a comprehensive, patient-centered manner, and the urgency of incorporating the needs and voices of diverse populations in the important work of cancer care delivery reform.

The study by Erfani et al. confirms that ACOs did not achieve the promise of cancer care cost reduction, but leaves open important questions about the impacts of accountable care on the quality, coordination, and equity of cancer care delivery.

eSyM: An Electronic Health Record-Integrated Patient-Reported Outcomes-Based Cancer Symptom Management Program Used by Six Diverse Health Systems

PURPOSE

Collecting patient-reported outcomes (PROs) can improve symptom control and quality of life, enhance doctor-patient communication, and reduce acute care needs for patients with cancer. Digital solutions facilitate PRO collection, but without robust electronic health record (EHR) integration, effective deployment can be hampered by low patient and clinician engagement and high development and deployment costs. The important components of digital PRO platforms have been defined, but procedures for implementing integrated solutions are not readily available.

METHODS

As part of the NCI's IMPACT consortium, six health care systems partnered with Epic to develop an EHR-integrated, PRO-based electronic symptom management program (eSyM) to optimize postoperative recovery and well-being during chemotherapy. The agile development process incorporated user-centered design principles that required engagement from patients, clinicians, and health care systems. Whenever possible, the system used validated content from the public domain and took advantage of existing EHR capabilities to automate processes.

RESULTS

eSyM includes symptom surveys on the basis of the PRO-Common Terminology Criteria for Adverse Events (PRO-CTCAE) plus two global wellness questions; reminders and symptom self-management tip sheets for patients; alerts and symptom reports for clinicians; and population management dashboards. EHR dependencies include a secure Health Insurance Portability and Accountability Act-compliant patient portal; diagnosis, procedure and chemotherapy treatment plan data; registries that identify and track target populations; and the ability to create reminders, alerts, reports, dashboards, and charting shortcuts.

CONCLUSION

eSyM incorporates validated content and leverages existing EHR capabilities. Build challenges include the innate technical limitations of the EHR, the constrained availability of site technical resources, and sites' heterogenous EHR configurations and policies. Integration of PRO-based symptom management programs into the EHR could help overcome adoption barriers, consolidate clinical workflows, and foster scalability and sustainability. We intend to make eSyM available to all Epic users.

Characteristics of unplanned hospitalisations among cancer patients in Singapore

INTRODUCTION

Cancer is a pervasive global problem with significant healthcare utilisation and cost. Emergency departments (EDs) see large numbers of patients with oncologic emergencies and act as "gate-keepers" to subsequent hospital admissions. A proportion of such hospital admissions are rapidly discharged within 2 days and may be potentially avoidable.

METHODS

Over a 6-month period, we conducted a retrospective audit of active cancer patients presenting to the ED with subsequent admission to the Department of Medical Oncology. Our aims were to identify independent factors associated with a length of stay ≤2 days; and characterise the clinical and resource needs of these short admissions.

RESULTS

Among all medical oncology admissions, 24.4% were discharged within 2 days. Compared to longer stayers, patients with short admissions were significantly younger (P=0.010), had lower National Early Warning Scores (NEWS) (P=0.006), and had a lower proportion of gastrointestinal and hepatobiliary cancers (P=0.005). Among short admissions, common presenting medical problems were infections (n=144, 36.3%), pain (n=116, 29.2%), gastrointestinal complaints (n=85, 21.4%) and respiratory complaints (n=76, 19.1%). These admissions required investigations and treatments already available at the ED.

CONCLUSION

Short admissions have low resource needs and may be managed in the ED. This may help save valuable inpatient bed-days and reduce overall healthcare costs.

Machine Learning Applied to Electronic Health Records: Identification of Chemotherapy Patients at High Risk for Preventable Emergency Department Visits and Hospital Admissions

PURPOSE

Acute care use (ACU) is a major driver of oncologic costs and is penalized by a Centers for Medicare & Medicaid Services quality measure, OP-35. Targeted interventions reduce preventable ACU; however, identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data in the electronic health record (EHR). We aimed to predict risk of preventable ACU after starting chemotherapy using machine learning (ML) algorithms trained on comprehensive EHR data.

METHODS

Chemotherapy patients treated at an academic institution and affiliated community care sites between January 2013 and July 2019 who met inclusion criteria for OP-35 were identified. Preventable ACU was defined using OP-35 criteria. Structured EHR data generated before chemotherapy treatment were obtained. ML models were trained to predict risk for ACU after starting chemotherapy using 80% of the cohort. The remaining 20% were used to test model performance by the area under the receiver operator curve.

RESULTS

Eight thousand four hundred thirty-nine patients were included, of whom 35% had preventable ACU within 180 days of starting chemotherapy. Our primary model classified patients at risk for preventable ACU with an area under the receiver operator curve of 0.783 (95% CI, 0.761 to 0.806). Performance was better for identifying admissions than emergency department visits. Key variables included prior hospitalizations, cancer stage, race, laboratory values, and a diagnosis of depression. Analyses showed limited benefit from including patient-reported outcome data and indicated inequities in outcomes and risk modeling for Black and Medicaid patients.

CONCLUSION

Dense EHR data can identify patients at risk for ACU using ML with promising accuracy. These models have potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted, preventative interventions.

Health care utilization among patients with oesophageal and gastric cancer: the impact of initial treatment strategy and assignment of a contact nurse

Background

Patients diagnosed with oesophageal and gastric cancer face a poor prognosis and numerous challenges of symptom management, lifestyle adjustments and complex treatment regimens. The multifaceted care needs and rapid disease progression reinforce the need for proactive and coherent health care. According to the national cancer strategy, providing coherent health care and palliative support is an area of priority. More knowledge is needed about health care utilization and the characteristics of the health care service in order to understand the readiness, accessibility and quality of current health care. The aim of this study was to describe individuals’ health care use from the time of treatment decision until death, and investigate the impact of the initial treatment strategy and assignment of a contact nurse (CN) on health care use among patients with oesophageal and gastric cancer.

Methods

This population-based cohort study included patients who died from oesophageal and gastric cancer in Sweden during 2014–2016. Through linking data from the National Register for Oesophageal and Gastric Cancer, the National Cause of Death Register, and the National Patient Register, 2614 individuals were identified. Associations between the initial treatment strategy and CN assignment, and health care use were investigated. Adjusted incidence rate ratios (IRRs) with 95% confidence intervals (CIs) were calculated using Poisson regression.

Results

Patients receiving palliative treatment and those receiving no tumour-directed treatment had a higher IRR for unplanned hospital stays and unplanned outpatient care visits compared with patients who received curative treatment. Patients receiving no tumour-directed treatment also had a lower IRR for planned hospital stays and planned outpatient care visits compared with patients given curative treatment. Compared with this latter group, patients with palliative treatment had a higher IRR for planned outpatient care visits. Patients assigned a CN had a higher IRR for unplanned hospital stays, unplanned outpatient care visits and planned outpatient care visits, compared with patients not assigned a CN.

Conclusions

A palliative treatment strategy and no tumour-directed treatment were associated with higher rates of unplanned health care compared with a curative treatment strategy, suggesting that a proactive approach is imperative to ensure quality palliative care.

Leveraging patient-reported outcomes (PROs) in patients with pancreatic cancer: The Pancreatic Cancer Action Network (PanCAN) online patient registry experience

Background

The Pancreatic Cancer Action Network (PanCAN) Patient Registry is an online, pancreatic cancer‐specific, global registry enabling patients to self‐report sociodemographics, disease/management characteristics, and patient‐reported outcomes (PROs). We sought to describe the creation, user experience, and research potential of the PanCAN Registry.

Methods

We obtained data to describe (1) the creation of the Registry (questionnaire development, marketing efforts, and regulatory considerations); (2) the user experience (user characteristics and interactions with the registry following inception); and (3) the research potential of the registry (comparing PROs and treatment patterns by age [±65 years] and treatment site [community or academic] for users with de novo metastatic disease).

Results

The Registry was conceived as part of PanCAN’s strategic plan for a personalized therapy initiative. PanCAN staff and disease expert consultants developed questionnaires hosted on an electronic PRO platform. Users had the option to include their data in research efforts, and the Registry platform received institutional review board approval. From 7/2015 to 12/2020, 2187 patients visited the registry and 1697 (77.6%) completed at least one survey (median age = 64 years [range: 24–90], 47.9% women, 88.7% White, 34.0% metastatic disease). Among patients with metastatic disease (N = 567), 46.0% were ≥65 years old and 67.5% received treatment at community sites. Patients ≥65 years reported feeling less hopeful about the treatment plan (12.4% vs. 24.3%, p = 0.003), and patients treated at community sites reported more frequent treatment breaks of >2 weeks (58.2% vs. 28.1%, p < 0.001).

Conclusions

Our findings demonstrate the feasibility, usability, and research potential of an online PRO registry for patients with cancer. This description of the PanCAN Registry should inform future registry‐building efforts to facilitate standardized PRO reporting and provide a valuable research database.

Clinicaltrial registration number: Not applicable.

Emergency department visits among people with cancer: Frequency, symptoms, and characteristics

OBJECTIVE

People with cancer are increasingly more likely to visit an emergency department for acute care than the general population. They often have long wait times and more exposure to infection and receive treatment from staff less experienced with cancer-related problems. Our objective was to examine emergency department (ED) visits among people with cancer to understand how often and why they seek care.

METHODS

We conducted a retrospective study of ED visits using the National Syndromic Surveillance Program BioSense Platform. Cancer reported during an ED visit was identified using International Classification of Diseases, Tenth Revision codes for any cancer type, including bladder, breast, cervical, colorectal, kidney, liver, lung, ovary, pancreas, prostate, or uterine cancers. Symptoms prompting the visit were identified for people with cancer who visited EDs in the United States from June 2017 to May 2018 in ≈4500 facilities, including 3000 EDs in 46 states and the District of Columbia (66% of all ED visits during a 1-year period).

RESULTS

Of 97 million ED visits examined, 710,297 (0.8%) were among people with cancer. Percentages were higher among women (50.1%) than men (49.5%) and among adults aged ≥65 years (53.6%) than among those ≤64 years (45.7%). The most common presenting symptoms were pain (19.1%); gastrointestinal (13.8%), respiratory (11.5%), and neurologic (5.3%) complaints; fever (4.9%); injury (4.1%); and bleeding (2.4%). Symptom prevalence differed significantly by cancer type.

CONCLUSIONS

The Centers for Medicare & Medicaid Services encourages efforts to reduce acute care visits among people with cancer. We characterized almost 70% of ED visits among this population.

A Machine Learning Model Approach to Risk-Stratify Patients With Gastrointestinal Cancer for Hospitalization and Mortality Outcomes

PURPOSE

Patients with gastrointestinal (GI) cancer frequently experience unplanned hospitalizations, but predictive tools to identify high-risk patients are lacking. We developed a machine learning model to identify high-risk patients.

METHODS AND MATERIALS

In the study, 1341 consecutive patients undergoing GI (abdominal or pelvic) radiation treatment (RT) from March 2016 to July 2018 (derivation) and July 2018 to January 2019 (validation) were assessed for unplanned hospitalizations within 30 days of finishing RT. In the derivation cohort of 663 abdominal and 427 pelvic RT patients, a machine learning approach derived random forest, gradient boosted decision tree, and logistic regression models to predict 30-day unplanned hospitalizations. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and prospectively validated in 161 abdominal and 90 pelvic RT patients using Mann-Whitney rank-sum test. Highest quintile of risk for hospitalization was defined as "high-risk" and the remainder "low-risk." Hospitalizations for high- versus low-risk patients were compared using Pearson's χ² test and survival using Kaplan-Meier log-rank test.

RESULTS

Overall, 13% and 11% of patients receiving abdominal and pelvic RT experienced 30-day unplanned hospitalization. In the derivation phase, gradient boosted decision tree cross-validation yielded AUC = 0.823 (abdominal patients) and random forest yielded AUC = 0.776 (pelvic patients). In the validation phase, these models yielded AUC = 0.749 and 0.764, respectively (P < .001 and P = .002). Validation models discriminated high- versus low-risk patients: in abdominal RT patients, frequency of hospitalization was 39% versus 9% in high- versus low-risk groups (P < .001) and 6-month survival was 67% versus 92% (P = .001). In pelvic RT patients, frequency of hospitalization was 33% versus 8% (P = .002) and survival was 86% versus 92% (P = .15) in high- versus low-risk patients.

CONCLUSIONS

In patients with GI cancer undergoing RT as part of multimodality treatment, machine learning models for 30-day unplanned hospitalization discriminated high- versus low-risk patients. Future applications will test utility of models to prompt interventions to decrease hospitalizations and adverse outcomes.

Development of an Oncology Acute Care Risk Prediction Model

PURPOSE

Acute care utilization (ACU), including emergency department (ED) visits or hospital admissions, is common in patients with cancer and may be preventable. The Center for Medicare & Medicaid Services recently implemented OP-35, a measure in the Hospital Outpatient Quality Reporting Program focused on ED visits and inpatient admissions for 10 potentially preventable conditions that arise within 30 days of chemotherapy. This new measure exemplifies a growing focus on preventing unnecessary ACU. However, identifying patients at high risk of ACU remains a challenge. We developed a real-time clinical prediction model using a discrete point allocation system to assess risk for ACU in patients with active cancer.

METHODS

We performed a retrospective cohort analysis of patients with active cancer from a large urban academic medical center. The primary outcome, ACU, was evaluated using a multivariate logistic regression model with backward variable selection. We used estimates from the multivariate logistic model to construct a risk index using a discrete point allocation system.

RESULTS

Eight thousand two hundred forty-six patients were included in the analysis. ED utilization in the last 90 days, history of chronic obstructive pulmonary disease, congestive heart failure or renal failure, and low hemoglobin and low neutrophil count significantly increased risk for ACU. The model produced an overall C-statistic of 0.726. Patients defined as high risk (achieving a score of 2 or higher on the risk index) represented 10% of total patients and 46% of ACU.

CONCLUSION

We developed an oncology acute care risk prediction model using a risk index-based scoring system, the REDUCE (Reducing ED Utilization in the Cancer Experience) score. Further efforts to evaluate the effectiveness of our model in predicting ACU are ongoing.

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

BACKGROUND

Oncology patients disproportionately utilize the emergency department (ED) for symptom management. At our institution, approximately 1 in 4 visits to the ED by oncology patients led to discharge. We hypothesized that many of the visits leading to ED discharge would be potentially preventable (PP).

METHODS

We retrospectively characterized ED discharges of oncology patients. Visits were classified by presenting symptom, type of cancer, and time of ED visit. Chart reviewers were additionally asked whether each case could have been safely managed as an outpatient.

RESULTS

We analyzed 100 ED discharges in a 4-month period in 2016 and 2017. Gastrointestinal (GI) complaints, pain, and fever were the most common presenting symptoms for these visits. We rated 44 of 100 ED discharges as potentially preventable. Given we analyzed only ED discharges which comprise about 25% of ED visits for patients with cancer, overall about 10% of all ED visits by these patients may be preventable. We also found that ED visits without a clinic appointment or phone call to the clinic on the day of ED presentation were more likely to be preventable (51% vs 27%, OR 2.9, p = 0.026).

CONCLUSIONS

Many ED visits by oncology patients may be preventable and occur for symptoms which can be managed as an outpatient. More of these visits also appear to occur in those who do not reach a clinic member prior to the visit. These findings suggest that improved access to clinics and standardized outpatient symptom management are next steps to consider in preventing ED visits in this vulnerable population.

Symptom Evolution in Patients with Esophageal and Gastric Cancer Receiving Palliative Chemotherapy: A Population-Based Study

INTRODUCTION

Palliative chemotherapy (PC) is associated with a modest survival benefit in patients with incurable esophageal and gastric cancer; however, changes in symptom profile during treatment are not well described. Understanding the trajectory of symptoms during treatment may lead to improved care and facilitate shared decision making. In this study, we address this knowledge gap among all patients receiving PC in the Canadian province of Ontario.

METHODS

Patients diagnosed with incurable esophageal and gastric cancer who received PC from 2012 to 2017 were identified from the Ontario Cancer Registry. Patients with one or more recorded Edmonton Symptom Assessment System (ESAS) scores in the 12 months following cancer diagnosis were included. The ESAS includes scores from 0 to 10 in nine domains (anxiety, depression, drowsiness, lack of appetite, nausea, pain, shortness of breath, tiredness, and lack of well-being). Symptom severity is categorized as none-mild (≤ 3), moderate (4-6), or severe (7-10). We focused on potentially modifiable symptoms, i.e. nausea, pain, and anxiety/depression. Logistic regression was used to identify factors associated with moderate-severe ESAS scores in these domains. Among those patients with serial ESAS scores (at 8 ± 2 and 12 ± 2 weeks) receiving chemotherapy, we describe changes during treatment (decrease by ≥ 1 = improved; - 1 > 0 > 1 = unchanged; increase by ≥ 1 = deteriorated).

RESULTS

The cohort included 1900 patients who received PC, of whom 79% (1497/1900) had one or more recorded ESAS scores. In multivariate analysis, younger patients were more likely to have moderate-severe scores in nausea (odds ratio [OR] 1.89, 95% confidence interval [CI] 1.23-2.90 [p < 0.01] in patients aged 41-50 years compared with patients aged ≥ 71 years) and pain (OR 1.88, 95% CI 1.36-2.60 [p < 0.01] in patients aged 51-60 years compared with patients aged ≥ 71 years). Compared with males, females were more likely to report moderate-severe scores in anxiety/depression (OR 1.58, 95% CI 1.21-2.08 [p < 0.01]). At 8 ± 2 weeks from PC initiation, symptom scores were unchanged in 19-42% of patients, improved in 30-51% of patients, and deteriorated in 17-35% of patients. The greatest change in symptom burden was observed for appetite (51% improvement) and anxiety/depression (35% deterioration). Similar trends were observed at 12 ± 2 weeks.

CONCLUSIONS

In this large, population-based study, we observed that younger patients were more likely to report moderate-severe symptoms in pain and nausea, and females were more likely to report moderate-severe symptoms in anxiety/depression. Anxiety/depression symptoms become increasingly problematic for a substantial proportion of patients receiving PC. Supportive care efforts to mitigate these symptoms in routine practice are needed.

Building a Clinically Relevant Risk Model: Predicting Risk of a Potentially Preventable Acute Care Visit for Patients Starting Antineoplastic Treatment

PURPOSE

To create a risk prediction model that identifies patients at high risk for a potentially preventable acute care visit (PPACV).

PATIENTS AND METHODS

We developed a risk model that used electronic medical record data from initial visit to first antineoplastic administration for new patients at Memorial Sloan Kettering Cancer Center from January 2014 to September 2018. The final time-weighted least absolute shrinkage and selection operator model was chosen on the basis of clinical and statistical significance. The model was refined to predict risk on the basis of 270 clinically relevant data features spanning sociodemographics, malignancy and treatment characteristics, laboratory results, medical and social history, medications, and prior acute care encounters. The binary dependent variable was occurrence of a PPACV within the first 6 months of treatment. There were 8,067 observations for new-start antineoplastic therapy in our training set, 1,211 in the validation set, and 1,294 in the testing set.

RESULTS

A total of 3,727 patients experienced a PPACV within 6 months of treatment start. Specific features that determined risk were surfaced in a web application, riskExplorer, to enable clinician review of patient-specific risk. The positive predictive value of a PPACV among patients in the top quartile of model risk was 42%. This quartile accounted for 35% of patients with PPACVs and 51% of potentially preventable inpatient bed days. The model C-statistic was 0.65.

CONCLUSION

Our clinically relevant model identified the patients responsible for 35% of PPACVs and more than half of the inpatient beds used by the cohort. Additional research is needed to determine whether targeting these high-risk patients with symptom management interventions could improve care delivery by reducing PPACVs.

The hospital care of patients with cancer: a retrospective analysis of the characteristics of their hospital stay in comparison with other medical conditions

PURPOSE

Hospital admission is a frequent occurrence among patients with cancer, and a significant proportion of patients admitted to medical units have cancer. Their hospital stay has features that may be different compared with patients without cancer. We performed a retrospective analysis of the characteristics of patients with cancer admitted for medical conditions.

PATIENTS AND METHODS

We studied the administrative data of patients with solid cancer admitted to the medical department of a large referral hospital over a 12-month period and compared them with those of patients without cancer.

RESULTS

Seven thousand eight hundred two consecutive admissions were analysed, of which 1099 (14.1%) had a principal or associated diagnosis of cancer. Admissions were distributed across 12 units, with 44% concentrated in the medical oncology unit and 56% in other units. Patients with cancer were more frequently men and were younger than patients without cancer. Admission less frequently involved the emergency department (ED), while discharge was more frequently assisted. The in-hospital death rate was higher, as was the readmission rate. Length of stay was longer (11.3 days vs. 9.8 days; p < 0.0001). Patients with cancer admitted to the medical oncology unit used the ED even less, and their length of stay was shorter than that of patients with cancer admitted in other units.

CONCLUSIONS

The in-hospital pathway of patients with cancer displays specific issues and adds complexity to hospital stay of patients with medical conditions. The medical oncology unit plays a role in reducing ED use and in providing efficient care. The evidence gathered should help in shaping new models of care and in improving adequate clinical competencies.

Hospitalization Rates Related to Coordinated Home Health Care Services With a Community Oncology Practice

PURPOSE:

Oncology care reimbursement has been shifting from a traditional fee-for-service model to either 1- or 2-sided risk models during the past 5 years. A major expense associated with the total cost of care is hospitalization cost. The study set out to investigate whether the creation of an Advanced Community Care Model (ACCM) of home health care would affect 60-day hospitalization and 30-rehospitalization rates in a community oncology setting.

METHODS:

In conjunction with a single home health care organization, an ACCM was modified for oncology care to include intervention protocols to address antiemetic issues, pain control, dehydration, shortness of breath, diarrhea, and fever. Weekly and monthly joint management meetings began. Quality metrics were defined.

RESULTS:

Overall, 457 unique home health care admissions were evaluated. Hospitalization associated with intervention protocols was evaluated. Sixty-day hospitalization rates decreased from 14% to 8%. Thirty-day rehospitalization rates decreased from 25% to 10%.

CONCLUSION:

An oncology ACCM, as created in this study, appears to have reduced both 60-day hospitalization and 30-day rehospitalization rates.

The Perceptions of Cancer Patients Regarding the Causes and Preventability of Unplanned Hospital Admissions

OBJECTIVE

The objective of this study was to determine the attitudes of oncology patients regarding the causes and preventability of unplanned hospitalizations.

METHODS

Convenience sample using a 36-question survey instrument adapted from prior studies of hospital readmissions.

RESULTS

A total of 95 evaluable patients answered >75% of survey items. Majorities (64%) agreed that they desired to avoid the admission, but disagreed (79%) that their own admission was preventable. Patients did not generally express lack confidence in their overall self-management abilities (only 36% agreed) or dissatisfaction with the level of home support, emotional or equipment (only 11% to 26% agreed). Patients did not complain of an inability to access their oncology care team (only 14% agreed), yet a strong majority (79%) endorsed the idea that emergency department visits represent the "quickest and easiest way to get needed care" and that the "hospital is the best place for me when I am sick" (60%). Overall, 79% indicated that their oncology care team directed them to visit the emergency department for evaluation. Most results did not differ by demographic factors.

CONCLUSIONS

These results differ from previous results that use methods other than a direct patient survey to determine the preventability or root causes of unplanned hospital admissions/ or readmissions. Accordingly, patient support programs may not address the root causes of unplanned admissions. The use of the emergency department for unplanned care may represent local culture and institutions planning reduction efforts should include patent perceptions to plan a holistic solution.

The impact of initial treatment strategy and survival time on quality of end-of-life care among patients with oesophageal and gastric cancer: A population-based cohort study

BACKGROUND

Oesophageal and gastric cancer are highly lethal malignancies with a 5-year survival rate of 15-29%. More knowledge is needed about the quality of end-of-life care in order to understand the burden of the illness and the ability of the current health care system to deliver timely and appropriate end-of-life care. The aim of this study was to describe the impact of initial treatment strategy and survival time on the quality of end-of-life care among patients with oesophageal and gastric cancer.

METHODS

This register-based cohort study included patients who died from oesophageal and gastric cancer in Sweden during 2014-2016. Through linking data from the National Register for Esophageal and Gastric Cancer, the National Cause of Death Register, and the Swedish Register of Palliative Care, 2156 individuals were included. Associations between initial treatment strategy and survival time and end-of-life care quality indicators were investigated. Adjusted risk ratios (RRs) with 95% confidence intervals were calculated using modified Poisson regression.

RESULTS

Patients with a survival of ≤3 months and 4-7 months had higher RRs for hospital death compared to patients with a survival ≥17 months. Patients with a survival of ≤3 months also had a lower RR for end-of-life information and bereavement support compared to patients with a survival ≥17 months, while the risks of pain assessment and oral assessment were not associated with survival time. Compared to patients with curative treatment, patients with no tumour-directed treatment had a lower RR for pain assessment. No significant differences were shown between the treatment groups regarding hospital death, end-of-life information, oral health assessment, and bereavement support.

CONCLUSIONS

Short survival time is associated with several indicators of low quality end-of-life care among patients with oesophageal and gastric cancer, suggesting that a proactive palliative care approach is imperative to ensure quality end-of-life care.

Hospitalization Risk During Chemotherapy for Advanced Cancer: Development and Validation of Risk Stratification Models Using Real-World Data

PURPOSE

Hospitalizations are a common occurrence during chemotherapy for advanced cancer. Validated risk stratification tools could facilitate proactive approaches for reducing hospitalizations by identifying at-risk patients.

PATIENTS AND METHODS

We assembled two retrospective cohorts of patients receiving chemotherapy for advanced nonhematologic cancer; cohorts were drawn from three integrated health plans of the Cancer Research Network. We used these cohorts to develop and validate logistic regression models estimating 30-day hospitalization risk after chemotherapy initiation. The development cohort included patients in two health plans from 2005 to 2013. The validation cohort included patients in a third health plan from 2007 to 2016. Candidate predictor variables were derived from clinical data in institutional data warehouses. Models were validated based on the C-statistic, positive predictive value, and negative predictive value. Positive predictive value and negative predictive value were calculated in reference to a prespecified risk threshold (hospitalization risk ≥ 18.0%).

RESULTS

There were 3,606 patients in the development cohort (median age, 63 years) and 634 evaluable patients in the validation cohort (median age, 64 years). Lung cancer was the most common diagnosis in both cohorts (26% and 31%, respectively). The selected risk stratification model included two variables: albumin and sodium. The model C-statistic in the validation cohort was 0.69 (95% CI, 0.62 to 0.75); 39% of patients were classified as high risk according to the prespecified threshold; 30-day hospitalization risk was 24.2% (95% CI, 19.9% to 32.0%) in the high-risk group and 8.7% (95% CI, 6.1% to 12.0%) in the low-risk group.

CONCLUSION

A model based on data elements routinely collected during cancer treatment can reliably identify patients at high risk for hospitalization after chemotherapy initiation. Additional research is necessary to determine whether this model can be deployed to prevent chemotherapy-related hospitalizations.

Conceptualizing and Counting Discretionary Utilization in the Final 100 Days of Life: A Scoping Review

CONTEXT

There has been surprisingly little attention to conceptual and methodological issues that influence the measurement of discretionary utilization at the end of life (DIAL), an indicator of quality care.

OBJECTIVE

The objectives of this study were to examine how DIALs have been operationally defined and identify areas where evidence is biased or inadequate to inform practice.

METHODS

We conducted a scoping review of the English language literature published from 1/1/04 to 6/30/17. Articles were eligible if they reported data on ≥2 DIALs within 100 days of the deaths of adults aged ≥18 years. We explored the influence of research design on how researchers measure DIALs and whether they examine demographic correlates of DIALs. Other potential biases and influences were explored.

RESULTS

We extracted data from 254 articles published in 79 journals covering research conducted in 29 countries, mostly focused on cancer care (69.1%). More than 100 DIALs have been examined. Relatively crude, simple variables (e.g., intensive care unit admissions [56.9% of studies], chemotherapy [50.8%], palliative care [40.0%]) have been studied more frequently than complex variables (e.g., burdensome transitions; 7.3%). We found considerable variation in the assessment of DIALs, illustrating the role of research design, professional norms and disciplinary habit. Variables are typically chosen with little input from the public (including patients or caregivers) and clinicians. Fewer than half of the studies examined age (44.6%), gender (37.3%), race (26.5%), or socioeconomic (18.5%) correlates of DIALs.

CONCLUSION

Unwarranted variation in DIAL assessments raises difficult questions concerning how DIALs are defined, by whom, and why. We recommend several strategies for improving DIAL assessments. Improved metrics could be used by the public, patients, caregivers, clinicians, researchers, hospitals, health systems, payers, governments, and others to evaluate and improve end-of-life care.

Predictors of hospital readmission among older adults with cancer

OBJECTIVE

Older adults with cancer are at higher risk for costly and potentially dangerous hospital readmissions. Identifying risk factors for readmission in this population is important for future prevention of readmission.

MATERIALS AND METHODS

Hospital discharges among patients ≥ 65 years with solid tumors on non-surgical services from 2006-2011 were reviewed in this matched case-control study. We abstracted patient/cancer characteristics; functional status; fall risk; chemotherapy line; comorbidities; laboratory values; discharge parameters; and miscellaneous information (Do Not Resuscitate Order, pain scores) from medical records. Conditional logistic regression was used for univariate and multivariable analysis.

RESULTS

This analysis included 184 case-patients readmitted within 30 days after discharge from the index admission and 184 sex- and age-matched control-patients discharged from index admission within three months of the cases with no readmission. Cases and controls had no differences in terms of primary cancer type, treatment, and index admission reason. Cases were more likely to have abnormal hemoglobin, albumin, sodium, and SGOT on discharge. Compared to those with ≤1 abnormal laboratory test, patients with 2 or more abnormal test results were 3 times more likely to be readmitted within 30 days.

CONCLUSION

This study demonstrated that older adults with cancer who had at least 2 abnormal laboratory results (hemoglobin, albumin, sodium, and SGOT) at discharge were 3 times more likely to be readmitted within 30 days compared to those with ≤1 abnormal results. These laboratory values may be predictive of the risk of readmission, and should be monitored before discharge to potentially prevent readmission.

Elements of Palliative Care in the Last 6 Months of Life: Frequency, Predictors, and Timing

IMPORTANCE

Persons living with serious illness often need skilled symptom management, communication, and spiritual support. Palliative care addresses these needs and may be delivered by either specialists or clinicians trained in other fields. It is important to understand core elements of palliative care to best provide patient-centered care.

OBJECTIVE

To describe frequency, predictors, and timing of core elements of palliative care during the last 6 months of life.

DESIGN

Retrospective chart review.

SETTING

Inpatient academic medical center.

PARTICIPANTS

Decedents with cancer, dementia, or chronic kidney disease (CKD) admitted during the 6 months preceding death.

EXPOSURES

We identified receipt and timing of core elements of palliative care: pain and symptom management, goals of care, spiritual care; and specialty palliative care utilization; hospital encounters; demographics; and comorbid diagnoses. We ran Poisson regression models to assess whether diagnosis or hospital encounters were associated with core elements of palliative care.

RESULTS

Among 402 decedents, the mean (SD) number of appropriately screened and treated symptoms was 2.9 (1.7)/10. Among 76.1% with documented goals of care, 58.0% had a primary goal of comfort; 55.0% had documented spiritual care. In multivariable models, compared with decedents with cancer, those with dementia or CKD were less likely to have pain and symptom management (respectively, 31% (incidence rate ratio [IRR], 0.69; 95% CI, 0.56-0.85) and 17% (IRR, 0.83; CI, 0.71-0.97)). There was a median of 3 days (IQR, 0-173) between transition to a goal of comfort and death, and a median of 12 days (IQR, 5-47) between hospice referral and death.

CONCLUSIONS AND RELEVANCE

Although a high proportion of patients received elements of palliative care, transitions to a goal of comfort or hospice happened very near death. Palliative care delivery can be improved by systematizing existing mechanisms, including prompts for earlier goals-of-care discussion, symptom screening, and spiritual care, and by building collaboration between primary and specialty palliative care services.