Costs Associated With Multimorbidity Among VA Patients

Yoon, Jean; Zulman, Donna M.; Scott, Jennifer Y.; Maciejewski, Matthew L.

doi:10.1097/mlr.0000000000000061

Cited by 104 publications

(102 citation statements)

References 6 publications

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“…24,25 As a result, clinically meaningful evaluations of multimorbidity need to consider the specific qualities of individual conditions, as well the qualities of common condition dyads and triads. 9,26,27 While multimorbidity generally refers to the presence of multiple clinical conditions, there is also growing recognition that a multitude of patient-level factors independent of specific comorbid conditions may complicate care and affect outcomes for multimorbid patients. 10,28,29 For example, Safford et al proposed a conceptual approach to complex patients that involves interactions between biological, socioeconomic, cultural, environmental, and behavioral forces as health determinants.…”

Section: Definition Of Multimorbiditymentioning

confidence: 99%

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

et al. 2013

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Multimorbidity-the presence of multiple chronic conditions in a patient-has a profound impact on health, health care utilization, and associated costs. Definitions of multimorbidity in clinical care and research have evolved over time, initially focusing on a patient's number of comorbidities and the associated magnitude of required care processes, and later recognizing the potential influence of comorbidity characteristics on patient care and outcomes. In this article, we review the relationship between multimorbidity and quality of care, and discuss how this relationship may be mediated by the degree to which conditions interact with one another to generate clinical complexity (comorbidity interrelatedness). Drawing on established theoretical frameworks from cognitive engineering and biomedical informatics, we describe how interactions among conditions result in clinical complexity and may affect quality of care. We discuss how this comorbidity interrelatedness influences the value of existing quality guidelines and performance metrics, and describe opportunities to quantify this construct using data widely available through electronic health records. Incorporating comorbidity interrelatedness into conceptualizations of multimorbidity has the potential to enhance clinical and research efforts that aim to improve care for patients with multiple chronic conditions.

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Section: Definition Of Multimorbiditymentioning

confidence: 99%

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

et al. 2013

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“…1 The positive association between the number of conditions and health expenditures and utilization is well established. 2–4 Less known is the relationship between specific combinations of conditions and resource use. 5 It is highly likely, however, that different combinations of conditions affect expenditures differently.…”

Section: Introductionmentioning

confidence: 99%

Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization

et al. 2017

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Background Multimorbidity affects the majority of elderly adults and is associated with higher health costs and utilization, but how specific patterns of morbidity influence resource use is less understood. Objective To identify specific combinations of chronic conditions, functional limitations, and geriatric syndromes associated with direct medical costs and inpatient utilization. Design Retrospective cohort study using the Health and Retirement Study (2008–2010) linked to Medicare claims. Analysis used machine learning techniques: classification and regression trees (CART) and random forest. Subjects A population-based sample of 5,771 Medicare-enrolled adults age 65 and older in the United States. Measures Main covariates: self-reported chronic conditions (measured as none, mild, or severe), geriatric syndromes, and functional limitations. Secondary covariates: demographic, social, economic, behavioral, and health status measures. Outcomes: Medicare expenditures in the top quartile and inpatient utilization. Results Median annual expenditures were $4,354, and 41% were hospitalized within two-years. The tree model shows some notable combinations: 64% of those with self-rated poor health plus ADL and IADL disabilities had expenditures in the top quartile. Inpatient utilization was highest (70%) in those age 77 – 83 with mild to severe heart disease plus mild to severe diabetes. Functional limitations were more important than many chronic diseases in explaining resource use. Conclusions The multimorbid population is heterogeneous and there is considerable variation in how specific combinations of morbidity influence resource use. Modeling the conjoint effects of chronic conditions, functional limitations, and geriatric syndromes can advance understanding of groups at greatest risk and inform targeted tailored interventions aimed at cost-containment.

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“…There is a wealth of data describing high-prevalence, high-impact multimorbidity among Veterans in general [21][22][23]. There is also a wealth of data describing comorbidities among Veterans with overweight/obesity, such as hypertension (HTN), type 2 diabetes, hypercholesterolemia, and heart disease [7,24], as well as alcohol and drug use disorders, depression, and posttraumatic stress disorder (PTSD) [24].…”

Section: Introductionmentioning

confidence: 99%

Prevalence and correlates of painful conditions and multimorbidity in national sample of overweight/obese Veterans

Higgins

Buta²,

Dorflinger³

et al. 2016

J Rehabil Res Dev

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Abstract-Chronic pain and overweight/obesity are prevalent public health concerns and occur at particularly high rates among Veterans. This study examined the prevalence and correlates of two common painful conditions (back pain and arthritis/ joint pain) among overweight/obese Veterans in Veterans Health Administration (VHA) care. Participants (N = 45,477) completed the MOVE!23, a survey intended to tailor treatment for Veterans in VHA's MOVE! weight-management program. Overall, 72% of the sample reported painful conditions, with 10% reporting back pain, 26% reporting arthritis/joint pain, and 35% reporting both. We used multinomial logistic regression with "no pain" as the reference category to examine the association between painful conditions and participant characteristics. After multivariable adjustment, female Veterans had higher odds of reporting arthritis/joint pain and combined back and arthritis/ joint pain than no pain. Participants with higher body mass index had higher odds of reporting arthritis/joint pain and both back and arthritis/joint pain. The likelihood of painful conditions was higher in Veterans with comorbidities (hypertension, hyperlipidemia, lung disease, depression, anxiety, or posttraumatic stress disorder) and generally increased with the number of comorbidities reported (i.e., 5 or more). Overweight/obese Veterans frequently report painful conditions and, among those with pain, often have multiple comorbidities. These factors may increase the complexity of clinical management and necessitate refinements to weight-management programs.

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Costs Associated With Multimorbidity Among VA Patients

Cited by 104 publications

References 6 publications

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

Quality of Care for Patients with Multiple Chronic Conditions: The Role of Comorbidity Interrelatedness

Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization

Prevalence and correlates of painful conditions and multimorbidity in national sample of overweight/obese Veterans

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