Faculty of Health Care and Nursing, Catholic University of Applied Sciences Mainz, Mainz, Germany.
Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.
BMC Health Serv Res. 2023 May 17;23(1):501. doi: 10.1186/s12913-023-09460-1.
Multimorbidity is a common phenomenon among patients treated in general practices. Key challenges within this group include functional difficulties, polypharmacy, treatment burden, fragmentation of care, reduced quality of life and increased health care utilization. These problems cannot be solved in the short consultation time of a general practitioner (GP) since there is an increasing shortage of GPs. In many countries, advanced practice nurses (APNs) are successfully integrated into primary health care for multimorbid patients. The objective of this study is to examine whether the integration of APNs in the primary care of multimorbid patients in Germany leads to optimized care of the target group and to a reduction in the workload of the GPs.
The intervention includes the integration of APNs into the care for multimorbid patients in general practice for twelve months. Qualifications for APNs include a master's level academic degree and 500 hours of project-specific training. Their tasks include in-depth assessment, preparation, implementation, monitoring and evaluation of a person-centred and evidence-based care plan. In this nonrandomized controlled trial, a prospective multicentre mixed methods study will be performed. The main inclusion criterion was the cooccurrence of three chronic diseases. For data collection in the intervention group (n = 817), routine data from health insurance companies and association of statutory health insurance physicians (ASHIP) will be used, as well as qualitative interviews. In addition, the intervention will be assessed through documentation of the care process and standardized questionnaires using a longitudinal design. The control group (n = 1634) will receive standard care. For the evaluation, routine data from health insurance companies are matched at a ratio of 1:2. Outcomes will be measured using emergency contacts and GP visits, treatment costs, health status of the patients and the satisfaction of parties involved. The statistical analyses will include Poisson regression to compare outcomes between the intervention and control groups. Descriptive and analytical statistical methods will be used in the longitudinal analysis of the intervention group data. Cost analysis will compare total costs and subgroup costs between the intervention and control groups. Qualitative data will be analysed using content analysis.
Challenges to this protocol could include the political and strategic environment as well as the planned number of participants.
DRKS00026172 on DRKS.
多病共存是在全科诊所接受治疗的患者中常见的现象。该人群的主要挑战包括功能困难、多种药物治疗、治疗负担、护理碎片化、生活质量降低和医疗保健利用增加。这些问题在全科医生（GP）的短咨询时间内无法解决，因为 GP 短缺日益严重。在许多国家，高级执业护士（APN）成功地整合到了多患者的初级保健中。本研究的目的是检验德国将 APN 整合到多病共存患者的初级保健中是否会优化目标人群的护理，并减轻 GP 的工作量。
该干预措施包括将 APN 整合到全科医生对多病共存患者的护理中，为期 12 个月。APN 的资格包括硕士学位和 500 小时的特定项目培训。他们的任务包括深入评估、准备、实施、监测和评估以患者为中心和基于证据的护理计划。在这项非随机对照试验中，将进行前瞻性多中心混合方法研究。主要纳入标准是三种慢性疾病同时存在。对于干预组（n=817）的数据收集，将使用健康保险公司和法定健康保险医师协会（ASHIP）的常规数据以及定性访谈。此外，将通过使用纵向设计记录护理过程和标准化问卷来评估干预措施。对照组（n=1634）将接受标准护理。对于评估，将使用健康保险公司的常规数据以 1:2 的比例进行匹配。通过急诊联系和 GP 就诊、治疗费用、患者健康状况和利益相关方的满意度来衡量结果。统计分析将包括泊松回归，以比较干预组和对照组的结果。将使用描述性和分析性统计方法对干预组数据进行纵向分析。成本分析将比较干预组和对照组之间的总费用和亚组费用。定性数据将使用内容分析进行分析。
该方案可能面临的挑战包括政治和战略环境以及计划的参与者人数。
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