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Process evaluation of a multi-disciplinary complex intervention to improve care for older patients with chronic conditions in rural areas (the HandinHand Study): study protocol



To improve health care in rural areas, especially for increasing numbers of people with chronic diseases, academically qualified nurses could take over expanded roles to meet the challenges of an ageing society and a decreasing number of General Practitioners (GPs). In the project “HandinHand” (HiH), qualified nurses (Expert nurses, ENs) will carry out home visits to older people with chronic diseases over a period of six months. ENs will prepare a care plan in cooperation with GPs to stabilise the care situation and avoid unplanned hospital admissions and GP visits. The process evaluation aims to provide an in-depth analysis of the implementation process and gather important information on barriers and facilitators to the implementation of ENs as a complementary health care structure in primary care, taking into account several context factors.


Based on the Medical Research Council (MRC) Framework for complex interventions, a logic model was developed and applied as the basis for data collection. Qualitative and quantitative data will be collected during the study. A mixed methods approach should allow to gain important insights from participants (e.g. ENs, GPs, patients) involved in the study as well as relevant stakeholders. Semi-structured interviews and surveys will be conducted. Data analysis will be based on the logical model, combining qualitative and quantitative data. Qualitative data will be analysed inductively-deductively using qualitative thematic framework analysis.


The process evaluation will provide guidance and conclusions on further development and transferability. Of particular interest is the expanded role of ENs in primary care, which has barely been implemented in Germany and can be seen as a precursor to the development of an Advanced Practice Nursing (APN) role in primary care.

Peer Review reports


Demographic change, increasing health care needs and consumer expectations highlight the need for transforming and restructuring healthcare services worldwide [26]. With a growing population of people over 60, healthcare systems are faced with challenges to meet growing demands within a context of a shortage of healthcare professionals. Most older people are able to care for themselves, but in later life many also suffer from one or multiple chronic illnesses and disabilities and require support from healthcare professionals. Health care needs of persons with chronic health conditions are multi-fold and complex and cannot be adequately met by one health profession alone. Rather, care models involving multidisciplinary teams and coordinating services to include a mix of skills and competencies tailored to the complex needs of persons with chronic conditions have shown to improve outcome [15, 21].

Particularly for people in rural areas, many countries have responded to growing demands for multidisciplinary care models acknowledging evidence of the importance of person-centred care approaches enabling support and empowerment for self-management at home for people with chronic conditions [8, 19]. In many countries, models of community-based, ambulatory care have been proposed instead of models of acute medical care provided mostly by hospitals aiming to increase health care access and reduce potentially avoidable hospitalisations [20, 21].

In primary care, the effectiveness of traditional, physician-driven models have been questioned and alternative models were successfully implemented [15]. Collaborative, integrated care models have been shown to have a positive impact on a number of patient outcomes in a variety of primary care settings [21]. New opportunities have emerged for nurses, especially advanced practice nurses (APN), to meet patients’ demands and unmet needs [1,2,3,4, 11, 19]. Internationally, APN claim essential roles as practitioners within health care systems and are in a prime position to drive innovative care models to improve the coordination of multidisciplinary health care for older people [19]. Advanced nursing practice has been defined as “patient-focused application of an expanded range of competencies to improve health outcomes for patients and populations in a specialized clinical area of the larger discipline of nursing.” (Tracy & O´Grady, [30]). Current evidence suggests that when APN are competent and empowered within the health system to practice as independent professionals, their work is associated with improvements in several measures of health outcomes and behaviour and leads to comparable or better results compared to care provided by medical doctors alone [17, 18].

In Germany, the establishment of educational and practice opportunities for nurses to become APN started later and developed slower than in many other Western countries, and the German health system still faces important legislative, professional and structural barriers that prevent APNs (or indeed any nurse) to practice as independent professionals. A re-organisation of health care provision and greater autonomy for nursing practice has been recommended by various legislative and professional bodies in Germany for many years but so far, the legal framework for such independent provision of healthcare by nurses is lacking [6, 27, 28]. In Germany, nurses are not entitled to bill for healthcare provided, refer patients to other health professionals, or prescribe drug or nursing aids. Nurses are authorised to practice medical care e.g. wound care management only upon delegation and referral from medical professionals. Also, academic educational opportunities for nurses beyond basic training in the form of tertiary education have developed much later than in most developed countries. Hence, from a global perspective, the development of APN roles and opportunities in Germany is clearly delayed and there is a dire need for concerted efforts to increase evidence-based advanced and expanded practice opportunities.

The “HandinHand” (HiH) study, funded by the German Innovation Fund of the Joint Federal Committee [9], addresses the development and evaluation of expanded nursing roles within an innovative, multidisciplinary care model in primary care. The study will investigate the effects of a complex intervention that aims to improve outcomes for community-dwelling older people with chronic conditions. The core of this intervention will be the implementation of an Expert Nursing Centre (ENC), comprising a team of qualified nurses with expanded practice competencies and additional tertiary nursing education at Bachelor-level working in collaboration with general practitioners (GPs) and other health care professionals (HCP). Successful development, implementation and utilisation of any new role is complex, particularly in multidisciplinary teams [29]. Therefore, a comprehensive process evaluation will be undertaken alongside the main study to explore barriers and facilitators regarding implementation, mechanisms of impact and the context of the study. This paper describes the process evaluation, including design and methods.



The overall aims of the process evaluation are to explain discrepancies between expected and observed results, identify how potential mechanisms of impact and the context influence the results, and provide insights to support further development and future implementation of the intervention.


The HiH intervention will be led by a core study team that consists of the principal investigator (PI), a project manager, 10 expert nurses (ENs), a nursing team leader and a co-leader (EN team leader), and an administration assistant. The wider study consortium will consist of eight institutions, whose responsibilities are shown in Table 1. An external advisory board, led by the University of Cologne, with representatives from various stakeholders (patients, nurses, physicians, scientific experts, educational institutions, health insurances) will be responsible for overseeing and regularly advising on the conduct of the study. The University of Lübeck and the University of Cologne will be responsible for the process evaluation.

Table 1 Study consortium

In the HiH study, patients over 60 with multiple chronic conditions and complex care needs will be identified and recruited by their GPs and, following informed consent, referred to the team of ENs, who will be based at an independent ENC specifically set up for the purpose of the study. The ENs will be provided with a description of the individual patients’ health needs and GPs will delegate specific interventions to be carried out by the ENs. As part of their first home visit, the ENs will perform a comprehensive health assessment and will develop a care plan together with the patients and their relatives, adding to the list of care needs identified by the GP as required. ENs will visit the patients in their home at least monthly, for six months, with the aim of providing timely access to health care, improving care coordination with other providers, relatives and community networks, and supporting self-management and stabilisation of the patients’ health situation. The main anticipated outcomes of the HiH study are reduced number of GP home visits, and reduced number of avoidable hospitalisations over a period of three years. Patient-reported outcomes include quality of life and satisfaction with care received.

The process evaluation will be undertaken in consultation with the external advisory board. The board will be informed about the progress of the process evaluation on a three-monthly basis via face-to-face/digital/phone conferences alternating as required and will provide feedback regarding its progress and the interpretation of interim results. The board will also be involved in designing data collection instruments as per individual board members’ expertise. The process evaluation team will also work closely with the HiH core study team, as well as the wider project consortium such as the teams responsible for data management and outcome evaluation. This will reduce the risk of duplicate data collection.


The theoretical basis of the process evaluation is based on the Medical Research Council (MRC) Framework for the process evaluation of complex interventions [23]. Given the intervention’s complexity, several dimensions of influence need to be considered and evaluated in order to provide recommendations for further development or adaptation of the intervention and/or its implementation into practice. The outcomes of a complex intervention cannot be determined by single, simply reproducible actions alone and are influenced by the interplay of several factors. These include the theoretical background of the intervention, the intervention itself, the implementation of the intervention, mechanisms of impact (which in turn are all influenced by providers and recipients of the interventions), and the context in which the intervention will be delivered. The purpose of a process evaluation is to highlight individual components of each of these factors during a study investigating a complex intervention. The results can help determine why and how this complex intervention has led to certain outcomes and hence provide transferrable conclusions and guidance on further development and implementation.

Therefore, this process evaluation aims to collect data in order to:

  • describe the content of the intervention, and dose, reach, fidelity and adaptations of the implementation.

  • identify mediator variables for the development of the effect of the intervention.

  • identify relevant contextual factors for the implementation of the intervention.

  • describe process outcome parameters.

Prior to planning the specific data collection trajectory and instruments, a logic model to clarify and specify relevant theoretical assumptions on which the intervention is based, was developed. The logic model states assumptions underpinning the assumed effect, the intervention itself, the implementation of the intervention, potential mechanisms of impact, outcomes, and the context in which the intervention is delivered [16, 23] (Fig. 1). Relevant literature was considered to develop the logic model in collaboration with the core study team, the wider consortium, and the external advisory board, who all provided recommendations for refinement of the model.

Fig. 1
figure 1

Logic model

Sample and sample size

As the purpose of the process evaluation is to collect information on different research questions from diverse perspectives, data collection will be conducted with different participants and stakeholders involved in the study. Therefore, the target groups for qualitative and quantitative data collection will be all ENs employed at the time of data collection (n = 10 at the beginning of the study), EN team leaders (n = 2), the principal investigator (n = 1) and GPs involved in the study (n = to be specified). In order to represent the perspective of those indirectly or directly affected by the project, interviews will be conducted with randomly selected patients (n = 18 over the course of the study) and relatives (n = 18 over the course of the study) as well as health care professionals (n = 5 at each point of data collection) from other health care institutions in the region involved in the project. Sample sizes have been determined pragmatically taking into account the potential burden for participants. In addition, the perspective of the health insurance as a relevant stakeholder and that of the PTHV as provider and implementer of the Bachelor's programme are of interest, thus, two representatives of each institution will be interviewed at different times during the course of the project.

Data collection

Qualitative data will be collected face-to-face, by telephone or video-telephony, recorded verbatim and transcribed, with data anonymised during the transcription process. All data will be stored anonymously, only date and time of measurement will be documented, and will only be analysed at group level. Contact with patients and relatives will be coordinated via the EN team leader, so that personal data will only be used for contact after a declaration of consent has been obtained. Quantitative data (questionnaires of ENs, EN team leaders, PI, GPs) will be collected online using Lime Survey (LimeSurvey Community Edition, Version 3.27.2), quantitative patient-related data will be collected in the electronic patient documentation system (ePa) and made available by RWI.

Following the identification of key concepts and important factors, the data collection plan was developed (Fig. 2).

Fig. 2
figure 2

Gantt-Chart of data collection

To answer the different research questions and to get a better understanding of the effect of the intervention, a mixed-methods approach consisting of quantitative (questionnaires, clinical documentation) and qualitative (semi-structured interviews, focus groups, narratives, files/literature reviews) methods is used. This can be classified as an embedded approach in a mixed methods intervention design following Creswell & Plano Clark [5] (Fig. 3). Thus, quantitative Data will be collected and analysed before, during, and after the qualitative data collection. Narratives provided by the core study team in the form of reports, protocols, case studies and E-Mail correspondence will be collected and additionally assigned to the constructs of the logic model. Data collections are planned at the beginning, during, and at the end of the study aiming to capture potential developments and changes over time.

Fig. 3
figure 3

Embedded mixed-methods approach for the HiH Study [5]

Based on the logic model, the process evaluation is planned to provide an adequate number of data collections during the implementation of the intervention incorporating the perspective of all relevant groups of persons (GP, EN, patients, relatives, EN team leader, principal investigator) and stakeholders (representatives of health insurance and professional bodies as well as other health care professionals). This will provide sufficient information to allow for a comprehensive description of different mechanisms of action and achieve data saturation.

In line with the MRC framework [23], the details of data collection and content in each of the process domains and indicators are described below. All adjustments and changes in data collection (time points/methods) will be recorded with reasons in a tabular overview.

  1. 1.

    Intervention, theoretical frameworks and assumptions

    1. a.

      Development process

      This will include a description of the intervention development processes carried out by the HiH core study team, including theoretical foundations and consensus building in cooperation with the wider project consortium and members of the advisory board. The process included a first consensus of the intervention with a refinement after four months of intervention implementation that led to the final description of the intervention. This step was necessary to allow for further specification and adaptation of the individual intervention components to the clinical and sociodemographic characteristics of included patients and a better understanding of their needs.

    2. b.

      Description of the intervention

      The components of the intervention were described in detail using the “Template for Intervention Description and Replication” (TIDieR) checklist and guide [12]. Details of data collections related to the intervention are described in Table 2.

      Table 2 Data collection in the process domain “intervention”
  2. 2.


    In this section, aspects of reach, dose, fidelity and adaptation will be explored. Details of data collections pertaining to the process domain of implementation are described in Table 3.

    1. a.


      Fidelity will include the extent to which the intervention was implemented as planned. The training and orientation concepts will be described, including the necessary skills and competencies as well as how these are acquired.

    2. b.


      This refers to the extent to which the intended population will come into contact with the intervention. It will include strategies both to recruit participating GPs as well as recruitment strategies to include patients into the study and reasons for excluding patients at GP level. Barriers and facilitators of recruitment and strategies to address challenges with recruitment will be explored.

    3. c.


      This essentially will refer to the quantity of the intervention delivered. Data on the frequency and duration of care will be collected. Information will also be collected on communication channels and types of communication that directly affect care (particularly communication between the expert nurses and GPs).

    4. d.


      This will describe alterations and modifications to the intervention on an individual basis to achieve better contextual fit. Reasons for person-centred adaptations will be described.

    Table 3 Data collection in the process domain “implementation”
  3. 3.

    Mechanisms of impact

    In this section, the overarching mediator variables identified in the development of the logic model are described according to the following thematic foci: structure, (core)participants, interpersonal and (inter)professional relationships. Details of data collections pertaining to the process domain of mechanisms of action are described in Table 4.

    1. a.


      As it can be assumed that structural conditions influence the intervention, the following aspects are identified as relevant and thus will be investigated:

      • Resources available to the EN and their team leader (e.g. material equipment as well as Standard Operating Procedures)

      • Aspects of safety regarding practice in rural areas; emergency management, availability of supporting system

      • Frequency of care provided to participating patients by other caregivers (formal/informal)

      • Communication and documentation structures (e.g. formal communication structures; documentation of patient data in an electronic documentation system)

      • Geographical conditions/special features of the catchment area (e.g. size of the catchment area, distances between ENC and patient homes, availability of data infrastructures).

    2. b.

      Core Participants

      Core participants are directly involved in the intervention. These include the participating patients and GPs, the ENs and other persons involved in the care of the patients, e.g. relatives, nurses in nursing homes or other health care professionals. In Table 4, it can be seen that, depending on the topic, data collection will be conducted with both core participants and other relevant stakeholders and people involved in the intervention.

      1. (1)


        In addition to describing baseline characteristics, self-reported needs, expectations, and preferences regarding participants’ health care in general and the care provided by ENs, as well as individual resources and coping strategies, and patient acceptance of ENs will be assessed.

      2. (2)

        Expert Nurses

        As the expanded role of nurses in primary care in Germany is new and has therefore not been well studied, role and competency development, as well as the associated barriers and facilitators, will be a focus of the research. In this context, it is of interest how the ENs as well as the GPs will describe the degree of perceived autonomy. As aspects such as mentoring, supervision, team and networking are described as relevant factors of role development [14, 29], these will also be investigated.

      3. (3)

        General Practitioners

        Physicians' motivation to participate in the project, whether and what experience they will have regarding collaboration with nurses with expanded roles, their expectations, and their attitudes toward delegating tasks to ENs will be explored.

      4. (4)

        Other health care professionals

        The perspective of other health care professionals on a new role in the health care system as well as their experience with taking over this new role will be explored. Therefore it will be investigated what expectations exist, what interfaces will be described and how they will handle them. Furthermore, trying to identify factors that promote or hinder role development will be another aim.

    3. c.

      Interpersonal and (inter)professional relationships

      The interpersonal and (inter)professional relationships between all participants can be counted as important mechanisms of impact [7, 24, 26, 29]. Therefore, the relationships between ENs and patients, ENs and relatives as well as the relationships between ENs and GPs, within the EN team and with other health care professionals will be examined. In this context, the focus will be on the following criteria:

      • Role understanding and role clarity; e.g. the understanding of the role and responsibilities, and differences to other roles in the health care systems

      • Encouragement and empowerment; e.g. to what extend the ENs perceive support and empowerment, but also to what extend patients and relatives describe perceived encouragement

      • Shared-Decision making; e.g. to what extend ENs feel confident to involve patients in care planning und how patients/relatives perceive involvement

      • Empathy; e.g. if and how patients and relatives perceive empathy

      • Cooperation and collaboration; e.g. experienced cooperation between health care professionals and what factors they describe as facilitating and hindering

      • Accessibility; e.g. how ENs and GPs assess mutual accessibility

      • Communication; e.g. communication experienced between ENs and GPs, ENs and EN team leader, within the EN team as well as between ENs and patients/relatives

      • Trust; e.g. whether patients/relatives describe the relationship with the ENs as trusting

    Table 4 Data collection in the process domain “mechanisms of impact”
  4. 4.


    In this section, several external factors that may influence the intervention will be explored, including aspects on the macro, meso, and micro levels. As recruitment for the HiH study started during the emergence of the worldwide COVID19 pandemic, this as a relevant context factor in the process evaluation will be included. Details of data collections pertaining to the process domain of “context” are described in Table 5.

    1. a.

      Macro level

      Important aspects to consider here will be the German health system including legal frameworks pertaining to the professional practice of health care professionals. An attempt will be made to reflect on the interprofessional culture in healthcare in Germany. Also, structural features and geographic conditions that impact on the intervention will be considered. This will include the innovative feature of the ENC as well as the rural nature of the region.

    2. b.

      Meso level

      At the meso level, the following institutions and aspects will be of interest in describing the context:

      • Equipment, staffing and structure of the ENC

      • Characteristics of participating medical practices and current main challenges for GP practices in general

      • Unique features of setting, in which the intervention will be implemented (primary care setting)

      • Number of hospital admissions, rehospitalisation and potentially avoidable hospitalisations in the catchment area in relation to the patient group targeted by the intervention

      • Description of type and availability of services in the catchment area (community-based support services and allied health services)

      • Contents of the EN’s university course where the ENs complete their accompanying studies as well as investigation of the perspective of university representatives concerning further development of the professional role of nurses

      • Examination of the perspective of representatives of health insurances, considered to be of great importance in the implementation of new health care structures.

    3. c.

      Micro level

      To develop a good understanding of the micro-level context, the characteristics and other relevant aspects of potential participants (patients, relatives, nurses with expanded roles, GPs) on group level will be described. Since medical assistants with further training also work in primary care, their role and qualifications in comparison to ENs, as well as the possible overlaps in this area will also be described. In addition, other health care professionals involved in the project will be asked about factors they see as facilitating and hindering the implementation of the new role and the ENC.

    4. d.


      The COVID-19 pandemic and related measures unexpectedly have become a relevant context factor for this study. Therefore, the question will be addressed to what extent the pandemic influences the medical care of patients, the work of the ENs and the ENC as well as the collaboration with other health care professionals and the project as a whole. COVID-19 has been identified as a contextual factor after completion of the logic model and is therefore not included in the model.

  5. 5.

    Process outcomes

    The central topic of nursing role and competency development will be considered in the domain of process outcomes. Longitudinal data on the experience of participants over time will also be collected. Details of data collections pertaining to the domain of process outcomes are described in Table 6.

    1. a.

      Nursing role and competency development over time

      To explore role and competency development, the perspective of ENs as well as EN team leaders and PTHV representatives who are each involved in supporting role and competency development will be investigated. The perspective of the GPs and other health care professionals will be of interest with regard to changes in the delegation of tasks. Patients and relatives will be asked to what extent they can describe a change in the perception of the EN's role. Furthermore, it will be investigated to what extent different participants of the study (ENs, EN team leader, representative of the PTHV, GPs, and the principal investigator) and stakeholders (representatives of a health insurance) describe barriers and facilitating factors regarding role and competence development.

    2. b.

      Experiences of participants over time

      Of particular interest here will be the perspective of patients and relatives regarding the perceived care by ENs, differences and similarities compared to care provided by GPs and other health care professionals, and to what extent they perceive changes in their health status as well as the perceived empathy by ENs [24]. Furthermore, core participants as well as the principal investigator will be asked about perceived benefits and disadvantages for patients and relatives, GPs and ENs, for others, the region and the health care system as a whole [10].

      In addition, all participants will regularly be asked about their recommendations for long-term implementation and what they see as hindering and facilitating factors.

Table 5 Data collection in the process domain “context”
Table 6 Data collection in the domain “process outcomes”

Data analysis

Quantitative data will be analysed descriptively using IBM SPSS Statistics (IBM Corp. Released 2020, IBM SPSS Statistics for Windows, Version Qualitative data will be inductively-deductively analysed using QCAmap [22] and MAXQDA Standard 2020 (Release 20.0.8, VERBI GmbH Berlin). A qualitative thematic framework analysis will be conducted [25]. All data will be analysed iteratively so that emerging themes from early interviews, focus groups or questionnaires can be explored in later ones. As recommend in the MRC Framework, qualitative data will be combined with quantitative data relating to key process variables and process outcomes where it is to be expected that they influence the effect and function of the intervention [23]. The logic model will serve as framework for assigning the different perspectives and findings to the constructs of implementation, the mechanisms of impact, the context and the outcome parameters. Narratives will be integrated after an initial analysis of qualitative data has been completed.


The comprehensive process evaluation will enable to obtain important indications at different levels as to which hindering and facilitating factors need to be taken into account in the future. Because of the complexity and the need to gain the relevant insights, the challenge will be to limit the analyses to the core questions and handle the amount and potential incommensurability of data. To overcome this challenge, the logic model will provide orientation and structure and will help to focus [23].

The MRC framework addresses further key recommendations for process evaluations [23] that need to be discussed. As there will be a separation between the process and outcome evaluation, the methods and timing of the data collections with the institutions responsible for the outcome evaluation (RWI) were discussed in advance and synergies were identified. The cooperation and communication is constructive and trusting. In addition, a representative of the RWI is a permanent guest at the meetings of the advisory board. Advisory support was provided by the research team in the development of the intervention. If required, different aspects of the intervention and nursing sciences in general are discussed between the EN team leader and the research team. As the research team is aware of the need to remain credible evaluators, they will reflect their role and the potential impact on the research process regularly within the research team.

As the intervention, for which the TIDieR instrument was used [12], was discussed in detail in the project advisory board and between the HiH core team and the research team, a precise description of the intervention exists. Changes made after four months were recorded accordingly.

The recommended entry level for ANP is Master-level tertiary education (ICN, [13]). Given the late development of Master-level tertiary education for nurses and that there are still hardly any APNs working regularly in primary care in Germany, the implementation of the ENC comprising ENs with an additional tertiary nursing education at Bachelor-level can be an important intermediate step to advance the development of nurses with expanded roles. At this level, nurses are provided with the skills and competencies required for evidence-based expanded practice. At the same time, the roles for this type of practice will need to be developed and evaluated in terms of scope, effectiveness, and integration into the existing healthcare system. Such roles could pave the way for an expanded, autonomous nursing practice towards ANP implementation in Germany to improve care for older people with chronic illnesses. As this complementary role of nurses does not yet exist in this setting, there will be a special focus on the development of the role of the ENs and their competencies as well as their scope of practice within the process evaluation.

The chosen methodological approach has several advantages. The applied mixed methods approach allows to measure key variables quantitatively as well as qualitative. This will enable to build upon quantitative findings more precisely in interviews or focus groups. In addition, all core participants and relevant stakeholders will be interviewed several times during the course of the project, so that the perspectives at different levels can be considered. To avoid collecting unnecessary data, smaller purposively selected samples have been chosen.

It will be essential to integrate relevant unpredictable contextual factors such as the COVID-19 pandemic into the data collection, which is why all interviewees will be asked about the influence of the pandemic. In the course of data collection, some planned data collections needed and will need to be postponed due to the COVID-19 pandemic and some data collection methods were and will be adapted, i.e. changing from face-to-face to video interviews or from focus groups to individual interviews.

Availability of data and materials

Due to the conditions of informed consent with participants, the datasets generated and analysed during the process evaluation will not be publicly available. Please contact the corresponding author in case of reasonable requests.



Advanced Nursing Practice


Advanced Practice Nurse


Electronic Patient Documentation System


Expert Nurse


Expert Nursing Centre

EN Team leader:

Team leader of the expert nurses


General Practitioner


Health Care Professionals




Not applicable


Principal Investigator


Philosophisch-Theologische Hochschule Vallendar (Catholic University), Faculty of Nursing Science, Germany






RWI—Leibniz Institute for Economic Research

TIDieR Checklist:

Template for Intervention Description and Replication


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We would like to express our sincere thanks to the members of the advisory board for their valuable comments, constructive advice and wise, thought-provoking questions during the planning and implementation of the process evaluation.

Members of the advisory board:

Jutta Bartmann, AOK Rhineland-Palatinate/Saarland, Eisenberg, Germany

Prof. (em) Dr. Maria Blettner, Institute of Medical Biostatistics, Epidemiology and Informatics, Mainz, Germany

Dr. Simone Inkrot, Institute for Social Medicine and Epidemiology, Nursing Research Section, University of Lübeck, Lübeck, Germany

Hedwig François-Kettner, Patient Safety Alliance e.V., Berlin, Germany;

Prof. Dr. Sascha Köpke, Head of advisory board, University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Nursing Science, Köln, Germany

Dr. Klaus Korte, General Practitioners' Association Rhineland-Palatinate e.V., Koblenz, Germany

Dr. Daniela Lehwaldt, Academic Lead Nursing, School of Nursing, Psychotherapy und Community Health, Dublin City University, Dublin, Ireland—Incumbent Chair ICN NP/APN Network, Chair SG International of German Network APN (DNAPN)

Sandra Postel, Nursing Council Rhineland-Palatinate, Mainz, Germany

Prof. Dr. Claudia Schmidtke, Federal Government Commissioner for Patients' Affairs, Member of German Parliament Berlin, Germany

Dr. h.c. Franz Wagner, President of the German Nursing Council; Chief Executive Director of the German Nurses Association, Berlin, Germany

PhD (Dr. sc. med.) Franziska Zúñiga, Head of education and university lecturer, Nursing Science, Department Public Health, University of Basel, Basel, Switzerland

We would also like to thank Dr. Ingo Kolodziej, RWI Leibniz Institute for Economic Research, Essen, Germany, who enriches the advisory board as a permanent guest; Prof. Dr. Gunther Lauven, who as Principal Investigator of the HiH Study supported the implementation of the process validation in every way; Silke Doppelfeld, Head of the ENC, Stefanie Klein, Deputy Head, as well as all Expert Nurses who provide important insights by participating in the data collections.


The study is funded by the German Innovation Fund of the Federal Joint Committee (G-BA) (grant number: NVF17047). The funding institution will not interfere at any stage of the study design or process evaluation.

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Authors and Affiliations



SI, SSP und SK designed the process evaluation. SK is the scientific leader of the process evaluation. SI und SSP are responsible for the data management and conduction. SSP and SI drafted the manuscript. All authors read, provided important revisions and approved the final version of the manuscript.

Corresponding author

Correspondence to Swantje Seismann-Petersen.

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Ethics approval and consent to participate

The ethics committee of the Medical Association of Rhineland-Palatinate approved the study and process evaluation prior to the start of recruitment (NO. 2019–14563). All participants provided written informed consent.

Consent to publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Seismann-Petersen, S., Köpke, S. & Inkrot, S. Process evaluation of a multi-disciplinary complex intervention to improve care for older patients with chronic conditions in rural areas (the HandinHand Study): study protocol. BMC Nurs 21, 151 (2022).

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  • Process evaluation
  • Complex intervention
  • Logic model
  • Mixed methods
  • Study protocol
  • Primary care
  • Nursing
  • Advanced nursing practice
  • Role development