Abstract
Introduction
This study aimed to provide insight into the merits of DementiaNet, a network-based primary care innovation for community-dwelling dementia patients.
Methods
Longitudinal mixed methods multiple case study including 13 networks of primary care professionals as cases. Data collection comprised continuously-kept logs; yearly network maturity score (range 0–24), yearly quality of care assessment (quality indicators, 0–100), and in-depth interviews.
Results
Networks consisted of median nine professionals (range 5–22) covering medical, care and welfare disciplines. Their follow-up was 1–2 years. Average yearly increase was 2.03 (95%-CI:1.20–2.96) on network maturity and 8.45 (95%-CI:2.80–14.69) on quality indicator score. High primary care practice involvement and strong leadership proved essential in the transition towards more mature networks with better quality of care.
Discussion
Progress towards more mature networks favored quality of care improvements. DementiaNet appeared to be effective to realize transition towards network-based care, enhance multidisciplinary collaboration, and improve quality of dementia care.
Introduction
Chronic conditions like dementia pose a great challenge to health care systems.[1] Primary care for community-dwelling dementia patients is multifaceted, especially in later stages in which the disease affects many aspects of the lives of patients and their informal caregivers. Medical issues fall under responsibility of the primary care physician (PP), but many patients also require other forms of care and support such as home care, nursing care, and temporary involvement of allied health professionals. Subsequently, patients often require case management to ensure continuity and availability of services, and primary care professionals are increasingly urged to work in a multidisciplinary manner.
In Dutch primary care system (Box 1), various care professionals are involved in care for community-dwelling people with dementia including medical disciplines (primary care physician, elderly care physician), care disciplines (community nurse, case managers), and social disciplines (social workers, caregiver supporters), who often work at different organizations. All Dutch inhabitants are registered at a primary care practice (PCP). Patients often have the same PP over many years resulting in long, trusting relationships. The PP has a gatekeeper function, has a generic perspective, and continues to be a key professional in the care for people with dementia. The Dutch care system is adapting to major policy changes, including widespread closing of elderly homes, a move towards a participatory society with incentives to stay at home longer, and stimulation of market mechanisms in health care. These trends have resulted in fragmentation, lack of expertise on dementia and multi-morbidity among primary care professionals, and unintended regional variation in care–characteristics that also exist in many other high-income countries.
Box 1. Primary care in the Netherlands
Primary care for community-dwelling dementia patients in the Netherlands
Community-dwelling dementia patients receive care from multiple care professionals, including medical disciplines (primary care physician, elderly care physician), care disciplines (community nurse, case managers), and social disciplines (social workers, respite care workers).
All Dutch inhabitants are registered at a primary care practice in close vicinity to where they live. Primary care physician referral is needed for specialist care. Indications to obtain home care are provided by municipalities or district nursing organizations.
All Dutch inhabitants are obliged to have health care insurance and are free to choose between various private health care insurance companies. There is fragmentation in finances of services: Primary care, home care and nursing care are part of insurance and are paid for directly by private health care insurance companies; the organization and financing of social care is the responsibility of municipalities; case management is paid for by insurance companies, and exists in multiple formats and may be independent or part of home care organizations.
Several national guidelines and documents are available on primary dementia care arrangements in the Netherlands, including guidelines for the primary care practice, a national standard for multidisciplinary dementia care, and agreements describing collaboration between the primary care practice and home care and elderly care physicians. Despite availability, uptake of and compliance with these documents in practice is low.
Dementia care on a local level is determined by national, regional and local policies as well as existing facilities and by individual initiatives undertaken by the healthcare professionals. As a result, services and quality of local care are highly variable throughout the Netherlands.
National and international efforts to improve dementia care have shown some promising results[2, 3], but room for improvement remains. Interventions targeting specific suboptimal aspects of the care system so far lacked effectiveness because they did not comprehensively improve the integration and continuity of dementia care.[4, 5] For instance, interventions targeting care coordination, early diagnosis or educational interventions aimed at expertise of primary care physicians did not lead to desired outcomes.[4, 6] It is likely that the health care system itself requires adaptation as well, since improvement of individual components is not effective in improving dementia care.
This insight led to the development of DementiaNet. DementiaNet is an innovative primary dementia care approach that targets the transition towards network-based primary care by forming networks of professionals, who are supported in their change efforts.[7] It embodies a complex health care innovation, given the multiple interacting components of the program, the required behavioral changes of professionals, and the high degree of flexibility required to adapt to different local circumstances.[8] The implementation context is also highly complex, as it involves many different stakeholders (e.g. care professionals, municipalities, insurers, government). This high degree of complexity results in unpredictability of the expected changes and warrants an appropriate perspective on its evaluation. Hence, instead of asking whether an intervention works, evaluation should be aimed to identify if and how it contributes to reshaping a system in favorable ways.[9] In order to gain insight into such effects and to facilitate evidence-based primary care, an evaluation study was performed. This study aimed to answer the following questions: what are the merits and drawbacks of the DementiaNet approach; how are these achieved; and which factors influence these processes?
Methods
DementiaNet networks
DementiaNet encompasses a transition towards high quality, network-based care organized at a local level. The program’s key strategy is practice facilitation, a promising approach to supporting care redesign in which trained facilitators support primary care professionals.[10, 11] Multidisciplinary networks of primary care professionals are formed, which jointly provide care to a number of dementia patients. Desirably, networks include at least one professional of the medical (e.g. PPs), care (e.g. community nurses) and welfare (i.e. social workers, case managers) discipline. Inclusion of professionals is defined by the networks themselves and tailored to local sources and needs. As a consequence, each network is different in terms of size, represented disciplines, starting level of collaboration and quality of care.
The DementiaNet program consists of fixed and tailored elements.[7] The following four key components were applied in each network. Firstly, a transition towards network-based care was initiated, aimed at structural instead of ad hoc collaboration. According to a contingency approach on interprofessional practice typology, network-based care is a type of structured collaboration in which coordination is the most essential component. This is most suited for the primary care setting, where clinical work is more predictable and less urgent than in a hospital setting.[12] Secondly, one or two professionals in each network took on the role of network leader and were supported in this leadership role via individual and group coaching. This coaching enabled them to stimulate and facilitate multidisciplinary collaboration and improvement actions. Coaching was performed by two experienced trainers with backgrounds in primary care, who were trained on the job by experts on interprofessional learning. Thirdly, networks followed the Plan-Do-Check-Act method for quality improvement based on jointly identified improvement goals. Fourth, interprofessional training and practice-based learning were used to increase knowledge and competencies on dementia care and multidisciplinary collaboration. Since each network and their context varied, various aspects of DementiaNet were tailored to the local setting and needs, including actual improvement goals and plans, content of the interprofessional training and extent of leadership coaching. The DementiaNet networks provided care for the all community-dwelling dementia patients registered at the PCPs in the networks. Care tasks start when first signals of cognitive decline are present and professionals are contacted, throughout diagnostic process, and continues until a patient is in the later stages up until institutionalization in a care facility or death.
The enrollment of networks in the DementiaNet program was aimed at early adopters. Through various media, the start of the program was announced and motivated primary care professionals were invited and supported to initiate the formation of a local network.
Study design
To fit the complexity of DementiaNet as a multi-faceted innovation embedded in a complex health care setting, a longitudinal mixed methods multiple case study was chosen (further elaborated in study protocol[13]). Each DementiaNet network served as a case with follow-up up to 24 months. This design fits the description of comparative case studies, in which qualitative and quantitative data are collected from multiple sources and integration of both types of data is performed to leverage the strengths of both.[14] Joint interpretation allows new insights to arise, beyond the information gained from separate sources.[15, 16] The study protocol was submitted for review to the medical ethics committee region Arnhem-Nijmegen, and they declared that formal judgment was not required (protocol number: 2015–2053). No informed consent was required.
Data collection
Multiple sources of data were collected during the study period study period (January 2015–July 2017) for all networks: logs were kept continuously for network narratives, quantitative data was collected at baseline and yearly, and qualitative data after 12 months.
Network narratives
A log on each network was kept with characteristics of the network and members, including the number of professionals and disciplines involved. Also, data was collected on the formation of the network and change efforts, with information on process and actions undertaken before enrolment; on collaboration at baseline and changes over time; on improvement goals, actions and achievements as part of quality improvement; and any specifics that may influence development over time.
Network maturity
As part of yearly assessments, structured interviews were held with network leaders with topics based on the Rainbow Model of Integrated Care to assess network maturity.[17] The global network maturity score (range 0–24) was derived by rating 8 items (population-based care, person-focused care, clinical integration, professional integration, organizational integration, system integration, functional integration, normative integration) on a scale with predefined levels (score 0–3). Rating was performed independently by two researchers (AR,TK), after which consensus was reached on each item. Higher scores indicate higher maturity. No psychometric properties of this score are reported in literature yet.
Quality of care
Prior to the study, an expert panel developed a set of 13 quality indicators (QIs) based on available dementia care guidelines and agreements, which was pilot-tested by primary care professionals for feasibility, relevance, and comprehensiveness.[13] Prior to analysis, baseline scores on the initial set of QIs were reviewed for appropriateness, taking into account feedback from the networks, missingness, floor and ceiling effects, and coherence with definitions. This led to a final, more concise set of six QIs: proportion of patients with (1) involvement of case management; (2) dementia diagnosis in primary care setting; (3) recent geriatric assessment; (4) recent consideration during a multidisciplinary meeting; (5) recent polypharmacy check; and (6) average number of emergency consultations per year.
Data on these QIs were reported for shared dementia patients of each network and collected yearly via a registration document, which was completed by a network member based on information as registered in electronic patient files. Sum score were constructed by averaging scores on each indicator, yielding a total score between 0 and 100 (higher scores indicating better quality).
Experiences and perspectives
Semi-structured interviews were held with professionals to obtain insight into experiences with and perspectives on DementiaNet, until data saturation was achieved. A purposive sample of professionals (n = 9) from networks that had been participating for at least one year were invited for interviews, securing input from multiple networks and different disciplines. A trained qualitative researcher (IM) performed the interviews using a topic list and performed a member check after the interviews.
Analyses
Quantitative analyses were performed in R (package lme4). Interview transcript analysis was performed in Atlas.ti.
Quantitative analysis
For all 13 networks, the global network maturity score and quality of care sum score were calculated at start and 12 months and for 6 networks also at 24 months. These scores were used for quantitative analysis to assess overall changes in network maturity and QI scores over time by means of mixed regression models to account for repeated measures (random intercepts per network, fixed effect for time). Association of network maturity with QI scores was assessed.
Qualitative analysis
Logs were processed into narratives of each network by three researchers (AR, MN, MP). Transcripts from the semi-structured interviews were independently coded by two trained researchers (AR, IM), after which both coding schemes were jointly reviewed to reach consensus. Subsequently, codes were categorized to identify major themes. Quotes belonging to each major theme were independently reviewed to draw overall findings per theme, after which a consensus round yielded the overall findings.
Integration
Trends on network maturity and QI scores of each individual network were jointly considered with narratives of each network, in order to identify possible explanations for (lack of) change. Both qualitative and quantitative data were presented in a joint display (table) that simultaneously arrays the quantitative and quantitative results, in order to integrate the data by bringing the data together through a visual means to draw out new insights beyond the information gained from the separate quantitative and qualitative results.[14] Networks with similarity in specific aspects of quantitative data were identified and compared based on the narratives to explain patterns, i.e. comparisons prompted by quantitative patterns. Such comparisons included: networks with comparable but low starting levels of network maturity, with some showing enormous increase and others only minor increase, networks with improvement in network maturity, with some showing accompanied improvement in quality of care and others not, and networks with declining levels of quality of care. Networks were grouped based on common characteristics to explore the influence on trends in quantitative measures, i.e. comparisons prompted by characteristics and narrative patterns. Characteristics that were considered included: whether it concerned a new or existing collaboration, the level of collaboration upon start in the study, the type of improvement goals, strength of leadership, the catchment area size of the networks, and size of the network. Also, networks with highly promising experiences (best practices) and networks that have failed were reviewed more in-depth. Additionally, findings of quantitative analysis in combination with narratives were compared to the findings from semi-structured interviews to identify convergence or divergence among topics and to identify how these complemented each other. Integration was carried out based on consensus (AR, MN, MP, MvdM) and verified by the other authors.
Results
DementiaNet networks
Seventeen networks started between January 2015 and June 2016. Four of them ceased active participation within the first year. Reasons were either related to lack of intrinsic motivation (e.g. participation was initiated by local government) or lack of time, resulting in insufficient momentum for a transition process. Hence, results refer to 13 networks.
The median number of professionals in the networks was 9 (range 5–22). The composition regarding disciplines varied, with PPs, practice nurses, case managers, and community nurses being most represented. Eleven networks included professionals from medical, care, and welfare disciplines. All networks were followed for at least one year, and six for two years, resulting in total in 19 yearly evaluations. A detailed description of each network’s characteristics and proceedings is described in Table 1.
Table 1. Characteristics and narrative summaries of the primary care networks in the DementiaNet program.
| Network | Compo-sition at start | Number of network members (number of disciplines) | Collaboration | Network leaders | Catch-ment area | Network maturity score (start; year 1; year 2) | Quality of care score (start; year 1; year 2) | Caseload of patients (start; year 1; year 2) | Improvement goals (year) | Narrative summary |
|---|---|---|---|---|---|---|---|---|---|---|
| A | 1 CM; 2 CN;1 GS; 1 PP; 1 PN. | 6 (5) | Existing collaboration | CM, PP | Small | 23.0; 25.5; 24.0 | 89.7; 94.8; 94.7 | 13; 17; 22 |
|
|
| B | 2 CM; 3 CN; 1 GS; 1 OT; 3 PP; 1 PT; 2 WF; 1 other. | 13 (8) | Existing collaboration | CM, CN | Large | 12.0; 14.0; 14.5 | 45.6; 50.6; unknown | 19; 16; unknown |
|
|
| C | 1 CM; 9 CN; 2 GS; 3 MM; 1 PP; 1 PN; 3 WF; 1 other. | 22 (8) | Existing collaboration | PP, PN | Large | 14.0; 16.0; 15.0 | 71.4; 71.8; 76.9 | 35; 25; 30 |
|
|
| D | 1 CM; 4 CN; 1 MM;2 PP; 2 WF. | 10 (5) | New collaboration with unacquainted members | 2 CNs | Large | 8.5; 9.0; 11.5 | 41.1; 47.2; 40.0 | 15; 12; 9 |
|
|
| E | 1 CM; 2 CN; 2 GS; 2 PP; 1 PN. | 8 (5) | Relatively new collaboration | CM, PN | Small | 10.0; 12.0; 14.0 | 42.9; 77.8; 68.5 | 7; 9; 13 |
|
|
| F | 1 CM; 1 CN; 2 PP; 2 PN; 1 other. | 7 (5) | Relatively new collaboration | CM, PN | Large | 9.0; 13.5; 16.5 | 48.2; 59.2; 79.7 | 12; 21; 31 |
|
|
| G | 7 CN; 1 OT; 1 PT. | 9 (3) | New collaboration with unacquainted members | 2 CNs | Large | 10.5; 9.0 | 70.8; 60.8 | 4; 5 |
|
|
| H | 1 CM; 2 CN; 2 PP; 1 WF. | 6 (4) | Existing collaboration | CN, PP | Small | 19.0; 22.5 | 40.7; 75.5 | 28; 28 |
|
|
| I | 1 CM; 6 CN; 1 OT; 2 PP; 4 WF; 2 other. | 16 (6) | New collaboration | CN | Large | 9.5; 10.0 | 53.6; 54.4 | 28; 25 |
|
|
| J | 1 CM; 1 CN; 1 MM;1 PP; 1 PN. | 5 (5) | New collaboration with unacquainted members | CN | Small | 10.5; 16.5 | 52.8; 56.3 | 18; 16 |
|
|
| K | 2 CM;2 CN;1 MM;1 OT;1 PT;2 WF;3 other. | 12 (7) | New collaboration with unacquainted members | OT, WF | Small | 10.5; 16.5 | 45.1; 50.0 | 8; 11 |
|
|
| L | 1 CM; 8 CN;2 PP. | 11 (3) | New collaboration | CM, CN | Small | 12.0; 16.5 | 39.9; 87.7 | 22; 30 |
|
|
| M | 1 CM; 4 CN; 1 GS; 1 PP; 1 PN; 1 WF. | 9 (6) | New collaboration | PN | Small | 10.0; 15.5 | 59.2; 59.4 | 11; 16 |
|
|
Catchment area: area from which the network attracts its patient population, defined by geographical size and population distribution and density; large = more than approximately 5,000 persons.
PP = primary care physician; PN = practice nurse; CM = case manager; CN = community nurse; GS = geriatric specialist; OT = occupational therapist; PT = physiotherapist; MM = management or municipality; WF = welfare worker.
Network maturity and quality of care
The individual network trajectories in network maturity and QI scores over time are shown in Fig 1A and 1B. In total, 19 yearly evaluations were completed with network maturity scores, of which 16 showed improvement and 13 increased more than 2 points. The networks completed 18 evaluations with QI scores, of which 14 showed improvement (10 evaluations with an increase of over 5 points). Improvements in network maturity were accompanied by an increase in QI scores in 13 of 15 cycles.
Fig 1.
A) Trajectories of all networks over time on network maturity; B) Trajectories of all networks over time on quality of care. Networks are indicated by letters A to M and correspond with letters in Table 1.
The regression model with network maturity as dependent variable showed an estimated increase of 2.03 (95%CI 1.20–2.96) in network maturity per year in the networks. The regression model with QI scores as dependent variable showed an average increase of 8.45 (95%CI 2.80–14.69) per year in the networks. When extending the latter model by including the network maturity score as a time-varying predictor, the QI scores indicated to be positively associated with network maturity (2.11; 95%CI 0.89–3.33).
Experiences with DementiaNet program
Collaboration
In general, care professionals perceived that participation resulted in shorter communication channels, higher acquaintanceship with each other’s disciplines as well as personally, increased overview of local professionals and easier access to other disciplines, such as occupational therapists and physiotherapists.
Care processes
Perceived impacts of DementiaNet on care were: increased and more active monitoring of individual dementia patients as well as at population level of older patients, introduction and improvement of multidisciplinary meetings, increased expertise in diagnostics subsequently resulting in more and earlier diagnoses, a shift towards diagnostics in primary care instead of referral to expert clinics, increased person-centered care regarding care needs of patients and informal caregivers, and better coordination of different care services.
Benefits for professionals and patients
Perceived benefits for professionals included more awareness about dementia in general and feeling more competent to care for people with dementia. Regarding the network collaboration, professionals experienced a more profound feeling of shared goals and visions, easier and more efficient collaboration among involved care professionals, and improved coordination of care. Professionals reported no disadvantages and felt that patients and their informal caregivers gained benefit from better-timed and more efficient processes regarding the diagnosis.
Contextual factors
Conditions that enhanced collaboration included a sufficient size of shared patient caseload, practice-based learning that transcends boundaries of individual disciplines and networks, concrete agreements about communication, and working in close proximity to other professionals, preferably in the same building. Factors to stimulate continuity of care were integration of services from different disciplines by means of multidisciplinary meetings and multidisciplinary care plans, and short communication channels between all involved care professionals (i.e. by shared infrastructure to exchange information). The presence of active and capable network leaders seemed to play a key role in achieving actual improvement goals.
Integration
Joint interpretation of the multiple data sources led to the identification of several patterns (Table 2, Figs 2–7). Although most networks increased in network maturity, patterns showed that those networks that started with professionals who were already acquainted with each other to some extent, were more likely to increase on QI scores. Unacquainted networks were more likely to choose improvement goals focusing on initiating their network and collaboration, whereas more acquainted networks were already able to work collaboratively on actual care processes.
Table 2. Inferences from joint interpretation of data sources.
| Patterns prompted by quantitative findings | |
| Networks starting at low quality of care |
|
| Network maturity as prerequisite to increase quality of care |
|
| Declining quality of care |
|
| Patterns prompted by network characteristics | |
| Strength of leadership |
|
| Improvement goals and starting level of collaboration |
|
| Catchment areas |
|
| Patterns prompted by success of networks | |
| Best practices |
|
| Unsuccessful networks |
|
Fig 2.
A) Network maturity trajectories of all networks; solid lines are networks with relatively low starting level of quality of care but with strong improvement; dashed lines are networks with equally low starting level of quality of care, but no susbtantial improvement. Networks with solid lines where characterized by high involvement of the primary care practice, network leaders in the primary care practice and operating in rural areas, and; B) quality of care trajectories.
Fig 7.
A) Network maturity trajectories of all networks; dashed lines are networks with above average catchment areas, solid lines are networks with smaller catchment areas. Solid lines show more increase than dashed lines, and; B) quality of care trajectories.
Fig 3.
A) Network maturity trajectories of networks that have shown considerable improvement on network maturity, but no substantial improvement on quality of care, reflected in improvement goals that were focused on collaboration and network strength, and; B) quality of care trajectories.
Fig 4.
A) Network maturity trajectories of networks with decreasing quality of care scores: solid lines are networks that had various problems leading to a decrease in quality of care, and; B) quality of care trajectories.
Fig 5.
A) Network maturity trajectories of networks with suboptimal leadership and display no substantial improvement on network maturity or quality of care, and; B) quality of care trajectories.
Fig 6.
A) Network maturity trajectories of all networks; improvement goals and starting level of collaboration: dashed lines are networks with existing collaborations; solid lines are networks with new collaborations. Dashed lines indeed start at higher levels of network maturity, and; B) quality of care trajectories.
The PCP was identified as an essential element of successful network-based care. Patterns showed that networks with highly involved PPs performed better than those without or with only little involvement. Especially, those networks in which leadership was assigned to staff working at the PCP (i.e. PP or practice nurse) improved. These findings were also confirmed in the two best performing practices, in which primary care practice involvement seemed to play a central role in their success.
Leadership in general was an important prerequisite for success. Networks that experienced problems with leadership and those without competent leaders showed no or only minor improvements. Furthermore, lack of accurate leadership was possibly one of the factors leading to decreases in QI scores and network maturity, along with not having all key disciplines involved in the network and interpersonal problems among network members.
The area in which networks operated seemed to influence network sizes and the magnitude of improvement: networks with larger catchment areas, on average, showed higher numbers of involved professionals, likely as a result of higher numbers of care providers operating in those catchment areas. This increases the complexity of collaboration and also decreases the shared caseload between several professionals in these networks. Networks from smaller catchment areas displayed increased progression of network maturity and QI scores.
Discussion
Seventeen networks were successfully established of which 13 accomplished one or more active years in the DementiaNet program. Overall, this multiple case study showed an increase in both network maturity and quality of care and a positive association was indicated between these measures. Multidisciplinary collaboration, communication, and coordination of care improved according to healthcare professionals in the networks, and DementiaNet enabled them to beneficially impact care. Importantly, prerequisites for successful transition towards more mature and integrated networks were identified.
These findings indicate that most DementiaNet networks successfully transitioned towards a more mature and integrated network. The estimated overall change over time in network maturity per year in the program was approximately two points and estimated change in QI scores was approximately 8.5 points. To illustrate practical relevance, this might indicate that in a single year, a network progresses two levels on the maturity model (e.g. from ad hoc to defined professional and clinical integration). For quality of care this implicates, for example, that more patients were discussed during multidisciplinary meetings. These results show beneficial impact, even after only one active year in the program. As the yearly evaluations reflect an iterative transition process, maximal effects are not realistically expected in such a short time frame. Therefore, likely, larger effects may be expected in the long term, as major change emerges from aggregation of marginal gains.[18]
Several enabling factors for the successful transition to network-based care were identified. These factors included strong and adequate leadership (preferably with leaders from primary care practice), high involvement of motivated PPs, high acquaintanceship with other network members, and network size with a compact network that operates in a relatively small geographical area. These empirical findings corroborate with theoretical models on primary care collaboration.[17, 19]
DementiaNet was developed from a system-level perspective to fit the complexity of clinical practice. Lessons from previous successful redesign efforts have shown that it is unlikely that single stakeholders can create a highly functioning system.[18] Indeed, some previous studies have shown that programs aimed at single aspects of care (e.g. lack of expertise) have had limited to no effects on the care system.[20, 21] Following from complexity theory, this may not be surprising, as changes on multiple levels are needed to ensure change on the system as a whole.[22, 23] In line with this assumption, studies targeted at a more comprehensive level, for example case management intensity and health and social services integration, resulted in beneficial effects for dementia patients.[24] Also, other collaborative care models employing a system-wide approach such as the Aging Brain Care Medical Homes in the US and the German Delphi-MV study, have shown positive results.[2, 22, 25, 26]
The major strengths of the DementiaNet program were the simultaneous focus on various essential aspects of high-quality network-based care, the practice facilitation approach with support at local level with local leadership, and its flexibility to be modified to varying circumstances of each individual network. Also, being able to choose and set their own goals appeared to be a major advantage of the program and motivated network member to work on improvements.
Multilevel programs are needed to achieve meaningful impact on healthcare systems,[9] yet, evaluation is challenging, especially when innovations are implemented in a complex setting as daily clinical practice.[27, 28] The current evaluation study succeeded in including the flexibility and individualization of the approach, and in identifying generalizable factors between networks. Its mixed methods design allowed for consequences of complexity such as unpredictability in outcomes, by ensuring an open view.[9] Also, the interviews provided relevant insights on the process of change, and allowed to include unanticipated effects (a feature of complex systems) as well. Moreover, the multiple case study design permitted for the analysis of group effects and to simultaneously study individual networks more closely to identify mechanisms and contextual factors that stimulated or hindered change.
This study had some limitations, starting with the relatively limited follow-up. The DementiaNet approach necessitates considerable changes in behavior and practice from large numbers of actors; such adaptations require time. Integration of data revealed the pattern that relatively immature networks had to define collaborative efforts first before changes in care processes could be addressed. This underlines the importance for endured time to mature for networks, especially in those that start as fully new collaborations. Even though major changes have been observed, longer follow-up is needed to show sustained effectiveness. Another limitation is the fact that the quality indicators used in this study were newly developed. Nonetheless, the initial set of QIs was rigorously developed through multiple consensus rounds and based on existing guidelines and agreements[13], and its face validity was assessed before application in this study. Furthermore, QIs were reviewed prior to analysis for coherence, missingness and floor and ceiling effects.
These findings might well be used to inform future application of network-based approaches, like for example care for frail elderly, where similar professionals are involved. For that purpose, the achieved diversity in the networks studied (i.e. newly or existing collaboration, small and large network size and catchment areas) is a valuable property in two ways. First, these multiple different networks have ensured information based on wide diversity of healthcare professionals and local settings. Secondly, it has shown that the design of DementiaNet allows for adaptation to local complexity and individualization, which might serve as a basis for translation to other populations and various settings as well. When research findings of the current study are to be applied to other settings, the context needs to be taken into account, as this plays an important role in the success of the DementiaNet program. By providing detailed contextual information, application to other settings is facilitated.
To conclude, the DementiaNet program resulted in a successful transition towards more integration in primary care networks, which was accompanied by an overall increase in quality of dementia care. Collaboration between network members from different disciplines and coordination of care improved. Explanatory mechanisms were involvement of the primary care practice, strong leadership and network catchment area and size. These transitions appear to benefit patients and informal caregivers, as well as primary care professionals. The use of a longitudinal mixed methods multiple case study revealed a complete and integrated picture of effectiveness, and can therefore contribute to the increased use of innovative research designs for the future evaluation of complex interventions.
Acknowledgments
The authors would like to thank Irma Maassen (IR) and Thamar Kroes (TK) for their efforts related to the interviews, the qualitative analysis, and interview ratings.
Data Availability
All relevant data are within the paper.
Funding Statement
This study was funded by Alzheimer Nederland (project number WE.09-2013-04 to MOR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
References
- 1.Wimo A, Jonsson L, Bond J, Prince M, Winblad B. The worldwide economic impact of dementia 2010. Alzheimer’s & dementia: the journal of the Alzheimer’s Association. 2013;9(1):1–11.e3. Epub 2013/01/12. doi: 10.1016/j.jalz.2012.11.006 . [DOI] [PubMed] [Google Scholar]
- 2.Callahan CM, Boustani MA, Weiner M, Beck RA, Livin LR, Kellams JJ, et al. Implementing dementia care models in primary care settings: The Aging Brain Care Medical Home. Aging & mental health. 2011;15(1):5–12. Epub 2010/10/15. doi: 10.1080/13607861003801052 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Wubbeler M, Thyrian JR, Michalowsky B, Erdmann P, Hertel J, Holle B, et al. How do people with dementia utilise primary care physicians and specialists within dementia networks? Results of the Dementia Networks in Germany (DemNet-D) study. Health & social care in the community. 2017;25(1):285–94. Epub 2016/01/12. doi: 10.1111/hsc.12315 . [DOI] [PubMed] [Google Scholar]
- 4.Iliffe S, Wilcock J, Drennan V, Goodman C, Griffin M, Knapp M, et al. Changing practice in dementia care in the community: developing and testing evidence-based interventions, from timely diagnosis to end of life (EVIDEM). Changing practice in dementia care in the community: developing and testing evidence-based interventions, from timely diagnosis to end of life (EVIDEM). Southampton (UK): NIHR Journals Library; 2015. [PubMed] [Google Scholar]
- 5.Iliffe S, Waugh A, Poole M, Bamford C, Brittain K, Chew-Graham C, et al. The effectiveness of collaborative care for people with memory problems in primary care: results of the CAREDEM case management modelling and feasibility study. Health technology assessment (Winchester, England). 2014;18(52):1–148. Epub 2014/08/21. doi: 10.3310/hta18520 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Boustani M, Callahan CM, Unverzagt FW, Austrom MG, Perkins AJ, Fultz BA, et al. Implementing a screening and diagnosis program for dementia in primary care. Journal of general internal medicine. 2005;20(7):572–7. Epub 2005/07/30. . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Nieuwboer MS, Richters A, van der Marck MA. Triple aim improvement for individuals, services and society in dementia care: The DementiaNet collaborative care approach. Zeitschrift fur Gerontologie und Geriatrie. 2017;50(Suppl 2):78–83. Epub 2017/02/22. doi: 10.1007/s00391-017-1196-4 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. International journal of nursing studies. 2013;50(5):587–92. Epub 2012/11/20. doi: 10.1016/j.ijnurstu.2012.09.010 . [DOI] [PubMed] [Google Scholar]
- 9.Rutter H, Savona N, Glonti K, Bibby J, Cummins S, Finegood DT, et al. The need for a complex systems model of evidence for public health. Lancet (London, England). 2017. Epub 2017/06/18. doi: 10.1016/s0140-6736(17)31267-9 . [DOI] [PubMed] [Google Scholar]
- 10.Parchman ML, Noel PH, Culler SD, Lanham HJ, Leykum LK, Romero RL, et al. A randomized trial of practice facilitation to improve the delivery of chronic illness care in primary care: initial and sustained effects. Implementation science: IS. 2013;8:93 Epub 2013/08/24. doi: 10.1186/1748-5908-8-93 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Baskerville NB, Liddy C, Hogg W. Systematic review and meta-analysis of practice facilitation within primary care settings. Annals of family medicine. 2012;10(1):63–74. Epub 2012/01/11. doi: 10.1370/afm.1312 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Reeves S, Xyrichis A, Zwarenstein M. Teamwork, collaboration, coordination, and networking: Why we need to distinguish between different types of interprofessional practice. Journal of interprofessional care. 2018;32(1):1–3. Epub 2017/11/14. doi: 10.1080/13561820.2017.1400150 . [DOI] [PubMed] [Google Scholar]
- 13.Richters A, Nieuwboer MS, Perry M, Olde Rikkert MGM, Melis RJF, van der Marck MA. Evaluation of DementiaNet, a network-based primary care innovation for community-dwelling patients with dementia: protocol for a longitudinal mixed methods multiple case study. BMJ open. 2017;7(8):e016433 Epub 2017/08/07. . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Fetters MD, Curry LA, Creswell JW. Achieving integration in mixed methods designs-principles and practices. Health services research. 2013;48(6 Pt 2):2134–56. Epub 2013/11/28. doi: 10.1111/1475-6773.12117 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Guetterman TC, Fetters MD, Creswell JW. Integrating Quantitative and Qualitative Results in Health Science Mixed Methods Research Through Joint Displays. Annals of family medicine. 2015;13(6):554–61. Epub 2015/11/11. doi: 10.1370/afm.1865 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Shaw EK, Ohman-Strickland PA, Piasecki A, Hudson SV, Ferrante JM, McDaniel RR Jr., et al. Effects of facilitated team meetings and learning collaboratives on colorectal cancer screening rates in primary care practices: a cluster randomized trial. Annals of family medicine. 2013;11(3):220–8, s1–8. Epub 2013/05/22. doi: 10.1370/afm.1505 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Valentijn PP, Vrijhoef HJ, Ruwaard D, Boesveld I, Arends RY, Bruijnzeels MA. Towards an international taxonomy of integrated primary care: a Delphi consensus approach. BMC family practice. 2015;16:64 Epub 2015/05/23. doi: 10.1186/s12875-015-0278-x . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bohmer RM. The Hard Work of Health Care Transformation. The New England journal of medicine. 2016;375(8):709–11. Epub 2016/08/25. doi: 10.1056/NEJMp1606458 . [DOI] [PubMed] [Google Scholar]
- 19.D'Amour D, Goulet L, Labadie JF, Martin-Rodriguez LS, Pineault R. A model and typology of collaboration between professionals in healthcare organizations. BMC health services research. 2008;8:188 Epub 2008/09/23. doi: 10.1186/1472-6963-8-188 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Iliffe S, Wilcock J. The UK experience of promoting dementia recognition and management in primary care. Zeitschrift fur Gerontologie und Geriatrie. 2017;50(Suppl 2):63–7. Epub 2017/01/18. doi: 10.1007/s00391-016-1175-1 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Wilcock J, Iliffe S, Griffin M, Jain P, Thune-Boyle I, Lefford F, et al. Tailored educational intervention for primary care to improve the management of dementia: the EVIDEM-ED cluster randomized controlled trial. Trials. 2013;14:397 Epub 2013/11/22. doi: 10.1186/1745-6215-14-397 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Boustani MA, Munger S, Gulati R, Vogel M, Beck RA, Callahan CM. Selecting a change and evaluating its impact on the performance of a complex adaptive health care delivery system. Clinical interventions in aging. 2010;5:141–8. Epub 2010/06/03. . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Rutter H. The Complex Systems Challenge of Obesity. Clinical chemistry. 2017. Epub 2017/11/04. doi: 10.1373/clinchem.2017.272831 . [DOI] [PubMed] [Google Scholar]
- 24.Somme D, Trouve H, Drame M, Gagnon D, Couturier Y, Saint-Jean O. Analysis of case management programs for patients with dementia: a systematic review. Alzheimer’s & dementia: the journal of the Alzheimer’s Association. 2012;8(5):426–36. Epub 2012/01/31. doi: 10.1016/j.jalz.2011.06.004 . [DOI] [PubMed] [Google Scholar]
- 25.Thyrian JR, Hertel J, Wucherer D, Eichler T, Michalowsky B, Dreier-Wolfgramm A, et al. Effectiveness and Safety of Dementia Care Management in Primary Care: A Randomized Clinical Trial. JAMA psychiatry. 2017;74(10):996–1004. Epub 2017/07/27. doi: 10.1001/jamapsychiatry.2017.2124 . [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Dreier-Wolfgramm A, Michalowsky B, Austrom MG, van der Marck MA, Iliffe S, Alder C, et al. Dementia care management in primary care: Current collaborative care models and the case for interprofessional education. Zeitschrift fur Gerontologie und Geriatrie. 2017;50(Suppl 2):68–77. Epub 2017/04/02. doi: 10.1007/s00391-017-1220-8 . [DOI] [PubMed] [Google Scholar]
- 27.van der Marck MA, Bloem BR. How to organize multispecialty care for patients with Parkinson’s disease. Parkinsonism & related disorders. 2014;20 Suppl 1:S167–73. Epub 2013/11/23. doi: 10.1016/s1353-8020(13)70040-3 . [DOI] [PubMed] [Google Scholar]
- 28.Bloem BR, Munneke M. Evidence or clinical implementation: which should come first? The Lancet Neurology. 2014;13(7):649 Epub 2014/06/20. doi: 10.1016/S1474-4422(14)70118-8 . [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All relevant data are within the paper.







