Clustering and Healthcare Costs With Multiple Chronic Conditions in a US Study

Lipid-Derived Biomarkers as Therapeutic Targets for Chronic Coronary Syndrome and Ischemic Stroke: An Updated Narrative Review

The incidence and prevalence of cardiac and cerebrovascular diseases are constantly increasing, with chronic coronary syndrome and ischemic stroke as the leading causes of morbidity and mortality worldwide. According to current knowledge, the heart-brain axis is more than a theoretical concept, with many common pathophysiological mechanisms involved in the onset and evolution of both coronary and cerebral ischemia. Moreover, the focus is on the prevention and early intervention of risk factors in searching for targeted and personalized medical treatment. In this context, this narrative review aims to offer, in a didactic and practice-oriented manner, an up-to-date overview of the role played by lipid-derived biomarkers (from low-density lipoprotein cholesterol to oxylipin and apolipoproteins) in chronic coronary syndrome and ischemic stroke. Firstly, the authors highlight, via relevant epidemiological data, the significant burden of chronic coronary syndrome and ischemic stroke in the general population, thus explaining the need for updated information on this topic. Subsequently, the most important lipid-derived biomarkers and their multiple roles in the pathogenesis of these two disorders are listed. Currently available and experimental targeted therapies based on these lipid-derived biomarkers are presented in the final part of this paper, representing this manuscript's original and novel input.

Learning prevalent patterns of co-morbidities in multichronic patients using population-based healthcare data

The prevalence of longstanding chronic diseases has increased worldwide, along with the average age of the population. As a result, an increasing number of people is affected by two or more chronic conditions simultaneously, and healthcare systems are facing the challenge of treating multimorbid patients effectively. Current therapeutic strategies are suited to manage each chronic condition separately, without considering the whole clinical condition of the patient. This approach may lead to suboptimal clinical outcomes and system inefficiencies (e.g. redundant diagnostic tests and inadequate drug prescriptions). We develop a novel methodology based on the joint implementation of data reduction and clustering algorithms to identify patterns of chronic diseases that are likely to co-occur in multichronic patients. We analyse data from a large adult population of multichronic patients living in Tuscany (Italy) in 2019 which was stratified by sex and age classes. Results demonstrate that (i) cardio-metabolic, endocrine, and neuro-degenerative diseases represent a stable pattern of multimorbidity, and (ii) disease prevalence and clustering vary across ages and between women and men. Identifying the most common multichronic profiles can help tailor medical protocols to patients' needs and reduce costs. Furthermore, analysing temporal patterns of disease can refine risk predictions for evolutive chronic conditions.

Multimorbidity clusters in adults 50 years or older with and without a history of cancer: National Health Interview Survey, 2018

BACKGROUND

Multimorbidity is increasing among adults in the United States. Yet limited research has examined multimorbidity clusters in persons aged 50 years and older with and without a history of cancer. An increased understanding of multimorbidity clusters may improve the cancer survivorship experience for survivors with multimorbidity.

METHODS

We identified 7580 adults aged 50 years and older with 2 or more diseases-including 811 adults with a history of primary breast, colorectal, cervical, prostate, or lung cancer-from the 2018 National Health Interview Survey. Exploratory factor analysis identified clusters of multimorbidity among cancer survivors and individuals without a history of cancer (controls). Frequency tables and chi-square tests were performed to determine overall differences in sociodemographic characteristics, health-related characteristics, and multimorbidity between groups.

RESULTS

Cancer survivors reported a higher prevalence of having 4 or more diseases compared to controls (57% and 38%, respectively). Our analysis identified 6 clusters for cancer survivors and 4 clusters for controls. Three clusters (pulmonary, cardiac, and liver) included the same diseases for cancer survivors and controls.

CONCLUSIONS

Diseases clustered differently across adults ≥ 50 years of age with and without a history of cancer. Findings from this study may be used to inform clinical care, increase the development and dissemination of multilevel public health interventions, escalate system improvements, and initiate innovative policy reform.

From electronic health records to clinical management systems: how the digital transformation can support healthcare services

Healthcare systems worldwide are currently undergoing significant transformations in response to increasing costs, a shortage of healthcare professionals and the growing complexity of medical needs among the population. Value-based healthcare reimbursement systems are emerging as an attempt to incentivize patient-centricity and cost containment. From a technological perspective, the transition to digitalized services is intended to support these transformations. A Health Information System (HIS) is a technological solution designed to govern the data flow generated and consumed by healthcare professionals and administrative staff during the delivery of healthcare services. However, the exponential growth of digital capabilities and applied advanced analytics has expanded their traditional functionalities and brought the promise of automating administrative procedures and simple repetitive tasks, while enhancing the efficiency and outcomes of healthcare services by incorporating decision support tools for clinical management. The future of HIS is headed towards modular architectures that can facilitate implementation and adaptation to different environments and systems, as well as the integration of various tools, such as artificial intelligence (AI) models, in a seamless way. As an example, we present the experience and future developments of the European Clinical Database (EuCliD®). EuCliD is a multilingual HIS used by 20 000 nurses and physicians on a daily basis to manage 105 000 patients treated in 1100 clinics in 43 different countries. EuCliD encompasses patients' follow-up, automatic reporting and mobile applications while enabling efficient management of clinical processes. It is also designed to incorporate multiagent systems to automate repetitive tasks, AI modules and advanced dynamic dashboards.

Racial differences in healthcare expenditures for prevalent multimorbidity combinations in the USA: a cross-sectional study

BACKGROUND

We aimed to model total charges for the most prevalent multimorbidity combinations in the USA and assess model accuracy across Asian/Pacific Islander, African American, Biracial, Caucasian, Hispanic, and Native American populations.

METHODS

We used Cerner HealthFacts data from 2016 to 2017 to model the cost of previously identified prevalent multimorbidity combinations among 38 major diagnostic categories for cohorts stratified by age (45-64 and 65 +). Examples of prevalent multimorbidity combinations include lipedema with hypertension or hypertension with diabetes. We applied generalized linear models (GLM) with gamma distribution and log link function to total charges for all cohorts and assessed model accuracy using residual analysis. In addition to 38 major diagnostic categories, our adjusted model incorporated demographic, BMI, hospital, and census division information.

RESULTS

The mean ages were 55 (45-64 cohort, N = 333,094) and 75 (65 + cohort, N = 327,260), respectively. We found actual total charges to be highest for African Americans (means $78,544 [45-64], $176,274 [65 +]) and lowest for Hispanics (means $29,597 [45-64], $66,911 [65 +]). African American race was strongly predictive of higher costs (p < 0.05 [45-64]; p < 0.05 [65 +]). Each total charge model had a good fit. With African American as the index race, only Asian/Pacific Islander and Biracial were non-significant in the 45-64 cohort and Biracial in the 65 + cohort. Mean residuals were lowest for Hispanics in both cohorts, highest in African Americans for the 45-64 cohort, and highest in Caucasians for the 65 + cohort. Model accuracy varied substantially by race when multimorbidity grouping was considered. For example, costs were markedly overestimated for 65 + Caucasians with multimorbidity combinations that included heart disease (e.g., hypertension + heart disease and lipidemia + hypertension + heart disease). Additionally, model residuals varied by age/obesity status. For instance, model estimates for Hispanic patients were highly underestimated for most multimorbidity combinations in the 65 + with obesity cohort compared with other age/obesity status groupings.

CONCLUSIONS

Our finding demonstrates the need for more robust models to ensure the healthcare system can better serve all populations. Future cost modeling efforts will likely benefit from factoring in multimorbidity type stratified by race/ethnicity and age/obesity status.

Multimorbidity patterns in the working age population with the top 10% medical cost from exhaustive insurance claims data of Japan Health Insurance Association

Although the economic burden of multimorbidity is a growing global challenge, the contribution of multimorbidity in patients with high medical expenses remains unclear. We aimed to clarify multimorbidity patterns that have a large impact on medical costs in the Japanese population. We conducted a cross-sectional study using health insurance claims data provided by the Japan Health Insurance Association. Latent class analysis (LCA) was used to identify multimorbidity patterns in 1,698,902 patients who had the top 10% of total medical costs in 2015. The present parameters of the LCA model included 68 disease labels that were frequent among this population. Moreover, subgroup analysis was performed using a generalized linear model (GLM) to assess the factors influencing annual medical cost and 5-year mortality. As a result of obtaining 30 latent classes, the kidney disease class required the most expensive cost per capita, while the highest portion (28.6%) of the total medical cost was spent on metabolic syndrome (MetS) classes, which were characterized by hypertension, dyslipidemia, and type 2 diabetes. GLM applied to patients with MetS classes showed that cardiovascular diseases or complex conditions, including malignancies, were powerful determinants of medical cost and mortality. MetS was classified into 7 classes based on real-world data and accounts for a large portion of the total medical costs. MetS classes with cardiovascular diseases or complex conditions, including malignancies, have a significant impact on medical costs and mortality.

Investigating the Association between Sociodemographic Factors and Chronic Disease Risk in Adults Aged 50 and above in the Hungarian Population

Chronic diseases are a major cause of mortality and morbidity globally, with non-communicable diseases being responsible for most deaths. Older adults are at a higher risk of developing chronic diseases due to various sociodemographic and lifestyle factors such as age, sex, income, education, employment, place of residence, dietary supplementation, tobacco use, and alcohol consumption. Understanding the relationship between these factors and chronic diseases is crucial for identifying vulnerable populations and improving healthcare delivery. Through both an online and an interview-based survey, this cross-sectional study aimed to examine these associations, focusing on adults aged 50 and above, with the goal of identifying potential areas for intervention and prevention. The study found that gender, area of residence, education status, employment status, nutritional supplementation, body mass index (BMI), alcohol usage, and age are associated with the risk of chronic disease, cardiovascular disease, and diabetes. Female gender, higher educational level, employment, normal BMI, and younger age were found to be protective factors, while living in rural areas, alcohol consumption, and older age were identified as risk factors. The study recommends targeted interventions and improved access to healthcare to reduce risk factors and enhance healthcare delivery for better health outcomes.

Optimizing Multidisciplinary Care of Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus

Diabetes is the leading cause of chronic kidney disease (CKD), a condition associated with significant morbidity and mortality. As these patients have a high risk of developing cardiovascular disease and end-stage kidney disease, there is a need for early detection and early initiation of appropriate therapeutic interventions that slow disease progression and prevent adverse outcomes. Due to the complex nature of diabetes and CKD management, a holistic, patient-centered, collaborative care approach delivered by a coordinated multidisciplinary team (ideally including a clinical pharmacist as part of a comprehensive medication management program) is needed. In this review, we discuss the barriers to effective care, the current multidisciplinary approach used for CKD prevention and treatment, and the potential ways that the multidisciplinary management of CKD associated with type 2 diabetes mellitus can be refined to improve patient outcomes.

Association between patient complexity and healthcare costs in primary care on a Japanese island: a cross-sectional study

OBJECTIVES

This study aimed to elucidate the relationship between patient complexity and healthcare costs in a primary care setting on a Japanese island.

DESIGN

Cross-sectional study.

SETTING

Tarama Clinic, Okinawa Miyako Hospital, on Tarama Island, Okinawa Prefecture, Japan.

PARTICIPANTS

Patients who visited Tarama Clinic from 1 April 2018 to 30 June 2018, were aged 20 years or above, were resident in Tarama Village and had decision-making capacity.

OUTCOME MEASURES

Patient complexity scored using Patient Centred Assessment Method (PCAM), healthcare costs per person per year/visit and participant characteristics.

RESULTS

We included 355 study participants. The means (SD) of the total PCAM scores and healthcare costs per person per year/visit were 21.4 (5.7) and 1056.4 (952.7)/125.7 (86.7) in US dollars, respectively. Spearman's rank correlation coefficients between the total PCAM scores and healthcare costs per person per year/visit were 0.33 and 0.28 (p values <0.0001 and <0.0001), respectively. The healthcare costs per person tended to be relatively low in the patient groups with the highest complexity. In the groups, the proportion of those with psychological conditions tended to be higher and those with cardiovascular diseases tended to be lower than in the other groups. Multiple regression analysis showed that total PCAM scores were associated with healthcare costs per person per year/visit, which were log-transformed: the regression coefficients were 3.87×10^-2 and 2.34×10^-2, respectively; the p values were <0.001 and <0.001, respectively.

CONCLUSIONS

This study clarified the association between patient complexity and healthcare costs in a primary care setting on a Japanese island. We found that such costs tended to be relatively low in patient groups with the highest complexity. In primary care, healthcare costs probably do not accurately reflect the value of services provided by medical institutions; it may be essential to introduce a system that provides incentives for problem-solving approaches to social issues.

Effectiveness and Safety of Direct Oral Anticoagulants Among Patients with Non-valvular Atrial Fibrillation and Multimorbidity

INTRODUCTION

In the USA, there is a steady rise of atrial fibrillation due to the aging population with increased morbidity. This study evaluated the risk of stroke/systemic embolism (S/SE) and major bleeding (MB) among elderly patients with non-valvular atrial fibrillation (NVAF) and multimorbidity prescribed direct oral anticoagulants (DOACs).

METHODS

Using the CMS Medicare database, a retrospective observational study of adult patients with NVAF and multimorbidity who initiated apixaban, dabigatran, or rivaroxaban from January 1, 2012 to December 31, 2017 was conducted. High multimorbidity was classified as having ≥ 6 comorbidities. Cox proportional hazard models were used to evaluate the hazard ratios of S/SE and MB among three 1:1 propensity score matched DOAC cohorts. All-cause healthcare costs were estimated using generalized linear models.

RESULTS

Overall 36% of the NVAF study population had high multimorbidity, forming three propensity score matched (PSM) cohorts: 12,511 apixaban-dabigatran, 60,287 apixaban-rivaroxaban, and 12,567 dabigatran-rivaroxaban patients. Apixaban was associated with a lower risk of stroke/SE and MB when compared with dabigatran and rivaroxaban. Dabigatran had a lower risk of stroke/SE and a similar risk of MB when compared with rivaroxaban. Compared to rivaroxaban, apixaban patients incurred lower all-cause healthcare costs, and dabigatran patients incurred similar all-cause healthcare costs. Compared to dabigatran, apixaban patients incurred similar all-cause healthcare costs.

CONCLUSION

Patients with NVAF and ≥ 6 comorbid conditions had significantly different risks for stroke/SE and MB when comparing DOACs to DOACs, and different healthcare expenses. This study's results may be useful for evaluating the risk-benefit ratio of DOAC use in patients with NVAF and multimorbidity.

A Systematic Review of Chronic Diseases and Their Prevalence Among the Population of Northern Borders Province (NBP) in Saudi Arabia

Estimation of the prevalence of chronic conditions is pivotal to effective healthcare planning and management. Therefore, our objective was to systemically review previous literature about the prevalence of chronic diseases among residents of Northern Borders Province (NBP) in Saudi Arabia. The electronic search has been done using scientific databases (PubMed, Ebsco, SciFinder, and Web of Science) and search engines up to September 2021. The following main key terms: chronic disease OR chronic conditions AND prevalence AND Northern Borders Province OR Northern Borders AND Saudi Arabia were applied. Other related terms with a more specific search were done with names of the main cities in the province and the most common diseases in Saudi Arabia. Duplicates were removed electronically by Endnote and manually. Extracted data were tabulated in the literature matrix. The risk of bias and quality of included studies were assessed using the "Strengthening the Reporting of Observational Studies in Epidemiology" (STROBE) checklist. Out of 63 observational studies that were assessed for eligibility, 21 observational studies were included to synthesize the evidence. These studies were conducted on Arar (n=16), Turaif (n=2), and Rafha (n=1), while the remaining were national studies in which NBP was one of the included regions (n=2). The most frequently studied diseases were diabetes (4 records), psychological diseases (4 records), and obesity (3 records). The most prevalent disease was gastroesophageal reflux disease (GERD), with an estimated prevalence of 61% among adults in Arar city. In conclusion, although some research is conducted about chronic diseases somewhere in NBP, further studies are needed to study chronic diseases using a representative sample of the whole NBP population.

Economic Impacts of Cardiovascular Diseases: An Econometric Evaluation in Turkey

Background

The study aimed to determine the impact of the burden of cardiovascular diseases on Gross Domestic Product (GDP) in Turkey.

Methods

GDP was taken as the dependent variable and the burden of cardiovascular diseases was taken as the independent variable. The variables were analyzed within the frame of Panel Data Analysis.

Results

Significant relationships were found between GDP and burden of cardiovascular diseases. The unidirectional Granger causality relationship was determined from burden of cardiovascular diseases to GDP and revealed that they acted together in the long term. The analysis that made with using econometric regression models revealed that generally 1 unit increased in per capita of cardiovascular diseases decreased GDP by between 477651.8 - 624485.6 units (PPP$).

Conclusion

The empirical results of the study revealed that the cardiovascular disease burden was one of the reasons for the decrease in GDP and their economic effects would continue in the long term in Turkey. From this perspective establishing and implementing policies to improve the burden of cardiovascular diseases in Turkey could be an important approach for the economic development.

The association between social care expenditure and multiple-long term conditions: A population-based area-level analysis

Background

Multiple long-term health conditions (MLTCs) are common and increasing among older people, yet there is limited understanding of their prevalence and association with social care expenditure.

Aim

To estimate the prevalence of MTLCs and association with English social care expenditure.

Methods

Our study population included those aged ≥ 65 who died in England in the year 2018 with any of the following long-term conditions recorded on their death certificate: diabetes; cardiovascular diseases (CVDs) including hypertension; dementia; stroke; respiratory; and chronic kidney diseases (CKDs). Prevalence was based on the proportion of death reported for older people with MTLCs (≥ 2) in each of the 152 English Local Authorities (LAs). Ordinary least square regression (OLS) was used to assess the relationship between prevalence of MTLCs and adult social care expenditure, adjusting for LA characteristics.

Results

Of the 409551 deaths reported, 19.9% (n = 81395) had ≥ 2 MTLCs, of which the combination of CVDs-diabetes was the most prevalent. Hospitals were the leading place of death for those with MTLCs. Results from the OLS regression model showed that an increased prevalence of MLTCs is associated with higher LA social care expenditure. A percentage point increase in prevalence of MLTCs is associated with an increase of about £8.13 in per capita LA social care expenditure.

Conclusion

Our findings suggest that the increased prevalence of MTLCs is associated with increased LA social care expenditure. It is important for future studies to further explore the mechanisms or link between LA social care expenditure and the prevalence of MTLCs.

Inequity in the healthcare utilization among latent classes of elderly people with chronic diseases and decomposition analysis in China

BACKGROUND

Studies have shown chronic disease-based healthcare utilization inequity is common. Hence, exploring this issue can help in establishing targeted measures and protecting the rights and interests of vulnerable groups. Against this background, the purpose of this study is to explore the latent classification of elderly patients with chronic disease and compare healthcare utilization inequity among latent classes.

METHODS

This study used the data of 7243 elderly patient with chronic diseases collected from the China Health and Retirement Longitudinal Study in 2018. Latent class analysis was used to classify the patients with chronic diseases, and analysis of variance and [Formula: see text] tests were utilized to test the differences in characteristics among latent classes. Healthcare utilization inequity was measured based on the concentration index (CI), and the CI was decomposed to compare the horizontal index of healthcare utilization among the latent classes.

RESULTS

The patients with chronic diseases were divided into five latent classes, namely, the musculoskeletal system, hypertension, respiratory system, digestive system and cardiovascular system groups. Statistically significant differences in social demographic characteristics were observed among the five latent classes (P &lt; 0.05). A pro-rich healthcare utilization inequity for all respondents was observed (outpatient CI = 0.080, inpatient CI = 0.135), and a similar phenomenon in latent classes was found except for the musculoskeletal system group in outpatient visits (CI = -0.037). The digestive system group had the worst equity (outpatient CI = 0.197, inpatient CI = 0.157) and the respiratory system group had the best (outpatient CI = 0.001, inpatient CI = 0.086). After balancing the influence of health need factors, healthcare utilization inequity was almost alleviated. Furthermore, for all respondents, the contribution of health need factors (65.227% for outpatient and 81.593% for inpatient) was larger than that of socioeconomic factors (-21.774% for outpatient and 23.707 for inpatient), and self-rated health status was the greatest contributor (57.167% for outpatient and 79.399% for inpatient). The characteristics were shown in latent classes.

CONCLUSIONS

Healthcare utilization inequity still exists in elderly patients with chronic diseases, and the specific performances of inequity vary among latent classes. Moreover, self-rated health status plays an important role in healthcare utilization inequity. Providing financial support to low-income patients with certain chronic diseases, focusing on their physical and mental feelings and guiding them to evaluate their health status correctly could be essential for alleviating healthcare utilization inequity among elderly patients with chronic diseases.

Eviction, post-traumatic stress, and emergency department use among low-income individuals in New Haven, CT

We sought to examine whether and how landlord-related forced moves (inclusive of, but not limited to, legal eviction) were associated with emergency department (ED) use over time. We used survey data collected between 2017 and 2019 among 283 low-income participants in New Haven, CT to examine whether experiencing a legal eviction or other landlord-related forced move (T₀) was associated with increased odds of ED use 6 months (T₁) and 12 months (T₂) later. We conducted bootstrapped mediation analyses to examine indirect effects of post-traumatic stress symptoms. One-fifth of participants (n = 61) reported a recent forced move at baseline (T₀); half of these were legally evicted. Landlord-related forced moves were associated with ED use at T₁ (AOR = 2.06, 95 % CI: 1.04-4.06) and T₂ (AOR = 3.05, 95 % CI: 1.59-5.88). After adjustment for sociodemographic factors and other health-related confounders, legal eviction was not significantly associated with ED use at T₁ (AOR = 1.61, 95 % CI: 0.68-3.81), but was significantly associated with ED use at T₂ (AOR = 3.58, 95 % CI: 1.58-8.10). Post-traumatic stress symptoms accounted for 15.1% of forced moves' association with ED use (p <.05). Landlord-related forced moves are positively associated with subsequent ED use, and post-traumatic stress symptoms are one factor that may help explain this association. Structural interventions that promote housing stability are needed to advance health equity, and they may also help to reduce preventable ED use. Such interventions are imperative in the context of the COVID-19 pandemic, which has strained health system capacity and exacerbated housing instability for many low-income renters. Results underscore the relevance of trauma-informed care and integrated care management to clinical practice in emergency settings.

Pharmacological Adherence Behavior Changes during COVID-19 Outbreak in a Portugal Patient Cohort

Concerns, behaviours, and beliefs influence how people deal with COVID-19. Understanding the factors influencing adherence behaviour is of utmost importance to develop tailored interventions to increase adherence within this context. Hence, we aimed to understand how COVID-19 affected adherence behaviour in Portugal. A cross-sectional online survey was conducted between 1 March and 3 April 2021. Descriptive statistics were performed, as well as univariable and multivariable regression models. Of the 1202 participants, 476 who were taking at least one medication prescribed by the doctor were selected. Of these, 78.2% were female, and the mean age was 40.3 ± 17.9 years old. About 74.2% were classified as being highly adherent. During the pandemic, 8.2% of participants reported that their adherence improved, while 5.9% had worsened adherence results. Compared with being single, widowers were 3 times more prone to be less adherent (OR:3.390 [1.106–10.390], p = 0.033). Comorbid patients were 1.8 times (OR:1.824 [1.155–2.881], p = 0.010) more prone to be less adherent. Participants who reported that COVID-19 negatively impacted their adherence were 5.6 times more prone to be less adherent, compared with those who reported no changes (OR:5.576 [2.420–12.847], p < 0.001). None of the other variables showed to be significantly associated with pharmacological adherence.

Healthcare cost of patients with multiple chronic diseases in Singapore public primary care setting

INTRODUCTION

The rising prevalence of multiple chronic diseases is an important public health issue as it is associated with increased healthcare utilisation. This paper aimed to explore the annual per capita healthcare cost in primary care for patients with multiple chronic diseases (multimorbidity).

METHODS

This was a retrospective cohort study conducted in a cluster of public primary care clinics in Singapore. De-identified data from electronic medical records were extracted from July 2015 to June 2017. Only patients with at least 1 chronic disease were included in the study. Basic demographic data and healthcare cost were extracted. A list of 20 chronic diseases was considered for multimorbidity.

RESULTS

There were 254,377 patients in our study population, of whom 52.8% were female. The prevalence of multimorbidity was 62.4%. The median annual healthcare cost per capita for patients with multimorbidity was about twice the amount compared to those without multimorbidity (SGD683 versus SGD344). The greatest percentage increment in cost was when the number of chronic diseases increased from 2 to 3 (43.0%).

CONCLUSION

Multimorbidity is associated with higher healthcare cost in primary care. Since evidence for the optimal management of multimorbidity is still elusive, prevention or delay in the onset of multimorbidity in the general population is paramount.