Comorbidity is associated with worse health outcomes, more complex clinical management, and increased health care costs. There is no agreement, however, on the meaning of the term, and related constructs, such as multimorbidity, morbidity burden, and patient complexity, are not well conceptualized. In this article, we review defi nitions of comorbidity and their relationship to related constructs. We show that the value of a given construct lies in its ability to explain a particular phenomenon of interest within the domains of (1) clinical care, (2) epidemiology, or (3) health services planning and fi nancing. Mechanisms that may underlie the coexistence of 2 or more conditions in a patient (direct causation, associated risk factors, heterogeneity, independence) are examined, and the implications for clinical care considered. We conclude that the more precise use of constructs, as proposed in this article, would lead to improved research into the phenomenon of ill health in clinical care, epidemiology, and health services.

IntroductionMultimorbidity is a major concern in primary care. Nevertheless, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. The aim of this study is to systematically review studies of the prevalence, patterns and determinants of multimorbidity in primary care.MethodsSystematic review of literature published between 1961 and 2013 and indexed in Ovid (CINAHL, PsychINFO, Medline and Embase) and Web of Knowledge. Studies were selected according to eligibility criteria of addressing prevalence, determinants, and patterns of multimorbidity and using a pretested proforma in primary care. The quality and risk of bias were assessed using STROBE criteria. Two researchers assessed the eligibility of studies for inclusion (Kappa  = 0.86).ResultsWe identified 39 eligible publications describing studies that included a total of 70,057,611 patients in 12 countries. The number of health conditions analysed per study ranged from 5 to 335, with multimorbidity prevalence ranging from 12.9% to 95.1%. All studies observed a significant positive association between multimorbidity and age (odds ratio [OR], 1.26 to 227.46), and lower socioeconomic status (OR, 1.20 to 1.91). Positive associations with female gender and mental disorders were also observed. The most frequent patterns of multimorbidity included osteoarthritis together with cardiovascular and/or metabolic conditions.ConclusionsWell-established determinants of multimorbidity include age, lower socioeconomic status and gender. The most prevalent conditions shape the patterns of multimorbidity. However, the limitations of the current evidence base means that further and better designed studies are needed to inform policy, research and clinical practice, with the goal of improving health-related quality of life for patients with multimorbidity. Standardization of the definition and assessment of multimorbidity is essential in order to better understand this phenomenon, and is a necessary immediate step.

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Methodological concerns limit the strength of inference regarding the impact of providing PRO information to clinicians. Results suggest great heterogeneity of impact; contexts and interventions that will yield important benefits remain to be clearly defined.

Multimorbidity is very common in primary care and in a system with strong gatekeeping is associated with high health care utilization and cost across the health care system. Interventions to address quality and cost associated with multimorbidity must focus on primary as well as secondary care.

PURPOSE Many patients consulting in primary care have multiple conditions (multimorbidity). Aims of this review were to identify measures of multimorbidity and morbidity burden suitable for use in research in primary care and community populations, and to investigate their validity in relation to anticipated associations with patient characteristics, process measures, and health outcomes.METHODS Studies were identifi ed using searches in MEDLINE and EMBASE from inception to December 2009 and bibliographies.RESULTS Included were 194 articles describing 17 different measures. Commonly used measures included disease counts (n = 98), Chronic Disease Score (CDS) / RxRisk (n = 17), Adjusted Clinical Groups (ACG) System (n = 25), the Charlson index (n = 38), the Cumulative Index Illness Rating Scale (CIRS; n = 10) and the Duke Severity of Illness Checklist (DUSOI; n = 6). Studies that compared measures suggest their predictive validity for the same outcome differs only slightly. Evidence is strongest for the ACG System, Charlson index, or disease counts in relation to care utilization; for the ACG System in relation to costs; for Charlson index in relation to mortality; and for disease counts or Charlson index in relation to quality of life. Simple counts of diseases or medications perform almost as well as complex measures in predicting most outcomes. Combining measures can improve validity. CONCLUSIONSThe measures most commonly used in primary care and community settings are disease counts, Charlson index, ACG System, CIRS, CDS, and DUSOI. Different measures are most appropriate according to the outcome of interest. Choice of measure will also depend on the type of data available. More research is needed to directly compare performance of different measures.

The Spanish version of the SF-36 and its recently developed versions is a suitable instrument for use in medical research, as well as in clinical practice.

BackgroundIn this paper, we report the findings of a realist synthesis that aimed to understand how and in what circumstances patient reported outcome measures (PROMs) support patient-clinician communication and subsequent care processes and outcomes in clinical care. We tested two overarching programme theories: (1) PROMs completion prompts a process of self-reflection and supports patients to raise issues with clinicians and (2) PROMs scores raise clinicians’ awareness of patients’ problems and prompts discussion and action. We examined how the structure of the PROM and care context shaped the ways in which PROMs support clinician-patient communication and subsequent care processes.ResultsPROMs completion prompts patients to reflect on their health and gives them permission to raise issues with clinicians. However, clinicians found standardised PROMs completion during patient assessments sometimes constrained rather than supported communication. In response, clinicians adapted their use of PROMs to render them compatible with the ongoing management of patient relationships. Individualised PROMs supported dialogue by enabling the patient to tell their story. In oncology, PROMs completion outside of the consultation enabled clinicians to identify problematic symptoms when the PROM acted as a substitute rather than addition to the clinical encounter and when the PROM focused on symptoms and side effects, rather than health related quality of life (HRQoL). Patients did not always feel it was appropriate to discuss emotional, functional or HRQoL issues with doctors and doctors did not perceive this was within their remit.ConclusionsThis paper makes two important contributions to the literature. First, our findings show that PROMs completion is not a neutral act of information retrieval but can change how patients think about their condition. Second, our findings reveal that the ways in which clinicians use PROMs is shaped by their relationships with patients and professional roles and boundaries. Future research should examine how PROMs completion and feedback shapes and is influenced by the process of building relationships with patients, rather than just their impact on information exchange and decision making.Electronic supplementary materialThe online version of this article (10.1186/s41687-018-0061-6) contains supplementary material, which is available to authorized users.