Worth a second look
Transferring research from researchers to knowledge users: the importance of relationships and getting them right
Journal of Health Services Research & Policy 2016, Vol. 21(2) 134–136 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1355819615602030 hsr.sagepub.com
Moriah Ellen1,2,3 and Adalsteinn Brown4
Heide JB and Miner AS. The shadow of the future: effects of anticipated interaction and frequency of contact on buyer-seller cooperation. Acad Manag J 1992; 35: 265–291. Health system reform efforts around the world focus on evidence-informed decision making as a critical element to creating high-performing health systems. Although the use of evidence to inform policy is limited, over the last decade, significant achievements have been made in supporting the use of evidence to inform policy making and decision making, in high, low and middle income countries. Knowledge transfer and exchange (KTE) has emerged as a paradigm to address many of the challenges and barriers associated with transferring evidence into policy and to start closing the ‘know-do’ gap. KTE is defined as ‘the synthesis, exchange, and application of knowledge by relevant stakeholders to accelerate the benefits of global and local innovation in strengthening health systems and improving people’s health.’1 However, the uptake of evidence is challenging and numerous barriers exist that impede the implementation of evidence-informed decision making.2 Scholars point to the importance of relationships when linking research and policy, but they rarely articulate why – from a theoretical perspective – relationships are important, nor do they create a platform for a deeper understanding of how to use relationships effectively to transfer evidence into practice.3,4 Within the business literature, inter-organizational relationships have been studied for decades with a traditional focus on fixed organizational traits (such as the effect of internal organizational characteristics, resource dependency or uncertainty on types of cooperation).5 Building on existing research, Heide and Miner5 examined the role of relationships and focused on ongoing interaction as a factor influencing the success of inter-organizational relationships. Interactive theorists suggest that cooperation comes from the commitment between two or more ‘players’, and that over time, the players care about the ‘other’ and cooperate
out of altruism. In their paper, Effects of Anticipated Interaction and Frequency of Contact on Buyer-Seller Cooperation, Heide and Miner5 explored whether the interaction patterns may themselves affect cooperation between players in an industrial purchasing setting. Heide and Miner identified four types of cooperation: (1) flexibility with one another or adjusting behaviour to accommodate the needs of the other, (2) information exchange or disclosing information to the other, (3) shared problem solving or relying on the other in order to solve issues together, and (4) restraint in the use of power or refraining from exploiting the other. Using a game theory approach based on the Prisoner’s Dilemma, where players can gain more from cooperation than from non-cooperation, Heide and Miner hypothesized that three factors would influence the degree of cooperation: (a) the extendedness of a relationship or how far into the future each party believes it will continue the relationship, (b) frequency or the expected amount of interaction between players; and (c) tolerance of performance ambiguity or the level of difficulty a player faces in evaluating the other party’s products and outcomes. The authors hypothesized that an increase in the first two factors would lead to an increase in cooperation, but a decrease in the third factor would lead to a decrease in cooperation. Heide and Miner tested these hypotheses by examining purchasing relationships between industrial suppliers and original equipment manufacturers whose 1 Senior Lecturer, School of Business, Jerusalem College of Technology, Israel 2 Senior Researcher, Gertner Institute for Epidemiology and Health Policy Research, Israel 3 Investigator, McMaster University, Canada 4 Director, Institute for Health Policy Management and Evaluation Head, Division of Public Health Policy, Dalla Lana School of Public Health, Canada
Corresponding author: Moriah Ellen, McMaster University 1280 Main St. West, CRL-209a Hamilton, Ontario, Canada, L8S 4K1. Email: [email protected]
Downloaded from hsr.sagepub.com at University of Birmingham on May 17, 2016
Ellen and Brown
135
relationships traditionally include interactions that are at times ‘arm’s length’ or even adversarial. Both buyers and suppliers were questioned through a mail-based questionnaire. The dependent variable extracted was the level of reciprocal cooperation between the buyer and the seller as measured by (1) flexibility, (2) information exchange, (3) shared problem solving and (4) restraint in the use of power. Interestingly, Heide and Miner found that cooperation did increase but the degree of increase and the nature of increase varied across factors and across types of cooperation. Overall, they found strong support for extendedness of a relationship having a positive effect on cooperation, partial support for frequency of contact having a positive effect on cooperation and no support that ambiguity of performance negatively effected cooperation. Heide and Miner’s research has had a huge impact in the field of business research. Many have used their work to inform research on topics such as trust, inter-firm collaboration and strategic alliances.6,7
Why are relationships and cooperation important to KTE in health care? Ensuring the use of research evidence in health system management and policy decisions is a critical element in improving the cost and quality of health care. Although we continue to generate more and more evidence, it is clear that relatively little finds its way into practice and thus never realizes its value.8 KTE primarily involves two main parties: knowledge producers (i.e. researchers and academics), and knowledge users (i.e. managers, decision makers and policy makers). There are knowledge brokers as well. However, for the sake of simplicity, the focus here is on the producers and the users. Researchers as producers of knowledge and evidence, generate the findings potentially helpful to making crucial and far-reaching policy decisions.9 From the researchers’ point of view, a long and tedious study that may have taken years to conduct, falls many a time on deaf ears at worst, or on impatient, getto-the-point ears at best.10 Even if a researcher managed to find the right policy maker at the right time, which is frequently not the case, there are still political forces and agendas to be taken into account, as well as bureaucracies.10,11 From a policy maker’s perspective, there are numerous barriers to incorporating the use of research into decision making such as a lack of personal contact with the researchers and research that is not timely, high quality or relevant.12 Thus, researchers and knowledge users generally operate in two different communities where one player produces research and the other makes
decisions. Rarely do the two communities cross paths,13 and it is unclear for how long parties will work together. These challenges are similar to the extendedness and frequency factors described by Heide and Miner. Moreover, the contexts in which they operate, their cultures and their long versus short-term orientation on results are quite different (see the Two Communities Theory13). The differences of mentalities, goals, attitude towards information, language, perceived credibility and scope of the problem at hand, have long been known to cause wariness similar to the performance ambiguity factor described above. International initiatives have been implemented to try and bridge this gap and enable the transfer of research into practice through the use of various mechanisms such as institutional entrepreneurs, training and infrastructure to support the use of evidence in practice.14,15 So what can we learn from the paper by Heide and Miner? They point out the importance of the contexts within which relationships occur. For the chance encounter – say, between a decision maker and a researcher at a conference – there is little relationship to speak of, so the transfer of evidence needs to be strongly packaged to match the immediate needs of the decision maker, and there needs to be a way to increase the perceived value of the research evidence. Normally, models like the integrated KTE model would suggest that efforts be made to reduce performance ambiguity, which in this situation, relates to the quality of the research and relevance of the findings. However, Heide and Miner suggest that this may be less important given that such ambiguity did not seem to harm cooperation in their study. For such short-term relationships, researchers would do well to be ready with their ‘elevator pitch’ and be able to signal high credibility. Little else may be of importance. In contrast, in longer term relationships with multiple encounters – where encounters are really transactions or different projects, not steps or meetings around a single project – Heide and Miner might argue that intent to do many projects and repeated communication may be the most influential factors in KTE. Building and fostering relationships between knowledge producers and knowledge users, which are long term and have a strong foundation of trust, should support the use of research to inform policy and practice. Promoting long lasting relationships between researchers and decision makers (as opposed to the occasional or accidental exchange) could, based on research findings to date, be a critical and, at least in the scholarly literature, largely ignored factor in the use of research to inform practice. Relationships are discussed, but they are not front and centre as one of the main influencing factors. Many other factors are highlighted as well such as how to present the evidence,
Downloaded from hsr.sagepub.com at University of Birmingham on May 17, 2016
136
Journal of Health Services Research & Policy 21(2)
and training policy makers to have the skills to acquire and assess the evidence. Many frameworks that focus on KTE discuss the importance of linkage and exchange between researchers and knowledge users.16,17 Strong links between policy makers, stakeholders and researchers can enhance the transfer of research into practice, and this is consistent with the hypothesis tested by Heide and Miner.5 However, the nature of even these relationships that conform to the integrated KTE model is rarely discussed. Regular contact, the promise of longer relationships and efforts to increase clarity around goals are all needed to improve cooperation. Linkage and exchange initiatives are more likely to be beneficial when the parties involved are committed to working together in asking, analysing and answering policy-relevant questions, when relationships are close and ongoing, and where there are meaningful partnerships where the role and expertise of all members are respected.18,19 References 1. Pablos-Mendez A and Shademani R. Knowledge translation in global health. J Cont Educ Health Profession 2006; 26: 81–86. 2. Ellen ME, Leon G, Bouchard G, et al. Barriers, facilitators and views about next steps to implementing supports for evidence-informed decision-making in health systems: a qualitative study. Implement Sci 9, http://www.implementationscience.com/content/9/1/179 (2014, accessed 8 August 2015). 3. Lomas J and Brown AD. Research and advice giving: a functional view of evidence-informed policy advice in a Canadian Ministry of Health. Milbank Q 2009; 87: 903–926. 4. Goering P, Butterill D, Jacobson N, et al. Linkage and exchange at the organizational level: a model of collaboration between research and policy. J Health Serv Res Pol 2003; 8: 14–19. 5. Heide JB and Miner AS. The shadow of the future: effects of anticipated interaction and frequency of contact on buyer-seller cooperation. Acad Manag J 1992; 35: 265–291. 6. Carson SJ, Madhok A, Varman R, et al. Information processing moderators of the effectiveness of trust-based governance in interfirm R&D collaboration. Organ Sci 2003; 14: 45–56.
7. Das TK and Teng BS. A resource-based theory of strategic alliances. J Manag 2000; 26: 31–61. 8. World Health Organization. Bridging the ‘‘Know-Do’’ dap. Geneva, Switzerland: WHO Press, 2006. 9. Corluka A, Hyder AA, Winch PJ, et al. Exploring health researchers’ perceptions of policymaking in Argentina: a qualitative study. Health Pol Plan 2014; 29: ii40–ii49. 10. Hyder AA, Corluka A, Winch PJ, et al. National policymakers speak out: are researchers giving them what they need? Health Pol Plan 2011; 26: 73–82. 11. Lavis JN. Research, public policymaking, and knowledge-translation processes: Canadian efforts to build bridges. J Cont Educ Health Professions 2006; 26: 37–45. 12. Oliver K, Innvar S, Lorenc T, et al. A systematic review of barriers to and facilitators of the use of evidence by policymakers. BMC Health Serv Res 14: 2, http:// www.biomedcentral.com/1472-6963/14/2 (2014, accessed 10 August 2015). 13. Caplan N. The two communities theory and knowledge utilization. Am Behav Sci 1979; 22: 459–470. 14. Currie G, Lockett A and El Enany N. From what we know to what we do: lessons learned from the translational CLAHRC initiative in England. J Health Serv Res Pol 2013; 18(Suppl 3.): 27–39. 15. Ellen ME, Leon G, Bouchard G, et al. What supports do health system organizations have in place to facilitate evidence-informed decision-making? A qualitative study. Implement Sci 8, http://www.implementationscience.com/ content/8/1/84 (2013, accessed 10 August 2015). 16. Damschroder LJ, Aron DC, Keith RE, et al. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 4, http://www.implementationscience.com/content/4/1/50 (2009, accessed 10 August 2015). 17. Ellen ME, Lavis JN, Ouimet M, et al. Determining research knowledge infrastructure for healthcare systems: a qualitative study. Implement Sci 6: 60, http://www.implementationscience.com/content/6/1/60, (2011, accessed 10 August 2015). 18. Lavis JN, Lomas J, Hamid M, et al. Assessing countrylevel efforts to link research to action. Bull World Health Organ 2006; 84: 620–628. 19. Sibbald SL, Tetroe J and Graham ID. Research funder required research partnerships: a qualitative inquiry. Implement Sci 9: 176, http://www.implementationscience. com/content/9/1/176, (2014, accessed 10 August 2015).
Downloaded from hsr.sagepub.com at University of Birmingham on May 17, 2016
Transferring research from researchers to knowledge users: the importance of relationships and getting them right
Journal of Health Services Research & Policy 2016, Vol. 21(2) 134–136 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1355819615602030 hsr.sagepub.com
Moriah Ellen1,2,3 and Adalsteinn Brown4
Heide JB and Miner AS. The shadow of the future: effects of anticipated interaction and frequency of contact on buyer-seller cooperation. Acad Manag J 1992; 35: 265–291. Health system reform efforts around the world focus on evidence-informed decision making as a critical element to creating high-performing health systems. Although the use of evidence to inform policy is limited, over the last decade, significant achievements have been made in supporting the use of evidence to inform policy making and decision making, in high, low and middle income countries. Knowledge transfer and exchange (KTE) has emerged as a paradigm to address many of the challenges and barriers associated with transferring evidence into policy and to start closing the ‘know-do’ gap. KTE is defined as ‘the synthesis, exchange, and application of knowledge by relevant stakeholders to accelerate the benefits of global and local innovation in strengthening health systems and improving people’s health.’1 However, the uptake of evidence is challenging and numerous barriers exist that impede the implementation of evidence-informed decision making.2 Scholars point to the importance of relationships when linking research and policy, but they rarely articulate why – from a theoretical perspective – relationships are important, nor do they create a platform for a deeper understanding of how to use relationships effectively to transfer evidence into practice.3,4 Within the business literature, inter-organizational relationships have been studied for decades with a traditional focus on fixed organizational traits (such as the effect of internal organizational characteristics, resource dependency or uncertainty on types of cooperation).5 Building on existing research, Heide and Miner5 examined the role of relationships and focused on ongoing interaction as a factor influencing the success of inter-organizational relationships. Interactive theorists suggest that cooperation comes from the commitment between two or more ‘players’, and that over time, the players care about the ‘other’ and cooperate
out of altruism. In their paper, Effects of Anticipated Interaction and Frequency of Contact on Buyer-Seller Cooperation, Heide and Miner5 explored whether the interaction patterns may themselves affect cooperation between players in an industrial purchasing setting. Heide and Miner identified four types of cooperation: (1) flexibility with one another or adjusting behaviour to accommodate the needs of the other, (2) information exchange or disclosing information to the other, (3) shared problem solving or relying on the other in order to solve issues together, and (4) restraint in the use of power or refraining from exploiting the other. Using a game theory approach based on the Prisoner’s Dilemma, where players can gain more from cooperation than from non-cooperation, Heide and Miner hypothesized that three factors would influence the degree of cooperation: (a) the extendedness of a relationship or how far into the future each party believes it will continue the relationship, (b) frequency or the expected amount of interaction between players; and (c) tolerance of performance ambiguity or the level of difficulty a player faces in evaluating the other party’s products and outcomes. The authors hypothesized that an increase in the first two factors would lead to an increase in cooperation, but a decrease in the third factor would lead to a decrease in cooperation. Heide and Miner tested these hypotheses by examining purchasing relationships between industrial suppliers and original equipment manufacturers whose 1 Senior Lecturer, School of Business, Jerusalem College of Technology, Israel 2 Senior Researcher, Gertner Institute for Epidemiology and Health Policy Research, Israel 3 Investigator, McMaster University, Canada 4 Director, Institute for Health Policy Management and Evaluation Head, Division of Public Health Policy, Dalla Lana School of Public Health, Canada
Corresponding author: Moriah Ellen, McMaster University 1280 Main St. West, CRL-209a Hamilton, Ontario, Canada, L8S 4K1. Email: [email protected]
Downloaded from hsr.sagepub.com at University of Birmingham on May 17, 2016
Ellen and Brown
135
relationships traditionally include interactions that are at times ‘arm’s length’ or even adversarial. Both buyers and suppliers were questioned through a mail-based questionnaire. The dependent variable extracted was the level of reciprocal cooperation between the buyer and the seller as measured by (1) flexibility, (2) information exchange, (3) shared problem solving and (4) restraint in the use of power. Interestingly, Heide and Miner found that cooperation did increase but the degree of increase and the nature of increase varied across factors and across types of cooperation. Overall, they found strong support for extendedness of a relationship having a positive effect on cooperation, partial support for frequency of contact having a positive effect on cooperation and no support that ambiguity of performance negatively effected cooperation. Heide and Miner’s research has had a huge impact in the field of business research. Many have used their work to inform research on topics such as trust, inter-firm collaboration and strategic alliances.6,7
Why are relationships and cooperation important to KTE in health care? Ensuring the use of research evidence in health system management and policy decisions is a critical element in improving the cost and quality of health care. Although we continue to generate more and more evidence, it is clear that relatively little finds its way into practice and thus never realizes its value.8 KTE primarily involves two main parties: knowledge producers (i.e. researchers and academics), and knowledge users (i.e. managers, decision makers and policy makers). There are knowledge brokers as well. However, for the sake of simplicity, the focus here is on the producers and the users. Researchers as producers of knowledge and evidence, generate the findings potentially helpful to making crucial and far-reaching policy decisions.9 From the researchers’ point of view, a long and tedious study that may have taken years to conduct, falls many a time on deaf ears at worst, or on impatient, getto-the-point ears at best.10 Even if a researcher managed to find the right policy maker at the right time, which is frequently not the case, there are still political forces and agendas to be taken into account, as well as bureaucracies.10,11 From a policy maker’s perspective, there are numerous barriers to incorporating the use of research into decision making such as a lack of personal contact with the researchers and research that is not timely, high quality or relevant.12 Thus, researchers and knowledge users generally operate in two different communities where one player produces research and the other makes
decisions. Rarely do the two communities cross paths,13 and it is unclear for how long parties will work together. These challenges are similar to the extendedness and frequency factors described by Heide and Miner. Moreover, the contexts in which they operate, their cultures and their long versus short-term orientation on results are quite different (see the Two Communities Theory13). The differences of mentalities, goals, attitude towards information, language, perceived credibility and scope of the problem at hand, have long been known to cause wariness similar to the performance ambiguity factor described above. International initiatives have been implemented to try and bridge this gap and enable the transfer of research into practice through the use of various mechanisms such as institutional entrepreneurs, training and infrastructure to support the use of evidence in practice.14,15 So what can we learn from the paper by Heide and Miner? They point out the importance of the contexts within which relationships occur. For the chance encounter – say, between a decision maker and a researcher at a conference – there is little relationship to speak of, so the transfer of evidence needs to be strongly packaged to match the immediate needs of the decision maker, and there needs to be a way to increase the perceived value of the research evidence. Normally, models like the integrated KTE model would suggest that efforts be made to reduce performance ambiguity, which in this situation, relates to the quality of the research and relevance of the findings. However, Heide and Miner suggest that this may be less important given that such ambiguity did not seem to harm cooperation in their study. For such short-term relationships, researchers would do well to be ready with their ‘elevator pitch’ and be able to signal high credibility. Little else may be of importance. In contrast, in longer term relationships with multiple encounters – where encounters are really transactions or different projects, not steps or meetings around a single project – Heide and Miner might argue that intent to do many projects and repeated communication may be the most influential factors in KTE. Building and fostering relationships between knowledge producers and knowledge users, which are long term and have a strong foundation of trust, should support the use of research to inform policy and practice. Promoting long lasting relationships between researchers and decision makers (as opposed to the occasional or accidental exchange) could, based on research findings to date, be a critical and, at least in the scholarly literature, largely ignored factor in the use of research to inform practice. Relationships are discussed, but they are not front and centre as one of the main influencing factors. Many other factors are highlighted as well such as how to present the evidence,
Downloaded from hsr.sagepub.com at University of Birmingham on May 17, 2016
136
Journal of Health Services Research & Policy 21(2)
and training policy makers to have the skills to acquire and assess the evidence. Many frameworks that focus on KTE discuss the importance of linkage and exchange between researchers and knowledge users.16,17 Strong links between policy makers, stakeholders and researchers can enhance the transfer of research into practice, and this is consistent with the hypothesis tested by Heide and Miner.5 However, the nature of even these relationships that conform to the integrated KTE model is rarely discussed. Regular contact, the promise of longer relationships and efforts to increase clarity around goals are all needed to improve cooperation. Linkage and exchange initiatives are more likely to be beneficial when the parties involved are committed to working together in asking, analysing and answering policy-relevant questions, when relationships are close and ongoing, and where there are meaningful partnerships where the role and expertise of all members are respected.18,19 References 1. Pablos-Mendez A and Shademani R. Knowledge translation in global health. J Cont Educ Health Profession 2006; 26: 81–86. 2. Ellen ME, Leon G, Bouchard G, et al. Barriers, facilitators and views about next steps to implementing supports for evidence-informed decision-making in health systems: a qualitative study. Implement Sci 9, http://www.implementationscience.com/content/9/1/179 (2014, accessed 8 August 2015). 3. Lomas J and Brown AD. Research and advice giving: a functional view of evidence-informed policy advice in a Canadian Ministry of Health. Milbank Q 2009; 87: 903–926. 4. Goering P, Butterill D, Jacobson N, et al. Linkage and exchange at the organizational level: a model of collaboration between research and policy. J Health Serv Res Pol 2003; 8: 14–19. 5. Heide JB and Miner AS. The shadow of the future: effects of anticipated interaction and frequency of contact on buyer-seller cooperation. Acad Manag J 1992; 35: 265–291. 6. Carson SJ, Madhok A, Varman R, et al. Information processing moderators of the effectiveness of trust-based governance in interfirm R&D collaboration. Organ Sci 2003; 14: 45–56.
7. Das TK and Teng BS. A resource-based theory of strategic alliances. J Manag 2000; 26: 31–61. 8. World Health Organization. Bridging the ‘‘Know-Do’’ dap. Geneva, Switzerland: WHO Press, 2006. 9. Corluka A, Hyder AA, Winch PJ, et al. Exploring health researchers’ perceptions of policymaking in Argentina: a qualitative study. Health Pol Plan 2014; 29: ii40–ii49. 10. Hyder AA, Corluka A, Winch PJ, et al. National policymakers speak out: are researchers giving them what they need? Health Pol Plan 2011; 26: 73–82. 11. Lavis JN. Research, public policymaking, and knowledge-translation processes: Canadian efforts to build bridges. J Cont Educ Health Professions 2006; 26: 37–45. 12. Oliver K, Innvar S, Lorenc T, et al. A systematic review of barriers to and facilitators of the use of evidence by policymakers. BMC Health Serv Res 14: 2, http:// www.biomedcentral.com/1472-6963/14/2 (2014, accessed 10 August 2015). 13. Caplan N. The two communities theory and knowledge utilization. Am Behav Sci 1979; 22: 459–470. 14. Currie G, Lockett A and El Enany N. From what we know to what we do: lessons learned from the translational CLAHRC initiative in England. J Health Serv Res Pol 2013; 18(Suppl 3.): 27–39. 15. Ellen ME, Leon G, Bouchard G, et al. What supports do health system organizations have in place to facilitate evidence-informed decision-making? A qualitative study. Implement Sci 8, http://www.implementationscience.com/ content/8/1/84 (2013, accessed 10 August 2015). 16. Damschroder LJ, Aron DC, Keith RE, et al. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci 4, http://www.implementationscience.com/content/4/1/50 (2009, accessed 10 August 2015). 17. Ellen ME, Lavis JN, Ouimet M, et al. Determining research knowledge infrastructure for healthcare systems: a qualitative study. Implement Sci 6: 60, http://www.implementationscience.com/content/6/1/60, (2011, accessed 10 August 2015). 18. Lavis JN, Lomas J, Hamid M, et al. Assessing countrylevel efforts to link research to action. Bull World Health Organ 2006; 84: 620–628. 19. Sibbald SL, Tetroe J and Graham ID. Research funder required research partnerships: a qualitative inquiry. Implement Sci 9: 176, http://www.implementationscience. com/content/9/1/176, (2014, accessed 10 August 2015).
Downloaded from hsr.sagepub.com at University of Birmingham on May 17, 2016
