跳至主要内容
临床试验/NCT07136168
NCT07136168招募中不适用

Healthy Ageing - an Interdisciplinary Randomised Study of Health Dialogues in Primary Care

Linkoeping University1 个研究点 分布在 1 个国家目标入组 2,952 人开始时间: 2025年8月25日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
招募中
发起方
入组人数
2,952
试验地点
1
主要终点
Change in health-related quality of life

研究概览

简要总结

The HOME Project evaluates the effects of structured health dialogues with individuals aged 67-84 years in the municipality of Borgholm, Sweden. A combination of registry data and survey responses will be used to monitor quality of life, morbidity, healthcare needs, and lifestyle factors over a six-year period. Outcomes will be compared between randomized groups within Borgholm municipality and a matched control group from seven other municipalities in Region Kalmar.

The project also includes an analysis of cost-effectiveness and the reach of the intervention. A qualitative interview study will explore participants' perceptions of their health, their motivations for health improvement, and their experiences of how the health dialogues may influence these aspects.

In a substudy, machine learning models will be developed to predict functional decline and high healthcare needs among older adults. These models will be validated against established risk assessment tools such as the Adjusted Clinical Groups (ACG) system and the Charlson Comorbidity Index. Digital motion analysis using Skeleton Avatar Technology will be employed both independently and in combination with other variables to support model development.

详细描述

BACKGROUND: The world faces a demographic shift with an aging population and increasing numbers of older adults experiencing frailty and complex care needs. Effective preventive strategies are requested from many stakeholders . Health dialogues have been introduced in several Swedish regions to promote healthier aging, yet evidence for their effectiveness and cost-efficiency remains limited. While systematic reviews have not confirmed significant effects on morbidity or mortality, some cohort studies suggest benefits in cardiovascular outcomes and a few primary preventive interventions have been directed at older individuals. The results are disputed, and several authors argue that health dialogues and health checks tend to reach individuals with lower cardiovascular risk rather than those at highest risk [4]. There is a lack of studies linking the outcomes of health dialogues to different risk levels.

One strategy to identify individuals in the population at highest risk of morbidity is to use risk assessment instruments. In primary care populations, Adjusted Clinical Groups (ACG) and Charlson Comorbidity Index (CCI) are the most studied. In recent years, several predictive instruments/models using existing health and medical data have been developed to identify older individuals at risk of future functional decline and morbidity. However, the relatively moderate precision of these instruments limits their clinical usefulness. Digital motion analysis using the SAT (Skeleton Avatar Technology) technique has shown potential in assessing physical activity levels, mobility, and balance in older individuals. Still, data from broader populations of older individuals with a wide range of diseases and functional levels are lacking, and the method has not been tested for its predictive ability regarding functional decline and extensive care needs.

Among older individuals, the wide variation in health and functional levels creates a greater need for individualized advice and interventions. Holistic interventions targeting frail older individuals are well-studied, and there is some evidence of positive effects, although results are also conflicting. International recommendations point to a multifactorial causal relationship behind frailty/functional decline, and there is consensus that increased physical activity and reduced malnutrition can counteract these issues, and that an active lifestyle is associated with a reduced risk of frailty.

A current question is which health outcomes are most important for the older population. Studies show that many older individuals value good quality of life and high independence more than maximum lifespan. As a complement to traditional measurements of health-related quality of life using EQ-5D, which focuses on symptoms and function, it is proposed to measure "Capability": the ability to perform activities that are meaningful and important to the individual . ICECAP-O is a quality-of-life instrument that has also been used for health economic evaluations [9].

AIM:

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Prevention
盲法
None

入排标准

年龄范围
67 Years 至 84 Years(Older Adult)
性别
All
接受健康志愿者
是

入选标准

  • •Living in Borgholm municipality or in one of 7 matched Demographical Statistical Area in Kalmar county
  • •Age between 67-84 years

排除标准

  • •Living in a nursing home
  • •Not speaking or understanding swedish language

研究组 & 干预措施

Health dialogue

Experimental

Participants will be invited to a health dialogue at primary health care center and to answer a questionnaire covering different aspects of health. Data from medical registers will be collected.

干预措施: Health dialogue (Behavioral)

Passive control

No Intervention

Participant will be invited to answer a questionnaire covering different aspects of health. Data from medical registers will be collected.

结局指标

主要结局

Change in health-related quality of life

时间窗: Baseline, at 16 months and 6 years from start of intervention

EQ5D-5L (Euroqol 5 dimensions 5 levels) collected via postal questionnaire

Change in quality of life

时间窗: Baseline, at 16 months and at 6 years from study start

Quality of life measured by ICECAP-0 ( ICEpop CAPability measure for older people)

次要结局

  • Hospital care days(16 months, 3 years and 6 years)
  • Hospital care episodes(16 months, 3 years and 6 years)
  • Healthcare visits(16 months, 3 years and 6 years from start of intervention)
  • Social care use(16 months and 6 years from the start of the intervention)
  • Mortality(16 months, 3 years and 6 years from start of intervention)
  • Healthcare cost(16 months, 3 years and 6 years from start of intervention)
  • Cost-effectiveness(16 months and 6 years from start of intervention)
  • Change in ADL (Activities of daily living)(at baseline, 16 months and 6 years from start of intervention)
  • Frailty(Baseline, at 16 months and 6 years from start of intervention)
  • Time to nursing home admission(16 months and 6 years from start of intervention)
  • Medication(16 months and 6 years from start of intervention)
  • Hospital care days(16 months, 3 years and 6 years)
  • Hospital care episodes(16 months, 3 years and 6 years)
  • Healthcare visits(16 months, 3 years and 6 years from start of intervention)
  • Social care use(16 months and 6 years from the start of the intervention)
  • Mortality(16 months, 3 years and 6 years from start of intervention)
  • Change in ADL (Activities of daily living)(at baseline, 16 months and 6 years from start of intervention)
  • Healthcare cost(16 months, 3 years and 6 years from start of intervention)
  • Cost-effectiveness(16 months and 6 years from start of intervention)
  • Frailty(Baseline, at 16 months and 6 years from start of intervention)
  • Time to nursing home admission(16 months and 6 years from start of intervention)
  • Medication(16 months and 6 years from start of intervention)
  • Maintenance of own housing(At 16 months, at 3 years and 6 years from start of intervention)

研究者

发起方
Linkoeping University
申办方类型
Other Gov
责任方
Principal Investigator
主要研究者

Magnus Nord

MD, PhD; Adjunct senior lecturer

Linkoeping University

研究点 (1)

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