Higher Healthcare Utilization Research Articles

Reasons for Hospital Admission in Individuals With Multiple Sclerosis.

Health care utilization is higher in individuals with multiple sclerosis (MS) than in the general population. However, there are limited data on the reasons for their hospital admissions. Our primary objective is to analyze the reasons for the hospitalization of individuals with MS with the goal of identifying preventable causes. We conducted a retrospective analysis of a cohort of adults with a confirmed diagnosis of MS admitted to Duke University Hospital between January 2018 and January 2020. This yielded a cohort of 210 individuals. Data were analyzed using descriptive statistics. The most common reason for admission was urinary tract infection (UTI; 10.3%). The average length of stay was 6.1 days for the individuals with MS vs 5.5 days for the general population. The 30-day readmission rates were 14.9% and 15.5%, respectively. A significant number of admitted patients were not on any disease-modifying therapy (DMT), and no difference in median age was identified between those with a DMT vs those without. Length of stay and readmission rates were similar to those of the general population in this contemporary cohort. Given the prevalence of bladder dysfunction in MS, it is not surprising that a UTI was the most common reason for admission. Actively addressing management of and techniques for bladder dysfunction may decrease the admission rate for individuals with MS. Though we now have more treatment options for MS, many individuals with the highest health care utilization are not on a DMT. Future research is needed to identify the factors that can be addressed to support these patients and reduce preventable hospitalizations.

Heart failure burden among adults with congenital heart disease

Abstract Background Adult congenital heart disease (ACHD) is associated with high rates of healthcare utilization and mortality. Data on Heart failure (HF) burden among ACHD patients are limited. Purpose To study the association between HF and healthcare utilization and mortality among ACHD patients in the community. Methods The retrospective cohort study comprised 11,653≥ 18 year old ACHD patients insured by two large Israeli healthcare providers between January 2007 and December 2011. We used multivariable Cox proportional hazard and negative binomial models to study the associations of HF with mortality and healthcare utilization, respectively. Inverse treatment probability weighting accounted for drug indication. Results ACHD-HF patients (N=908; 7.8%) were older (median: 69 vs. 45 years), more likely men (53% vs. 45%), with complex congenital heart disease (14% vs. 4%), and higher comorbidity rates than ACHD patients without HF. HF was associated with higher healthcare utilization. Compared to patients without HF, ACHD-HF patients had higher adjusted relative rates (RR) of primary care (1.26, 95% confidence interval [CI]: 1.17-1.3), and cardiology clinic visits (1.9, 95% CI: 1.7-2.0), higher hospitalization rates (RR=2.0, 95% CI: 1.7-2.1), and higher risk of death (mortality hazard ratio [HR]: 1.9, 95% CI: 1.5-20.) over the study period. Among ACHD-HF patients, Angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, beta-blockers, and diuretics were associated with a lower mortality risk (treated vs. untreated HR=0.56, 95% CI: 0.48-0.65; HR=0.7, 95% CI: 0.6-0.8; HR=0.84, 95% CI: 0.73-0.97; respectively). Conclusions HF presents a major burden on ACHD patients and health care systems. Drugs recommended to the general HF patient population are also associated with lower risk of hospitalization and mortality in ACHD patients. Clinical trials are needed to establish the benefit of HF pharmacotherapy in ACHD patients.Age adjusted ACHD patient survival by HF

Machine-learning based prediction for high health care utilizers using a multi-institution registry

Abstract Background Rising healthcare costs worldwide have spurred interest in using machine learning to pinpoint major healthcare utilizers for population health efforts. Previous studies have focused on individuals who impose the highest financial burden, such as targeting high-need high-cost utilizers, a small group with limited potential for cost reduction. Therefore, we developed models to predict future healthcare utilization across various thresholds. Methods We leveraged data from a multi-institutional diabetes database to develop binary classification models capable of predicting healthcare utilization in the following year. The models predicted six different outcomes: patients with an annual total length of stay of ≥ 7, ≥14, and ≥30 days, and emergency department (ED) attendance of ≥ 3, ≥5, and ≥10 visits. To mitigate class imbalance, we applied random and synthetic minority oversampling techniques and compared against models trained without oversampling. Models were trained with 2019 data and tested on unseen data from 2020 and 2021. Results Models trained with random oversampling, including logistic regression, multivariate adaptive regression splines, boosted trees, and multilayer perceptron, consistently demonstrated high AUC (>0.80) and sensitivity (>0.60) across both training-validation and test datasets. Addressing class imbalance was found to be crucial, as models without oversampling displayed satisfactory AUC (>0.80) but significantly lower sensitivity (<0.10). Key predictors identified included age, number of ED visits in the present year, chronic kidney disease stage, inpatient bed days in the present year, and mean HbA1c levels. Conclusions Our machine learning models successfully predict high service level utilization with strong performance, offering valuable tools for policymakers and health planners to develop targeted health initiatives based on patient utilization patterns. Key messages • Machine learning models can be leveraged to predict future healthcare utilization and facilitate interventional program development. • Annual total length of stay and total emergency department visits are useful service level indicators.

18 Past and current care practices for neonates with complex medical needs: A scoping review to support clinical program evaluation

Abstract Background Neonates with complex medical needs (NCMN) are a rapidly growing patient population internationally. Although NCMN are a relatively small proportion of all Neonatal Intensive Care Unit (NICU) admissions, they are high healthcare utilizers. Since 2018, a dedicated Neonatal Complex Care Team (NCCT) has cared for NCMN at a large quaternary care center. The NCCT cares for NCMN in a dedicated, single-family room, patient area within the NICU. This model of care has yet to be evaluated for its potential impact on healthcare outcomes. Objectives The objective of the scoping review is to determine the breadth of available literature on the care practices for the management of NCMN and to collate the available evidence to define outcome measures to be used in a formal program evaluation. Design/Methods The review followed the PRISMA extension for scoping reviews and utilized resources from the Joanna Briggs Institute. The two databases that were utilized include Medline via OVID and CINAHL. The dates for included publications are January 1st 1993, until July 15th 2023. Only studies published in English and primary research were included. Two independent reviewers performed the initial title and abstract screening, and the full text review. The data extraction was completed by one independent reviewer. Results 102 articles were included in the title and abstract screen, and 12 were considered for full text review. Four articles were included. Interventions discussed in the included articles ranged from discharge conferences with patient’s caregivers, to the implementation of an entirely new model of care. Multidisciplinary health care teams appear to be integral to the in-hospital care and smooth discharge of NCMN. We identified that caregiver involvement and satisfaction are important to the discharge process as they are primarily responsible for their infant’s care after discharge, and so it is important that the specifics of care are communicated and taught effectively. The outcomes of interest identified as most useful for clinical program evaluation were length of stay and readmission rate. Additionally there was limited data reported on long-term health outcomes of this patient population. Conclusion This scoping review identified few articles that reported new models of care, a lack of consistent outcomes used in evaluating existing care models and overall a gap in research in this rapidly growing patient population. There is more work to be done to improve care of NCMN and our findings will be used in designing future studies that evaluate care models.

Inpatient hospitalisations for patients with Prader-Willi syndrome: a 2019-2021 National Inpatient Sample analysis.

Prader-Willi syndrome (PWS) is a genetic disorder characterised by hyperphagia, intellectual disability and increased propensity to a range of medical disorders. To better characterise the clinical presentation of PWS across the lifespan, this study reports on the demographics and clinical diagnosis of individuals with PWS hospitalised in the United States. The National Inpatient Sample, an all-payor administrative claims database of hospitalisations in the United States, was queried for patients with a coded diagnosis of PWS from October 2019 through December 2021. Hospitalisations for patients with PWS were matched to five non-PWS hospitalisations based on age, sex, year and hospital characteristics. There were 4400 (95% CI: 3,885 to 4,915) PWS hospitalisations, with a median age of 24. Compared to controls, PWS hospitalisations had longer hospital stays (median 5 vs. 3days) and higher in-hospital mortality (2.2% vs. 1.3%). Infectious (19.0%) and respiratory (16.2%) diagnoses were most common for PWS patients. Codes for overweight or obesity were present in 38.1% of PWS hospitalisations, with Hispanic ethnicity was associated with a higher odds of overweight/obesity in PWS patients (aOR 1.73; 95% CI: 1.11-2.71). PWS hospitalisations are characterised by higher healthcare utilisation and complexity compared to matched controls. The high prevalence of obesity and significant rates of infectious and respiratory conditions highlight specific health challenges for PWS patients. Validation of the Q87.11 administrative claims code is an essential step for ongoing health services research in this condition.

Machine Learning-Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation.

The cost of health care in many countries is increasing rapidly. There is a growing interest in using machine learning for predicting high health care utilizers for population health initiatives. Previous studies have focused on individuals who contribute to the highest financial burden. However, this group is small and represents a limited opportunity for long-term cost reduction. We developed a collection of models that predict future health care utilization at various thresholds. We utilized data from a multi-institutional diabetes database from the year 2019 to develop binary classification models. These models predict health care utilization in the subsequent year across 6 different outcomes: patients having a length of stay of ≥7, ≥14, and ≥30 days and emergency department attendance of ≥3, ≥5, and ≥10 visits. To address class imbalance, random and synthetic minority oversampling techniques were employed. The models were then applied to unseen data from 2020 and 2021 to predict health care utilization in the following year. A portfolio of performance metrics, with priority on area under the receiver operating characteristic curve, sensitivity, and positive predictive value, was used for comparison. Explainability analyses were conducted on the best performing models. When trained with random oversampling, 4 models, that is, logistic regression, multivariate adaptive regression splines, boosted trees, and multilayer perceptron consistently achieved high area under the receiver operating characteristic curve (>0.80) and sensitivity (>0.60) across training-validation and test data sets. Correcting for class imbalance proved critical for model performance. Important predictors for all outcomes included age, number of emergency department visits in the present year, chronic kidney disease stage, inpatient bed days in the present year, and mean hemoglobin A1c levels. Explainability analyses using partial dependence plots demonstrated that for the best performing models, the learned patterns were consistent with real-world knowledge, thereby supporting the validity of the models. We successfully developed machine learning models capable of predicting high service level utilization with strong performance and valid explainability. These models can be integrated into wider diabetes-related population health initiatives.

Economic Burden Associated with Pulmonary Arterial Hypertension in the United States.

Pulmonary arterial hypertension (PAH) is a progressive disease characterized by elevated pressure in the pulmonary arteries, commonly resulting in right heart failure. PAH is associated with a high economic burden throughout the duration of the disease. This retrospective cohort study of the Milliman Contributor Health Source Data, the Medicare 100% Research Identifiable Files, and the Merative Marketscan® Commercial dataset between 2018 and 2020 identified adult patients with prevalent PAH based on the earliest qualifying diagnosis date or medication date ('index date') between January 1, 2019 and November 30, 2020. Outcomes were assessed using patient data from index date through the earliest of end of enrollment, end of data, or death (Medicare fee-for-service [FFS] only). All-cause and PAH-related medical and pharmacy costs per-patient per-month (PPPM) and healthcare resource utilization per 1000 patients were summarized. The study included 11,670 Medicare FFS, 1021 Medicare Advantage, 274 Medicaid, and 1174 commercially insured patients in the US. The annual national burden to payers was estimated to be US$3.1 billion. The PPPM payer costs ranged from US$6500 to US$14,742; out-of-pocket (OOP) costs ranged from US$341 to US$907 PPPM. Inpatient utilization rate ranged from 435 to 770 per 1000 patients for all-cause admissions and from 15 to 58 per 1000 patients for PAH-related admissions. This study demonstrates that PAH continues to be associated with a high economic burden and healthcare resource utilization across all payer types within the US healthcare system.

Predictive model for the risk of paediatric intensive care utilization in children with medical complexity: A longitudinal retrospective cohort study.

Children with medical complexity (CMC) are at increased risk of admission in intensive care. Despite improvements in mortality rates, there remains a burden of morbidity, long-term health care needs and hospital readmissions. Beyond clinical factors, socio-demographic determinants could impact utilization of acute services. To identify risk factors that can differentiate CMC who are admitted to the paediatric intensive care unit (PICU). A 6-year longitudinal retrospective cohort study evaluated clinical, socio-demographic and health care utilization. A total of 248 CMC were included, with a median age of 13 years (9.75-17.00). Intensive care admission rate was 47.2%. The risk of PICU admission was higher for children undergoing surgical interventions (HR = 1.58, 95% CI 1.34-1.86, p < .001) and those using medical devices (HR = 1.81, 95% CI 1.54-2.13, p < .001). Mother's higher educational level was a protective factor (HR = 0.66, 95% CI 0.55-0.79, p < .001). Multivariable analysis revealed significant associations between risk of admission and the presence of malignancy, comorbidities, home medical devices, surgical procedures and higher health care utilization. Children's age and higher maternal educational level acted as protective factors. Socio-demographic factors should be considered in the provision of care to CMC. Individualized assessments to guide supportive interventions adapted to socio-economic factors may prevent PICU admissions. This study highlights the importance of integrating individualized assessments of socio-demographic risk factors, such as maternal educational level, into the clinical practice of paediatric nurses. Moreover, targeted interventions, including educational resources and community support programmes, may optimize care.

8189 Demographics and Healthcare Utilization of Diabetic Versus Non-Diabetic Gastroparesis hospitalization in the United States Using the National Inpatient Sample database

Abstract Disclosure: S. Khan: None. L. Zia: None. M. Khan: None. M. Amin: None. M. Khan: None. F. Sattar: None. Background: Gastroparesis is commonly associated with neuropathy secondary to Diabetes and Non-Diabetic causes such as Idiopathic, Post-Viral and Surgical with a wide spectrum of clinical manifestations impairing quality of life, worsening morbidity, and mortality. The purpose of this study is to assess Demographic disparities and utilization of healthcare services between Diabetic (DG) Versus Non-Diabetic Gastroparesis (NDG) admissions. Methods: Data were extracted from the National Inpatient Sample Database for the year 2020. It comprises discharge data obtained from a 20% stratified sample of community hospitals across the country. We conducted a retrospective cohort study focusing on admissions of patients aged 18 years and above with diagnosis of DG and NDG were identified using ICD-10 codes. Multivariate regression analysis was used to estimate the Mean difference of the Average length of hospital stay (LOS), and total hospital charges (THC). Multivariate logistic and linear regression was used accordingly to adjust for confounders. Analysis was performed using STATA 18. Results: Our study identified 10330 patients hospitalized due to gastroparesis, among them 1446 (14%) had DG. Hospitalizations with DG in comparison with NDG had lower number of women (65% Vs 80.7%, P≤0.05), a higher proportion of black adults (36.5% Vs 17%), a lower proportion of white adults (46.4% Vs 70%), and a higher Charlson Comorbidity Index. In DG, 104(7.19%) patients had EGD and non-diabetic gastroparesis, 977 (11%) had EGD during admission. The mean LOS in hospital was 4.72 days and mean total hospital charges were 51327 USD. Comparing both cohorts, there was statistically significant decrease in the mean LOS in DG, Adjusted Mean difference of 1.27 days (P = 0.006). In addition, there was significant decrease in the total cost of hospitalization with an adjusted Mean difference of 13832 (P=0.001). Thirty patients with NDG died during hospital course and none with Diabetic gastroparesis. Conclusion: According to our findings, majority of admissions with gastroparesis are related with non-diabetic causes with higher healthcare utilization and mortality rate. Gastroparesis is a relatively frequent and poorly understood condition which needs considerate effort to have a better understanding of disease. Presentation: 6/2/2024

Identifying Frailty and Its Risk Factors in Pediatric Patients with Fontan Physiology.

Frailty is a clinical syndrome common in adults with chronic disease with resultant vulnerability to adverse health outcomes. Little is known about frailty in pediatric patients, including those with single-ventricle heart disease. This study aimed to examine the prevalence of frailty and its associated risk factors in patients with Fontan circulation. A single-center, prospective cohort study assessed frailty in patients (10-21years old) after Fontan palliation. Slowness, weakness, exhaustion, shrinkage, and diminished physical activity were evaluated and scored using a modified Fried frailty assessment comprised of validated pediatric tests. Providers estimated subjects' degree of frailty. Patient-reported quality of life (QOL) was assessed. Of 54 participants (median age 15.3years, 61% male), 18 (33%) were identified as frail, while 26 (48%) were pre-frail. Patients frequently exhibited frailty in the domains of slowness (93%), weakness (41%), and diminished physical activity (39%). There was poor correlation between frailty scores and provider estimates of frailty (Kappa = 0.11). Frail subjects had lower PedsQL physical functioning scores (mean 62.8 ± SD 18.5 in Frail vs. 75.7 ± 16.0 in No/pre-Frail; p = 0.01). Factors associated with frailty included protein-losing enteropathy (p = 0.03) and at least one hospitalization in the last year (p = 0.047). One-third of pediatric patients after Fontan palliation were frail which was associated with lower physical functioning and higher healthcare utilization. Providers poorly recognized frailty. These findings highlight the need for improved screening and support for an at-risk population where frailty is not easily identified.

Impact of supportive oncology (SO) visits on healthcare utilization.

199 Background: Palliative care (PC) has demonstrated a reduction in acute care utilization for health systems. PC input for patients with cancer has been associated with fewer emergency room visits, hospitalizations and hospital deaths in the last 30 days of life. Less is known about the upstream effects of PC referral on healthcare utilization (HCU). We examined HCU among patients in the 90 days after first SO appointment and predictors of high HCU. Methods: Patients ≥18 years with first SO consult between 01/01/2021-06/30/2023 were included. Patients who died within 90 days of their first SO appointment and incomplete utilization data were censored. Data on patient demographics, acute healthcare and hospice utilization, cancer treatment and mortality was extracted from the electronic health record (EHR). Number of ED visits in 90 days before and after first SO visit were recorded. We used descriptive statistics to describe patients’ sociodemographics, clinical characteristics and healthcare utilization. High HCU was defined as patients in the top 10% of ED visits and IP stays. Logistic regression was employed to assess whether being a high utilizer is associated with baseline characteristics. Results: We included 859 patients. On average, there were approximately 0.12, 95%CI: [0.07,0.17] more ED visits in the 90 days before the first SO appointment compared to 90 days after. There was no difference in hospitalization rates before and after the first SO appointment. Overall, 45 patients met the criteria for high HCU. The median number of ED visits and hospitalizations of high utilizers was 6 visits, compared to 1 visit for remainder of the population. There was a significant association with ethnicity with those identified as Hispanic (60%) being high HCU. There was no significant association between age, insurance status, cancer type, primary language and high HCU. High utilizers were 189% more likely to die in hospital although this did not meet statistical significance (p= 0.242). Conclusions: The findings reveal significant variations in healthcare utilization, particularly among Hispanic patients, indicating a need for targeted interventions to address these disparities. Despite no observed changes in hospitalization rates, the study emphasizes the need for further research to understand the underlying factors contributing to high healthcare utilization. Future efforts should focus on developing tailored strategies to optimize PC referrals and enhance patient outcomes across diverse populations. Race/ethnicity by utilization group. Category &lt;90th Percentile Utilization (n=814) % &gt;90th Percentile Utilization (n=45) % P value Race (%) &lt;0.001 Asian 97 (11) 0 (0) Black or African American 173 (21) 8 (18) Hispanic 198 (24) 27 (60) Other 50 (6) 3 (7) White 296 (36) 7 (16)

Impact of respiratory syncytial virus infection among patients with hematological cancer in the era of post-coronavirus pandemic.

400 Background: Two vaccine is recently approved for elderly patient with compromised immunity. Despite the recommendation by Center for Disease Control and Prevention (CDC), RSV vaccination is remains low among patient with hematological malignancy, when compare to influenza vaccination. Thus, we conducted an observational study to estimate the impact of RSV infection among patients with hematological malignancy. Methods: We conducted a population-based retrospective cohort utilized the TritNetx dataset, which consist of patients across 63 U.S. healthcare organization. This study included patient who had respiratory viral infection after a diagnosis of hematological malignancy during 6/1/2022 - 4/1/2022. Hematological malignancy was identified using ICD-10 codes. CPT code and ICD-10 code were used to identify diagnosis of respiratory viral infection after respiratory pathogen panel testing. Patient who was diagnosed with RSV, influenza or COVID-19 were paired based on the following variable, including demographics, body mass index, comorbidities, and anti-neoplastic therapy. Hazard ratio (HR) was estimated by Cox proportional hazard regression models and log-rank test. Risk ratio (RR) was calculated by logistic regression. Results: A total of 6,088 patients with hematological malignancy contracted RSV, influenza or COVID during the observation period. When compare to influenza, patients with RSV infection were associate with high healthcare utilization, including emergency visit (HR: 1.20, 95% CI:[1.00-1.41]), and hospitalization (HR: 1.29, 95% CI:[1.06-1.57]). RSV infection was also resulted in higher acuity including viral pneumonia (HR: 15.42, 95% CI:[9.26-25.68]), use of antibiotics (HR: 1.54, 95% CI:[1.28-1.86]), renal replacement therapy (HR: 2.09, 95% CI:[1.10-3.96]), and acute respiratory failure (HR: 1.54, 95% CI:[1.14-2.07]). When compare to COVID-19, RSV infection showed similar trend including more frequent emergency visit (HR: 1.30, 95% CI:[1.10-1.54]), and high risk of developing viral pneumonia (HR 23.48, 95% CI: [12.79-43.09]). Interestingly, the intubation rate, 28 days all-cause mortality and 90 days all-cause mortality were similar between the three cohort. Conclusions: RSV infection was associated with higher rate of pneumonia and healthcare utilization. RSV vaccination should be considered to prevent RSV-associated morbidity among patients with hematological malignancy.

Association between malnutrition risk and healthcare utilization in a culturally diverse sample of ambulatory patients with cancer.

254 Background: Malnutrition is prevalent among cancer patients placing them at an increased risk for treatment-related complications and poor clinical outcomes. This study investigated the relationship between malnutrition risk and healthcare utilization in a diverse sample of adult ambulatory cancer patients from the Sylvester Comprehensive Cancer Center. Methods: A retrospective analysis was conducted with data collected through the My Wellness Check (MWC), an electronic health record (EHR)-based assessment. Malnutrition was assessed through the NUTRISCORE, an integrated and validated nutritional screening tool within MWC that evaluates self-reported weight loss, appetite, cancer type, and treatment modality to assess risk of malnutrition. A NUTRISCORE greater or equal to 5 is considered malnutrition risk. Time to an emergency room (ER) visit and hospitalization were calculated in days from the first MWC questionnaire assignment and the first event, respectively. All ER visits and hospitalizations in the University of Miami Health System, self-reported patient demographics, and clinical characteristics were captured from the EHR. Uni- and multi-variate logistic regression models were used to examine factors associated with malnutrition risk. For survival analyses, the Kaplan-Meier method was used to calculate the cumulative incidence function of events and the cox proportional hazards regression models adjusting for patient demographics and clinical characteristics. Results: A total of5,984 ambulatory patients completed the MWC assessment between October 2019, and August 2023, with 31.2% (n=1,868) identified at malnutrition risk (NUTRISCORE ≥5). Patients were predominately White (n=5,092, 85.2%), and Hispanic (n=2,341, 39.1%). Hematologic cancer was the most common diagnosis (n=1284, 21.5%) followed by malignancies in digestive system (n=903, 15.1%) and male genitourinary (n=892, 14.9%). After adjusting for covariates, patients at malnutrition risk were at significantly higher risk for both ER visits (HR 1.57, 95% CI; 1.29 - 1.91, p&lt;0.0001) and hospitalizations (17.4% vs. 7.4% at 100 days, p&lt;0.0001) compared to those with low malnutrition risk. Factors associated with malnutrition risk included Hispanic ethnicity (aOR 1.17, 95% CI; 1.01-1.35), fatigue (aOR 1.62, 95%CI; 1.07-2.45), declined physical function (aOR 1.75, 95% CI;1.37 - 2.24), physical inactivity (aOR 1.20, 95%CI;1.04 - 1.38) and low HRQOL (aOR 2.48, 95%CI; 1.93-3.19). Conclusions: Malnutrition was associated with higher healthcare utilization in a diverse sample of ambulatory cancer patients. Hispanic ethnicity and worse PROs are factors associated with higher risk for malnutrition. Results from this work underscore the need of early nutritional interventions to prevent malnutrition and improve clinical outcomes.

Financial hardship and healthcare utilization among older cancer survivors with comorbidities.

349 Background: Financial burden among older cancer survivors (65y+) is understudied, particularly with regard to how comorbidities may affect financial burden and healthcare utilization despite Medicare eligibility. We assessed the relationship between financial hardship (FH), healthcare utilization, and comorbidities among cancer survivors. Methods: The University of Alabama at Birmingham tumor registry was used to identify patients diagnosed at ≥65y with lymphoma, breast, colorectal, prostate, or lung cancer types and received curative-intent treatment from 2000 to 2019. Patients were surveyed on FH, healthcare utilization, and comorbid conditions. FH was defined as having answered ‘Yes’ to experiencing material, psychological, or behavioral hardship in the past year. Visits to a primary care physician (PCP), oncologist, non-oncology specialist, or emergency department (ED) in the past 2 years were self-reported. A modified Common Terminology Criteria for Adverse Events (CTCAE) grading system captured 45 self-reported comorbidities. A CTCAE of 3 or 4 was considered severe. Multivariable models were used to determine the differences in risk of any FH between severe vs. non-severe CTCAE and to determine differences in healthcare utilization. All models were adjusted for age at survey completion, years from diagnosis to survey, sex, race, income, stage, distance travelled to medical center. Results: Among the 759 survivors included, median age was 77 (IQR=73-82), a majority identified as White (82%), half were female (53%) and a third reported annual income of less than 20,000 (32%). Breast (33%) was the most common cancer type followed by prostate (26%), lung (17%), colorectal (15%), and lymph (9%). Moderate or Severe comorbidities were reported by 46% of participants. FH was most commonly associated with coronary heart disease (18-47%), chronic obstructive pulmonary disease (20-57%), and myocardial infarction (25-60%) across all cancer types. Overall, patients with severe comorbidities had a higher risk of any FH (RR, 1.50; 95%CI, 1.15, 1.97), ED visits (IRR, 2.20; 95%CI, 1.22, 3.95), specialists (IRR, 1.52; 95%CI, 1.25, 1.87), and PCP (IRR 1.15; 95%CI, 1.01, 1.30). Those with severe comorbidities and financial hardship had higher utilization of PCP (p &lt; 0.003), but not other types of utilization. Conclusions: Older patients with severe comorbidities were at increased risk of financial hardship while also utilizing healthcare facilities at a higher rate than those with fewer comorbidities. While those with severe comorbidities and financial hardship utilized their PCP more often, they did not utilize all healthcare facilities more than those with fewer comorbidities. Financial burden and high healthcare utilization remain after entering into cancer survivorship but is exacerbated by additional comorbid conditions.

Days Not at Home: Association of Vulnerability with Healthcare Utilization After Hospitalization for Heart Failure.

Heart failure (HF) hospitalizations are characterized by vulnerability in functioning and frequent post-discharge healthcare utilization in both acute and post-acute settings. To determine, in patients hospitalized for decompensated HF, the association of vulnerability with (1) detailed forms of post-discharge healthcare utilization, and (2) days spent away from home after initial hospital discharge. Secondary analysis of a prospective longitudinal cohort study from a single-center academic institution in the USA. Adults admitted with acute decompensated HF who were discharged alive. The Vulnerable Elders Survey 13 (VES-13) measured functional vulnerability at baseline. The primary outcome was the Highest Healthcare Utilization (HHU) 90days post-discharge, from the following ordered categories: at home, emergency room visit, skilled nursing facility stay, hospital readmission, or death. The secondary outcome was the proportion of days not at home (DNAH) within the first 90days. Analyses were performed using a partial proportional odds model with adjustment for demographics and health characteristics. A total of 806 patients were included with median age 65, interquartile range [IQR] 55-73years. Fewer than half (N = 345 [43%]) of patients remained alive and at home during 90-day follow-up. There were 286 [35%] hospital readmissions and 70 [8.7%] participants died. The median DNAH was 3 [IQR 0-16]. Increased vulnerability was associated with (1) HHU, (2) higher odds of utilizing healthcare or dying versus being at home alive 90days post-discharge (OR 1.81 [95% CI, 1.35, 2.42]), and (3) higher odds of DNAH in the first 90days (OR 1.55 [95% CI, 1.27, 1.89]). In this cohort of patients hospitalized for decompensated HF, vulnerability predicted higher levels of healthcare utilization, as well as total days not at home in the 90days following hospitalization. Vulnerability may have clinical applications to identify patients at greatest need for comprehensive, patient-centered discharge planning.

Care trajectories for musculoskeletal disorders following a new episode of low back pain

Abstract This study explored diverse care trajectories (CTs) for low back pain (LBP) and other musculoskeletal disorders (MSDs), over a 5-year period following a first episode of LBP. Based on Quebec's administrative health data from 2007 to 2011, this longitudinal cohort study involved 12,608 adults seeking health care for LBP. Using a new multidimensional state sequence analysis, we identified 6 distinct types of CTs. The most prevalent types 1, 2, and 3 (comprising 79.2%, 18.0%, and 21.7% of the cohort, respectively) exhibit rapid recovery and similar patterns of healthcare use over 5 years but differing in initial diagnoses: nonspecific LBP in type 1, trauma-related LBP in type 2 (mostly younger men and highest initial emergency consultation), and specific LBP in type 3. Types 4 to 6, representing smaller groups, show high healthcare utilization with comparable mixed LBP diagnoses at entry but distinctive subsequent care use patterns. Patients in types 4 and 6 (mainly older age groups and women) sought care for other MSDs from general practitioners or specialists, while middle-aged patients in type 5 experienced persistent nonspecific LBP with frequent general practitioner consultations over 5 years. The CTs typology revealed several key areas for improvement in nonpharmacological interventions, including the need to address possible inappropriate medical imaging and invasive interventions for older women with MSDs and the lack of ambulatory care access for younger patients with trauma-related LBP. Finally, results clearly highlighted poor access to rehabilitation physicians and rehabilitation services for all patients suffering from LBP and MSDs.

The extent and burden of high multimorbidity on older adults in the US: a descriptive analysis of Medicare beneficiaries

BackgroundThe impact of multimorbidity (≥ 2 chronic diseases) on the well-being of older adults is substantial but variable. The burden of multimorbidity varies by the number and kinds of conditions, and timing of onset. The impact varies by age, race, ethnicity, socioeconomic status, and health indicators. Large scale longitudinal surveys linked to medical claims provide unique opportunities to characterize this variability.MethodsWe analyzed Medicare-linked Health and Retirement Study data for respondents 65 and older with 3 or more years of fee-for-service coverage (n = 17,199; 2000–2016). We applied standardized claims algorithms for operationalizing 21 chronic diseases. We compared multimorbidity levels, demographics, and outcomes at baseline and over time and escalation to high multimorbidity levels (≥ 5 conditions).ResultsAt baseline, 51.2% had no multimorbidity, 36.5% had multimorbidity, and 12.4% had high multimorbidity. Loss of function, cognitive decline, and higher healthcare utilization were up to ten times more prevalent in the high multimorbidity group. Greater rates of high multimorbidity were seen among non-Hispanic Black and Hispanic groups, those with lower wealth, younger birth cohorts, and adults with obesity. Rates of transition to high multimorbidity varied greatly and was highest among Hispanic and respondents with lower education.ConclusionsThe development and progression of multimorbidity in old age is influenced by many factors. Higher levels of multimorbidity are associated with sociodemographic characteristics, suggesting possible mitigation strategies.

Health care utilization up to 11years after diagnosis among patients with a hematologic malignancy and its association with socioeconomic position.

To investigate health care utilization among patients with hematologic malignancies and its association with socioeconomic position (SEP) and compare health care utilization with a cancer-free population. Patients with aggressive lymphoma, indolent lymphoma, or multiple myeloma (MM), diagnosed between 1999-2010 and 2015-2019, participated in longitudinal patient-reported outcome research, up to 11years post-diagnosis. Questionnaires assessed health care utilization at the general practitioner (GP), medical specialist, and additional health care. SEP was based on education and income, categorized as low, medium, or high. Sociodemographic and clinical data were obtained from the Netherlands Cancer Registry. Mixed models and logistic regression analyses were performed. The study included 2319 patients (71% response rate), who completed on average five measurements. Patients with MM reported the highest health care utilization, both at the GP and medical specialist. Low SEP was associated with higher utilization at the GP (medium education β = - 0.72, p = 0.01; high education β = - 1.15, p < 0.001) and lower utilization of additional physical (OR = 1.7, p = 0.01) and psychosocial (OR = 1.5, p < 0.05) care, among all patients. For patients with MM, high SEP was also associated with higher utilization of health care at the medical specialist (high education β = 2.56, p < 0.05). Hematologic malignancy-related and SEP-related disparities in health care utilization were observed. To ensure equal access to health consumption, attention is needed for patients with a low SEP to provide better guidance in their cancer (survivorship) care. Improving health literacy and involving informal caregivers and nurse-led patient navigation may help reduce disparities in access to (additional) health care.

The impact of medication-assisted treatment for opioid use disorder on congestive heart failure outcomes

Congestive heart failure (CHF) and opioid use disorder (OUD) commonly coexist and are major contributors to high healthcare utilization in the United States. Medication assisted treatment (MAT; e.g., buprenorphine and methadone) reduces opioid-related mortality by about 50 %; yet little is known about how OUD treatment impacts CHF outcomes in patients with both CHF and OUD. We examined the impact of MAT (buprenorphine, methadone, and naltrexone) on CHF outcomes in patients diagnosed with OUD and CHF, and which MAT (buprenorphine or methadone) medication is associated with the fewest CHF outcomes. A retrospective cohort study of patients 18 years or older diagnosed with both CHF and OUD was conducted using Optum's de-identified Clinformatics® Data Mart Database. Multivariate logistic regression modeling was used to compared patients who were prescribed MAT to those who were not. The primary outcomes were CHF hospitalizations and CHF emergency department visits. No significant differences in the primary outcomes between the MAT and non-MAT cohorts were observed. In conclusion, the lack of association of MAT with negative CHF outcomes suggest that life-saving MAT can be safely used for OUD treatment in the CHF setting.

Utilization of Healthcare Services in Patients with Chronic Diseases under 18 Years Old: Differences and Contributing Factors.

Pediatric patients with chronic conditions frequently have unmet care needs, make extensive use of healthcare services, and often encounter fragmented, non-centered care. This study aimed to analyze the differences in the utilization of primary care (PC) and hospital care (HC) services by these patients according to sex, age, and complexity and to identify associated factors. A cross-sectional study was conducted in a basic health area of Madrid, including patients under 18 years. Among these patients, 15.7% had ≥1 chronic disease, 54.1% were male, the average age was 9.5 years, 3.5% had complexity, and 11.3% had multimorbidity. The mean number of contacts/year with the healthcare system was 9.1, including 8.3 contacts/year with PC (4.9 with pediatricians and 1.9 with nurses) and 0.8 contacts/year with HC (0.8 in external consultations and 0.01 hospitalizations). The factors associated with PC utilization were complexity; female sex; European origin; and diseases like asthma, epilepsy, stroke, recurrent urinary infection, attention deficit hyperactivity disorder, and anxiety, while older age was negatively associated. Thyroid disorders were significantly associated with HC utilization. These findings could help guide the design of optimized pediatric patient-centered care approaches to coordinate care across healthcare services and reduce high healthcare utilization, therefore improving the healthcare outcomes and quality of life for these patients.