Burfeindt Corinna, Darmann-Finck Ingrid, Stammann Carina, Stegbauer Constance, Stolle-Wahl Claudia, Zündel Matthias, Rothgang Heinz
SOCIUM Research Center On Inequality and Social Policy Mary-Somerville-Straße 3, University of Bremen, 28359, Bremen, Germany.
High-Profile Area of Health Sciences, University of Bremen, Bibliothekstraße 1, 28359, Bremen, Germany.
BMC Nurs. 2024 Mar 26;23(1):201. doi: 10.1186/s12912-024-01883-3.
Staffing ratios in nursing homes vary among the federal states of Germany, but there are no rational grounds for these variations. In a previous study, a new instrument for the standardized calculation of staffing requirements in nursing homes was developed (Algorithm 1.0). The development was based on a new empirical data collection method that derives actual and target values for the time and number of care interventions provided. Algorithm 1.0 found an increased requirement of 36% of staff in German nursing homes. Based on these results, the German legislature has commissioned a model program to trial and evaluate a complex intervention comprising increased staffing combined with strategies for organizational development.
The mixed-methods study consists of (i) developing a concept for restructuring the work organization, (ii) the application of this concept combined with increased staffing in 10 nursing homes (complex intervention), and the further development of the concept using a participatory and iterative formal evaluation process. The intervention consists of (a) quantitative measures of increased staffing based on a calculation using Algorithm 1.0 and (b) qualitative measures regarding organizational development. The intervention will be conducted over one year. The effects of the intervention on job satisfaction and quality of care will be evaluated in (iii) a comprehensive prospective, controlled summative evaluation. The results will be compared with ten matched nursing homes as a control group. Finally, (iv) prototypical concepts for qualification-oriented work organization, a strategy for the national rollout, and the further development of Algorithm 1.0 into Algorithm 2.0 will be derived.
In Germany, there is an ongoing dynamic legislation process regarding further developing the long-term care sector. The study, which is the subject of the study protocol presented here, generates an evidence-based strategy for the staffing requirements for nursing homes.
This study was approved by the Ethics Committee of the German Association of Nursing Science (Deutsche Gesellschaft für Pflegewissenschaft) on 02.08.2023 (amended on 20.09.2023). Research findings are disseminated through presentations at national and international conferences and publications in peer-reviewed scientific journals.
German Clinical Trails Register DRKS00031773 (Date of registration 09.11.2023).
德国各联邦州养老院的人员配备比例各不相同，但这些差异并无合理依据。在之前的一项研究中，开发了一种用于标准化计算养老院人员配备需求的新工具（算法1.0）。该开发基于一种新的实证数据收集方法，该方法可得出所提供护理干预的时间和数量的实际值和目标值。算法1.0发现德国养老院的人员需求增加了36%。基于这些结果，德国立法机构委托开展了一个示范项目，以试验和评估一项复杂干预措施，该措施包括增加人员配备以及组织发展策略。
这项混合方法研究包括：（i）制定工作组织重组概念；（ii）在10家养老院应用该概念并增加人员配备（复杂干预），并通过参与式和迭代式正式评估过程进一步完善该概念。干预措施包括：（a）基于算法1.0计算增加人员配备的定量措施；（b）关于组织发展的定性措施。干预将持续一年。将在（iii）一项全面的前瞻性对照总结性评估中评估干预对工作满意度和护理质量的影响。结果将与作为对照组的十家匹配养老院进行比较。最后，将得出（iv）面向资质的工作组织的原型概念、全国推广策略以及将算法1.0进一步开发为算法2.0。
在德国，关于长期护理部门进一步发展的立法进程正在动态推进。本研究方案所涉及的这项研究为养老院人员配备需求生成了一项基于证据的策略。
本研究于2023年8月2日获得德国护理科学协会伦理委员会批准（2023年9月20日修订）。研究结果将通过在国内和国际会议上的报告以及在同行评审科学期刊上发表来传播。
德国临床试验注册中心DRKS00031773（注册日期2023年11月9日）。
