Older adults experience a higher prevalence of multiple chronic conditions (MCCs). Establishing the presence and pattern of MCCs in individuals or populations is important for healthcare delivery, ...research, and policy. This report describes four emerging approaches and discusses their potential applications for enhancing assessment, treatment, and policy for the aging population. The National Institutes of Health convened a 2‐day panel workshop of experts in 2018. Four emerging models were identified by the panel, including classification and regression tree (CART), qualifying comorbidity sets (QCS), the multimorbidity index (MMI), and the application of omics to network medicine. Future research into models of multiple chronic condition assessment may improve understanding of the epidemiology, diagnosis, and treatment of older persons.
Raver et al found that the number of chronic conditions was not associated with disenrollment from Medicare Advantage (MA) to medicare fee-for-service (FFS) or from FFS to MA between 2010 and 2019. ...Burke uses their study findings to discuss the MA program as a whole and raises concern that some individuals may not completely understand MA plans' utilization management tools and subsequently find it difficult to switch to FFS because they cannot find a generous Medigap policy at an affordable price. As the MA program is rapidly expanding among Medicare beneficiaries, Burke's concerns are valid. However, their study did not examine any of the issues Burke raises and never intended to. In an unbiased way, they reported factual trends in Medicare enrollment patterns, indicating that MA disenrollment has decreased over time, including among those with multiple chronic conditions.
IMPORTANCE: Medically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this ...patient population have had limited success to date. OBJECTIVE: To define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters. DESIGN, SETTING, AND PARTICIPANTS: This cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles. MAIN OUTCOMES AND MEASURES: Complex patient profiles, 1-year health care utilization, and mortality outcomes by profile. RESULTS: The analysis included 104 869 individuals representing 3.3% of the adult population (mean SD age, 70.7 14.5 years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 95% CI, 7.1-8.8, P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management. CONCLUSIONS AND RELEVANCE: The findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.
Debate continues on how to measure and weight diseases in multimorbidity. We quantified the association of a broad range of chronic diseases with physical health-related qualify of life and used ...these weights to develop and validate a multimorbidity weighted index (MWI). Community-dwelling adults in 3 national, prospective studies-the Nurses' Health Study (n = 121,701), Nurses' Health Study II (n = 116,686), and Health Professionals Follow-up Study (n = 51,529)-reported physician-diagnosed diseases and completed the Short Form 36 physical functioning (PF) scale over multiple survey cycles between 1992 and 2008. Mixed models were used to obtain regression coefficients for the impact of 98 morbid conditions on PF. The MWI was formed by weighting conditions by these coefficients and was validated through bootstrapping. The final sample included 612,592 observations from 216,890 participants (PF mean score = 46.5 (standard deviation, 11)). The association between diseases and PF varied severalfold (median, -1.4; range, -10.6 to 0.8). End-stage organ diseases were associated with the greatest reduction in PF. The mean MWI score was 4.8 (median, 3.7; range, 0-53), and the mean number of comorbid conditions was 3.3 (median, 2.8; range, 0-34). This validated MWI weights diseases by severity using PF, a patient-centered outcome. These results suggest that simple disease count is unlikely to capture the full impact of multimorbidity on health-related quality of life, and that the MWI is feasible and readily implemented.
The prevalence of multiple chronic conditions (MCC) among older persons is increasing worldwide and is associated with poor health status and high rates of healthcare utilization and costs. Current ...health and social services are not addressing the complex needs of this group or their family caregivers. A better understanding of the experience of MCC from multiple perspectives is needed to improve the approach to care for this vulnerable group. However, the experience of MCC has not been explored with a broad sample of community-living older adults, family caregivers and healthcare providers. The purpose of this study was to explore the experience of managing MCC in the community from the perspectives of older adults with MCC, family caregivers and healthcare providers working in a variety of settings.
Using Thorne's interpretive description approach, semi-structured interviews (n = 130) were conducted in two Canadian provinces with 41 community-living older adults (aged 65 years and older) with three or more chronic conditions, 47 family caregivers (aged 18 years and older), and 42 healthcare providers working in various community settings. Healthcare providers represented various disciplines and settings. Interview transcripts were analyzed using Thorne's interpretive description approach.
Participants described the experience of managing MCC as: (a) overwhelming, draining and complicated, (b) organizing pills and appointments, (c) being split into pieces, (d) doing what the doctor says, (e) relying on family and friends, and (f) having difficulty getting outside help. These themes resonated with the emotional impact of MCC for all three groups of participants and the heavy reliance on family caregivers to support care in the home.
The experience of managing MCC in the community was one of high complexity, where there was a large gap between the needs of older adults and caregivers and the ability of health and social care systems to meet those needs. Healthcare for MCC was experienced as piecemeal and fragmented with little focus on the person and family as a whole. These findings provide a foundation for the design of care processes to more optimally address the needs-service gap that is integral to the experience of managing MCC.
The number of older adults is increasing worldwide, including in Asian countries. Various problems associated with medical care for older adults are being highlighted in aging societies. As the ...number of chronic diseases increases with age, older adults are more likely to have multiple chronic diseases simultaneously (multimorbidity). Multimorbidity results in poor health-related outcomes, leading to increased use and cost of healthcare. Above all, it leads to deterioration in older adults' quality of life. However, it is unclear whether any medical interventions are effective for multimorbidity, which means medical practitioners currently offer medical care "in the dark." It is therefore necessary for researchers and medical professionals involved in geriatric medicine to establish ways to manage multimorbidity among older adults. This means that the development of research in this field is essential. Geriatr Gerontol Int 2019; 19: 699-704.
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