Background
Technological innovations in health care have cured diseases, reduced harm and risk in surgical procedures, prolonged the average life expectancy and consequently increased demand for additional care with corresponding costs [
1,
2]. In many countries, policy makers and management believe that innovation, and especially the uptake of information technology (IT) innovations, will make a major contribution to improved efficiency in health care [
3]. Adoption of IT-innovations is supposed to create sustainable health care through increasing the efficiency of care processes and increasing the retention and attraction of employees by providing challenging and meaningful work.
However, contrary to these beliefs and despite an abundance of novel ideas and work practices, the implementation of innovations in hospitals is hampered [
4]; 10,000 new studies per year are published in MEDLINE, but many of these potentially beneficial IT-based [
5‐
7] innovations fail to reach the target groups and are not applied in daily practice. This failing may be understood by addressing the questions of who benefits from which innovation and who bears the costs. There are numerous examples of innovations implemented in health care that in hindsight failed to deliver obvious benefits [
8,
9], or for which the perceptions of the benefits vary between the actors involved [
10].
An innovation is a practice or object that is perceived as new by the actor who adopts it [
11]. We assume that an actor will adopt (start to use or implement) an innovation when the perceived benefits of using the innovation outweigh the perceived costs, and hence, the new practice or object is an improvement on the current situation. Grol et al. [
4] summarized the factors that affect the success of implementing change (including innovations) in health care: features of the innovation itself, features of the target group, features of the patients, features of the social setting, financial features, administrative and organizational context, and features of the methods and strategies for dissemination and implementation used [
4]. Successful technological diffusion of innovations is seen as the result of a process of mutual adaptation among technology producers, users, and external groups [
11,
12], and the system that adopts the innovation. The interplay of these factors can shape the properties of the new technology, the use of the technology, the organizational context, and the societal context.
Studies identify physicians as a barrier to be overcome in the implementation of, especially administrative, IT innovations [
13]. However, not all delay can be blamed on physicians since some of the IT software has noteworthy flaws, adding unnecessary costs to the adoption of innovation for the users [
14]. This may explain part of the users’ resistance or avoidance strategies [
15,
16]. These resistance or avoidance strategies may be inspired by political considerations and power struggles, which may affect the diffusion of innovations as much as more ’rational’ considerations such as benefits of the innovation [
17].
In this paper, we focus on one aspect of the social setting of adoption of innovations: stakeholders’ preferences regarding IT innovations and their expected benefits. Monetary costs may be an important cause for slow diffusion [
18]. In this study, however, the costs and benefits are broader than monetary. The costs to and benefits for the different actors will be at different levels of the innovation process: the environmental level (e.g., a benefit may be improved exchange of information; a cost may be renewing work flow with external partners); the organizational level (e.g., a benefit may be solving an organizational problem; a cost may be investment in new infrastructure, resistance in the organization, providing employees with new skills (training, education)); the social level (social support or negative attitudes of co-workers); the psychological level (feelings of improved self-efficacy or loss of control); and the user level (better quality of work, versus initially being less productive because a new way to work has to be learned) [
19,
20].
Stakeholders are known to disagree on the relative importance of innovations and may therefore use their resources to influence other stakeholders [
21] and resort to politics and power to affect implementation processes. Politics and the power balance between stakeholders may be particularly important for innovations that span a large part of an (health care) organization where multiple stakeholders holding different positions in the organization are mutually dependent in the implementation and utilization of the innovation. The different positions of stakeholders and the concomitant differences in priorities and agendas are likely to affect each stage of the implementation process. In all stages, from the first stage of experiencing and defining a problem, to looking for solutions, to balancing investments against the improvements and the evaluation, the differences in structural (stakeholder) positions will affect the costs and benefits for the different stakeholders and the consequent preferences and priorities of the stakeholders.
The understanding of differences in positions between stakeholders thwarting the implementation of innovations is not new but has received little attention in empirical research so far, as far as we know [
11,
22‐
24]. It has been argued that when the implementation of clinical information systems is purely seen as a technical implementation rather than a complex social implementation, the chances of failure are larger [
16,
25]. In some models, the presence of stakeholders is mentioned [
17], and studies have shown that when stakeholders disagree on the priority of the innovation, uptake will be difficult [
26]. Applying stakeholder theory [
27] to the implementation of innovations in health care, organizations may better understand why the diffusion of possibly valuable innovations proceeds more slowly than many stakeholders wish it would. Because of this slower diffusion, the potential benefits of IT innovations may be hampered unnecessarily.
The preference structures of the stakeholders are likely to be based on their perceived costs and benefits of the innovation. For instance, doctors misspelling diagnoses [
15] did not do so because they wanted to be rebels, but because their perceived costs of the time lost by clicking on pop-ups were higher than the added safety value of the warning of dangerous combinations of medicines. We expect to find similar cost–benefit estimations for other innovations and for other stakeholders, explaining their respective preference structures. In turn, we expect that when the differences between these preference structures become larger, the speed of diffusion of innovations will slow down.
The questions addressed by this paper are therefore: Do different stakeholders have different preference structures concerning the relative relevance of IT-innovations in health care? Can these differences be explained by differences in the costs and benefits associated with the innovations for the stakeholders?
Results
Importance of the decision criteria
Table
2 shows the importance of the decision criteria to the stakeholder groups. The priorities of all main decision criteria (efficiency, health gain, satisfaction and investment) and all sub-criteria related to the same main criterion sum up to one. The scores are to be interpreted as relative weights of importance; the higher the score, the higher the relevance of the criterion according to the stakeholder group.
Within the stakeholder groups, the consistency ratios are 0.02 for patients, 0.04 for nurses, 0.13 for physicians, 0.10 for managers, 0.03 for health insurers, and 0.02 for policy makers. All consistency ratios are acceptable.
Efficiency is emphasized most strongly by policy makers (0.46; being the highest value), while patients, nurses and physicians least emphasize the importance of efficiency (0.22, 0.21 and 0.20 respectively). Health gain is judged to be most important by health insurers, nurses and patients (0.43, 0.35 and 0.42 respectively). Satisfaction is relatively important according to physicians, managers and nurses (0.33, 0.33 and 0.31 respectively). For managers and physicians, satisfaction (particularly patient satisfaction) can be even the most important decision criterion in selecting IT innovations.
Preferences for the IT innovations
Table
3 shows the preferences of the different stakeholder groups for the IT innovations. A higher priority reflects a higher preference for this innovation. The priorities of all innovations add up to one. Results providing further insight into the distribution of priorities of individual respondents within each stakeholder group are presented as box plots in Additional file
3.
Table 3
Prioritization of innovations
Baseline innovation
| 0.05 | 0.05 | 0.05 | 0.05 | 0.04 | 0.05 |
Virtual consultation
| 0.08 | 0.09 | 0.08 | 0.09 | 0.11 | 0.09 |
Digital hospital portal
| 0.10 | 0.12 | 0.11 | 0.12 | 0.12 | 0.11 |
Planning operations
| 0.12 | 0.13 | 0.11 | 0.11 | 0.09 | 0.11 |
Telepathology
| 0.08 | 0.07 | 0.09 | 0.08 | 0.10 | 0.07 |
Barcodes
| 0.16 | 0.13 | 0.09 | 0.12 | 0.10 | 0.13 |
PDA
| 0.09 | 0.10 | 0.16 | 0.09 | 0.11 | 0.09 |
Telesurgery
| 0.08 | 0.06 | 0.07 | 0.06 | 0.09 | 0.06 |
Regional EPF
| 0.15 | 0.15 | 0.19 | 0.14 | 0.11 | 0.11 |
Self-tests
| 0.09 | 0.10 | 0.06 | 0.13 | 0.13 | 0.18 |
Patients appear to prefer medication barcodes and the regional electronic patient file (EPF), although their opinions on the value of the two innovations vary. Arguments are most strongly related to the perceived health gains and satisfaction resulting from the use of the two innovations.
Nurses also prefer most strongly the regional EPF and barcodes, together with planning software for operations. Similar to the patients, the nurses strongly differ in judgment about the expected value of barcodes and the EPF (see Additional file
3: Figure A2). The regional EPF is particularly valued because of its expected health gains and impact on satisfaction, the planning software because of the high satisfaction expected, and the barcodes because of the perceived health gains.
Physicians prefer the EPF most followed by the PDA because of their effects on satisfaction, health gains and efficiency. They particularly agree on the value of the PDA but less so on the value of the EPF.
Managers strongly prefer the regional EPF on account of its expected health gain and satisfaction, self-tests on account of the expected health gain, satisfaction and efficiency gain, and the digital hospital portal on account of the expected efficiency, satisfaction and health gain. No strong disagreements are found in the preference for the EPF, yet the value of self-tests is disputed among the managers.
Health care insurers prefer self-testing because of the expected efficiency and health gain, the digital hospital portal because of the low investment and efficiency gain, and the PDA because of its expected effect on satisfaction and health gain. Policy makers prefer self-testing on account of its expected increase in efficiency, barcodes on account of their health gains, and the digital hospital portal on account of the expected satisfaction to patients.
Policy makers strongly prefer self-tests, because of their strong, favorable effect on efficiency as expected by them. Self-tests are significantly favored over multiple other innovations (95% CI). This preference is followed by the preference for barcodes due to the expected health gain, and the digital hospital portal due to its expected effect on patient satisfaction.
Among the innovations, the regional EPF is in the top three preferences of four out of six stakeholders (patients, nurses, physicians and managers). However, the stakeholder most likely to bear a substantial part of the cost, the policy makers, did not appear to have much faith in this innovation at the time they filled out the questionnaire.
Even though preferences for barcodes strongly vary within most stakeholder groups, barcodes are among the top three preferences of four stakeholders (patients, nurses, physicians and policy makers). An important benefit of barcodes is perceived to be improved medication safety. Proper use will reduce incidents, and their resulting turmoil, (physical) damage and additional need for care. Policy makers, in particular, appear to be more unanimously convinced of this potential benefit.
A particularly large difference is found for digital hospital portals and self-tests. Managers, insurers and policy makers highly value these innovations, emphasizing their benefits, while the other stakeholder groups score these innovations lowly. The two innovations are clearly aimed at improving self-management and health care efficiency. These goals are important to the stakeholders who have to pay for the innovations (policy makers and insurers) and seem less important to the stakeholders who need to change their work practices because of increased self-management. Policy makers assigned a significantly higher priority to self-tests than patients did (95% CI).
Conclusions and discussion
The main questions of this paper were: Do different stakeholders have different preference structures concerning the relative relevance of IT-innovations in health care? And, can these differences be understood from the differences in the costs and benefits associated with the innovations for the stakeholders? Understanding the differences in preferences and subsequent priorities in innovation agendas of different stakeholders may lead to an understanding of the differences in the speed of diffusion of innovations.
We found differences in preferences between six stakeholder groups with regard to nine IT innovations in hospitals. For example, substantial differences were found in the preference for self-testing. Patients who would play a vital role in the effective implementation of self-tests do not give self-tests a high priority. This can be partly understood by cost–benefit considerations. To conduct self-tests, patients have to learn new skills and take responsibility for their care process, which they may not aspire to do so. The benefits of more efficient health care are mainly found within the system.
The highest level of consensus between the six stakeholder groups was found for a regional EPF. Even the stakeholders who may have to bear substantial costs in terms of having to change their daily routines (i.e., nurses and physicians) see the added benefits of the innovation. The implementation of an EPF involves different costs for different stakeholders. Nurses and physicians need to change their work practices in the sense that many of their treatment-related activities are computerized. (This change depends on the interface, but working with stations, the change can be quite cumbersome.) Hospitals need to invest in IT systems and national policy makers need to invest in regional data infrastructures. The perceived benefits of EPF are, however, not without controversy. Among the stakeholder groups, judgments differed most strongly on the EPF as well as medicine barcodes and self-tests.
The strongest preferences found in this study are those of the policy makers for self-tests, and those of the physicians for PDAs. For the policy makers, self-tests could result in a decrease in costs because part of the disease diagnosing process is done by the patients themselves, thereby reducing the number of general-practitioner consultations. Therefore, they expect a gain in efficiency of care. The physicians prefer the PDA, probably because of the ease of use, with all relevant data being readily available at the patient’s bedside or the operating table. For the PDA to work, a well-functioning EPF is necessary, which is their second preference. This seems to indicate that the physicians in our study will embrace the benefits of a well-functioning EPF with a mobile interface.
There were indications that stakeholder preferences can be understood from the benefits they gain from the innovation. We also saw that these benefits differ between stakeholders, affecting their prioritization of which innovation to implement first. We saw little direct evidence of costs having a major effect on the decisions of the stakeholders.
In terms of the relative importance of the decision criteria, policy makers deviate from the other stakeholders. To policy makers, efficiency in health care is the most important factor in deciding whether an innovation has added benefits. For patients, nurses and insurers, health gains constitute the decisive factor in deciding on beneficial innovations, and for physicians and managers, the decisive factor is (patient) satisfaction.
All policy makers operated on the national level and were very concerned about the increasing health care expenditure. This concern was translated in the high priority of the efficiency gains due to the innovations. In the interviews, policy makers indicated that they use different tools to steer the innovation process. Besides implementing taxes, making inspections and providing funding, they may establish contact between innovators and care providers to start meaningful cooperation. The interviews revealed an important difference between policy makers and other stakeholders, in that the majority of them found it difficult, if not impossible, to appreciate the implications of single innovations. They were better equipped to discuss general directions and macro consequences of innovations.
None of the stakeholders indicated that they consider investment to be the most relevant factor in deciding on the added value of an innovation. It should be noted that these outcomes are based on subjective expectations, and not on evidence from health economic studies. A drawback of this study is that the respondents reported their subjective expectations and these expectations may differ from real life choices that stakeholder groups make. The relatively small weight that was assigned to the costs may point towards such bias.
We measured the preferences of the various stakeholders. These preferences are likely to affect the decisions on adopting innovations. The preferences appeared to be related to the cost–benefit ratio of each stakeholder. This cost–benefit ratio is affected by the stakeholders’ position in an organization or a health care system. We did not study the actual effect of preferences on decision making. The effect of preferences on decisions about adoption may be the topic of another study.
Even though we tried to be specific in our descriptions of innovations, we also had to find a description that would be understood by all stakeholders. The result may have been too general a description of the innovations. For instance, the EPF has many different applications and methods of operation. It may have been that different respondents had different ideas of the EPF while answering the question, based on their own experience.
Another way to improve this study is to increase the number of respondents. It was found particularly difficult to have physicians answer the questionnaire. We received feedback that some of them found it too difficult to answer the questions, or that completing the questionnaire was too time consuming. Still, we explored the possibilities for the use of AHP in innovation research, and even with the relatively small number of respondents, believe that we have obtained promising results that can be understood in terms of the stakeholder framework. Later studies may build on the ideas presented in this paper.
If in subsequent studies it is possible to increase the number of respondents, further differentiations among a larger number of stakeholders may be possible. For instance, we did not further differentiate the management of hospitals. However, when managers operate on different levels or in different positions in an organization, this may affect their preferences. The differences are expected to be smaller than those between the stakeholder groups we included, but these small differences may delay the innovation processes. With further differentiation, an even more diverse picture of differences between stakeholders is likely to emerge. An increased number of respondents may also be used to correct analyses for aspects such as cultural differences and resemble the wider variety of health care organizations.
What would we expect concerning the speed of the diffusion of the innovations that were included in this study? Virtual consultations, telepathology and telesurgery did not appear in any of the top three preferences of any of the stakeholders. We therefore do not expect rapid and broad diffusion of these innovations soon. The planning of operations is ranked by patients and nurses to be important; however, it will need to be implemented by the hospital organization. We believe that the planning is an inevitable step in creating an efficient hospital and expect it to diffuse at a medium rate. Self-tests are highly ranked by the stakeholders that do not use it (managers, health insurers and policy makers), but not by those who will need to use it. We therefore expect a slow implementation of self-tests. For the digital hospital portal, we find a similar preference structure. However, these kinds of implementations are performed more by the hospital organization. This type of innovation may therefore diffuse more quickly. Barcodes are seen as useful innovations by most of the stakeholders. The use of barcodes may therefore diffuse quickly with the support of all stakeholders. The use of a PDA is mainly found to be important by the physicians and the EPF by most of the stakeholders close to the care process. Even though the two are seen in this study as separate innovations, the PDA can be used as a mobile interface for the EPF. If these two technologies are combined, a mobile source of information becomes available to the care professionals, possibly integrating data input more closely to the care process. The combination of readily available information with quick and easy data input may create more momentum for the ongoing diffusion of registration of patient data. Future research may empirically test these expectations.
Competing interests
The authors have no competing interests as described in the authors’ instructions for this journal, nor other competing interests.
Authors’ contributions
ML developed the idea of the paper and the theoretical framework. He also recruited respondents, conducted and interpreted interviews, judged the results of the literature searches, and wrote the text. MH conducted a literature search, made the online questionnaire, conducted AHP analyses and wrote the text. All authors read and approved the final manuscript.