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* Original Research Article
* Published: 23 June 2018
IMPACT OF REDUCING GLYCATED HEMOGLOBIN ON HEALTHCARE COSTS AMONG A POPULATION
WITH UNCONTROLLED DIABETES
* Megha Bansal1,
* Mona Shah1,
* Brian Reilly2,
* Susan Willman3,
* …
* Max Gill1 &
* Francine R. Kaufman1
Show authors
Applied Health Economics and Health Policy volume 16, pages 675–684 (2018)Cite
this article
* 582 Accesses
* 10 Citations
* 10 Altmetric
* Metrics details
ABSTRACT
INTRODUCTION
Glycated hemoglobin (A1C) is considered a “gold standard” measure of glycemic
control in patients with diabetes and is correlated with a lower risk of
diabetes complications and cost savings. This retrospective claims-analysis
assessed the impact of A1C reduction on healthcare costs in patients with
uncontrolled Type 1 and Type 2 diabetes.
METHODS
Using a large repository of US health plan administrative data linked to A1C
values, patients with a diabetes diagnosis and at least two A1C values between 1
January 2009 and 31 December 2014 were selected to identify changes in A1C and
associated changes in healthcare expenditure. We used all medical and pharmacy
claims to calculate direct healthcare costs from 1 year prior to the index A1C
to 2 years after the index A1C. A propensity score method was used to match
patients with decreased A1C to patients whose A1C did not decrease, based on
potentially confounding variables. Then, a generalized linear model regression
was used to estimate the difference-in-difference (DD) effect on costs between
the two groups.
RESULTS
Of the 3,197 patients who had a first A1C ≥ 9%, 2,273 patients (71%) had a
decrease in A1C (Decreasers) and 924 patients (27%) had an increase in A1C
(Non-decreasers). After matching, we compared 912 Decreasers to 912
Non-decreasers. Patients in the former group had average annual healthcare costs
that were 24% lower during the first year of follow-up and 17% lower during the
second year of follow-up, compared to patients whose A1C did not decrease. This
reflected a savings of US$2503 and US$1690, respectively. For both time periods,
the outpatient category was the largest contributor to cost savings.
DISCUSSION
In our analysis, A1C reduction among patients with T1DM and T2DM was associated
with slower growth in healthcare costs within 1–2 years. These findings suggest
that programs aimed at reducing A1C over a short timeframe may lead to
substantial savings and may be worth pursuing by health plans and other payers.
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Fig. 1
Fig. 2
Fig. 3
REFERENCES
1. Centers for Disease Control and Prevention. National Diabetes Statistics
Report. 2017. Atlanta, GA: Centers for Disease Control and Prevention, US
Dept of Health and Human Services, 2017.
2. American Diabetes Association. Economic costs of diabetes in the US in
2012. Diabetes Care. 2013;36(4):1033–46.
Article PubMed Central Google Scholar
3. Boyle JP, Thompson TJ, Gregg EW, Barker LE, Williamson DF. Projection of
the year 2050 burden of diabetes in the US adult population: dynamic
modeling of incidence, mortality, and prediabetes prevalence. Popul Health
Metr. 2010;8:29-7954-8-29.
Article Google Scholar
4. American Diabetes Association. Standards of medical care in diabetes-2017
abridged for primary care providers. Clin Diabetes. 2017;35(1):5–26.
Article PubMed Central Google Scholar
5. Diabetes Control and Complications Trial Research Group, Nathan DM, Genuth
S, Lachin J, Cleary P, Crofford O, et al. The effect of intensive treatment
of diabetes on the development and progression of long-term complications
in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep
30;329(14):977–86.
Article Google Scholar
6. Herman WH, Eastman RC. The effects of treatment on the direct costs of
diabetes. Diabetes Care. 1998 Dec;21(Suppl 3):C19–24.
Article PubMed Google Scholar
7. American Diabetes Association. 6. Glycemic Targets. Diabetes Care.
2017;40(Suppl 1):S48–56.
Article Google Scholar
8. Disease Management Performance Measures. 2017.
http://www.ncqa.org/programs/accreditation/disease-management-dm/dm-performance-measures.
Accessed 1 Nov 2017.
9. Comprehensive Diabetes Care. 2017.
http://www.ncqa.org/report-cards/health-plans/state-of-health-care-quality/2016-table-of-contents/diabetes-care.
Accessed 17 Nov 2017.
10. Eastman RC, Javitt JC, Herman WH, Dasbach EJ, Zbrozek AS, Dong F, et al.
Model of complications of NIDDM. I. Model construction and assumptions.
Diabetes Care. 1997;20(5):725–34.
Article PubMed CAS Google Scholar
11. Eastman RC, Javitt JC, Herman WH, Dasbach EJ, Copley-Merriman C, Maier W,
et al. Model of complications of NIDDM. II. Analysis of the health benefits
and cost-effectiveness of treating NIDDM with the goal of normoglycemia.
Diabetes Care. 1997 May;20(5):735–44.
Article PubMed CAS Google Scholar
12. Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC.
Effect of improved glycemic control on health care costs and utilization.
JAMA. 2001;285(2):182–9.
Article PubMed CAS Google Scholar
13. Gilmer TP, O’Connor PJ, Rush WA, Crain AL, Whitebird RR, Hanson AM, et al.
Predictors of health care costs in adults with diabetes. Diabetes Care.
2005;28(1):59–64.
Article PubMed Google Scholar
14. Shetty S, Secnik K, Oglesby AK. Relationship of glycemic control to total
diabetes-related costs for managed care health plan members with type 2
diabetes. J Manag Care Pharm. 2005;11(7):559–64.
PubMed Google Scholar
15. Menzin J, Korn JR, Cohen J, Lobo F, Zhang B, Friedman M, et al.
Relationship between glycemic control and diabetes-related hospital costs
in patients with type 1 or type 2 diabetes mellitus. J Manag Care Pharm.
2010;16(4):264–75.
PubMed Google Scholar
16. Juarez D, Goo R, Tokumaru S, Sentell T, Davis J, Mau M. Association between
sustained glycated hemoglobin control and healthcare costs. Am J Pharm
Benefits. 2013;5(2):59–64.
PubMed PubMed Central Google Scholar
17. Degli Esposti L, Saragoni S, Buda S, Sturani A, Degli Esposti E. Glycemic
control and diabetes-related health care costs in type 2 diabetes;
retrospective analysis based on clinical and administrative databases.
Clinicoecon Outcomes Res. 2013 May;14(5):193–201.
Article Google Scholar
18. Oglesby AK, Secnik K, Barron J, Al-Zakwani I, Lage MJ. The association
between diabetes related medical costs and glycemic control: a
retrospective analysis. Cost Eff Resour Alloc. 2006;4:1-7547-4-1.
Article Google Scholar
19. Menzin J, Langley-Hawthorne C, Friedman M, Boulanger L, Cavanaugh R.
Potential short-term economic benefits of improved glycemic control: a
managed care perspective. Diabetes Care. 2001;24(1):51–5.
Article PubMed CAS Google Scholar
20. 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):373–83.
Article PubMed CAS Google Scholar
21. Clinformatics Data Mart. 2018.
https://www.optum.com/content/dam/optum/resources/productSheets/Clinformatics_for_Data_Mart.pdf.
Accessed 30 Apr 2018.
22. Young BA, Lin E, Von Korff M, Simon G, Ciechanowski P, Ludman EJ, et al.
Diabetes complications severity index and risk of mortality,
hospitalization, and healthcare utilization. Am J Manag Care.
2008;14(1):15–23.
PubMed PubMed Central Google Scholar
23. Testa MA, Simonson DC. Health economic benefits and quality of life during
improved glycemic control in patients with type 2 diabetes mellitus: a
randomized, controlled, double-blind trial. JAMA. 1998;280(17):1490–6.
Article PubMed CAS Google Scholar
24. Schwartz DS, Dick DE, McMahon C, Cohen DO, Knoulton J, Arunachalam S. Novel
medtronic turning point program improves compliance and HBA1C in at-risk
patients with type 1 or type 2 diabetes. Diabetes Technol Ther.
2017;19(S1):A59.
Article Google Scholar
Download references
ACKNOWLEDGEMENTS
The authors thank Keren Price, MS, RD, for her assistance with writing this
manuscript, and Toni Cordero, PhD, for her assistance with manuscript review.
AUTHOR INFORMATION
AFFILIATIONS
1. Medtronic, 18000 Devonshire Street, Northridge, CA, 91325, USA
Megha Bansal, Mona Shah, Max Gill & Francine R. Kaufman
2. Medtronic, 18302 Talavera Ridge, San Antonio, TX, 78257, USA
Brian Reilly
3. Medtronic, 3033 Campus Drive, Plymouth, MN, 55441, USA
Susan Willman
Authors
1. Megha Bansal
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2. Mona Shah
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3. Brian Reilly
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You can also search for this author in PubMed Google Scholar
4. Susan Willman
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You can also search for this author in PubMed Google Scholar
5. Max Gill
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6. Francine R. Kaufman
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You can also search for this author in PubMed Google Scholar
CONTRIBUTIONS
Megha Bansal—developed concept, conducted statistical analysis, developed
manuscript. Mona Shah—developed concept, reviewed statistical analysis and
manuscript. Brian Reilly—provided data by extracting it from larger database and
reviewed manuscript. Susan Willman—reviewed concept, results, and manuscript.
Max Gill—developed the concept; reviewed statistical analysis and manuscript.
Francine R. Kaufman—provided a clinical perspective and reviewed manuscript.
CORRESPONDING AUTHOR
Correspondence to Megha Bansal.
ETHICS DECLARATIONS
DATA AVAILABILITY STATEMENT
According to our contract with OptumInsight, we are not permitted to share data
from the Optum Clinformatics® Data Mart database outside of our organization. We
have provided details of the model in an Appendix (see Online Supplementary
Material).
ETHICAL STANDARDS
All authors (Megha Bansal, Mona Shah, Brian Reilly, Susan Willman, Max Gill, and
Francine R. Kaufman) are employees of Medtronic. Medtronic has an interest in
this paper because it illustrates the impact of decreasing versus increasing A1C
on short-term costs in patients with uncontrolled diabetes.
FUNDING
No financial assistance was used to conduct this study or prepare this
manuscript.
ELECTRONIC SUPPLEMENTARY MATERIAL
Below is the link to the electronic supplementary material.
SUPPLEMENTARY MATERIAL 1 (DOCX 41 KB)
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Bansal, M., Shah, M., Reilly, B. et al. Impact of Reducing Glycated Hemoglobin
on Healthcare Costs Among a Population with Uncontrolled Diabetes. Appl Health
Econ Health Policy 16, 675–684 (2018). https://doi.org/10.1007/s40258-018-0398-2
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* Published: 23 June 2018
* Issue Date: October 2018
* DOI: https://doi.org/10.1007/s40258-018-0398-2
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* References
* Acknowledgements
* Author information
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* Electronic supplementary material
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* About this article
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* Fig. 1
* Fig. 2
* Fig. 3
1. Centers for Disease Control and Prevention. National Diabetes Statistics
Report. 2017. Atlanta, GA: Centers for Disease Control and Prevention, US
Dept of Health and Human Services, 2017.
2. American Diabetes Association. Economic costs of diabetes in the US in
2012. Diabetes Care. 2013;36(4):1033–46.
Article PubMed Central Google Scholar
3. Boyle JP, Thompson TJ, Gregg EW, Barker LE, Williamson DF. Projection of
the year 2050 burden of diabetes in the US adult population: dynamic
modeling of incidence, mortality, and prediabetes prevalence. Popul Health
Metr. 2010;8:29-7954-8-29.
Article Google Scholar
4. American Diabetes Association. Standards of medical care in diabetes-2017
abridged for primary care providers. Clin Diabetes. 2017;35(1):5–26.
Article PubMed Central Google Scholar
5. Diabetes Control and Complications Trial Research Group, Nathan DM, Genuth
S, Lachin J, Cleary P, Crofford O, et al. The effect of intensive treatment
of diabetes on the development and progression of long-term complications
in insulin-dependent diabetes mellitus. N Engl J Med. 1993 Sep
30;329(14):977–86.
Article Google Scholar
6. Herman WH, Eastman RC. The effects of treatment on the direct costs of
diabetes. Diabetes Care. 1998 Dec;21(Suppl 3):C19–24.
Article PubMed Google Scholar
7. American Diabetes Association. 6. Glycemic Targets. Diabetes Care.
2017;40(Suppl 1):S48–56.
Article Google Scholar
8. Disease Management Performance Measures. 2017.
http://www.ncqa.org/programs/accreditation/disease-management-dm/dm-performance-measures.
Accessed 1 Nov 2017.
9. Comprehensive Diabetes Care. 2017.
http://www.ncqa.org/report-cards/health-plans/state-of-health-care-quality/2016-table-of-contents/diabetes-care.
Accessed 17 Nov 2017.
10. Eastman RC, Javitt JC, Herman WH, Dasbach EJ, Zbrozek AS, Dong F, et al.
Model of complications of NIDDM. I. Model construction and assumptions.
Diabetes Care. 1997;20(5):725–34.
Article PubMed CAS Google Scholar
11. Eastman RC, Javitt JC, Herman WH, Dasbach EJ, Copley-Merriman C, Maier W,
et al. Model of complications of NIDDM. II. Analysis of the health benefits
and cost-effectiveness of treating NIDDM with the goal of normoglycemia.
Diabetes Care. 1997 May;20(5):735–44.
Article PubMed CAS Google Scholar
12. Wagner EH, Sandhu N, Newton KM, McCulloch DK, Ramsey SD, Grothaus LC.
Effect of improved glycemic control on health care costs and utilization.
JAMA. 2001;285(2):182–9.
Article PubMed CAS Google Scholar
13. Gilmer TP, O’Connor PJ, Rush WA, Crain AL, Whitebird RR, Hanson AM, et al.
Predictors of health care costs in adults with diabetes. Diabetes Care.
2005;28(1):59–64.
Article PubMed Google Scholar
14. Shetty S, Secnik K, Oglesby AK. Relationship of glycemic control to total
diabetes-related costs for managed care health plan members with type 2
diabetes. J Manag Care Pharm. 2005;11(7):559–64.
PubMed Google Scholar
15. Menzin J, Korn JR, Cohen J, Lobo F, Zhang B, Friedman M, et al.
Relationship between glycemic control and diabetes-related hospital costs
in patients with type 1 or type 2 diabetes mellitus. J Manag Care Pharm.
2010;16(4):264–75.
PubMed Google Scholar
16. Juarez D, Goo R, Tokumaru S, Sentell T, Davis J, Mau M. Association between
sustained glycated hemoglobin control and healthcare costs. Am J Pharm
Benefits. 2013;5(2):59–64.
PubMed PubMed Central Google Scholar
17. Degli Esposti L, Saragoni S, Buda S, Sturani A, Degli Esposti E. Glycemic
control and diabetes-related health care costs in type 2 diabetes;
retrospective analysis based on clinical and administrative databases.
Clinicoecon Outcomes Res. 2013 May;14(5):193–201.
Article Google Scholar
18. Oglesby AK, Secnik K, Barron J, Al-Zakwani I, Lage MJ. The association
between diabetes related medical costs and glycemic control: a
retrospective analysis. Cost Eff Resour Alloc. 2006;4:1-7547-4-1.
Article Google Scholar
19. Menzin J, Langley-Hawthorne C, Friedman M, Boulanger L, Cavanaugh R.
Potential short-term economic benefits of improved glycemic control: a
managed care perspective. Diabetes Care. 2001;24(1):51–5.
Article PubMed CAS Google Scholar
20. 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):373–83.
Article PubMed CAS Google Scholar
21. Clinformatics Data Mart. 2018.
https://www.optum.com/content/dam/optum/resources/productSheets/Clinformatics_for_Data_Mart.pdf.
Accessed 30 Apr 2018.
22. Young BA, Lin E, Von Korff M, Simon G, Ciechanowski P, Ludman EJ, et al.
Diabetes complications severity index and risk of mortality,
hospitalization, and healthcare utilization. Am J Manag Care.
2008;14(1):15–23.
PubMed PubMed Central Google Scholar
23. Testa MA, Simonson DC. Health economic benefits and quality of life during
improved glycemic control in patients with type 2 diabetes mellitus: a
randomized, controlled, double-blind trial. JAMA. 1998;280(17):1490–6.
Article PubMed CAS Google Scholar
24. Schwartz DS, Dick DE, McMahon C, Cohen DO, Knoulton J, Arunachalam S. Novel
medtronic turning point program improves compliance and HBA1C in at-risk
patients with type 1 or type 2 diabetes. Diabetes Technol Ther.
2017;19(S1):A59.
Article Google Scholar
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