Health and treatment priorities in patients with multimorbidity: Report on a workshop from the European General Practice Network meeting ‘Research on multimorbidity in general practice’

Abstract

Setting health and treatment priorities is necessary when caring for multiple and complex patient issues. This is already done in the doctorpatient consultation—yet implicitly rather than explicitly. The aim of this European General Practice Network workshop was to advance a consultation approach that deals with shared priority setting. The workshop was divided into three parts: (1) how to gain a comprehensive health overview for patients with multiple problems as a basis for priority setting; (2) how to establish priorities considering patient and doctor perspectives; and (3) how to practice a communication style that achieves shared priority setting. The workshop participants preferred to gain information on patients’ health status using documentations from patient records rather than conducting systematic assessments. The group emphasized that medical as well as everyday life problems need to be considered when determining priorities, a procedure that requires time and resources not readily available in daily practice. Existing skills for person-centred communication with patients should be applied in order to agree on priorities. Overall it became apparent how challenging it is to arrange and prioritize an array of health problems in a consultation with patients. Existing concepts augmented by innovative systematic methods may be the way forward.     

Development of a new predictive model for polypathological patients. The PROFUND index

Background

There is a concern about the accuracy of the available prognostic indexes when applying them to the emergent population of polypathological patients (PP).

Methods

To develop a 1-year mortality predictive index on PP, we developed a multicenter prospective cohort-study recruiting 1.632 PP after hospital discharge, outpatient clinics, or home hospitalization, from 33 hospitals. Potential risk factors were obtained in the 1.525 PP who completed follow-up. Each factor independently associated with mortality in the derivation cohort (757 PP from western hospitals) was assigned a weight, and risk scores were calculated by adding the points of each factor. Accuracy was assessed in the validation cohort (768 PP from eastern hospitals) by risk quartiles calibration, and discrimination power, by ROC curves. Finally, accuracy of the index was compared with that of the Charlson index.

Results

Mortality in the derivation/validation cohorts was 35%/39.5%, respectively. Nine independent mortality predictors were identified to create the index (age ≥ 85 years, 3points; No caregiver or caregiver other than spouse, 2points; active neoplasia, 6points; dementia, 3points; III-IV functional class on NYHA and/or MRC, 3points; delirium during last hospital admission, 3points; hemoglobinemia < 10 g/dl, 3points; Barthel index < 60 points, 4points; ≥ 4 hospital admissions in last 12 months, 3points). Mortality in the derivation/validation cohorts was 12.1%/14.6% for patients with 0-2points; 21.5%/31.5% for those with 3-6 points; 45%/50% for those with 7-10 points; and 68%/61.3% for those with ≥ 11points, respectively. Calibration was good in derivation/validation cohorts, and discrimination power by area under the curve was 0.77/0.7. Calibration of the Charlson index was good, but discrimination power was suboptimal (area under the curve, 0.59).

Conclusions

This prognostic index provides an accurate and transportable method of stratifying 1-year death risk in PP.     

A multi-institutional, hospital-based assessment of clinical, functional, sociofamilial and health-care characteristics of polypathological patients (PP)

Little is known about the main features of the emergent population of PP. Our objective was to determine the clinical, care and social characteristics of a multi-institutional population of PP, by means of a cross-sectional study including a reference population of hospital-based PP from 36 hospitals. The main clinical, functional, mental and social features and their associated factors were assessed: 1632 PP (53% males, mean age 77.9 ± 9.8 years) were included. An informal caregiver was required by 52% (78% of caregivers were close female relatives). The mean inclusion criteria (Cat): were 2.7 ± 0.8 (49.5% presented ≥3 Cat). The most frequent inclusion Cat were heart (77.5%), lung (45.6%), neurological (38.2%), and kidney diseases (32.2%), whereas the mean of other comorbidities was 4.5 ± 2.7 per PP. The mean Charlson comorbidity index (CCI) was 4; 47.6%, and 52.4% presented dyspnea ≥3 on the NYHA, and on the MRC, respectively; nearly 19% required home oxygen therapy, 19% had suffered >1 fall in previous year, and 11% suffered an active neoplasia. The mean hospital admissions in last 12/3 months, and chronically prescribed drugs were 2/1, and 8 ± 3, respectively. More than 70% presented obesity, while 60% had hypoalbuminemia. The basal/inclusion Barthel index (BI) score was 69 ± 31/58 ± 34 (BI score < 60 was present in 31.5%/44%, respectively); and the mean Pfeiffer score was 2.94 ± 3.2 (43% answered with ≥3 errors). More than half of the subjects were at risk or already had established social problems. This emergent population is considerably homogeneous, highly complex, clinically vulnerable, functionally impaired, dependent on caregivers and socially fragile. They need to receive more attention in clinical research and more support in health interventions based on comprehensive attention and continuity of care.     

Post-hospitalization experiences of older adults diagnosed with diabetes: “It was daunting!”

Multimorbidity combined with geriatric syndromes in older adults with diabetes exacerbate their risks for poor post-discharge outcomes. The purpose of this study was to examine self-described hospital-to-home transition challenges encountered by older adults with a diagnosis of diabetes within the first 30 days following discharge. The qualitative responses for this paper emerged from a larger mixed methods study (n = 96) in which participants provided free responses specifying transition challenges during follow-up telephone interviews on the 7th day (n = 67) and 30th day (n = 55) post-discharge. Using inductive content analysis techniques four major themes emerged: a) “The daily stuff is difficult”; b) engineering care at home is complex; c) “life is very difficult”; and d) managing complex health problems is difficult. Findings suggest existing system-level metrics such as readmission rates fail to capture the complex and dynamic interplay of personal, family and social factors which complicate hospital-to-home transitions of older adults with pre-existing diabetes.     

Does multimorbidity still remain a matter of the elderly: Lithuanian national data analysis

IntroductionMultimorbidity – the coexistence of ≥2 chronic conditions in same individual is usually associated with older age. There is an increase in its prevalence at a much younger age, however with very limited research specifying that.ObjectiveTo identify age breaking points for the occurrence of multimorbidity.MethodsThe study included patients, who used any healthcare services between the 01/01/2012 and 30/06/2014. Patients were divided into two groups – with single chronic condition and with multimorbidity. Age-specific proportion of multimorbidity, rate of primary and outpatient visits, number of hospitalizations and prescribed reimbursed medications between these groups were analyzed.ResultsThe study included 452578 patients, 94.63% of them had more than one chronic condition. The risk increase with every consecutive year for developing multimorbidity was between the age of 28 and 39 years. The age breaking point for the rapid increase in hospitalizations was about 29 years in multimorbidity group. The proportion of patients with multimorbidity using expensive medications starts to increase at the age of 41.ConclusionsThe risk of acquiring an additional chronic condition rises exponentially from the age of 29 years and platos between the age of 51 and 57. Patients with multimorbidity require increasing amounts of primary healthcare resources, where patients with single chronic condition require decreasing primary care usage, possibly attributed to successful patient empowerment.     

基于倾向得分匹配的农村中老年人慢性病共病对失能的影响研究

背景 随着人口老龄化的加速和预期寿命的延长,慢性病共病和失能对全球卫生和社会保健系统带来重大挑战。慢性病共病与失能之间关联紧密,目前尚缺乏关注农村中老年人群体慢性病共病对失能影响的研究。目的 探讨农村中老年人慢性病共病对失能的影响,为制订农村中老年人慢性病共病和失能的管理策略提供参考依据。方法 2022年3月,提取2018年中国健康与养老追踪调查（CHARLS）数据库中11 088例≥45岁农村中老年慢性病患者的数据资料,包括基本情况、患慢性病情况、日常生活自理能力（ADL）与工具性日常生活自理能力（IADL）失能情况。依据慢性病患者所患慢性病是否≥2种将其分为共病组和非共病组。采用倾向性得分匹配（PSM）法将共病组与非共病组以1∶1比例进行基本情况匹配,应用二元条件Logistic回归分析慢性病共病对ADL失能和IADL失能的影响。结果 11 088例农村中老年慢性病患者中,2 711例（24.45%)ADL失能,4 216例（38.02%)IADL失能,7 673例（69.20%）为慢性病共病患者。不同性别、年龄、婚姻状况、受教育程度、睡眠时间、吸烟史、饮酒史、残疾情况、参加社交活...     

Grupos de morbilidad ajustados: características y comorbilidades de los pacientes crónicos según nivel de riesgo en Atención Primaria

AimsTo describe the characteristics of patients with chronic conditions according to their risk levels assigned by the adjusted morbidity groups (AMG). To analyse the factors associated with a high risk level and to study their effect.DesignObservational cross-sectional study with an analytical focus.LocationPrimary care (PC), Madrid Health Service.ParticipantsPopulation of 18,107 patients stratified by their risk levels with the AMG in the computerised clinical records of Madrid PC.Main measurementsThe variables studied were: socio-demographic, clinical-nursing care and use of services. Univariate, bivariate, and multivariate analysis were performed.ResultsOf the 18,107 patients, 9,866(54.4%) were identified as chronic patients, with 444 (4.5%) stratified as high risk, 1784 (18,1%) as medium risk, and 7,638 (77.4%) as low risk. The high risk patients, compared with medium and low risk, had an older mean age [77.8 (SD = 12.9), 72.1 (SD = 12.9), 50.6 (SD = 19.4)], lower percentage of women (52.3%, 65%, 61.1%), a higher number of chronic diseases [6.7 (SD = 2.4), 4.3 (SD = 1.5), 1.9 (SD = 1.1)], polymedication (79.1%, 43.3%, 6.2%), and contact with PC [33.9 (28), 21.4 (17.3), 7.9 (9.9)] (P <. 01). In the multivariate analysis, the high risk level was independently related to age > 65 [1.43 (1.03-1.99), male gender (OR = 3.46, 95% CI = 2.64-4.52), immobility (OR = 6.33, 95% CI = 4.40-9.11), number of chronic conditions (OR = 2.60, 95% CI = 2.41-2.81), and PC contact > 7 times (OR = 1.95, 95% CI = 1.36-2.80)] (P < .01).ConclusionsMore than half of the population is classified by the AMG as a chronic, and it is stratified into 3 risk levels that show differences in gender, age, functional impairment, need for care, morbidity, complexity, and use of Primary Care services. Age > 65, male gender, immobility, number of chronic conditions, and contact with PC > 7 times were the factors associated with high risk.