Testing patient-informed approaches for visually depicting the hemoglobin A1c value to patients with poorly controlled diabetes: a randomized, controlled trial

Anjali Gopalan, Leah Suttner, Andrea B Troxel, Kevin McDonough, Marilyn M Schapira, Anjali Gopalan, Leah Suttner, Andrea B Troxel, Kevin McDonough, Marilyn M Schapira

Abstract

Background: Patients' understanding of the hemoglobin A1c (HbA1c) has been linked to better diabetes care outcomes (glycemic control, self-care). This is concerning given low documented rates of HbA1c understanding. In this non-blinded, randomized trial, we compared two formats for communicating the HbA1c, selected based on input from people with diabetes, to standard presentation to assess their impact on participants' glycemic control and diabetes-related perceptions.

Methods: To design the tested formats, we interviewed 25 patients with diabetes and reviewed a range of possible formats, including color-based scales and graphs. The interviews were recorded, transcribed, and subjected to thematic analysis. Synthesizing interviewees' feedback, we selected two formats, one using a combination of words and colors (Words) and one using a color-coded graph (Graph), for further evaluation. We then randomized adults with poorly controlled diabetes to receive mailed information on their current diabetes control in one of three ways: 1) standard lab report (control), 2) Words format, or 3) Graph format. The primary outcome was HbA1c change at 6 months. Also examined were changes in participants' diabetes-related perceptions and choice of participation incentive.

Results: Of the 234 enrolled participants, 76.9% were Black, and their median baseline HbA1c was 9.1% (interquartile range 8.4-10.4). There were no between-arm differences in HbA1c change (- 1.04% [SD 2.2] Control vs. -0.59% [SD 2.0] Words vs. -0.54% [SD 2.1] Graph, p > 0.05 for all comparisons). Participants in the Words arm had an increase in the accuracy of their perceptions of diabetes seriousness (p = 0.04) and in the number of participants reporting a diabetes management goal (p = 0.01).

Conclusions: The two patient-informed communication formats did not differentially impact glycemic control among adults with inadequately controlled diabetes. However, a significant proportion of participants in the Words arm had an increase in the accuracy of their perception of diabetes seriousness, a potential mediating factor in positive diabetes-related behavioral changes. With increasing use of patient-facing online portals, thoughtfully designed approaches for visually communicating essential, but poorly understood, information like the HbA1c to patients have the potential to facilitate interpretation and support self-management.

Clinical trial registration: Prospectively registered as NCT01886170.

Keywords: Diabetes; Hemoglobin A1c; Patient portal; Patient-provider communication; Qualitative research.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Formats for communicating the HbA1c value tested in each study arm. Top: Standard (control), Middle: Words format, Bottom: Graph format
Fig. 2
Fig. 2
CONSORT Flow diagram overviewing randomization, enrollment, and follow-up

References

    1. Beard E, et al. Do people with diabetes understand their clinical marker of long-term glycemic control (HbA1c levels) and does this predict diabetes self-care behaviours and HbA1c? Patient Educ Couns. 2010;80:227–232. doi: 10.1016/j.pec.2009.11.008.
    1. Berikai P, et al. Gain in patients' knowledge of diabetes management targets is associated with better glycemic control. Diabetes Care. 2007;30(6):1587–1589. doi: 10.2337/dc06-2026.
    1. Wang S, et al. Lack of knowledge of glycosylated hemoglobin in patients with diabetic retinopathy. Diabetes Res Clin Pract. 2008;81(1):e15–e17. doi: 10.1016/j.diabres.2008.03.011.
    1. Stark Casagrande S, et al. Diabetes knowledge and its relationship with achieving treatment recommendations in a national sample of people with type 2 diabetes. Diabetes Care. 2012;35(7):1556–1565. doi: 10.2337/dc11-1943.
    1. Zikmund-Fisher BJ, Exe NL, Witteman HO. Numeracy and literacy independently predict patients' ability to identify out-of-range test results. J Med Internet Res. 2014;16(8):e187. doi: 10.2196/jmir.3241.
    1. Polonsky WH, Fisher L. When does personalized feedback make a difference? A narrative review of recent findings and their implications for promoting better diabetes self-care. Curr Diab Rep. 2015;15(8):50. doi: 10.1007/s11892-015-0620-7.
    1. Parkes G, et al. Effect on smoking quit rate of telling patients their lung age: the Step2quit randomised controlled trial. BMJ. 2008;336(7644):598–600. doi: 10.1136/bmj.39503.582396.25.
    1. Thorndike AN, et al. Traffic-light labels and choice architecture: promoting healthy food choices. Am J Prev Med. 2014;46(2):143–149. doi: 10.1016/j.amepre.2013.10.002.
    1. Gopalan A, et al. Translating the hemoglobin A1C with more easily understood feedback: a randomized controlled trial. J Gen Intern Med. 2014;29(7):996–1003. doi: 10.1007/s11606-014-2810-4.
    1. Rosenstock C, Strecher VJ, Becker MH. Social learning theory and the health belief model. Health Educ Q. 1998;15(2):175–183. doi: 10.1177/109019818801500203.
    1. Glanz K, Rimer BK, Viswanath K. Health behavior: Theory, Research, and Practice, vol. xxv. Fifth ed. San Francisco: Jossey-bass public health; 2015. p. 485.
    1. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Effective Clin Pract. 1998;1(1):2–4.
    1. Inbanez, N. Avoid Mixed Signals By Learning. 2012 July 4, 2012; Available from: . [cited 2015 November 11].
    1. Government of Canada. Forest fire danger rating tool. June 15, 2015 [cited 2015 November 11, 2015]; Available from: .
    1. History Commons . Ridge Announces Homeland Security Advisory System. 2002.
    1. Apple Inc. iPod: About the battery charge status icon. [cited 2015 November 11]; Available from: .
    1. Foley, J. 5 WordPress Goal Tracking Plugins to Keep You Motivated. 2012 January 4, 2012 [cited 2015 November 11]; Available from: .
    1. Weight Watchers. Weight Watchers eTools. [cited 2015 November 11]; Available from: .
    1. The College Board. Class Rank and College Admission. 2015 [cited 2015 November 11]; Available from: .
    1. The American Heart Association. Good vs. Bad Cholesterol. 2015 January 12, 2015 [cited 2015 November 11]; Available from: .
    1. Yelp. [cited 2015 November 11]; Available from: .
    1. Gutierrez J, Long JA. Reliability and validity of diabetes specific health beliefs model scales in patients with diabetes and serious mental illness. Diabetes Res Clin Pract. 2011;92(3):342–347. doi: 10.1016/j.diabres.2011.02.018.
    1. Whooley MA, et al. Case-finding instruments for depression. Two questions are as good as many. J Gen Intern Med. 1997;12(7):439–445. doi: 10.1046/j.1525-1497.1997.00076.x.
    1. Zikmund-Fisher BJ, et al. Validation of the subjective numeracy scale: effects of low numeracy on comprehension of risk communications and utility elicitations. Med Decis Mak. 2007;27(5):663–671. doi: 10.1177/0272989X07303824.
    1. Fagerlin A, et al. Measuring numeracy without a math test: development of the subjective numeracy scale. Med Decis Mak. 2007;27(5):672–680. doi: 10.1177/0272989X07304449.
    1. The Diabetes Control and Complications Trial Research Group. The relationship of glycemic exposure (HbA1c) to the risk of development and progression of retinopathy in the diabetes control and complications trial. Diabetes. 1995;44(8):968–83.
    1. Molyneaux LM, et al. Better glycaemic control and risk reduction of diabetic complications in type 2 diabetes: comparison with the DCCT. Diabetes Res Clin Pract. 1998;42(2):77–83. doi: 10.1016/S0168-8227(98)00095-3.
    1. Little RGA, Rubin DB. Statistical analysis with missing data. New York: Wiley; 1987.
    1. Long JA, et al. Peer mentoring and financial incentives to improve glucose control in African American veterans: a randomized trial. Ann Intern Med. 2012;156(6):416–424. doi: 10.7326/0003-4819-156-6-201203200-00004.
    1. Choe HM, et al. Proactive case management of high-risk patients with type 2 diabetes mellitus by a clinical pharmacist: a randomized controlled trial. Am J Manag Care. 2005;11(4):253–260.
    1. Gopalan A, et al. Exploring how patients understand and assess their diabetes control. BMC Endocr Disord. 2018;18(1):79. doi: 10.1186/s12902-018-0309-4.
    1. Soames Job R F. Effective and ineffective use of fear in health promotion campaigns. American Journal of Public Health. 1988;78(2):163–167. doi: 10.2105/AJPH.78.2.163.
    1. Tannenbaum MB, et al. Appealing to fear: a meta-analysis of fear appeal effectiveness and theories. Psychol Bull. 2015;141(6):1178–1204. doi: 10.1037/a0039729.
    1. Hendricks LE, Hendricks RT. Greatest fears of type 1 and type 2 patients about having diabetes: implications for diabetes educators. Diabetes Educ. 1998;24(2):168–173. doi: 10.1177/014572179802400206.
    1. Kuniss N, et al. Expectations and fear of diabetes-related long-term complications in people with type 2 diabetes at primary care level. Acta Diabetol. 2019;56(1):33–38. doi: 10.1007/s00592-018-1217-9.
    1. Higbee KL. Fifteen years of fear arousal: research on threat appeals: 1953-1968. Psychol Bull. 1969;72(6):426–444. doi: 10.1037/h0028430.
    1. Ratanawongsa N, et al. Communication and Medication Refill Adherence: The Diabetes Study of Northern California. Arch Intern Med. 2012:1–9.
    1. White RO, et al. Health communication, self-care, and treatment satisfaction among low-income diabetes patients in a public health setting. Patient Educ Couns. 2015;98(2):144–149. doi: 10.1016/j.pec.2014.10.019.

Source: PubMed

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

3
Abonnieren