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Clinical Trial Summary

Case management (CM) has been recommended as a way of inspiring measurable changes in individual behaviors and improving clinical outcomes for patients with chronic diseases. However, data on its effectiveness for Taiwanese patients with rheumatoid arthritis (RA) are limited. This study aimed to determine the long-term effectiveness of CM that focused on nurses' role among Taiwanese RA patients.


Clinical Trial Description

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by inflammation and progressive damage of the joints that affects 0.5-1.0% of the population worldwide. It usually occurs in individuals who are 30 to 50 years-old, and about 20-30% of affected individuals exhibited some arthritis-attributable work limitations, thereby posing major burdens to patients, families and social care systems. In light of the increasing threat of RA, optimal management of RA may improve clinical outcome and decrease mortality, thus resulting in reduced hospitalization and medical cost. Recently, case management (CM) has drawn more attention in medical practice as an approach to such a high-cost and high-risk chronic disease. European league against rheumatism (EULAR) further launched that the involvement of CM, which was delivered by the trained nurse, in the management of chronic inflammatory arthritis to achieve favorable prognosis. Consequently, there has been increased attention to the influence of CM among arthritis patients. Nevertheless, the corresponding effects still remained conflicting. Of the studies conducted thus far, the investigators found that the majority of these studies were conducted in Western populations. Information on whether the CM delivered by the nurses could influence the clinical outcomes for RA patients in Taiwan was still limited. To narrow this gap in the literature, the present study aimed to clarify the long-term effectiveness of CM through NLC for RA patients by using generalized estimating equations (GEEs), with the intent that the findings could serve as a reference for providing empirically robust grounds for healthcare providers to formulate some care programs that are culturally appropriate for Asian RA patients. Methods Study design and subjects A quasi-experimental pre-posttest control group design, with purposive sampling, will be used to recruit participants from the Rheumatologic department of a hospital in southern Taiwan from July of 2016 to June of 2017. The inclusion criteria were (i) being at least 20 years old at the time of recruitment (ii) having no cognitive impairment and severe complications, (iii) being able to express opinions in either Mandarin or Taiwanese, and (iv) having a diagnosis of RA. To ensure participants' anonymity, all questionnaires were marked with an encryption code to facilitate data analysis, but with no personal identifiers. Sample size calculation Sample size calculation for this analysis of repeated measures to detect an effect size of 0.2 at 80% power and a 0.05 significance level indicated that a sample size of 68 patients is needed (according to G- POWER 3.1 analytical software, Franz Faul, Universitat Kiel, Germany). A sample of at least 90 participants for both groups combined was required on the basis of these parameters, allowing for a 30% attrition rate. Intervention Because continued participation was essential for this study, the participants were divided into the experiment or control group in accordance with the personal willingness. The control group received usual health education lasting for about 15 minutes per medical visit from ward nurses, which consisted of consultation in terms of disease symptoms, related treatments or the doctor's order. They would receive health education instruction leaflets for reference purposes if necessary. Outcome measures A packet of measures was used for data collection, which included the Taiwanese Depression Questionnaire (TDQ), and Arthritis Self-Efficacy Scale (ASES), as well as a questionnaire that requested information on demographic variables and disease characteristics. Data collection procedure The investigators had obtained the agreement by the Ethics Committee of Dalin Tzuchi Hospital prior to the recruitment of participants. Researchers explained the purpose of study and its procedure to all participants. Signed informed consent was obtained after the patients understood and agreed to participate in this study. Thereafter, the investigators applied an observer-blind approach for data collection. A trained interviewer, who was blind with the study design and participants, was assigned to collect the participants' information on demographic and disease characteristics. All data were obtained at three time points: before NLC program (T0), three days after NLC program (T1), and three months after NLC program (T2). To reduce the dropout rate, the interviewer helped ask participants to return the hospital for the completion of assessments via phone reminders. However, participants were still given the option to withdraw from the study at any time without any penalty. Statistical analysis Descriptive and inferential statistical analyses were conducted in accordance with the study aims and the nature of the variables. Descriptive parameters, including mean, standard deviation (SD), and percentage, were used to describe the distributions of demographic and disease data. Differences between the two groups were compared initially using t-test and χ2 test as appropriate. For inferential analysis, generalized estimating equation (GEE) procedure with identity link function with normal distribution was used to assess the long-term effects of NLC, while taking into account within-subject correlations between measurements over time and the influence of potential confounding covariates. All analyses were conducted using SAS statistical software. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03446989
Study type Interventional
Source Dalin Tzu Chi General Hospital
Contact
Status Completed
Phase N/A
Start date August 1, 2016
Completion date June 30, 2018

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