Currently Viewing:
The American Journal of Managed Care October 2018
Putting the Pieces Together: EHR Communication and Diabetes Patient Outcomes
Marlon P. Mundt, PhD, and Larissa I. Zakletskaia, MA
Primary Care Physician Resource Use Changes Associated With Feedback Reports
Eva Chang, PhD, MPH; Diana S.M. Buist, PhD, MPH; Matt Handley, MD; Eric Johnson, MS; Sharon Fuller, BA; Roy Pardee, JD, MA; Gabrielle Gundersen, MPH; and Robert J. Reid, MD, PhD
From the Editorial Board: Bruce W. Sherman, MD
Bruce W. Sherman, MD
Recent Study on Site of Care Has Severe Limitations
Lucio N. Gordan, MD, and Debra Patt, MD
The Authors Respond and Stand Behind Their Findings
Yamini Kalidindi, MHA; Jeah Jung, PhD; and Roger Feldman, PhD
The Characteristics of Physician Practices Joining the Early ACOs: Looking Back to Look Forward
Stephen M. Shortell, PhD, MPH, MBA; Patricia P. Ramsay, MPH; Laurence C. Baker, PhD; Michael F. Pesko, PhD; and Lawrence P. Casalino, MD, PhD
Currently Reading
Nudging Physicians and Patients With Autopend Clinical Decision Support to Improve Diabetes Management
Laura Panattoni, PhD; Albert Chan, MD, MS; Yan Yang, PhD; Cliff Olson, MBA; and Ming Tai-Seale, PhD, MPH
Clinical Outcomes and Healthcare Use Associated With Optimal ESRD Starts
Peter W. Crooks, MD; Christopher O. Thomas, MD; Amy Compton-Phillips, MD; Wendy Leith, MS, MPH; Alvina Sundang, MBA; Yi Yvonne Zhou, PhD; and Linda Radler, MBA
Medicare Savings From Conservative Management of Low Back Pain
Alan M. Garber, MD, PhD; Tej D. Azad, BA; Anjali Dixit, MD; Monica Farid, BS; Edward Sung, BS, BSE; Daniel Vail, BA; and Jay Bhattacharya, MD, PhD
CMS HCC Risk Scores and Home Health Patient Experience Measures
Hsueh-Fen Chen, PhD; J. Mick Tilford, PhD; Fei Wan, PhD; and Robert Schuldt, MA
An Early Warning Tool for Predicting at Admission the Discharge Disposition of a Hospitalized Patient
Nicholas Ballester, PhD; Pratik J. Parikh, PhD; Michael Donlin, MSN, ACNP-BC, FHM; Elizabeth K. May, MS; and Steven R. Simon, MD, MPH
Gatekeeping and Patterns of Outpatient Care Post Healthcare Reform
Michael L. Barnett, MD, MS; Zirui Song, MD, PhD; Asaf Bitton, MD, MPH; Sherri Rose, PhD; and Bruce E. Landon, MD, MBA, MSc

Nudging Physicians and Patients With Autopend Clinical Decision Support to Improve Diabetes Management

Laura Panattoni, PhD; Albert Chan, MD, MS; Yan Yang, PhD; Cliff Olson, MBA; and Ming Tai-Seale, PhD, MPH
Incorporating an autopend functionality into clinical decision support improved glycated hemoglobin laboratory test completion by between 21.1% and 33.9% for reminder messages read within 57 days.

We evaluated the impact of incorporating a novel autopend functionality into the CDS on routine A1C laboratory test completion. We found that for HMT reminders read within 57 days, reminders sent in the postautopend period were associated with a 21.1% (HR, 1.211; P = .050) to 33.9% (HR, 1.339; P = .003) increase in the likelihood of laboratory test completion. This result included 68% of the HMT reminders. However, the likelihood of laboratory test completion decreased the longer it took the patient to read the reminder. Among unread reminders, we found no statistical difference in A1C laboratory test completion in the postautopend period.

The autopend design was guided by the behavioral economics principle of nudging people to do the right thing. Autopend allowed the majority of patients to skip checking an additional website and potentially contacting their provider to check the laboratory test’s authorization status. Relocating provider triggers from the patient’s chart to a separate electronic folder for providers to approve, as well as coordinating the timing and content of the patient reminders with the provider authorization, may have minimized alert fatigue,16 the electronic task demand (eg, clicks, data entry, and time), and the downstream actions required by both parties. This in turn may have reduced providers’ workflow interruption and cognitive burden, improving job performance and satisfaction.17,18 However, the effects of these design features were associated with diminishing improvements for patients who took longer to read their reminders.

Although 87.0% of the postautopend period HMT reminders had autopend content, caution should be exercised before concluding that laboratory test completion rates could have been higher had all patients received autopend content. Patient and provider characteristics associated with the usual-content HMT reminders, and not the actual reminder content, may have contributed to the lower rates. Future research should explore these factors and the CDS designs that address them.

Stage II of the Meaningful Use criteria established expectations of using CDS to engage patients and improve population health.19 Although technology such as autopend may have an important role in helping health systems realize the potential of EHRs, physicians spend significant time meeting the demands of “desktop medicine.”20-22 Requiring physicians to approve autopend orders for regulatory compliance, rather than allowing them to go directly to patients or to the inboxes of other care team members, may have unintended consequences on physicians’ workflow. The functionality may need to be modified to enable other care team members to approve these orders.


This study has some limitations. The observational pre-post study design limits our ability to rule out confounding factors. However, we did statistically control for time trends through the use of quarter fixed effects. Secondly, this study took place in a single multispecialty delivery organization, which was an early adopter of EHRs, and autopend was added onto an existing EpicCare-specific HMT reminder system. Furthermore, this study included only patients with an active patient portal, limiting generalizability to other settings and patient populations. However, these principles of CDS design could be applied to other EHR systems.


Our study results suggest that incorporating an autopend functionality into a CDS system was associated with improvements in A1C laboratory test completion among patients with diabetes who read their HMT reminders in a timely fashion. This multifaceted functionality was designed to simplify workflow, remove barriers, and coordinate the actions of patients and clinicians. Such a CDS tool can improve the care of chronically ill patients in the spirit of the Quadruple Aim.23

Author Affiliations: Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center (LP), Seattle, WA; Sutter Health Office of Patient Experience (AC), Sacramento, CA; Palo Alto Medical Foundation Research Institute (AC, YY, CO), Palo Alto, CA; University of California San Diego School of Medicine (MT-S), San Diego, CA.

Source of Funding: Agency for Healthcare Research and Quality R18 HS 019167.

Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (LP, AC, YY, CO, MT-S); acquisition of data (CO, MT-S); analysis and interpretation of data (LP, AC, YY, CO); drafting of the manuscript (LP, AC); critical revision of the manuscript for important intellectual content (LP, AC, YY, MT-S); statistical analysis (YY); provision of patients or study materials (MT-S); obtaining funding (MT-S); administrative, technical, or logistic support (AC); and supervision (MT-S).

Address Correspondence to: Laura Panattoni, PhD, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109. Email:

1. Hsu WC. Consequences of delaying progression to optimal therapy in patients with type 2 diabetes not achieving glycemic goals. South Med J. 2009;102(1):67-76. doi: 10.1097/SMJ.0b013e318182d8a2.

2. CDC. Prevalence of receiving multiple preventive-care services among adults with diabetes — United States, 2002-2004. CDC website. Published November 11, 2005. Accessed September 14, 2017.

3. eHealthUniversity. Clinical decision support: more than just ‘alerts’ tipsheet. CMS website. Published 2014. Accessed September 14, 2017.

4. Tierney WM, Hui SL, McDonald CJ. Delayed feedback of physician performance versus immediate reminders to perform preventive care: effects on physician compliance. Med Care. 1986;24(8):659-666.

5. Garg AX, Adhikari NKJ, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223-1238. doi: 10.1001/jama.293.10.1223.

6. Shojania KG, Jennings A, Mayhew A, Ramsay CR, Eccles MP, Grimshaw J. The effects of on-screen, point of care computer reminders on processes and outcomes of care. Cochrane Database Syst Rev. 2009;(3):CD001096. doi: 10.1002/14651858.CD001096.pub2.

7. Embi PJ, Leonard AC. Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study. J Am Med Inform Assoc. 2012;19(e1):e145-e148. doi: 10.1136/amiajnl-2011-000743.

8. Ash JS, Sittig DF, Campbell EM, Guappone KP, Dykstra RH. Some unintended consequences of clinical decision support systems. AMIA Annu Symp Proc. 2007:26-30.

9. Halbert RJ, Leung KM, Nichol JM, Legorreta AP. Effect of multiple patient reminders in improving diabetic retinopathy screening. a randomized trial. Diabetes Care. 1999;22(5):752-755. doi: 10.2337/diacare.22.5.752.

10. Tricco AC, Ivers NM, Grimshaw JM, et al. Effectiveness of quality improvement strategies on the management of diabetes: a systematic review and meta-analysis. Lancet. 2012;379(9833):2252-2261. doi: 10.1016/S0140-6736(12)60480-2.

11. Wright A, Poon EG, Wald J, et al. Randomized controlled trial of health maintenance reminders provided directly to patients through an electronic PHR. J Gen Intern Med. 2012;27(1):85-92. doi: 10.1007/s11606-011-1859-6.

12. Ziemer DC, Doyle JP, Barnes CS, et al. An intervention to overcome clinical inertia and improve diabetes mellitus control in a primary care setting: Improving Primary Care of African Americans with Diabetes (IPCAAD) 8. Arch Inter Med. 2006;166(5):507-513. doi: 10.1001/archinte.166.5.507.

13. Schoenfeld D. Partial residuals for the proportional hazards regression model. Biometrika. 1982;69(1):239-241. doi: 10.2307/2335876.

14. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-383.

15. STATA Survival Analysis and Epidemiological Tables Reference Manual Release 13. College Station, TX: Stata Press; 2013.

16. Kesselheim AS, Cresswell K, Phansalkar S, Bates DW, Sheikh A. Clinical decision support systems could be modified to reduce ‘alert fatigue’ while still minimizing the risk of litigation. Health Aff (Millwood). 2011;30(12):2310-2317. doi: 10.1377/hlthaff.2010.1111.

17. Baethge A, Rigotti T. Interruptions to workflow: their relationship with irritation and satisfaction with performance, and the mediating roles of time pressure and mental demands. Work Stress. 2013;27(1):43-63. doi: 10.1080/02678373.2013.761783.

18. Weigl M, Müller A, Vincent C, Angerer P, Sevdalis N. The association of workflow interruptionsand hospital doctors’ workload: a prospective observational study. BMJ Qual Saf. 2012;21(5):399-407. doi: 10.1136/bmjqs-2011-000188.

19. Meaningful Use and MACRA. website. Accessed February 8, 2017.

20. Sinsky C, Colligan L, Li L, et al. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Ann Intern Med. 2016;165(11):753-760. doi: 10.7326/M16-0961.

21. Shanafelt T, Dyrbye L, Sinsky C, et al. Relationship between clerical burden and characteristics of the electronic environment with physician burnout and professional satisfaction. Mayo Clin Proc. 2016;91(7):836-848. doi: 10.1016/j.mayocp.2016.05.007.

22. Tai-Seale M, Olson CW, Li J, et al. Electronic health record logs indicate that physicians split time evenly between seeing patients and desktop medicine. Health Aff (Millwood). 2017;36(4):655-662. doi: 10.1377/hlthaff.2016.0811.

23. Bodenheimer T, Sinsky C. From Triple to Quadruple Aim: care of the patient requires care of the provider. Ann Fam Med. 2014;12(6):573-576. doi: 10.1370/afm.1713.
Copyright AJMC 2006-2020 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
Welcome the the new and improved, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up