Currently Viewing:
The American Journal of Managed Care February 2017
Synchronized Prescription Refills and Medication Adherence: A Retrospective Claims Analysis
Jalpa A. Doshi, PhD; Raymond Lim, MA; Pengxiang Li, PhD; Peinie P. Young, PharmD, BCACP; Victor F. Lawnicki, PhD; Andrea B. Troxel, ScD; and Kevin G. Volpp, MD, PhD
Addressing the Chronification of Disease
Michael E. Chernew, PhD, Co-Editor-in-Chief, The American Journal of Managed Care
Currently Reading
Economic Burden of Hypoglycemia With Basal Insulin in Type 2 Diabetes
Vivian Fonseca, MD; Engels Chou, MS; Hsing-Wen Chung, PhD; and Charles Gerrits, PhD, PharmD
An Examination of the Relationship Between Care Management With Coaching for Activation and Patient Outcomes
Cindy Reistroffer, DSc; Larry R. Hearld, PhD; and Jeff M. Szychowski, PhD
Sustained Participation in a Pay-for-Value Program: Impact on High-Need Patients
Dori A. Cross, BSPH; Genna R. Cohen, PhD; Christy Harris Lemak, PhD; and Julia Adler-Milstein, PhD
Value-Based Contracting Innovated Medicare Advantage Healthcare Delivery and Improved Survival
Aloke K. Mandal, MD, PhD; Gene K. Tagomori, BSc; Randell V. Felix, BSc; and Scott C. Howell, DO, MPH&TM
Community-Based Asthma Education
Rohini Rau-Murthy, BA; Leslie Bristol, RRT, AE-C; and David Pratt, MD, MPH
Perceptions of the Medical Home by Parents of Children With Chronic Illnesses
Emily B. Vander Schaaf, MD, MPH; Elisabeth P. Dellon, MD, MPH; Rachael A. Carr, BA; Neal A. deJong, MD; Asheley C. Skinner, PhD; and Michael J. Steiner, MD, MPH
Patient Characteristics and Healthcare Utilization of a Chronic Pain Population Within an Integrated Healthcare System
Robert J. Romanelli, PhD; Sonali N. Shah, RPh, MBA, MPH; Laurence Ikeda, MD; Braden Lynch, PharmD, MS, CPEHR; Terri L. Craig, PharmD, CPEHR; Joseph C. Cappelleri, PhD, MPH, MS; Trevor Jukes, MS; and D
Patients With Diabetes in Pay-for-Performance Programs Have Better Physician Continuity of Care and Survival
Chien-Chou Pan, MD, PhD; Pei-Tseng Kung, ScD; Li-Ting Chiu, MHA; Yu Pei Liao, MHA; and Wen-Chen Tsai, DrPH

Economic Burden of Hypoglycemia With Basal Insulin in Type 2 Diabetes

Vivian Fonseca, MD; Engels Chou, MS; Hsing-Wen Chung, PhD; and Charles Gerrits, PhD, PharmD
Hypoglycemia after basal insulin initiation is associated with high clinical and economic burden that precedes insulin initiation and persists during 1 to 2 years of follow-up.

Objectives: To assess the impact of hypoglycemia and potential underlying factors of economic burden in patients with type 2 diabetes (T2D) who are initiating basal insulin therapy.
Study Design: This retrospective cohort study combined commercial insurance and Medicare Advantage data from the Clinformatics Data Mart. 
Methods: Adults with T2D on oral antidiabetes drugs initiating basal insulin (n = 18,918) were assessed at baseline (12 months prior to insulin initiation) and follow-up (1 and 2 years). The population was stratified by whether or not patients experienced hypoglycemia during year 1 after insulin initiation. Outcomes included hypoglycemia rate, complications, comorbidities, and adjusted economic burden (primary).
Results: There were 1683 (8.9%) patients in the hypoglycemia group and 17,235 (91.1%) in the no-hypoglycemia group. During year 1, the estimated rate of hypoglycemia events was 0.412 per member per year. Baseline hypoglycemia was the strongest predictor of subsequent hypoglycemia. The hypoglycemia group was older, with a significantly greater clinical and economic burden at baseline; these differences persisted during follow-up. In the hypoglycemia group, for every 100 members per year, 463 hypoglycemia episodes were recorded, with a mean cost per episode of $986. Hypoglycemia-related medical expenses accounted for 12.6% ($4563/$36,272) of total healthcare expenditure, with hypoglycemia-related hospitalizations accounting for 19.7% ($2602/$13,191) of total hospitalization expenditure.
Conclusions: Compared with patients with no hypoglycemia-related claims in year 1 after basal insulin initiation, patients with a hypoglycemia-related claim had a greater burden of complications and comorbidity associated with significantly higher healthcare utilization and cost at baseline; these persisted during follow-up. 

Am J Manag Care. 2017;23(2):114-122
Takeaway Points

Patients with type 2 diabetes (T2D) who experienced hypoglycemia after adding basal insulin to oral antidiabetes drugs had a significantly greater clinical and economic healthcare burden at baseline, which persisted during follow-up. 
  • This analysis combined members of both commercial and Medicare Advantage plans, providing a representative sample of T2D in the United States. 
  • Consistent with other reports, we suggest hypoglycemia may be a marker for increased susceptibility to adverse healthcare outcomes. 
  • We speculate that earlier basal insulin initiation (ie, when disease burden is low) may incur a lower hypoglycemia risk, whereas delayed insulin (ie, when disease burden is high) may require closer monitoring. However, the current analysis was not designed to assess this, and prospective clinical trials are needed.
The economic burden of diabetes in the United States is estimated to be $245 billion annually (in 2012 US$), representing $176 billion in direct medical costs and $69 billion in lost productivity.1 Type 2 diabetes (T2D) may initially be managed with noninsulin therapies, such as oral antidiabetes drugs (OADs); however, with disease progression, patients may require insulin therapy to achieve glycemic control.2 If glycemic targets are not achieved after 3 months on metformin, adding basal insulin therapy is among the recommended management strategies and is considered to have the highest efficacy.3 Clinical evidence supports the conclusion that basal insulins—particularly longer-acting formulations—are associated with fewer hypoglycemia events than shorter-acting insulins4,5; however, even with basal insulin, hypoglycemia is a concern.

Hypoglycemia is a major burden to the healthcare eco-system. Not only is it a barrier to achieving glycemic control in diabetes, but it also may be associated with increased clinical and economic healthcare burdens, and have a negative impact on patient quality of life and medication adherence.6-10 Better insight into risk factors for hypoglycemia could help identify patients who are more likely to experience hypoglycemia and could thus help guide management.11,12

This retrospective cohort study used commercial and Medicare Advantage data to allow inclusion of a broad population representative of adults with T2D in the United States. Study aims were to identify risk factors for hypoglycemia and to assess the clinical and economic burdens of hypoglycemia in patients with T2D who added basal insulin to OADs.


This retrospective cohort study used combined commercial insurance (patients of working age) and Part C Medicare Advantage (elderly patients) with Part D populations from the nationwide Clinformatics Data Mart Database (OptumInsight, Eden Prairie, Minnesota). Administrative data, medical and pharmacy claims, and some laboratory results were available. Data were submitted by managed care organizations, hospitals, Medicare supplement (ie, beneficiaries enrolled in Part C), and employers (small- to large-scale).

Patient Selection and Cohort Construction

Adults 18 years or older with T2D were identified from January 1, 2007, to September 30, 2014, via International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes: 250.xx, 357.2, 362.0x, 366.41. Additional criteria were used to “de-select” individuals with type 1 diabetes, as follows: a) if no OADs were prescribed within 1 year from the diagnosis of diabetes and the medication possession ratio (MPR) of any insulin was ≥80%, b) or if the patient was younger than 30 years and on insulin only, c) or if diabetic ketoacidosis was diagnosed and the MPR of any insulin was ≥80% in the following year. Gestational diabetes was excluded.

Eligible patients had been dispensed at least 2 prescriptions of basal insulin (insulin glargine, insulin detemir, or neutral protamine Hagedorn insulin) within 6 months of initiating basal insulin as an add-on to OADs. At least 36 months of continuous healthcare coverage were required (baseline defined as 12 months before basal insulin initiation [index]; follow-up defined as 12 and 24 months after initiation). Only patients with at least 2 prescriptions for OADs during baseline were included.

Outcome Measures

Clinical outcome measures included hypoglycemia (ICD-9-CM codes: 250.8, 251.0, 251.1, 251.2), glycated hemoglobin (A1C), diabetes complications (macrovascular: cardiovascular disease, peripheral arterial disease, and stroke; microvascular: retinopathy, kidney disease/nephropathy, and neuropathy, including foot infection and lower extremity amputation), comorbid conditions, and concomitant medications. ICD-9-CM codes for diabetes complications and comorbid conditions are provided in eAppendix A (eAppendices available at The Charlson Comorbidity Index (CCI) score, predicting 10-year mortality by weighing 17 comorbid conditions, was calculated to measure disease burden and case mix.13

Healthcare utilization point-of-service (POS) settings included inpatient hospitalizations and procedures, emergency department (ED) visits, skilled nursing facility (SNF) stays, home care visits (eg, visiting nurses), and outpatient/office visits. Utilization was reported by annual rate and by number of episodes per member per year (PMPY). Hypoglycemia-related utilization was reported by episodes per 100 members per year. For healthcare cost, total PMPY spending (pharmacy and medical) and PMPY spending corresponding to each POS setting were calculated. Hypoglycemia-related medical costs were calculated for each POS setting.

Statistical Methods

Descriptive statistics—mean (standard deviation [SD]) or median—and percentage and frequencies of various outcome measures were stratified by whether patients experienced hypoglycemia (hypoglycemia group) or did not experience hypoglycemia (no-hypoglycemia group) during year 1. To identify hypoglycemia risk factors, univariate analyses (Mann-Whitney test or t test for continuous variables, and Cochran-Mantel-Haenszel/χ2 test for categorical variables) and a multivariate logistic regression model were employed. Patient baseline characteristics (ie, demographic/clinical characteristics, underlying conditions, medications, and hospital and ED utilization) were considered.

Unadjusted costs were presented as overall cost, diabetes-related cost, and hypoglycemia-related cost. Because the total expenditure was highly skewed to the right, assumption of constant variance was often violated, and inpatient hospitalization was uncommon, a generalized linear model assuming gamma distribution with log-link function was adapted to estimate total expenditure and inpatient hospital cost, adjusting for patient baseline characteristics. Adjusted cost was run on Statistical Analysis Software (SAS) version 9.2 (SAS Institute, Cary, North Carolina).

Baseline characteristics, including those that were statistically significant in multivariate logistic regression, were added into the cost model and included: age at basal insulin initiation (≥65/<65 years), hypoglycemia (yes/no), endocrinologist visits (yes/no), cardiologist visits (yes/no), metformin (yes/no), sulfonylureas (yes/no), dipeptidyl peptidase-4 inhibitors (yes/no), any antihypertension medication (yes/no), CCI score, nephropathy exam (yes/no), retinopathy (yes/no), neuropathy (yes/no), chronic kidney disease (yes/no), any pancreatitis (yes/no), hyperlipidemia (yes/no), hypertension (yes/no), any macrovascular disease (yes/no), any gastrointestinal disorders (yes/no), any cardiovascular procedures (yes/no), obesity (yes/no), mental illness (yes/no), foot infection (yes/no), any inpatient visit (yes/no), any ED visit (yes/no), and total cost.

Sensitivity analyses were conducted to assess the potential impact of sulfonylureas, prandial insulin, and/or beta-blockers, since these medication classes can cause hypoglycemia or mask hypoglycemia symptoms and influence hypoglycemia rates. A subgroup analysis by A1C  achieved during year 1 of follow-up was conducted. Baseline characteristics were also stratified by health plan (commercial vs Medicare Advantage) and age (≥65 years vs <65 years).


Patient Population

A total of 18,918 basal insulin initiators were identified (eAppendix B). The mean age was 64 years (SD = 13) and 1732 (9.2%) patients initiated basal insulin in the hospital. In the 12 months before initiating basal insulin, 3.9% (741/18,918) of patients had experienced hypoglycemia. During year 1 after basal insulin initiation, 8.9% of patients experienced hypoglycemia. There were 7792 hypoglycemia events in year 1, corresponding to an estimated rate of 0.412 events PMPY in the overall population. When stratified by hypoglycemia during year 1 (ie, hypoglycemia [n = 1683] and no-hypoglycemia [n = 17,235] groups), gender distribution was comparable; however, the hypoglycemia group had more patients 65 years or older versus the no-hypoglycemia group (62.2% vs 51.6%; P <.001) (Table 1). Additional baseline differences included more patients experiencing hypoglycemia (16.2% vs 2.7%) prior to insulin initiation, a higher prevalence of microvascular (60.0% vs 39.8%) and macrovascular (49.2% vs 30.2%) complications, and greater CCI score (4.2 [2.6] vs 3.0 [2.3]) in the hypoglycemia versus no-hypoglycemia group (all P <.001). Baseline healthcare utilization and cost were significantly higher in the hypoglycemia group (Tables 2 and 3).

Predicting Hypoglycemia During Year 1 After Basal Insulin Initiation

The strongest predictor of hypoglycemia during year 1 was hypoglycemia at baseline (OR, 5.49; 95% CI, 4.79-6.28) (Figure 1). Additional significantly predictive baseline factors included foot infection, neuropathy, inpatient hospitalization, macrovascular complications, chronic kidney disease, ED visits, and being at least 65 years.

Clinical Outcomes

Baseline differences observed between the hypoglycemia versus the no-hypoglycemia group remained significant during years 1 and 2 of follow-up (Table 1 and eAppendix C). In both groups, the median number of OADs decreased from 2 to 1 during year 1 and remained at 1 during year 2. Reductions were seen for all OAD classes. For example, in the hypoglycemia group, sulfonylurea use declined from 71% at baseline to 46% during year 1 and to 32% during year 2. Declines in sulfonylurea use in the no-hypoglycemia group appeared comparable.

Microvascular and macrovascular complications and comorbidities appeared to increase to a greater degree in the hypoglycemia group versus the no-hypoglycemia group. In line with these observations, in the hypoglycemia group, the CCI score changed from 4.2 (2.6) at baseline to 5.0 (2.8) and 4.8 (2.9) in years 1 and 2, respectively; whereas in the no-hypoglycemia group, the CCI score changed from 3.0 (2.3) to 3.2 (2.4) and 3.4 (2.5).

Glycemic control data at baseline and follow-up were available for a subset of patients (n = 2512; 13.3%). A1C decreased by 0.5% and 0.7% in the hypoglycemia and no-hypoglycemia groups, respectively, during year 1, and by an additional 0.1% in both groups during year 2. The proportion of patients with A1C ≥9% decreased from 41% at baseline to 32% during year 1 in the hypoglycemia group and from 52% to 39% in the no-hypoglycemia group; reductions were maintained in year 2.

Healthcare Utilization and Cost

Copyright AJMC 2006-2017 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

Sign In

Not a member? Sign up now!