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Exploring differences in the use of the statin choice decision aid and diabetes medication choice decision aid in primary care
© The Author(s). 2017
Received: 30 September 2016
Accepted: 31 July 2017
Published: 10 August 2017
Shared decision making is essential to patient centered care, but can be difficult for busy clinicians to implement into practice. Tools have been developed to aid in shared decision making and embedded in electronic medical records (EMRs) to facilitate use. This study was undertaken to explore the patterns of use and barriers and facilitators to use of two decision aids, the Statin Choice Decision Aid (SCDA) and the Diabetes Medication Choice Decision Aid (DMCDA), in primary care practices where the decision aids are embedded in the EMR.
A survey exploring factors that influenced use of each decision aid was sent to eligible primary care clinicians affiliated with the Mayo Clinic in Rochester, MN. Survey data was collected and clinician use of each decision aid via links from the EMR was tracked.
The survey response rate was 40% (105/262). Log file data indicated 51% of clinicians used the SCDA and 9% of clinicians used the DMCDA. Reasons for lack of use included lack of knowledge of the EMR link, not finding the decision aids helpful, and time constraints. Survey responses indicated that use of the tool as intended was low, with many clinicians only discussing decision aid topics that they found relevant.
Although guidelines for both the treatment of blood cholesterol with a statin and for the treatment of hyperglycemia in type 2 diabetes recommend shared decision making, tools that facilitate shared decision making are not routinely used even when embedded in the EMR. Even when decision aids are used, their use may not reflect patient centered care.
Shared decision making involves three essential elements: (1) awareness that a decision is required; (2) sharing of evidence about the pros and cons of different treatment options; and (3) a discussion of patient values and preferences . Shared decision making is critical to patient-centered care , but implementing shared decision-making is not easy . For this reason, decision aids, which do not guarantee shared decision-making, but have been shown to increase the likelihood clinicians engage patients in treatment decisions, have been developed . Decisions aids can take many forms, but often involve a graphic presentation of the evidence of risks and benefits, and are used during a clinical encounter to facilitate discussion between clinicians and patients. In some practices electronic versions of decision aids have been incorporated into the electronic medical record (EMR) to facilitate use. However, even when embedded in the work-flow, decision aids are not routinely used . Given the increasing emphasis on shared decision-making by organizations such as the National Quality Forum and the likely development of quality metrics based on the use of decision aids under the Affordable Care Act , understanding the factors that promote and impede use of decision aids in clinical practice is paramount. This study investigated patterns of use as well as barriers and facilitators of use for two decision aids: the Statin Choice Decision Aid (SCDA) and the Diabetes Medication Choice Decision Aid (DMCDA) in primary care practices affiliated with the Mayo Clinic.
We administered a survey to investigate factors that encouraged or discouraged use of the SCDA and the DMCDA by primary care clinicians at the Mayo Clinic, an academic tertiary healthcare center. Decision aid use was measured by querying log-file data that recorded the use of links to the decision aids from the EMR. The Mayo Clinic Institutional Review Board approved all study procedures.
The statin choice decision aid and the diabetes medication choice decision aid
The SCDA and DMCDA were developed at the Mayo Clinic to encourage patient involvement in treatment decisions. In randomized trials, both decision aids have shown to increase patient knowledge and engagement and to decrease decisional conflict [7–11]. Both decision aids were designed with input from primary care clinicians practicing at the Mayo Clinic [12, 13].
Links to the decision aids are located in the EMR, in a section routinely used by primary care clinicians at the Mayo Clinic to ensure preventative services and tests for chronic conditions are up to date. Clinicians in primary care were notified by e-mail of the presence of the links to the decision aids when the links were initially added to the EMR, but no training on the use of the decision aids to facilitate shared decision-making was given.
The statin choice decision aid
The SCDA is a tool that helps clinicians and patients discuss the pros and cons of statin use. It graphically displays information about a patient’s estimated 10-year cardiovascular risk, the degree of risk reduction with a statin, and the likelihood of adverse events (https://statindecisionaid.mayoclinic.org). At the Mayo Clinic, each patient’s data from the EMR is imported into the tool in order to individualize presentation.
The diabetes medication choice decision aid
The DMCDA uses electronic issue cards to display the impact of different diabetes medications on daily routine, blood sugar control, risk of hypoglycemia, weight change, and cost (https://diabetesdecisionaid.mayoclinic.org). Patients and clinicians identify the best medication for a particular patient based on reviewing 2–3 of issue cards.
All primary care clinicians (nurse practitioners, physician assistants, physicians, and physicians in training) practicing in the divisions of Family Medicine or Primary Care Internal Medicine at Mayo Clinic in Rochester, Minnesota were eligible for participation in the study.
A 14-question survey on decision aid use was designed by the study team. Survey questions covered the following topics: use of the decision aid, barriers and facilitators to use, and type of use. The survey was administered electronically by Qualtrics and sent to all eligible primary care clinicians (262) via email on June 16th, 2015. Reminder emails (3) were sent, until the survey closed on September 16, 2015.
All survey questions were in a check box format. One survey question, in addition to the check box format, allowed additional data entry in a free-text format. Clinicians had to answer each question before advancing to the next question. If a clinician indicated that they had not used a decision aid, then they were not asked the specific questions pertaining to that decision aid. At the end of the survey, clinicians had the option to submit their answers. Only submitted surveys were available for analysis.
For some questions a Likert scale was used, with similar responses combined for the purpose of data analysis. Also for the purpose of analysis, survey responses detailing barriers and facilitators to use were subdivided into three categories—knowledge barriers and facilitators, attitudes barriers and facilitators, and external barriers and facilitators – based on the classification scheme used by Legare et al. Please see Additional file 1 for survey questions and detailed explanation of coding.
Log file data
Data on decision aid use was captured for all clinicians by log file data that recorded use of the links to each decision aids from the EMR. The total number of uses as well as the number of distinct clinicians using each decision aid each month was captured for a 12 month period of time, from December 16th, 2014 to December 15th, 2015. This time period was chosen to capture the 6 months before the survey was first sent and the 6 months after the survey was first sent.
Clinician characteristics including age, gender, and type of training (nurse practitioners, physician assistants, physicians, and physicians in training), and years in practice was obtained from administrative sources.
Summary statistics were created using frequencies for categorical data and means and standard deviation for continuous data.
Characteristics of Clinicians
n = 105% or m(SD)
n = 262% or m(SD)
Type of clinician
Physician in Training
Years in Practice
Decision Aid Use, Log File Data
Survey Respondents (n = 105)
All Clinicians (n = 262)
# of times
% of clinicians
# of times
% of clinicians
# of times
% of clinicians
# of times
% of clinicians
Six months pre- survey
Six months post-survey
Entire 12 months period
Decision Aid Use, Barriers and Facilitators of Use, and Type of Use, Survey Data (n = 105)
Unfamiliar with decision aid
Unaware of EMR link
Appropriate amount of information
Often impacts treatment decision
Type of use
Only discuss topics patient is interested in
Only discuss topics I find relevant
Discuss all topics (use as intended)
Barriers to Use, Free Text Survey Data
-“I don’t have experience using all the meds listed on the decision aid”
-“Don’t know enough about it”
-“I prefer to send my patients to Endocrinology to discuss treatment options”
-“Often forget it exists”
-“For most of my patients there is an appropriate next step and giving them choices for medications that I would not prescribe doesn’t make sense”
-“Decision aid seems to underestimate benefit”
-“First choice should be metformin”
-“Patients never choose to use a statin with this decision aid”
-“A patient may choose a newer pricey medication with the attractive profile with the attitude of ‘Well, I’m not paying for it’”
-“Computer in rooms often do not pull up the decision aid fast enough”
-“Most patients are already on statins”
-“Decision aid is slow to load. Laminated cards would be helpful”
-“Sometimes discussing options over the phone after test results and hard to use the decision aid remotely”
-“I have a very small number of patients on medications for diabetes”
-“Most of my patients are already on insulin and/or oral agents”
-“Navigating the tool seems a bit clunky”
Facilitators of decision aid use included clinicians finding them very useful, and their impact on treatment decisions. Both of these facilitators were reported more frequently by clinicians for the SCDA than for the DMCDA (56% vs. 30% and 42% vs 22%, respectively).
For both the SCDA and DMCDA there was some indication that use of the tools as intended for shared decision-making was suboptimal with many clinicians indicating they only discussed the topics they found relevant (60% vs.46%).
Guidelines for both the treatment of blood cholesterol with a statin and the treatment of hyperglycemia in type 2 diabetes recommend shared decision-making [14, 15]. However, our results indicate that even when decision aids are embedded in the EMR, many clinicians never use these tools. Forty-nine percent of clinicians did not use the SCDA and 91% of clinicians did not use the DMCDA during the 12 months of data collection. Clinician responses to survey questions indicated reasons for lack of use included lack of knowledge of the EMR link, not finding the decision aids helpful, and time constraints. Free text data revealed concerns about lack of alignment of decision aids with guidelines, lack of applicability to patient populations, and in some cases lack of interest of clinicians in involving patients in treatment decisions. These responses point to a lack alignment of values and purpose among clinicians around engaging patients, or a lack of coherence as described by Carl May’s normalization process theory, a conceptual model for how new technologies become embedded in routine practice .. Others have also noted lack of coherence as a barrier to successful implementation of shared decision making .
Interestingly, our results revealed strikingly different use of the two decision aids by clinicians, with approximately five times more clinicians using the SCDA. This indicates that many clinicians who use a decision aid when deciding on initiation of statin therapy do not do so when deciding on medications for treatment of diabetes. Our survey indicates this may have been at least partially due to lack of knowledge about the existence of the DMCDA. However, the lack of increased use of the DMCDA after the survey by the survey respondents makes it likely that factors intrinsic to the decision aid or to the decision itself are also responsible. Unfortunately, our survey only hinted at what these factors may be. The SCDA was perceived as more useful and as having a larger impact on treatment decisions, but why this is the case is unknown. One potential explanation is that the SCDA automatically calculates the patient’s cardiovascular risk and thus saves the clinicians’ time. However, more clinicians indicated they did not use the SCDA because of time constraints than indicated they did not use the DMCDA due to time pressures. Further research is needed to more fully understand the reasons for differential use.
Importantly, as shown by others , our results indicate that use of decision aids does not guarantee shared decision-making. Clinicians indicated they prefer to use the decision aids to discuss only the topics they find relevant, and write-in comments revealed paternalistic views about the desired involvement of patients in treatment decisions. Others have noted poor documentation of shared decision-making when clinicians use links to decision aids from the EMR, perhaps indicating lack of use as intended . Thus even if decision aid use is incentivized through measures such as quality metrics, true patient-centered care will not be achieved without a change in the culture of care. Clinician training in the proper use of decision aids to facilitate shared decision-making, emphasizing the importance of patient engagement in discussions of risk, benefits, alternatives, values and preferences is needed . But perhaps more importance are discussions among clinicians to address divergent views on the value of engaging patients, which would hopefully move clinicians towards coherence in attitudes that promote careful and kind interactions .
Strengths and limitations
The main strength of our study is that it reports on the use of decision aids in routine clinical practice, not in the setting of a trial, making the findings more representative of typical use. The main weakness of the study was that it was done in a tertiary academic practice and thus may lack generalizability to other practice settings.
Financial support for this study was provided entirely by the Mayo Clinic Office of Information and Knowledge Management. The funding agreement ensured that the authors independence in designing the study, interpreting the data, writing and publishing the report.
Availability of data and materials
Data is available from the corresponding author on reasonable request.
AB, MS, and RC were involved in the development and administration of the survey. MS, MK, and VM analyzed the data. MK and MS wrote the first draft of the manuscript and all other authors revised it critically. All authors gave final approval for publication.
Ethics approval and consent to participate
The Mayo Clinic Institutional Review Board approved all study procedures.
Consent for publication
The authors declare that they have no competing interests.
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- Legare F, Witteman HO. Shared decision making: examining key elements and barriers to adoption into routine clinical practice. Health affairs (Project Hope). 2013;32(2):276–84.View ArticleGoogle Scholar
- Institute of Medicine Committee on Quality of Health Care in A. In: Crossing the Quality Chasm: A New Health System for the 21st Century. Washington (DC): National Academies Press (US) Copyright 2001 by the National Academy of Sciences. All rights reserved.; 2001. https://www.ncbi.nlm.nih.gov/pubmed/25057539.
- Legare F, Ratte S, Gravel K, Graham ID. Barriers and facilitators to implementing shared decision-making in clinical practice: update of a systematic review of health professionals’ perceptions. Patient Educ Couns. 2008;73(3):526–35.View ArticlePubMedGoogle Scholar
- Legare F, Stacey D, Turcotte S, Cossi MJ, Kryworuchko J, Graham ID, Lyddiatt A, Politi MC, Thomson R, Elwyn G, et al. Interventions for improving the adoption of shared decision making by healthcare professionals. Cochrane Database Syst Rev 2014;15(9):CD006732.Google Scholar
- Couet N, Desroches S, Robitaille H, Vaillancourt H, Leblanc A, Turcotte S, Elwyn G, Legare F. Assessments of the extent to which health-care providers involve patients in decision making: a systematic review of studies using the OPTION instrument. Health Expect. 2015;18(4):542–61.View ArticlePubMedGoogle Scholar
- Frosch DL, Moulton BW, Wexler RM, Holmes-Rovner M, Volk RJ, Levin CA. Shared decision making in the United States: policy and implementation activity on multiple fronts. Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen. 2011;105(4):305–12.View ArticlePubMedGoogle Scholar
- Weymiller AJ, Montori VM, Jones LA, Gafni A, Guyatt GH, Bryant SC, Christianson TJ, Mullan RJ, Smith SA. Helping patients with type 2 diabetes mellitus make treatment decisions: statin choice randomized trial. Arch Intern Med. 2007;167(10):1076–82.View ArticlePubMedGoogle Scholar
- Mann DM, Ponieman D, Montori VM, Arciniega J, McGinn T. The Statin Choice decision aid in primary care: a randomized trial. Patient Educ Couns. 2010;80(1):138–40.View ArticlePubMedGoogle Scholar
- Mullan RJ, Montori VM, Shah ND, Christianson TJ, Bryant SC, Guyatt GH, Perestelo-Perez LI, Stroebel RJ, Yawn BP, Yapuncich V, et al. The diabetes mellitus medication choice decision aid: a randomized trial. Arch Intern Med. 2009;169(17):1560–8.View ArticlePubMedGoogle Scholar
- Branda ME, LeBlanc A, Shah ND, Tiedje K, Ruud K, Van Houten H, Pencille L, Kurland M, Yawn B, Montori VM. Shared decision making for patients with type 2 diabetes: a randomized trial in primary care. BMC Health Serv Res. 2013;13:301.View ArticlePubMedPubMed CentralGoogle Scholar
- Agoritsas T, Heen AF, Brandt L, Alonso-Coello P, Kristiansen A, Akl EA, Neumann I, Tikkinen KA, Weijden T, Elwyn G, et al. Decision aids that really promote shared decision making: the pace quickens. BMJ (Clinical research ed). 2015;350:g7624.PubMed CentralGoogle Scholar
- Breslin M, Mullan RJ, Montori VM. The design of a decision aid about diabetes medications for use during the consultation with patients with type 2 diabetes. Patient Educ Couns. 2008;73(3):465–72.View ArticlePubMedGoogle Scholar
- Montori VM, Breslin M, Maleska M, Weymiller AJ. Creating a conversation: insights from the development of a decision aid. PLoS Med. 2007;4(8):e233.View ArticlePubMedPubMed CentralGoogle Scholar
- Stone NJ, Robinson JG, Lichtenstein AH, Bairey Merz CN, Blum CB, Eckel RH, Goldberg AC, Gordon D, Levy D, Lloyd-Jones DM, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Journal of the American College of Cardiology. 2014;63(25 Pt B):2889–934.View ArticlePubMedGoogle Scholar
- Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, Peters AL, Tsapas A, Wender R, Matthews DR. Management of hyperglycemia in type 2 diabetes, 2015: a patient-centered approach: update to a position statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2015;38(1):140–9.View ArticlePubMedGoogle Scholar
- May CR, Mair F, Finch T, MacFarlane A, Dowrick C, Treweek S, Rapley T, Ballini L, Ong BN, Rogers A, et al. Development of a theory of implementation and integration: Normalization Process Theory. Implementation science : IS. 2009;4:29.View ArticlePubMedPubMed CentralGoogle Scholar
- Lloyd A, Joseph-Williams N, Edwards A, Rix A, Elwyn G. Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC). Implementation science : IS. 2013;8:102.View ArticlePubMedPubMed CentralGoogle Scholar
- Wyatt KD, Branda ME, Anderson RT, Pencille LJ, Montori VM, Hess EP, Ting HH, LeBlanc A. Peering into the black box: a meta-analysis of how clinicians use decision aids during clinical encounters. Implementation science : IS. 2014;9:26.View ArticlePubMedPubMed CentralGoogle Scholar
- Inselman J, Branda M, Castaneda-Guarderas A, Gionfriddo MR, Zeballos-Palacios CL, Morris MM, Shah ND, Montori VM, LeBlanc A. Uptake and Documentation of the Use of an Encounter Decision Aid in Usual Practice: A Retrospective Analysis of the Use of the Statin/Aspirin Choice Decision Aid. Medical decision making : an international journal of the Society for Medical Decision Making. 2016;36(4):557–61.View ArticleGoogle Scholar
- Diouf NT, Menear M, Robitaille H, Painchaud Guerard G, Legare F. Training health professionals in shared decision making: Update of an international environmental scan. Patient Educ Couns. 2016;99(11):1753–8.View ArticlePubMedGoogle Scholar
- Joseph-Williams N, Lloyd A, Edwards A, Stobbart L, Tomson D, Macphail S, Dodd C, Brain K, Elwyn G, Thomson R. Implementing shared decision making in the NHS: lessons from the MAGIC programme. BMJ (Clinical research ed). 2017;357:j1744.View ArticleGoogle Scholar