Experiences of People with Diabetes by Payer Type: An Analysis of the Roper Diabetes Data Set

Increase Access, Reduce Disparities: Recommendations for Modifying Medicaid CGM Coverage Eligibility Criteria

Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore the conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. In an earlier article, we discussed the limitations and inconsistencies of the agency's CGM eligibility criteria relative to current scientific evidence and proposed practice solutions to address this issue and improve the safety and care of Medicare beneficiaries with diabetes. Although Medicaid is administered through CMS, there is no consistent Medicaid policy for CGM coverage in the United States. This article presents a rationale for modifying and standardizing Medicaid CGM coverage eligibility across the United States.

Variations in Use of Diabetes Drugs With Cardiovascular Benefits Among Medicaid Patients

IMPORTANCE

Cardiovascular death remains the leading cause of mortality in patients with type 2 diabetes (T2D). A better understanding of the current use and adoption of glucose-lowering drugs with cardiovascular benefit can inform state policies to ensure their appropriate use in patients with T2D.

OBJECTIVE

To characterize the use of glucose-lowering agents with known cardiovascular benefit over time and across states.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional pharmacoepidemiological study of Medicaid prescription rates of glucose-lowering agents with known cardiovascular benefit vs those with less well-established cardiovascular benefit was conducted between 2014 and 2019. In 50 states and the District of Columbia, the study focused on nonmetformin, noninsulin glucose-lowering drugs divided into 3 cohorts: (1) sodium-glucose cotransporter 2 (SGLT2) inhibitors, (2) glucagon-like peptide 1 (GLP1) receptor agonists, and (3) all other classes of glucose-lowering drugs. Data were analyzed from January 2014 to December 2019.

MAIN OUTCOMES AND MEASURES

Number of days supplied of each cohort, use ratios between the aggregated days supplied of glucose-lowering agents with known cardiovascular benefit vs those with less well-established cardiovascular benefit, and the mean change in use ratios per quarter.

RESULTS

Across the 50 states and the District of Columbia, the use ratio of glucose-lowering agents with known cardiovascular benefit ranged from 1.58 to 0.14 (mean [SD], 0.48 [0.27]) in 2019. A lower use ratio was seen in states with a higher prevalence of diabetes (β = -0.049; 95% CI, -0.086 to -0.012; P = .01), a larger total population (β = -0.013; 95% CI, -0.023 to -0.003; P = .01), a greater number of Medicaid enrollees (β = -0.054; 95% CI, -0.096 to -0.014; P = .01), a greater proportion of people enrolled in Medicaid (β = -0.018; 95% CI, -0.030 to -0.007; P = .002), and a greater proportion of Medicaid patients enrolled in managed care organizations (β = -0.0032; 95% CI, -0.0051 to -0.0013; P = .002). Higher Medicaid expenditures per enrollee (β = 0.047; 95% CI, 0.007 to 0.089; P = .03) were associated with a higher use ratio of these agents. The relative use of glucose-lowering agents with known cardiovascular benefit by Medicaid enrollees increased 7.4% per year from 2014 to 2019, with wide variations across state Medicaid programs.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, glucose-lowering agents with cardiovascular benefit increased in use during the study period, but also demonstrated considerable variation among states in their relative use. Medicaid programs should try to clarify which factors may be contributing to relative underuse of these potentially life-saving drugs.

Medicaid Payer Status Is Associated With Increased 90-Day Resource Utilization, Reoperation, and Infection Following Aseptic Revision Total Hip Arthroplasty

Background

Prior literature has demonstrated increased resource utilization and perioperative complications in patients with a Medicaid payor status undergoing primary total hip and knee arthroplasty. This relationship has yet to be explored in patients undergoing revision total hip arthroplasty (rTHA).

Methods

The National Readmissions Database was queried from 2010 to 2015 for all patients undergoing aseptic rTHA. 90-day complication data were collected, and patients were separated into two cohorts based on insurance payor type: Medicaid and non-Medicaid. Patients were propensity score matched 2:1 on a number of comorbid and operative characteristics. The relationship between Medicaid payor status and postoperative outcomes was then assessed using binomial logistic regression analysis.

Results

3,110 Medicaid patients were identified and matched to 6,175 non-Medicaid patients. Medicaid patients had increased odds of an early prosthetic joint infection (Odds Ratio [OR] 1.29, p=0.019), superficial surgical site infection (OR: 1.48, p=0.003), and early reoperation (OR: 1.18, p=0.045). Medicaid patients also experienced higher odds of readmissions, extended length of stay, non-home discharge status, and medical complications. Finally, the Medicaid cohort had a $3,332 (95% CI: 2,412-4,253, p<0.001) increased adjusted total cost of care when compared to the non-Medicaid cohort.

Conclusion

This study identifies the Medicaid payor status as an independent risk factor for increased resource utilization, reoperation, and infection in the early postoperative period for patients undergoing rTHA. This relationship is likely due to an interplay of multiple variables, including socioeconomic status and access to care. Level of Evidence: IV.

Patient-specific factors associated with use of diabetes self-management education and support programs in Louisiana

INTRODUCTION

The prevalence of diabetes self-management education and support (DSME/S) use among patients with newly diagnosed type 2 diabetes mellitus (T2DM) and patients with insulin prescription has not been evaluated. It is also unclear what demographic, behavioral, and clinical factors associated with use of DSME/S.

RESEARCH DESIGN AND METHODS

This retrospective analysis was based on electronic health records from the Research Action for Health Network (2013-2019). Patients with newly diagnosed T2DM were identified as 35-94 year-olds diagnosed with T2DM≥1 year after the first recorded office visit. Patients with insulin were identified by the first insulin prescription records. DSME/S (Healthcare Common Procedure Coding System G0108 and G0109) codes that occurred from 2 months before the 'new diagnosis date' or first insulin prescription date through 1 year after were defined as use of DSME/S. Age-matched controls (non-users) were identified from the Electronic Health Records (EHR). The date of first DSME/S record was selected as the index date. Logistic regression was used to estimate the associations between patient factors and use of DSME/S.

RESULTS

The prevalence of DSME/S use was 6.5% (8909/137 629) among patients with newly diagnosed T2DM and 32.7% (13,152/40,212) among patients with diabetes taking insulin. Multivariable analysis found that among patients with newly diagnosed T2DM, black and male patients were less likely to use DSME/S, while in patients with insulin, they were more likely to use the service compared with white and female counterparts, respectively. Among patients taking insulin, those with private insurance or self-pay status were significantly less likely, while those with Medicaid were more likely to use the service compared with their Medicare counterparts. A strong positive association was found between HbA1c, obesity, and DSME/S use in both cohorts, while hypertension was negatively associated with DSME/S in both cohorts.

CONCLUSION

We showed a low rate of DSME/S use in Louisiana, especially in patients with newly diagnosed T2DM. Our findings demonstrated heterogeneity in factors influencing DSME/S use between patients with newly diagnosed T2D and patients with insulin.

Distance from the endocrinology clinic and diabetes control in a rural pediatric population

OBJECTIVE

We analyzed the impact of geographic distance from the clinic on adherence to recommended clinic visits and diabetes control among patients with type 1 diabetes (T1D) seen in a pediatric endocrinology clinic serving a rural region in eastern North Carolina.

METHODS

We retrospectively included patients with T1D age ≤20 years seen in our clinic during 2017. Outcomes were tracked until June 2018. Distance from the clinic was determined according to the zone improvement plan (ZIP) code of patient address. Visit adherence was defined based on the number of attended visits during the study period, aiming for 1 every 3 months. Glycated hemoglobin (HbA1c) was measured at the first and last visits during the review period.

RESULTS

The analysis included 368 patients, of whom 218 (59%) completed at least 1 visit every 3 months. The median HbA1c was 9.1 (interquartile range [IQR]: 8.0, 10.3) at the initial visit, and 9.3 (IQR: 8.0, 11.1) at the final visit. Median distance from the clinic was 56 km (IQR: 35, 86). On multivariable logistic regression, greater distance from the clinic was associated with lower odds of visit adherence (odds ratio per 10 km: 0.93; 95% confidence interval: 0.87, 0.99; p=0.030). Neither distance to the clinic nor clinic visit adherence were associated with HbA1c.

CONCLUSIONS

Patients living further away from the clinic were less likely to adhere to the recommended visit schedule, but distance was not correlated with HbA1c levels. Further work is needed to assist families living far from the clinic with adhering to recommended visits.

Flash CGM Is Associated With Reduced Diabetes Events and Hospitalizations in Insulin-Treated Type 2 Diabetes

Purpose

Suboptimal glycemic control among individuals with diabetes is a leading cause of hospitalizations and emergency department utilization. Use of flash continuous glucose monitoring (flash CGM) improves glycemic control in type 1 and type 2 diabetes, which may result in lower risk for acute and chronic complications that require emergency services and/or hospitalizations.

Methods

In this retrospective, real-world study, we analyzed IBM MarketScan Commercial Claims and Medicare Supplemental databases to assess the impact of flash CGM on diabetes-related events and hospitalizations in a cohort of 2463 individuals with type 2 diabetes who were on short- or rapid-acting insulin therapy. Outcomes were changes in acute diabetes-related events (ADE) and all-cause inpatient hospitalizations (ACH), occurring during the first 6 months after acquiring the flash CGM system compared with event rates during the 6 months prior to system acquisition. ICD-10 codes were used to identify ADE for hypoglycemia, hypoglycemic coma, hyperglycemia, diabetic ketoacidosis, and hyperosmolarity.

Results

ADE rates decreased from 0.180 to 0.072 events/patient-year (hazard ratio [HR]: 0.39 [0.30, 0.51]; P < 0.001) and ACH rates decreased from 0.420 to 0.283 events/patient-year (HR: 0.68 [0.59 0.78]; P < 0.001). ADE reduction occurred regardless of age or gender.

Conclusions

Acquisition of the flash CGM system was associated with reductions in ADE and ACH. These findings provide support for the use of flash CGM in type 2 diabetes patients treated with short- or rapid-acting insulin therapy to improve clinical outcomes and potentially reduce costs.

Trends in Emergency Department Visits and Inpatient Admissions for Hyperglycemic Crises in Adults With Diabetes in the U.S., 2006-2015

OBJECTIVE

To report U.S. national population-based rates and trends in diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar state (HHS) among adults, in both the emergency department (ED) and inpatient settings.

RESEARCH DESIGN AND METHODS

We analyzed data from 1 January 2006 through 30 September 2015 from the Nationwide Emergency Department Sample and National Inpatient Sample to characterize ED visits and inpatient admissions with DKA and HHS. We used corresponding year cross-sectional survey data from the National Health Interview Survey to estimate the number of adults ≥18 years with diagnosed diabetes to calculate population-based rates for DKA and HHS in both ED and inpatient settings. Linear trends from 2009 to 2015 were assessed using Joinpoint software.

RESULTS

In 2014, there were a total of 184,255 and 27,532 events for DKA and HHS, respectively. The majority of DKA events occurred in young adults aged 18-44 years (61.7%) and in adults with type 1 diabetes (70.6%), while HHS events were more prominent in middle-aged adults 45-64 years (47.5%) and in adults with type 2 diabetes (88.1%). Approximately 40% of the hyperglycemic events were in lower-income populations. Overall, event rates for DKA significantly increased from 2009 to 2015 in both ED (annual percentage change [APC] 13.5%) and inpatient settings (APC 8.3%). A similar trend was seen for HHS (APC 16.5% in ED and 6.3% in inpatient). The increase was in all age-groups and in both men and women.

CONCLUSIONS

Causes of increased rates of hyperglycemic events are unknown. More detailed data are needed to investigate the etiology and determine prevention strategies.

Health Care Utilization and Burden of Diabetic Ketoacidosis in the U.S. Over the Past Decade: A Nationwide Analysis

OBJECTIVE

Diabetes is one of the most common chronic diseases and a leading cause of morbidity and mortality in the U.S. Although our ability to treat diabetes and its associated complications has significantly improved, presentation with uncontrolled diabetes leading to ketoacidosis remains a significant problem.

RESEARCH DESIGN AND METHODS

We aimed to determine the incidence and costs of hospital admissions associated with diabetic ketoacidosis (DKA). We reviewed the National Inpatient Sample database for all hospitalizations in which DKA (ICD-9 codes 250.10, 250.11, 250.12, and 250.13) was the principal discharge diagnosis during 2003-2014 and calculated the population incidence by using U.S. census data. Patients with ICD-9 codes for diabetic coma were excluded because the codes do not distinguish between hypoglycemic and DKA-related coma. We then analyzed changes in temporal trends of incidence, length of stay, costs, and in-hospital mortality by using the Cochrane-Armitage test.

RESULTS

There were 1,760,101 primary admissions for DKA during the study period. In-hospital mortality for the cohort was 0.4% (n = 7,031). The total number of hospital discharges with the principal diagnosis of DKA increased from 118,808 in 2003 to 188,965 in 2014 (P < 0.0001). The length of stay significantly decreased from an average of 3.64 days in 2003 to 3.24 days in 2014 (P < 0.01). During this period, the mean hospital charges increased significantly from $18,987 (after adjusting for inflation) per admission in 2003 to $26,566 per admission in 2014. The resulting aggregate charges (i.e., national bill) for diabetes with ketoacidosis increased dramatically from $2.2 billion (after adjusting for inflation) in 2003 to $ 5.1 billion in 2014 (P < 0.001). However, there was a significant reduction in mortality from 611 (0.51%) in 2003 to 620 (0.3%) in 2014 (P < 0.01).

CONCLUSIONS

Our analysis shows that the population incidence for DKA hospitalizations in the U.S. continues to increase, but the mortality from this condition has significantly decreased, indicating advances in early diagnosis and better inpatient care. Despite decreases in the length of stay, the costs of hospitalizations have increased significantly, indicating opportunities for value-based care intervention in this vulnerable population.

Does insulin therapy matter? Determinants of diabetes care outcomes

OBJECTIVE

To evaluate adherence to care standards for people with diabetes (PWDs) on insulin therapy versus PWDs who are not on insulin therapy, controlling for social determinants.

RESEARCH DESIGN AND METHODS

Utilizing the United States 2015 Behavioral Risk Factor Surveillance System Survey, this study used logistic regression analyses to estimate differences in self-care behaviors, healthcare provider quality of care, and diabetic complications for individuals on insulin therapy and individuals not on insulin therapy.

RESULTS

PWDs on insulin therapy are more likely to adhere to self-care measures (self-glucose checks [OR: 7.57], self-foot checks [OR: 1.27], diabetes class participation [OR: 1.96]), adherence to provider care standards (diabetes-related doctor visits [OR: 1.24], comprehensive foot exam [OR: 1.80], dilated eye exam [OR: 1.34]), and to self-report diabetic complications (retinopathy [OR: 2.77], kidney disease [OR:2.14]), controlling for sociodemographic variables.

CONCLUSION

PWDs on insulin and their healthcare providers are more likely to meet the treatment goals set by the American Diabetes Association. PWDs on insulin therapy may have better overall relationships with providers due to a reduction in stigmatization based on the social construction of diabetes.

For Diabetes Shared Savings Programs, 1 Year of Data Is Not Enough

Fee-for-service payment models are moving toward pay-for-performance designs, many of which rely on shared savings for financial sustainability. Shared savings programs divide the cost savings between health care purchaser and provider based on provider performance. Often, these programs measure provider performance as the delivery of agreed-upon clinical practice guidelines that usually are represented as evidence-based medicine (EBM). Multiyear studies show a negative relationship between total cost and EBM, indicating that long-term shared savings can be substantial. This study explores expectations for the rewards in the first year of a shared savings program. It also indicates the effectiveness of using 1 year of claims to assess cost savings from evidence-based care, especially in a patient population with high turnover. This study analyzed 1956 adults with diabetes insured through Medicaid. Results of linear regression showed that the relationship between total cost of care and each element of evidence-based medical care during a 1-year period was positive (higher cost) or insignificant. The results indicate that diabetes EBM programs cannot expect to see significant cost savings if the evaluation lasts only 1 year or less. The study concludes that improvements in EBM incentive programs could come from investigating the length of time needed to realize cost savings from each element of diabetes EBM. Investigating other factors that could affect the expected amount of cost savings also would benefit these programs, especially factors derived from sources external to insurance program information such as the medical record and care management data.