Trajectories of multimorbidity: exploring patterns of multimorbidity in patients with more than ten chronic health problems in life course

Abstract

BackgroundPhysicians are frequently confronted with complex health situations of patients, but knowledge of intensive forms of multimorbidity and their development during life is lacking.This study explores patterns and trajectories of chronic health problems of patients with multimorbidity particularly those with more than ten conditions and type and variety of organ systems involved in these patterns during life.MethodLife time prevalence patterns of chronic health problems were determined in patients with illness trajectories accumulating more than ten chronic health problems during life as registered by general practitioners in the South of the Netherlands in the Registration Network Family Practices (RNH).ResultsOverall 4,560 subjects (5%) were registered with more than ten chronic health problems during their life (MM11+), accounting for 61,653 (20%) of the 302,808 registered health problems in the population (N = 87,837 subjects). More than 30% accumulates 4 or more chronic health conditions (MM4-5: 4–5 conditions (N = 14,199; 16.2%); MM6-10: 6–10 conditions (N = 14,365; 16.4%).Gastro-intestinal, cardiovascular, locomotor, respiratory and metabolic conditions occur more frequently in the MM11+ patients than in the other patients, while the nature and variety of body systems involved in lifetime accumulation of chronic health problem clusters is both generic and specific. Regarding chronic conditions afflicting multiple sites throughout the body, the number of neoplasms seems low (N = 3,592; 5.8%), but 2,461 (49%) of the 4,560 subjects have registered at least one neoplasm condition during life. A similar pattern is noted for inflammation (N = 3,537, 78%), infection (N = 2,451, 54%) and injury (N = 3,401, 75%).ConclusionThere are many challenges facing multimorbidity research, including the implementation of a longitudinal, life-time approach from a family practice perspective. The present study, although exploratory by nature, shows that both general and specific mechanisms characterize the development of multimorbidity trajectories. A small proportion of patients has a high number of chronic health problems (MM11+) and keeps adding health problems during life. However, GP’s need to realise that more than one third of their patients accumulate four or more chronic health problems (MM4-5 and MM6-10) during life.

A Biobehavioral Framework to Address the Emerging Challenge of Multimorbidity

“…This type of evidence provides a snapshot of the prevalence of pairings and triads of different diseases (4,30) but the developmental trajectories of these diseases are unclear (10, 18). The mapping of trajectories of emergence and succession of multiple morbidities has the potential to assess how close they are to each other with respect to pathogenic mechanisms (27).…”

“…Presence of one chronic disease is often associated with a greater than expected, subsequent occurrence of other disorders (10), [e.g., diabetes with the risk of colorectal cancer (11); melanoma with death from amyotrophic lateral sclerosis (12); depression with diabetes or coronary heart disease (13, 14)]. As these examples show, the co-occurrence of multiple diseases crosses organ and system divides (10).…”

“…As these examples show, the co-occurrence of multiple diseases crosses organ and system divides (10). Such clinical and epidemiological observations suggest a synergistic or activated process might underlie the emergence of multiple chronic conditions (15) that may have profound implications for research, treatment and health policy (16–18).…”

“…The U.S. Department of Health and Human Services designation, however, refers to both illnesses and “conditions” (e.g., “risk for falls” in the latter category) lasting a year or more and requiring ongoing medical attention and/or limit activities of daily living (24). We prefer multi-morbidity because of its focus on illness and because MCC implies a “snapshot” of the patient although in many cases one illness emerges prior to the others (10, 15). The phrase, “complex” or “complicated” patients has also been applied to multiple disease scenarios, but the ways that patients are complex or complicated is left ambiguous.…”

Value-Based Health Care Supported by Data Science

“…In fact, application of single-disease guidelines to patients with multimorbidity can increase treatment and self-management complexity, risk of interactions between guideline recommendations, potential adverse events, hospitalization and poorer health outcomes [32][33][34][35]. Consequently, quality measurement in the setting of multimorbidity is challenging-multimorbidity is not simply a count of conditions [36] and co-occurring conditions can be interrelated in a variety of ways [33], even in chronology [28,37]. Intelligent information systems, given reliable data, could better be able to handle the complexity and probabilistic nature of potential outcomes for patients with multimorbidity, and thereby measure care quality in a more nuanced manner representative of the population.…”