Risk Of Unplanned Hospitalization Research Articles

Remote Activity Monitoring and Electronic Patient-Reported Outcomes Collection During Radiotherapy for Head and Neck Cancer: A Pilot Study.

Modern wearable devices provide objective and continuous activity data that could be leveraged to enhance cancer care. We prospectively studied the feasibility of monitoring physical activity using a commercial wearable device and collecting electronic patient-reported outcomes (ePROs) during radiotherapy (RT) for head and neck cancer (HNC). Patients planned for a course of external beam RT with curative intent for HNC were instructed to use a commercial fitness tracker throughout the RT course. During weekly clinic visits, physician-scored adverse events were recorded during using Common Terminology Criteria for Adverse Events version 4.0, and patients completed ePRO surveys using a clinic tablet or computer. Feasibility of activity monitoring was defined as collection of step data for at least 80% of the RT course for at least 80% of patients. Exploratory analyses described associations between step counts, ePROs, and clinical events. Twenty-nine patients with HNC were enrolled and had analyzable data. Overall, step data were recorded on 70% of the days during patients' RT courses, and there were only 11 patients (38%) for whom step data were collected on at least 80% of days during RT. Mixed effects linear regression models demonstrated declines in daily step counts and worsening of most PROs during RT. Cox proportional hazards models revealed a potential association between high daily step counts and both reduced risk of feeding tube placement (hazard ratio [HR], 0.87 per 1,000 steps, P < .001) and reduced risk of hospitalization (HR, 0.60 per 1,000 steps, P < .001). We did not achieve our feasibility end point, suggesting that rigorous workflows are required to achieve continuous activity monitoring during RT. Although limited by a modest sample size, our findings are consistent with previous reports indicating that wearable device data can help identify patients who are at risk for unplanned hospitalization.

Classifying home care clients’ risk of unplanned hospitalization with the resident assessment instrument

Key summary pointsAimThe aim was to identify tools for classifying the risk of unplanned hospitalization among home care clients utilizing the Resident Assessment Instrument-Home Care (RAI-HC).FindingsThe Detection of Indicators and Vulnerabilities for Emergency Room Trips (DIVERT) Scale predicts unplanned hospitalizations in home care clients. In the oldest age groups, however, it works poorly.MessageDIVERT Scale can be used for identifying high-risk home care clients needing urgent care planning to prevent unplanned hospital admissions and their potential adverse consequences. Clients scoring high in the scale and experiencing the outcome earlier than others, should be the primary group for more detailed assessment.

Comparison of clinician and model estimates of risk for hospitalization during systemic therapy for advanced cancer.

1530 Background: Patients receiving treatment for advanced cancer are at substantial risk for unplanned hospitalization. A validated two-variable risk model can identify patients at increased risk for hospitalization. However, little is known about how model-based estimates of hospitalization risk compare with assessments of treating clinicians. Methods: We identified patients initiating a new line of systemic therapy for advanced non-hematologic cancer. For each patient, we assigned three categorical estimates of 30-day hospitalization risk. The first risk estimate was generated by a validated two-variable risk prediction model with inputs of pretreatment plasma sodium and albumin (PMID: 30995122); continuous risk scores were converted to risk tertiles. We solicited a second risk estimate by real-time survey of a treating oncology clinician; clinicians were instructed to estimate hospitalization risk as low, intermediate, or high, as compared with other patients. A third hybrid risk estimate retained the highest risk category from either the clinician or model risk assessment. We describe the agreement of clinician and model-based estimates of 30-day hospitalization risk, and we compare the sensitivity and specificity of clinician, model, and hybrid high-risk assessments, using McNemar’s test. We compared discrimination of the three risk estimates via the area under the ROC curve (AUC). Results: We identified 104 patients with valid clinician and model hospitalization risk estimates and complete 30-day follow-up. The most common cancer type was lung cancer (27%), the median age was 68 years, and 62% of patients were male. 30-day hospitalization occurred in 21 patients (20.2%). There was moderate to poor agreement between clinician and model categorical estimates of hospitalization risk (weighted kappa = 0.245). The proportion of patients identified as high-risk by the clinician, model, and hybrid assessments was 15.4%, 26.0%, and 33.7%. Sensitivity and specificity of the high-risk categorization for 30-day hospitalization were 38% and 90% for the clinician assessment, 57% and 82% for the model assessment (NSS for comparison with clinician assessment), and 76% and 77% for the hybrid assessment (greater sensitivity [p = 0.008] and lesser specificity [p = 0.001] than clinician assessment). The AUC values for the clinician, model, and hybrid assessments were 0.674, 0.757, and 0.764, respectively. Conclusions: Compared with the estimate of a treating clinician, a two-variable risk model exhibited similar sensitivity and specificity for 30-day hospitalization risk. A hybrid risk assessment incorporating information from the risk model significantly improved on the sensitivity of the clinician risk assessment. Future research should test strategies to prevent hospitalizations by targeting interventions to high-risk patients.

Prediction of Unplanned Hospitalizations in Older Patients Treated with Chemotherapy.

Simple SummaryUnplanned hospitalizations (UHs) are common among elderly patients with cancer who receive chemotherapy. This fact decreases quality of life or performance status and increases health costs. Our objective was to determine predictive factors for UH in this population. A score based on six variables taken from geriatric assessment and chemotherapy characteristics was developed in a series of 493 elderly patients receiving chemotherapy. The use of this score may reliably identify patients at risk for UH, thus helping to plan treatment, implement adaptive measures, and set up a close follow-up schedule.Purpose: To determine the incidence of unplanned hospitalization (UH) and to identify risk factors for UH in elderly patients with cancer who start chemotherapy. Methods: In all, 493 patients over 70 years starting new chemotherapy regimens were prospectively included. A pre-chemotherapy geriatric assessment was performed, and tumor and treatment variables were collected. The association between these factors and UH was examined by using multivariable logistic regression. Score points were assigned to each risk factor. Results: During the first 6 months of treatment, 37% of patients had at least one episode of UH. Risk factors were the use of combination chemotherapy at standard doses, a MAX2 index ≥1, a Charlson comorbidity score ≥2, albumin level <3.5 g/dL, falls in the past 6 months ≥1, and weight loss >5%. Three risk groups for UH were established according to the score in all patients: 0–1: 17.5%; 2: 34%; and 3–7: 57% (p < 0.001). The area under receiver operation characteristic (ROC) curve was 0.72 (95% CI: 0.67–0.77). Conclusion: This simple tool can help to reduce the incidence of UH in elderly patients with cancer who are scheduled to initiate chemotherapy treatment.

Association of psychosocial factors with all-cause hospitalizations in patients with atrial fibrillation.

BackgroundA high burden of cardiovascular comorbidities puts patients with atrial fibrillation (AF) at high risk for hospitalizations, but the role of other factors is less clear.HypothesisTo determine the relationship between psychosocial factors and the risk of unplanned hospitalizations in AF patients.MethodsProspective observational cohort study of 2378 patients aged 65 or older with previously diagnosed AF across 14 centers in Switzerland. Marital status and education level were defined as social factors, depression and health perception were psychological components. The pre‐defined outcome was unplanned all‐cause hospitalization.ResultsDuring a median follow‐up of 2.0 years, a total of 1713 hospitalizations occurred in 37% of patients. Compared to patients who were married, adjusted rate ratios (aRR) for all‐cause hospitalizations were 1.28 (95% confidence interval [CI], 0.97‐1.69) for singles, 1.31 (95%CI, 1.06‐1.62) for divorced patients, and 1.02 (95%CI, 0.82‐1.25) for widowed patients. The aRRs for all‐cause hospitalizations across increasing quartiles of health perception were 1.0 (highest health perception), 1.15 (95%CI, 0.84‐1.59), 1.25 (95%CI, 1.03‐1.53), and 1.66 (95%CI, 1.34‐2.07). No different hospitalization rates were observed in patients with a secondary or primary or less education as compared to patients with a college degree (aRR, 1.06; 95%CI, 0.91‐1.23 and 1.05; 95%CI, 0.83‐1.33, respectively). Presence of depression was not associated with higher hospitalization rates (aRR, 0.94; 95%CI, 0.68‐1.29).ConclusionsThe findings suggest that psychosocial factors, including marital status and health perception, are strongly associated with the occurrence of hospitalizations in AF patients. Targeted psychosocial support interventions may help to avoid unnecessary hospitalizations.Trial registration ClinicalTrials.gov Identifier NCT02105844.

Socioeconomic position and risk of unplanned hospitalization among nursing home residents: a nationwide cohort study.

BackgroundSocioeconomic inequalities in health and healthcare use in old age have been on the rise during the past two decades. So far, it is unknown whether these inequalities have permeated the nursing home setting. This study aimed to assess whether the socioeconomic position of newly admitted nursing home residents had an influence on their risk of unplanned hospitalization.MethodsWe identified older persons (≥75 years) who were newly admitted to a nursing home between March 2013 and December 2014 using a set of linked routinely collected administrative and healthcare data in Sweden. The number of unplanned hospitalizations for any cause and the cumulative length of stay were defined as primary outcomes. Unplanned hospitalizations for potentially avoidable causes (i.e. fall-related injuries, urinary tract infections, pneumonia and decubitus ulcers) were considered as our secondary outcome.ResultsAmong 40 545 newly admitted nursing home residents (mean age 86.8 years), the incidence rate of unplanned hospitalization ranged from 53.9 per 100 person-years among residents with tertiary education up to 55.1 among those with primary education. After adjusting for relevant confounders, we observed no meaningful difference in the risk of unplanned hospitalization according to the education level of nursing home residents (IRR for tertiary vs. primary education: 0.96, 95% CI 0.92–1.00) or to their level of income (IRR for highest vs. lowest quartile of income: 0.98, 0.95–1.02). There were also no differences in the cumulative length of hospital stays or in the risk of experiencing unplanned hospitalizations for potentially avoidable causes.ConclusionsIn sum, in this large cohort of newly admitted nursing home residents, we found no evidence of socioeconomic inequalities in the risk of unplanned hospitalization.

P3782Frailty to predict unplanned hospitalizations, stroke, bleeding and death in atrial fibrillation

Abstract Aim We investigated the prevalence of frailty, and the relationships between frailty and the risk of adverse clinical outcomes in patients with atrial fibrillation (AF). Methods Patients with known AF were enrolled in a nation-wide observational cohort study in Switzerland. Information on medical history, medication, lifestyle factors and clinical measurements were obtained. The primary outcome was unplanned hospitalizations, secondary outcomes were all-cause mortality, bleeding and stroke. The frailty index (FI) was measured using a cumulative deficit approach according to previously published criteria. Participants were divided into three groups (non-frail, pre-frail and frail) according to their FI at study entry. The association between frailty and clinical outcomes was assessed using multivariable adjusted Cox proportional hazard models. Results We included 2369 patients with a mean age of 73±8 years (27.3% female). The prevalence of frailty and pre-frailty was 10.6% and 60.7%, respectively. Frailty was associated with unplanned hospitalization (adjusted hazard ratio [HR] 3.59; 95% confidence interval [95% CI], 2.78–4.63; p&lt;0.001), all-cause mortality (adjusted HR 16.72; 95% CI 7.75–36.05; p&lt;0.001), bleeding (adjusted HR 2.46; 95% CI 1.61–3.77; p&lt;0.001), and stroke (adjusted HR 3.29; 95% CI 1.29–8.39; p=0.01) (Figure). Similarly, pre-frailty was significantly associated with unplanned hospitalization (adjusted HR 1.82; 95% CI 1.49–2.22; p&lt;0.001), all-cause mortality (adjusted HR 5.07; 95% CI 2.43–10.59; p&lt;0.001) and bleeding (adjusted HR 1.53; 95% CI 1.11–2.13; p=0.01), but not with stroke. Cumulative incidence of adverse events Conclusion In our cohort, more than two thirds of AF patients were either pre-frail or frail. These patients have a high risk of unplanned hospitalizations and other adverse outcomes, indicating that frailty is a powerful tool to predict adverse clinical outcomes in AF patients. Acknowledgement/Funding Swiss National Science Foundation; Foundation for Cardiovascular Research Basel; University of Basel

Potential drug-drug interactions and risk of unplanned hospitalization in older patients with cancer: A survey of the prospective ELCAPA (ELderly CAncer PAtients) cohort

BackgroundBecause of comorbidities and polypharmacy, older patients with cancer have a greater risk of iatrogenic events. We aimed to characterize potential drug-drug interactions (PDIs) and the risk of unplanned hospitalization in older patients with cancer treated with antineoplastic agents (ANAs). MethodsWe analyzed all older patients (≥70 years) from the prospective ELCAPA cohort referred for geriatric assessment (2007–2014) prior to treatment with ANA at Henri Mondor Hospital (Créteil, France). PDIs were identified using Lexicomp®, and Theriaque® for French medications. Factors associated with PDIs, and association between PDIs and unplanned hospitalization in the 6 months following geriatric assessment were analyzed using ordered multivariate logistic regression (MLR). ResultsWe included 442 patients (median [interquartile range] age: 77 years [74–80]); number of medications/patient/day: 6 [3–8]); ECOG-PS ≤ 2: 79%; metastasis: 70%). Most patients had a digestive tract cancer (colorectal: 22%; upper digestive tract: 23%). We identified 1742 PDIs; 76.5% of patients had ≥1 PDI; 13% of the PDIs involved an ANA. In a multivariate analysis, cardiovascular disorders (ischemic heart disease, heart failure, atrial fibrillation and/or arterial hypertension) were independently associated with PDIs (p < .001, after adjustment for polypharmacy and tumor site/stage). A high number of PDIs between two daily medications was independently associated with the risk of unplanned hospitalization (adjusted-odds ratio [95% confidence interval] per PDI: 1.05 [1.00;1.11], p = .05), while polypharmacy was not. ConclusionPatients with cardiovascular comorbidities were more likely to have a PDI. A higher number of PDIs may be an independent risk factor for early unplanned hospitalization.

Association between dysphagia risk and unplanned hospitalization in older patients receiving home medical care.

Home medical care for older adults with chronic conditions is becoming an increasing important issue in Japan. We need to support long-term medical care at home and avoid unplanned hospitalizations, which can adversely affect activities of daily living and quality of life. In this study, we investigated whether swallowing function is a risk for unplanned hospitalization in older patients with functional decline who are receiving home medical care. In the current study, we examined data obtained in the Observational study of Nagoya Elderly with HOme MEdical study (ONEHOME) that investigated the medical health of older adults receiving home medical care services in Nagoya City, Japan. The data analyzed were patients' age, sex, number of medications, Dysphagia Severity Scale, Charlson Comorbidity Index, Barthel Index, Mini Nutritional Assessment - Short Form, Frailty Index and dementia independent scale. The Dysphagia Severity Scale was categorized into the presence or absence of dysphagia risk. The association between dysphagia risk and days until first hospitalization was investigated by Cox regression analysis. In total, 86 out of 178 patients had a hospitalization during the study period of 4 years. Cox regression analysis with adjustment for age, sex, Charlson Comorbidity Index, Barthel Index and Mini Nutritional Assessment - Short Form scores showed that a lower Dysphagia Severity Scale score was significantly associated with unexpected hospitalization. Dysphagia risk predicts the first unexpected hospitalization in older individuals receiving home medical care. Patients' swallowing function is an important factor for estimating prognosis. Geriatr Gerontol Int 2019; 19: 977-981.

Objective metrics of patient activity: Use of wearable trackers and patient reported outcomes in predicting unexpected healthcare events in cancer patients undergoing highly emetogenic chemotherapy.

6519Background: Functional status and predictors that identify those cancer patients at risk for unplanned hospitalization can have broad implications for the health care system and clinical trials...

Potentially Inappropriate Medication Prescribing and Risk of Unplanned Hospitalization among the Elderly: A Self-Matched, Case-Crossover Study.

An association between potentially inappropriate medication (PIM) use and adverse events has been established. However, PIM criteria for elderly patients and medical circumstance vary in different countries. We investigated the association between PIM use according to Japanese guidelines and unplanned hospitalization among elderly patients. A case-crossover study was conducted. We used the Japanese Medical Data Vision database of 17.9 million people from 270 acute care hospitals across Japan. Records from 247,897 patients aged ≥ 65years with unscheduled admissions between January 2009 and December 2015 were analyzed. We defined PIM use according to the Japanese Guidelines for Medical Treatment and Its Safety in the Elderly and used conditional logistic regression analysis to fit self-matched case-crossover models and compared each patient's PIM use over five case periods (1, 2, 4, 8, and 12weeks) prior to each unplanned hospitalization. We found the highest odds ratios (ORs) of unscheduled admission related to PIM use in the 1-week case period [OR 4.15; 95% confidence interval (CI) 4.05-4.25], followed by the 2-week (OR 3.01; 95% CI 2.95-3.07), 4-week (OR 3.91; 95% CI 3.83-4.00), 8-week (OR 2.00; 95% CI 1.96-2.05), and 12-week case periods (OR 1.48; 95% CI 1.44-1.51). Elderly patients commonly used PIMs, especially antidiabetics and diuretics. PIM use was associated with a 1.5- to 4-fold increase in the ORs of unplanned hospitalization among them.

Risk of Unplanned Hospitalization During Treatment With Concomitant Chemoradiation Therapy

Patients undergoing treatment with concomitant chemoradiation therapy (CRT-CT) are at increased risk for unplanned hospitalization as a complication of treatment. However, to our knowledge, the rate of hospitalizations during CRT-CT and the risk factors associated with it are unknown.

Unplanned hospitalizations among gastrointestinal cancer patients in the state of Texas.

6634 Background: Hospitalization rates and cost of care for patients with Gastrointestinal (GI) malignancies are among the highest in the spectrum of cancers. It is poorly understood if these are driven by planned or unplanned hospitalizations. Methods: We conducted a retrospective cohort study using linked Texas Cancer Registry and Medicare claims data to describe the patterns of unplanned hospitalization among GI cancer patients in Texas. Our outcome, unplanned hospitalization, was defined as any emergent or urgent admission. Prior comorbidities were assessed using a modified Charlson score. Data were collected for 2 years from date of cancer diagnosis. Modified Poisson regression model was used to identify factors associated with the outcome. Results: 30,199 patients aged &gt;66 years were included in the study. 25,096 patients had 70,256 in-patient claims. 53.6% of these claims were unplanned hospitalizations. The top 3 reasons for unplanned hospitalization were pneumonia, congestive heart failure and volume depletion. Unplanned hospitalization rates ranged from 57.9% (colon) to 67.4% (esophageal) among the different cancer types. After multivariate analysis, unplanned hospitalization was more likely among those with esophageal cancer (RR=1.15, CI 1.1-1.2), gastric cancer (RR=1.07, CI 1.04-1.11), pancreatic cancer (RR=1.04, CI 1.01-1.07) and rectal cancer (RR= 1.03, CI 1.00-1.06). Patients with regional and distant disease were at higher risk for unplanned hospitalization (RR=1.14, CI 1.11-1.16 and RR=1.13 CI 1.1-1.16 respectively), as well as those aged &gt;80 (RR=1.04 CI 1.01-1.06), of black race (RR=1.06, CI 1.02-1.09), and living in census tract with &gt;21% poverty level (RR=1.06 CI 1.03-1.09). Risk of unplanned hospitalization also increased with Charlson scores (p&lt;.0001). Conclusions: The majority of hospitalizations were unplanned. Top reasons for unplanned hospitalization were diagnoses that are considered potentially preventable, and should be a focus for intervention. The disparity in unplanned hospitalizations among blacks and those living in poverty-stricken areas warrants further investigation as to whether this finding correlates with timely access to outpatient care in this population.