Journal of multimorbidity and comorbidity最新文献

Introduction: People living with multiple long-term conditions (MLTC-M) (multimorbidity) experience a range of inter-related symptoms. These symptoms can be tracked longitudinally using consumer technology, such as smartphones and wearable devices, and then summarised to provide useful clinical insight.

Aim: We aimed to perform an exploratory analysis to summarise the extent and trajectory of multiple symptom ratings tracked via a smartwatch, and to investigate the relationship between these symptom ratings and demographic factors in people living with MLTC-M in a feasibility study.

Methods: 'Watch Your Steps' was a prospective observational feasibility study, administering multiple questions per day over a 90 day period. Adults with more than one clinician-diagnosed long-term condition rated seven core symptoms each day, plus up to eight additional symptoms personalised to their LTCs per day. Symptom ratings were summarised over the study period at the individual and group level. Symptom ratings were also plotted to describe day-to-day symptom trajectories for individuals.

Results: Fifty two participants submitted symptom ratings. Half were male and the majority had LTCs affecting three or more disease areas (N = 33, 64%). The symptom rated as most problematic was fatigue. Patients with increased comorbidity or female sex seemed to be associated with worse experiences of fatigue. Fatigue ratings were strongly correlated with pain and level of dysfunction.

Conclusion: In this study we have shown that it is possible to collect and descriptively analyse self reported symptom data in people living with MLTC-M, collected multiple times per day on a smartwatch, to gain insights that might support future clinical care and research.

Background: Ageing of the population increases the prevalence and coexistence of many chronic diseases; a condition called multimorbidity. In Finland, information on the significance of multimorbidity and its relation to the sustainability of healthcare is scarce.

Aim: To assess the prevalence of multimorbidity, the transitions between patient groups with and without multiple diseases and the associated healthcare cost in Finland in 2017-2019.

Methods: A register-based cohort study covering all adults (n = 3,326,467) who used Finnish primary or specialised healthcare services in 2017. At baseline, patients were classified as 'non-multimorbid', 'multimorbid' or 'multimorbid at risk' based on the recordings of a diagnosis of interest. The costs were calculated using the care-related patient grouping and national standard rates. Transition plots were drawn to observe the transition of patients and costs between groups during the two-year follow-up.

Results: At baseline, 62% of patients were non-multimorbid, 23% multimorbid and 15% multimorbid at risk. In two years, the proportion of multimorbid patients increased, especially those at risk. Within the multimorbid at-risk group, total healthcare costs were greatest (€5,027 million), accounting for 62% of the total healthcare cost of the overall patient cohort in 2019. Musculoskeletal diseases, cardiometabolic diseases and tumours were the most common and expensive chronic diseases contributing to the onset of multimorbidity.

Conclusion: Multimorbidity is causing a heavy burden on Finnish healthcare. The estimates of its effect on healthcare usage and costs should be used to guide healthcare planning.

Objectives: To compare the agreement between percentile ranks from 4 multi-morbidity scores.

Design: Population-based descriptive study.

Setting: Olmsted County, Minnesota (USA).

Participants: We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years).

Methods: For each person, we calculated 4 multi-morbidity scores using readily available diagnostic code lists from the US Department of Health and Human Services, the Clinical Classifications Software, and the Elixhauser Comorbidity Index. We calculated scores using diagnostic codes received in the 5 years before the index birthday and fit quantile regression models across age and separately by sex to transform unweighted, simple counts of conditions into percentile ranks as compared to peers of same age and of same sex. We compared the percentile ranks of the 4 multi-morbidity scores using intra-class correlation coefficients (ICCs).

Results: We assessed agreement in 181,553 persons who reached a total of 1,075,433 birthdays at ages 18 years through 85 years during the study period. In general, the percentile ranks of the 4 multi-morbidity scores exhibited high levels of agreement in 6 score-to-score pairwise comparisons. The agreement increased with older age for all pairwise comparisons, and ICCs were consistently greater than 0.65 at ages 50 years and older.

Conclusions: The assignment of percentile ranks may be a simple and intuitive way to assess the underlying trait of multi-morbidity across studies that use different measures.

Background: Structured Medication Reviews (SMRs) are intended to help deliver the NHS Long Term Plan for medicines optimisation in people living with multiple long-term conditions and polypharmacy. It is challenging to gather the information needed for these reviews due to poor integration of health records across providers and there is little guidance on how to identify those patients most urgently requiring review.

Objective: To extract information from scattered clinical records on how health and medications change over time, apply interpretable artificial intelligence (AI) approaches to predict risks of poor outcomes and overlay this information on care records to inform SMRs. We will pilot this approach in primary care prescribing audit and feedback systems, and co-design future medicines optimisation decision support systems.

Design: DynAIRx will target potentially problematic polypharmacy in three key multimorbidity groups, namely, people with (a) mental and physical health problems, (b) four or more long-term conditions taking ten or more drugs and (c) older age and frailty. Structured clinical data will be drawn from integrated care records (general practice, hospital, and social care) covering an ∼11m population supplemented with Natural Language Processing (NLP) of unstructured clinical text. AI systems will be trained to identify patterns of conditions, medications, tests, and clinical contacts preceding adverse events in order to identify individuals who might benefit most from an SMR.

Discussion: By implementing and evaluating an AI-augmented visualisation of care records in an existing prescribing audit and feedback system we will create a learning system for medicines optimisation, co-designed throughout with end-users and patients.

Introduction: Multidisciplinary Team Conferences (MDTs) are complex interventions in the modern healthcare system and they promote a model of coordinated patient care and management. However, MDTs within chronic diseases are poorly defined. Therefore, the aim of this scoping review was to summarise the current literature on physician-led in-hospital MDTs in chronic non-malignant diseases.

Method: Following the PRISMA-ScR guideline for scoping reviews, a search on MDT interventions in adult patients, with three or more medical specialties represented, was performed.

Results: We identified 2790 studies, from which 8 studies were included. The majority of studies were non-randomised and focused on a single disease entity such as infective endocarditis, atrial fibrillation, IgG4-related disease, or arterial and venous thrombosis. The main reason for referral was confirmation or establishment of a diagnosis, and the MDT members were primarily from medical specialties gathered especially for the MDT. Outcomes of the included studies were grouped into process indicators and outcome indicators. Process indicators included changes in diagnostic confirmation as well as therapeutic strategy and management. All studies reporting process indicators demonstrated significant changes before and after the MDT.

Conclusion: MDTs within chronic diseases appeared highly heterogeneous with respect to structure, reasons for referral, and choice of outcomes. While process indicators, such as change in diagnosis, and treatment management/plan seem improved, such have not been demonstrated through outcome indicators.

Background: Inter-relationships between multimorbidity and geriatric syndromes are poorly understood. This study assesses heterogeneity in joint trajectories of somatic disease, functional status, cognitive performance, and depressive symptomatology.

Methods: We analyzed 16 years of longitudinal data from the Health and Retirement Study (HRS, 1998-2016) for n = 11,565 older adults (≥65 years) in the United States. Group-based mixture modeling identified latent clusters of older adults following similar joint trajectories across domains.

Results: We identified four distinct multidimensional trajectory groups: (1) Minimal Impairment with Low Multimorbidity (32.7% of the sample; mean = 0.60 conditions at age 65, 2.1 conditions at age 90) had limited deterioration; (2) Minimal Impairment with High Multimorbidity (32.9%; mean = 2.3 conditions at age 65, 4.0 at age 90) had minimal deterioration; (3) Multidomain Impairment with Intermediate Multimorbidity (19.9%; mean = 1.3 conditions at age 65, 2.7 at age 90) had moderate depressive symptomatology and functional impariments with worsening cognitive performance; (4) Multidomain Impairment with High Multimorbidity (14.1%; mean = 3.3 conditions at age 65; 4.7 at age 90) had substantial functional limitation and high depressive symptomatology with worsening cognitive performance. Black and Hispanic race/ethnicity, lower wealth, lower education, male sex, and smoking history were significantly associated with membership in the two Multidomain Impairment classes.

Conclusions: There is substantial heterogeneity in combined trajectories of interrelated health domains in late life. Membership in the two most impaired classes was more likely for minoritized older adults.

Introduction: Persistent pain (PP) and long-term conditions are all associated with psychological well-being. Less is known about their associations with reduced psychological well-being when co-occurring. We investigated how PP and long-term physical and mental conditions relate to psychological well-being when occurring together.

Method: Data collected in the Danish population-based Lolland-Falster Health study were used in this cross-sectional study. Participants aged ≥18 years completing questions concerning PP, long-term conditions and psychological well-being were included. PP and long-term conditions were defined as conditions lasting 6 months or longer. Psychological well-being was assessed by the World Health Organization Well-Being Index (WHO-5). Multiple linear regression investigated combinations of PP and physical and mental long-term conditions and their associations with WHO-5.

Results: Of 11,711 participants, 10,744 had available data. One third had PP (n = 3250), while 6144 (57%), 213 (2%) and 946 (9%) reported having only physical conditions, only mental conditions or both, respectively. All combinations of PP and long-term conditions were negatively associated with WHO-5. PP in combination with mental (-23.1 (95% CI -28.3 to -17.8)) or both physical and mental conditions (-25.1 (-26.7 to -23.52) yielded the strongest negative associations. Two or more pain sites together with long-term physical and mental conditions was associated with a lower WHO-5 score (-6.2 (-8.9 to -3.5) compared to none or one pain site.

Conclusion: The presence of PP and long-term conditions, in particular mental conditions, were strongly associated with worse psychological well-being. This highlights the importance of assessing psychological well-being in individuals with PP and long-term conditions.

Objectives: To categorize and examine the effectiveness regarding health-related quality of life (HRQoL), mental health, and mortality of care models for persons with multimorbidity in primary care, community care, and hospitals through a systematic review.

Methods: We searched PubMed, Embase, and Cochrane Central Register of Controlled Trials up to May 2020. One author screened titles and abstracts, and to validate, a second author screened 5% of the studies. Two authors independently extracted data and assessed risk of bias using the tool by the Cochrane Effective Practice and Organisation of Care group. Study inclusion criteria were (1) participants aged ≥ 18 years with multimorbidity; (2) referred to multimorbidity or two or more specific chronic conditions in the title or abstract; (3) randomized controlled design; and (4) HRQoL, mental health, or mortality as primary outcome measures. We used the Foundation Framework to categorize the models and the PRISMA-guideline for reporting.

Results: In this study, the first to report effectiveness of care models in patients with multimorbidity in hospital settings, we included 30 studies and 9,777 participants with multimorbidity. 12 studies were located in primary care, 9 in community care, and 9 in hospitals. HRQoL was reported as the primary outcome in 12 studies, mental health in 17 studies, and mortality in three studies-with significant improvements in 5, 14, and 2, respectively. The studies are presented according to settings.

Conclusions: Although 20 of the care models reported positive effects, the variations in populations, settings, model elements, and outcome measures made it difficult to conclude on which models and model elements were effective.