Trajectories of Treatment Burden Among Primary Care Patients with Long-Term Conditions in Southern China: A Latent Class Growth Analysis.

IF 2.7 4区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Risk Management and Healthcare Policy Pub Date : 2024-08-22 eCollection Date: 2024-01-01 DOI:10.2147/RMHP.S464434
Zhihui Jia, Zimin Niu, Jia Ji Wang, Jose Hernandez, Yu Ting Li, Harry H X Wang
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引用次数: 0

Abstract

Background: Treatment burden is a patient-centred, dynamic concept. However, longitudinal data on the changing pattern of treatment burden among patients with one or more long-term conditions (LTCs) are relatively scanty. We aimed to explore the longitudinal trajectories of treatment burden and associated risk factors in a large, patient population in primary care settings.

Methods: We analysed data from 5573 primary care patients with long-term conditions (LTCs) recruited using a multistage sampling method in Shenzhen, southern China. The treatment burden was assessed by the Mandarin Chinese version of the Treatment Burden Questionnaire (TBQ). We used latent class growth mixture modelling (LCGMM) to determine trajectories of treatment burden across four time points, ie, at baseline, and at 6, 12, and 18 months. Predictors of trajectory classes were explored using multivariable logistic regression analysis.

Results: The mean TBQ scores of patients with a single LTC (n = 2756), 2 LTCs (n = 1871), 3 LTCs (n = 699), and ≥4 LTCs (n = 247) were 18.17, 20.28, 21.32, and 26.10, respectively, at baseline. LCGMM identified three discrete classes of treatment burden trajectories over time, ie, a high-increasing class, a low-stable class, and a high-decreasing class. When controlling for individual-level factors including age, education, monthly household income per head, smoking, alcohol consumption, and attendance in health education, patients who had a clinical diagnosis of 3 LTCs (adjusted odds ratio [aOR] = 1.49, 95% CI = 1.21-1.86, P < 0.001) or ≥4 LTCs (aOR = 1.97, 95% CI = 1.44-2.72, P < 0.001) were more likely to belong to the high-increasing class. Sensitivity analysis using propensity score methods obtained similar results.

Conclusion: Our study revealed the presence of discrete patterns of treatment burden over time in Chinese primary care patients with LTCs, providing directions for tailored interventions to optimise disease management. Patients with 3 or more LTCs should receive close attention in healthcare delivery as they tend to experience a greater treatment burden.

中国南方长期病患者基层医疗治疗负担的轨迹:潜类增长分析
背景:治疗负担是一个以患者为中心的动态概念:治疗负担是一个以患者为中心的动态概念。然而,关于患有一种或多种长期疾病(LTC)的患者治疗负担变化模式的纵向数据相对较少。我们的目的是在大量初级医疗机构患者中探索治疗负担的纵向轨迹和相关风险因素:我们分析了在中国南方深圳采用多阶段抽样方法招募的 5573 名患有长期疾病(LTC)的基层医疗患者的数据。治疗负担由治疗负担问卷(TBQ)的中文普通话版本进行评估。我们使用潜类增长混合模型(LCGMM)来确定四个时间点(即基线、6 个月、12 个月和 18 个月)的治疗负担轨迹。使用多变量逻辑回归分析探讨了轨迹等级的预测因素:基线时,单个 LTC(n = 2756)、2 个 LTC(n = 1871)、3 个 LTC(n = 699)和≥4 个 LTC(n = 247)患者的平均 TBQ 分数分别为 18.17、20.28、21.32 和 26.10。LCGMM 确定了治疗负担随时间变化的三个离散等级,即高增加等级、低稳定等级和高减少等级。在控制了包括年龄、教育程度、家庭人均月收入、吸烟、饮酒和健康教育出席率在内的个体水平因素后,临床诊断为 3 种 LTC(调整赔率 [aOR] = 1.49,95% CI = 1.21-1.86,P < 0.001)或≥4 种 LTC(aOR = 1.97,95% CI = 1.44-2.72,P < 0.001)的患者更有可能属于高递增等级。使用倾向得分法进行的敏感性分析也得出了类似的结果:我们的研究揭示了中国基层医疗机构中长期慢性病患者的治疗负担随时间变化的离散模式,为优化疾病管理的定制干预提供了方向。患有 3 种或 3 种以上长期慢性病的患者往往会承受更大的治疗负担,因此在提供医疗服务时应给予密切关注。
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来源期刊
Risk Management and Healthcare Policy
Risk Management and Healthcare Policy Medicine-Public Health, Environmental and Occupational Health
CiteScore
6.20
自引率
2.90%
发文量
242
审稿时长
16 weeks
期刊介绍: Risk Management and Healthcare Policy is an international, peer-reviewed, open access journal focusing on all aspects of public health, policy and preventative measures to promote good health and improve morbidity and mortality in the population. Specific topics covered in the journal include: Public and community health Policy and law Preventative and predictive healthcare Risk and hazard management Epidemiology, detection and screening Lifestyle and diet modification Vaccination and disease transmission/modification programs Health and safety and occupational health Healthcare services provision Health literacy and education Advertising and promotion of health issues Health economic evaluations and resource management Risk Management and Healthcare Policy focuses on human interventional and observational research. The journal welcomes submitted papers covering original research, clinical and epidemiological studies, reviews and evaluations, guidelines, expert opinion and commentary, and extended reports. Case reports will only be considered if they make a valuable and original contribution to the literature. The journal does not accept study protocols, animal-based or cell line-based studies.
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