Economic value of nonsurgical weight loss in adults with obesity.

BACKGROUND: Obesity imposes a substantial economic burden on the United States. The short-term value of nonsurgical weight loss (WL) and nonsurgical sustained WL (i.e., WL not resulting from bariatric surgery) is poorly understood. OBJECTIVES: To assess short-term (1 year) effect of nonsurgical WL and sustained nonsurgical WL (i.e., approximately 2 years) on per-patient-per-month (PPPM) total all-cause health care costs among adults with obesity in the United States. METHODS: In this retrospective cohort study, we analyzed data from the IBM MarketScan Explorys Claims-EMR Data Set from January 1, 2012, through June 30, 2018. Adults aged 18-64 years with a body mass index (BMI) measurement ≥ 30 kg/m2 on the index date and BMI measurements at 12, 24, and 36 months were classified into weight-gain (≥ 3%), no-weight-change (within ± 3%), and WL (≥ 3%-≤ 5%, > 5%-≤ 10%, and > 10%-≤ 20%) cohorts based on the change from first to second BMI measurements (baseline), and sustained nonsurgical WL based on WL during baseline and < 3% weight gain from second to third BMI measurement. PPPM all-cause health care costs were calculated for baseline, first year, and second year of follow-up. Generalized linear models were used to examine if PPPM all-cause health care cost change (ΔPPPM) from baseline to follow-up differed significantly between nonsurgical WL/sustained WL and no-weight-change cohorts. Analyses were stratified by index obesity class (class 1: BMI 30- < 34.9 kg/m2, class 2: BMI 35- < 39.9 kg/m2, class 3: BMI ≥ 40 kg/m2). Specific nonsurgical WL treatments used by individuals in the study were not studied. RESULTS: The sample included 20,488 adults who were grouped as follows: weight-gain cohort (24.8%), no-weight-change cohort (56.6%), ≥ 3%- ≤ 5% WL cohort (8.2%), > 5%- ≤ 10% WL cohort (7.7%), and > 10%- ≤ 20% WL cohort (2.8%). Compared with the no-weight-change cohort, adjusted mean ΔPPPM all-cause health care cost from baseline to first year of follow-up was lower in all WL cohorts (≥ 3%- ≤ 5% WL: -$57.36, > 5%- ≤ 10% WL: -$135.35 [P < 0.05], > 10%- ≤ 20% WL: -$193.54 [P < 0.05]). In the second year of follow-up (n = 15,307), the cohorts were weight-gain (43.4%), no-weight-change (59.4%), ≥ 3%- ≤ 5% sustained WL (7.3%), ≥ 5%- ≤ 10% sustained WL (6.3%), and > 10%- ≤ 20% sustained WL (1.8%). Adjusted mean ΔPPPM all-cause health care cost was lower in all sustained WL groups (-$26.38, -$157.41 [P < 0.05], and -$185.41 for ≥ 3%- ≤ 5%, ≥ 5%- ≤ 10%, and > 10%- ≤ 20% WL, respectively). Greater nonsurgical WL and sustained nonsurgical WL were generally associated with larger reduction in short-term all-cause health care costs. Results stratified by index obesity class were mixed, due to small samples. CONCLUSIONS: Substantial all-cause health care cost savings were observed 1 year after nonsurgical WL and after sustained (on average for 2 years) nonsurgical WL in adults with obesity, with greater nonsurgical WL and sustained nonsurgical WL associated with greater cost savings. Comprehensive solutions to chronic weight management, including improved access to antiobesity medications in combination with lifestyle interventions, could be valuable to patients, employers, and payers. DISCLOSURES: This study was sponsored by Novo Nordisk, which also purchased the data. Blanchette is an employee of Novo Nordisk. Smolarz and Ramasamy are employees of Novo Nordisk and hold equity in Novo Nordisk. Ding, Fan, and Weng were employees of Novo Nordisk at the time this study was conducted. The findings from this study were previously presented at Obesity Week 2019; November 3-7, 2019; Las Vegas, NV.

Assessing Prevalence of Hypoglycemia in a Medical Transcription Database.

PURPOSE: The prevalence of hypoglycemia in patients with diabetes mellitus is likely underreported, particularly with regard to non-severe episodes, and representative estimates require more detailed data than claims or typical electronic health record (EHR) databases provide. This study examines the prevalence of hypoglycemia as identified in a medical transcription database. PATIENTS AND METHODS: The Amplity Insights database contains medical content dictated by providers detailing patient encounters with health care professionals (HCPs) from across the United States. Natural language processing (NLP) was used to identify episodes of hypoglycemia using both symptom-based and non-symptom-based definitions of hypoglycemic events. This study examined records of 41,688 patients with type 1 diabetes mellitus and 317,399 patients with type 2 diabetes mellitus between January 1, 2016, and April 30, 2018. RESULTS: Using a non-symptom-based definition, the prevalence of hypoglycemia was 18% among patients with T1DM and 8% among patients with T2DM. These estimates show the prevalence of hypoglycemia to be 2- to 9-fold higher than the 1% to 4% prevalence estimates suggested by claims database analyses. CONCLUSION: In this exploration of a medical transcription database, the prevalence of hypoglycemia was considerably higher than what has been reported via retrospective analyses from claims and EHR databases. This analysis suggests that data sources other than claims and EHR may provide a more in-depth look into discrepancies between the mention of hypoglycemia events during a health care visit and documentation of hypoglycemia in patient records.

Association between shared medical appointments and weight loss outcomes and anti-obesity medication use in patients with obesity.

OBJECTIVE: In shared medical appointments (SMAs), multiple patients with a similar clinical diagnosis are seen by a multidisciplinary team for interactive group sessions. Very few studies have specifically studied SMAs and weight loss in patients with obesity. This study compared weight loss outcomes and anti-obesity medication (AOM) access between patients with obesity managed through (SMAs) versus individual appointments. METHODS: Retrospective study of adults seen for obesity between September 2014 and February 2017 at Cleveland Clinic Institute of Endocrinology and Metabolism. Percent weight loss from baseline was compared between two propensity score-matched populations: patients who attended ≥1 SMA and patients managed with individual medical appointments. RESULTS: From all eligible patients identified (n=310 SMA, n=1,993 non-SMA), 301 matched pairs were evaluated for weight loss. The SMA group (n=301) lost a mean of 4.2%, 5.2% and 3.8% of baseline weight over 6, 12 and 24 months; the non-SMA group (n=301) lost significantly less weight (1.5%, 1.8% and 1.6%, respectively) (paired t-test, P<.05). All patients were eligible for US Food and Drug Administration-approved AOMs based on obesity diagnosis; however, 49.8% (150/301) of matched SMA patients were prescribed an AOM versus 12.3% (37/301) of matched non-SMA patients. CONCLUSION: This study suggests that SMAs may offer a promising alterative for obesity management and one that may facilitate greater utilization of AOMs. In propensity score-matched cohorts, SMAs were associated with greater weight loss outcomes when compared to usual care facilitated through individual medical appointments alone.

The Probability of A1C Goal Attainment in Patients With Uncontrolled Type 2 Diabetes in a Large Integrated Delivery System: A Prediction Model.

OBJECTIVE: To assess patient characteristics and treatment factors associated with uncontrolled type 2 diabetes (T2D) and the probability of hemoglobin A1c (A1C) goal attainment. RESEARCH DESIGN AND METHODS: This was a retrospective cohort study using the electronic health record at Cleveland Clinic. Patients with uncontrolled T2D (A1C >9%) were identified on the index date of 31 December 2016 (n = 6,973) and grouped by attainment (n = 1,653 [23.7%]) or nonattainment (n = 5,320 [76.3%]) of A1C <8% by 31 December 2017, and subgroups were compared on a number of demographic and clinical variables. On the basis of these variables, a nomogram was created for predicting probability of A1C goal attainment. RESULTS: For the entire population, median age at index date was 57.7 years (53.3% male), and the majority were white (67.2%). Median A1C was 10.2%. Obesity (50.6%), cardiovascular disease (46.9%), and psychiatric disease (61.1%) were the most common comorbidities. Metformin (62.7%) and sulfonylureas (38.7%) were the most common antidiabetes medications. Only 1,653 (23.7%) patients achieved an A1C <8%. Predictors of increased probability of A1C goal attainment were older age, white/non-Hispanic race/ethnicity, Medicare health insurance, lower baseline A1C, higher frequency of endocrinology/primary care visits, dipeptidyl peptidase 4 inhibitor use, thiazolidinedione use, metformin use, glucagon-like peptide 1 receptor agonist use, and fewer classes of antidiabetes drugs. Factors associated with lower probability included insulin use and longer time in the T2D database (both presumed as likely surrogates for duration of T2D). CONCLUSIONS: A minority of patients with an A1C >9% achieved an A1C <8% at 1 year. While most identified predictive factors are nonmodifiable by the clinician, pursuit of frequent patient engagement and tailored drug regimens may help to improve A1C goal attainment.

Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of future severe hypoglycemia (SH). RESEARCH DESIGN AND METHODS: From 2005 to 2017, we identified NSH events by diagnosis codes and NLP. We then built an SH prediction model. RESULTS: There were 204,517 patients with type 2 diabetes and no diagnosis codes for NSH. Evidence of NSH was found in 7,035 (3.4%) of patients using NLP. We reviewed 1,200 of the NLP-detected NSH notes and confirmed 93% to have NSH. The SH prediction model (C-statistic 0.806) showed increased risk with NSH (hazard ratio 4.44; P < 0.001). However, the model with NLP did not improve SH prediction compared with diagnosis code-only NSH. CONCLUSIONS: Detection of NSH improved with NLP in patients with type 2 diabetes without improving SH prediction.

The prevalence of cardiovascular disease by vascular bed and impact on healthcare costs in a large, real-world population with type 2 diabetes.

INTRODUCTION: The purpose of this study was to assess prevalence of atherosclerotic cardiovascular disease (ASCVD) according to number of affected vascular beds and the impact on healthcare utilization and costs in persons with type 2 diabetes mellitus (type 2 DM) and established ASCVD. METHODS: In this retrospective, cross-sectional analysis, adults with type 2 DM and ASCVD in a large US administrative claims database were categorized by number of ASCVD-affected vascular beds (brain, heart, peripheral vasculature). Annual healthcare utilization and costs for 2015 were determined, including subgroup analyses by age group (18-44, 45-64, ≥65 years). RESULTS: Among 539 089 individuals with type 2 DM and ASCVD, 47.0% had ASCVD affecting >1 vascular bed. The most prevalent ASCVD diagnoses were acute coronary syndrome (26.6%), peripheral arterial disease (24.5%) and stroke (18.6%). Mean annual total healthcare costs per person increased with increasing number of vascular beds, from 1 ($17 741) to 2 ($25 877) to 3 ($33 412). A similar pattern of increased healthcare utilization with increasing number of vascular beds was observed. Among individuals with 1 affected vascular bed, mean total healthcare costs per person were comparable across age subgroups; however, if >1 vascular bed was affected, the mean total healthcare costs were highest in the youngest age cohort. CONCLUSIONS: These real-world data showed that almost half of individuals with type 2 DM and ASCVD had ASCVD affecting >1 vascular bed. A higher number of affected vascular beds were associated with higher mean total healthcare costs and utilization, with a disproportionate increase noted in younger relative to older people.

Impact of atherosclerotic cardiovascular disease on healthcare resource utilization and costs in patients with type 2 diabetes mellitus in a real-world setting.

BACKGROUND: This study evaluated the impact of atherosclerotic cardiovascular disease (ASCVD) on healthcare resource utilization and costs in patients with type 2 diabetes mellitus (T2DM). METHODS: This study was a retrospective, cross-sectional study using US claims data. Adult patients with T2DM were stratified by presence or absence of ASCVD and compared regarding annual (2015) healthcare resource utilization and associated costs. Subgroup analyses were conducted for three age groups (18-44, 45-64, and ≥ 65 years). RESULTS: Among 1,202,596 eligible patients with T2DM, 45.2% had documented ASCVD. The proportions of patients with inpatient and ER-based resource utilization during 2015 were three-to-four times greater in the ASCVD cohort as compared to the non-ASCVD cohort for the categories of inpatient visits (15.6% vs 4.4% of patients), outpatient ER visits (18.4% vs 5.2% of patients), and inpatient ER visits (4.3% vs 0.9% of patients). Outpatient utilization also was higher among patients with ASCVD as compared to those without ASCVD (mean number of annual office visits per patient, 9.1 vs 5.6), and more than twice as many patients with ASCVD had ≥ 9 office visits (43.5% vs 19.8%). Average per-patient total healthcare cost was $22,977 for ASCVD vs $9735 for non-ASCVD, with medical costs primarily driving the difference ($17,849 vs $6079); the difference in pharmacy costs was smaller ($5128 vs $3656). In the 18-44, 45-64, and ≥ 65 age subgroups respectively, total annual healthcare costs were 143, 127, and 114% higher in ASCVD vs non-ASCVD patients. CONCLUSIONS: These findings indicate significantly higher healthcare resource utilization and associated costs in patients having T2DM with ASCVD compared to T2DM without ASCVD.

The prevalence of cardiovascular disease and antidiabetes treatment characteristics among a large type 2 diabetes population in the United States.

OBJECTIVES: The purpose of this study was to assess atherosclerotic cardiovascular disease (ASCVD) prevalence, antidiabetes medication usage and physician specialty encounters among individuals with type 2 diabetes mellitus (T2DM) in the United States during 2015. DESIGN: Retrospective, cross-sectional analysis. PATIENTS: Adults with T2DM in a large US administrative claims database. Patients were divided into ASCVD and non-ASCVD groups. Subgroup analyses were conducted for three age groups (18-44, 45-64 and 65+ years). RESULTS: Of 1 202 596 patients with T2DM, 45.2% had established ASCVD. About 40% of T2DM patients with ASCVD had visited a cardiologist during 2015, compared to 11% in the non-ASCVD group. The use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose co-transporter 2 inhibitors (SGLT-2is) was low overall (<12%), and even lower in the ASCVD group (<9%). The prevalence of ASCVD was 15%, 36% and 71% in the 18-44, 45-64 and 65+ year age groups, respectively. GLP-1RA and SGLT-2i use was ≤5% in the 65+ subgroup, regardless of ASCVD status. CONCLUSIONS: These real-world data showed a high prevalence of ASCVD among T2DM patients, and confirmed, as a baseline assessment, low use of GLP-1RAs and SGLT-2is in these at-risk patients prior to the 2017 American Diabetes Association guidelines recommending use of agents with proven cardiovascular benefits.

Persistence of newer anti-obesity medications in a real-world setting.

AIMS: Evaluate real-world data on persistence with anti-obesity medications (AOMs) and explore associated patient factors. METHODS: Truven Health MarketScan® data were analyzed to evaluate utilization of AOMs approved for long-term use between 4/2015 and 3/2016. Kaplan-Meier survival analyses were used to evaluate treatment persistence. A multivariate analysis was performed to identify associations between persistence and relevant factors. RESULTS: In total, 26,522 adult patients were identified as newly prescribed naltrexone/bupropion (44.0%, mean age 47.1, 80.5% female), lorcaserin (24.8%, 48.5, 79.3%), phentermine/topiramate extended release (15.8%, 46.7, 82.2%) or liraglutide 3.0 mg (15.4%, 46.9, 72.4%). At 6 months, 41.8% of patients were still on liraglutide 3.0 mg, compared to 15.9% lorcaserin (p < 0.001), 18.1% naltrexone/bupropion (p < 0.001), and 27.3% phentermine/topiramate (p < 0.001). After adjusting for baseline factors, patients on liraglutide 3.0 mg had significantly lower risk of discontinuation compared to those on lorcaserin (HR = 0.46, p < 0.0001), naltrexone/bupropion (HR = 0.48, p < 0.0001), and phentermine/topiramate (HR = 0.64, p < 0.0001) over the course of follow-up (mean follow-up duration, 342-427 days). Older age, male gender, having hyperlipidemia, and no prior phentermine use were associated with higher persistence. Over 95% of study patients had commercial insurance. CONCLUSIONS: In a real-world setting, patients on liraglutide 3.0 mg had the highest persistence rate of the four AOMs studied.

Antidiabetic treatment patterns and specialty care utilization among patients with type 2 diabetes and cardiovascular disease.

BACKGROUND: To evaluate real-world patient characteristics, medication use, and health care utilization patterns in patients with type 2 diabetes with established cardiovascular disease (CVD). METHODS: Cross-sectional analysis of patients with type 2 diabetes seen at Cleveland Clinic from 2005 to 2016, divided into two cohorts: with-CVD and without-CVD. Patient demographics and antidiabetic medications were recorded in December 2016; department encounters included all visits from 1/1/2016 to 12/31/2016. Comorbidity burden was assessed by the diabetes complications severity index (DCSI) score. RESULTS: Of 95,569 patients with type 2 diabetes, 40,910 (42.8%) were identified as having established CVD. Patients with CVD vs. those without were older (median age 69.1 vs. 58.2 years), predominantly male (53.8% vs. 42.6%), and more likely to have Medicare insurance (69.4% vs. 35.3%). The with-CVD cohort had a higher proportion of patients with a DCSI score ≥ 3 than the without-CVD cohort (65.0% vs. 10.3%). Utilization rates of glucagon-like peptide-1 receptor agonists and sodium-glucose co-transporter-2 inhibitors were low in both with-CVD (4.1 and 2.5%) and without-CVD cohorts (5.4 and 4.1%), respectively. The majority of patient visits (75%) were seen by a primary care provider. During the 1-year observation period, 81.9 and 62.0% of patients with type 2 diabetes and CVD were not seen by endocrinology or cardiology, respectively. CONCLUSIONS: These data indicated underutilization of specialists and antidiabetic medications reported to confer CV benefit in patients with type 2 diabetes and CVD. The impact of recently updated guidelines and cardiovascular outcome trial results on management patterns in such patients remains to be seen.

Effect of glycemic control on the Diabetes Complications Severity Index score and development of complications in people with newly diagnosed type 2 diabetes.

BACKGROUND: The aim of the present study was to assess the longitudinal accumulation of diabetes-related complications and the effect of glycemic control on the Diabetes Complications Severity Index (DCSI) score in people with newly diagnosed type 2 diabetes (T2D). METHODS: A retrospective cohort study was conducted using electronic health records from a large integrated healthcare system. People with newly diagnosed T2D were identified between 2005 and 2016 and stratified by initial HbA1c category (<7%, <8%, ≥8%). The DCSI scores were determined for each study year, and the cumulative incidence of diabetes-related complications was assessed. A Cox proportional hazard model was used to evaluate the effect of baseline HbA1c and worsening glycemic (HbA1c) control on longitudinal changes in DCSI scores. RESULTS: Of 32 174 people identified as having newly diagnosed T2D, 14 016 (44%), 21 657 (67%), and 9983 (31%) had an initial or baseline HbA1c <7%, <8%, and ≥8%, respectively. Ten years after diabetes diagnosis, retinopathy, chronic kidney disease, coronary heart disease, and neuropathy were diagnosed in 22%, 29%, 24%, and 36% of people. Baseline HbA1c did not affect the observed trend in longitudinal changes in DCSI scores throughout the 11-year period. For people in each of the initial HbA1c groups (<7%, <8%, ≥8%), worsening or persistently poor glycemic control was significantly associated with a 10%, 19%, or 16% increase in the risk of experiencing an increased DCSI score, respectively (all P < 0.01). CONCLUSIONS: Baseline glycemic control had no apparent effect on longitudinal changes in DCSI score. Worsening or persistently poor glycemic control was associated with an increased risk of an increase in the DCSI score.

Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system.

OBJECTIVE: To determine the prevalence of obesity and its related comorbidities among patients being actively managed at a US academic medical centre, and to examine the frequency of a formal diagnosis of obesity, via International Classification of Diseases, Ninth Revision (ICD-9) documentation among patients with body mass index (BMI) ≥30 kg/m2. DESIGN: The electronic health record system at Cleveland Clinic was used to create a cross-sectional summary of actively managed patients meeting minimum primary care physician visit frequency requirements. Eligible patients were stratified by BMI categories, based on most recent weight and median of all recorded heights obtained on or before the index date of 1July 2015. Relationships between patient characteristics and BMI categories were tested. SETTING: A large US integrated health system. RESULTS: A total of 324 199 active patients with a recorded BMI were identified. There were 121 287 (37.4%) patients found to be overweight (BMI ≥25 and <29.9), 75 199 (23.2%) had BMI 30-34.9, 34 152 (10.5%) had BMI 35-39.9 and 25 137 (7.8%) had BMI ≥40. There was a higher prevalence of type 2 diabetes, pre-diabetes, hypertension and cardiovascular disease (P value<0.0001) within higher BMI compared with lower BMI categories. In patients with a BMI >30 (n=134 488), only 48% (64 056) had documentation of an obesity ICD-9 code. In those patients with a BMI >40, only 75% had an obesity ICD-9 code. CONCLUSIONS: This cross-sectional summary from a large US integrated health system found that three out of every four patients had overweight or obesity based on BMI. Patients within higher BMI categories had a higher prevalence of comorbidities. Less than half of patients who were identified as having obesity according to BMI received a formal diagnosis via ICD-9 documentation. The disease of obesity is very prevalent yet underdiagnosed in our clinics. The under diagnosing of obesity may serve as an important barrier to treatment initiation.

Treatment patterns and clinical characteristics of patients with type 2 diabetes mellitus according to body mass index: findings from an electronic medical records database.

OBJECTIVE: This study evaluated relationships between glycaemic control, body mass index (BMI), comorbidities and pharmacological treatment in patients with type 2 diabetes mellitus (T2D). RESEARCH DESIGN AND METHODS: This was a retrospective, cross-sectional analysis of Quintiles electronic medical records research data (study period 1 October 2013-30 September 2014). Eligibility included age ≥18 years, T2D diagnosis, and at least one available BMI measurement. RESULTS: The study included 626 386 patients (mean age, 63.8 year; 51.3% female; 78.5% white; 62.6%, BMI ≥30 kg/m2). A1c data were available for 414 266 patients. The proportion of patients with good glycaemic control (A1c ≤6.5) decreased as BMI category increased, ranging from 40.1% of patients with BMI <30% to 30.1% of patients with BMI ≥40. The proportions of patients with poor glycaemic control (A1c >8% and A1c ≥9%) increased with increasing BMI category. Oral antidiabetic drugs (OAD) were the most frequently used (54.4% of patients with A1c values). Among patients using insulin-based therapy, 50% had an A1c ≥8% and 29% had an A1c ≥9% regardless of concomitant OAD or glucagon-like peptide 1 receptor agonist use. Among patients using three or more OADs, 34.3% and 16.1% had A1c values ≥8% and ≥9%, respectively. There was no common trend observed for changes in the proportion of patients with T2D-related comorbidities according to BMI category. The most notable trend was a 7.6% net increase in the percentage of patients with hypertension from BMI <30 to BMI ≥40. CONCLUSIONS: This large dataset provides evidence that roughly one out of four patients with T2D is not well controlled, and the prevalence of poor glycaemic control increases as BMI increases.

Association of glucagon-like peptide-1 receptor agonist use and rates of acute myocardial infarction, stroke and overall mortality in patients with type 2 diabetes mellitus in a large integrated health system.

AIMS: To assess the potential impact of glucagon-like peptide-1 receptor agonist (GLP-1RA) exposure on cardiovascular disease (CVD) and mortality outcomes in patients with type 2 diabetes (T2D), using a large retrospective cohort. RESEARCH DESIGN AND METHODS: Patients who had T2D between 2005 and 2014 (N = 105 862) were identified from the electronic health record system at Cleveland Clinic using a validated electronic phenotype. A time-dependent, Cox, multiple regression analysis was used to assess the association between GLP-1RA exposure and risk of acute myocardial infarction (AMI), stroke/cerebrovascular accident (CVA), and overall mortality, as well as the composite of all three outcomes. The findings were further evaluated by assessing the effect of GLP-1RAs on the same variables in patients with and without prior CVD. The model adjusted for differences in demographic information, hypertension, laboratory/vital signs, history of outcomes, and T2D medications. RESULTS: There were significantly lower rates of AMI (hazard ratio [HR] 0.80, 95% confidence interval [CI] 0.65 to 0.99; P = .045), CVA (HR 0.82, 95% CI 0.74 to 0.91, P < .001), overall mortality (HR 0.48, 95% CI 0.41 to 0.57; P < .001), and the composite outcome (HR 0.82, 95% CI 0.74 to 0.91; P < .002) during the consolidated time that patients were exposed to GLP-1RAs compared to corresponding rates during intervals without GLP-1RA exposure. GLP-1RA treatment was associated with a significant decrease in CVA, mortality, and the composite outcome in patients with and without established CVD, not significantly affecting AMI in these subgroups. CONCLUSIONS: GLP-1RA exposure was found to be associated with a reduction in the risk of cardiovascular events observed and overall mortality among patients with T2D with and without established CVD, after adjusting for potential confounders.

Changes in Characteristics and Treatment Patterns of Patients with Newly Diagnosed Type 2 Diabetes in a Large United States Integrated Health System between 2008 and 2013.

To assess changes in the clinical characteristics and treatment patterns of patients with newly diagnosed type 2 diabetes (T2D), the electronic health record system at Cleveland Clinic was used to create cross-sectional summaries of all patients with new-onset T2D in 2008 and 2013. Differences between the 2008 and 2013 data sets were assessed after adjusting for age, gender, race, and income. Approximately one-third of patients with newly diagnosed T2D in 2008 and 2013 had an A1C ≥8%, suggesting the continued presence of a delayed recognition of the disease. Patients with newly diagnosed T2D in 2008 were older than those in 2013. Hypertension, cardiovascular disease, and neuropathy were highly prevalent among patients diagnosed with T2D. The prevalence of neuropathy, cerebrovascular disease, and peripheral vascular disease increased from 2008 to 2013. Metformin was the most commonly prescribed antidiabetic medication. Sulfonylurea usage remained unchanged, while use of thiazolidinediones decreased considerably.

Decreasing incidence of type 2 diabetes mellitus in the United States, 2007-2012: Epidemiologic findings from a large US claims database.

AIMS: To explore epidemiological trends in type 2 diabetes mellitus (T2D) in the US between 2007 and 2012 using a large US claims database, with a particular focus on demographics, prevalence, newly-diagnosed cases, and comorbidities. METHODS: Truven Health MarketScan® Databases were used to identify patients with claims evidence of T2D in the years 2007 and 2012. Newly-diagnosed T2D was characterized by an absence of any T2D claims or related drug claims for 6months preceding the index claim. Demographic and comorbidity characteristics of the prevalent and new-onset T2D groups were compared and analyzed descriptively for trends over time. RESULTS: The overall prevalence of T2D remained stable from 2007 (1.24 million cases/15.07 million enrolled; 8.2%) to 2012 (2.04 million cases/24.52 million enrolled; 8.3%), while the percentage of newly-diagnosed cases fell dramatically from 2007 (152,252 cases; 1.1%) to 2012 (147,011 cases; 0.65%). The mean age of patients with prevalent T2D was similar in 2007 (60.6y) and 2012 (60.0y), while the mean age of newly-diagnosed T2D patients decreased by 3years from 2007 (57.7y) to 2012 (54.8y). Hypertension and hyperlipidemia were the most common comorbidities, evident in 50-75% of T2D patients, and increased markedly from 2007 to 2012 in both prevalent and new-onset T2D populations. Cardiovascular disease decreased slightly in prevalent (-0.9%) and new-onset (-2.8%) cases. CONCLUSIONS: This large US health claims database analysis suggests stabilization in prevalence and declining incidence of T2D over a recent 5-year period, a downward shift in age at T2D diagnosis, but increases in several comorbidities.

Longitudinal Changes in Medical Services and Related Costs in a Single Cohort of Patients Newly Diagnosed With Type 2 Diabetes, 2006 to 2012.

PURPOSE: Documenting diabetes treatment patterns and associated costs over time is an important step in gauging the medical and economic impact of current treatment guidelines in a real-world setting. This study was designed to assess changes in medication treatment patterns, health care costs, and comorbidities over a 6-year period after a new diagnosis of type 2 diabetes mellitus (T2DM). This analysis is the first of its kind to observe, over time, a single US cohort of patients newly diagnosed with T2DM. METHODS: This study was a longitudinal assessment of changes in medical services and comorbidities for a single cohort (N = 35,017) of adults newly diagnosed with T2DM in 2006 using claims data from Truven Health Analytics MarketScan(®) databases. Prevalence of diabetes-related comorbidities and utilization/costs of inpatient/outpatient services and medications were analyzed annually for the index (diagnosis) year (Y1) through year 6 (Y6) postindex. Costs were adjusted to 2012 dollars. FINDINGS: From Y1 to Y6, increased prevalence was noted for several T2DM-associated comorbidities: cerebrovascular disease (13%-21%), peripheral vascular disease (3%-10%), nephropathy (3%-13%), and retinopathy (4%-14%). All-cause costs of inpatient and outpatient services and medications were analyzed for the index year (Y1) through Y6 postindex (adjusted to 2012 dollars). Total health care utilization costs (services plus drugs) increased by 33.3% from Y1 ($329.8 million) to Y6 ($439.5 million). Inpatient costs across the entire cohort increased 19.3% from Y1 ($49.8 million; $1421/patient) to Y6 ($59.4 million; $1695/patient) but increased 46.6% among utilizers, despite a decline in inpatient utilizers (7.3% to 5.9% of patients). The percentage of outpatient services utilizers remained stable (Y1, 98.2%; Y6, 97.2%), but total visits increased by 9.1%. Costs of outpatient services increased by 32.5%, from $145 million (Y1) to $192 million (Y6). Total drug costs increased from $101.5 million (Y1) to $114.7 million (Y6) but accounted for a smaller percentage of all health care costs in Y6 versus Y1 (26.1% vs 30.7%). Antidiabetes drugs accounted for a small percentage of overall costs in both Y1 (3.6%) and Y6 (5.3%). IMPLICATIONS: Overall, we found evidence of increasing comorbidities paralleled by large increases in costs for medical services but less for prescriptions. These findings confirm a need for aggressive diabetes management to slow disease progression and minimize comorbidity and economic burdens of the disease.

Clinical characteristics, complications, comorbidities and treatment patterns among patients with type 2 diabetes mellitus in a large integrated health system.

PURPOSE: To compare the prevalence of diabetes-related complications and comorbidities, clinical characteristics, glycemic control, and treatment patterns in patients with type 2 diabetes (T2D) within a large integrated healthcare system in 2008 vs 2013. METHODS: An electronic health record system was used to create a cross-sectional summary of all patients with T2D as on 1 July 2008 and 1 July 2013. Differences between the two data sets were assessed after adjusting for age, gender, race, and household income. RESULTS: In 2008 and 2013, 24 493 and 41 582 patients with T2D were identified, respectively, of which the majority were male (52.3% and 50.1%) and Caucasian (79% and 75.2%). The mean ages (years) were 64.8 and 64.3. The percentages of patients across the defined A1C categories were 64.3 and 66.7 for <7%, 21.1 and 18.8 for 7-7.9%, 7.8 and 7.5 for 8-8.9%, and 6.8 and 7.0 for ≥9% in 2008 and 2013, respectively. The most prevalent T2D-related comorbidities were hypertension (82.5% and 87.2%) and cardiovascular disease (26.9% and 22.3%) in 2008 and 2013, respectively. Thiazolidinedione and sulfonylurea use decreased, whereas metformin and dipeptidyl peptidase-4 inhibitor use increased in the 5-year period. CONCLUSIONS: Patients with T2D are characterized by a high number of comorbidities. Over 85% of the patients had an A1C<8% within our integrated health delivery system in 2008 and 2013. In 2008 and 2013, metformin therapy was the most commonly utilized antidiabetic agent, and sulfonylureas were the most commonly utilized oral antidiabetic agent in combination with metformin. As integrated health systems assume greater shared financial risk in newer payment models, achieving glycemic targets (A1C) and the management of comorbidities will become ever-more important, for preventing diabetes-related complications, as well as to ensure reimbursement for the medical care that is rendered to patients with diabetes.

Trends in the incidence of diabetes, its clinical sequelae, and associated costs in pregnancy.

BACKGROUND: Increasing diabetes prevalence affects a substantial number of pregnant women in the United States. Our aims were to evaluate health outcomes, medical costs, risks and types of complications associated with diabetes in pregnancy for mothers and newborns. METHODS: In this retrospective claims analysis, patients were identified from the Truven Health MarketScan(®) database (2004-2011 inclusive). Participants were aged 18-45 years, with ascertainable diabetes status [Yes/No], date of birth event >2005 and continuous health plan enrolment ≥21 months before and 3 months after the birth. RESULTS: In total, 839 792 pregnancies were identified, and 66 041 (7.86%) were associated with diabetes mellitus [type 1 (T1DM), 0.13%; type 2 (T2DM), 1.21%; gestational (GDM), 6.29%; and GDM progressing to T2DM (patients without prior diabetes who had a T2DM diagnosis after the birth event), 0.23%]. Relative risk (RR) of stillbirth (2.51), miscarriage (1.28) and Caesarean section (C-section) (1.77) was significantly greater with T2DM versus non-diabetes. Risk of C-section was also significantly greater for other diabetes types [RR 1.92 (T1DM); 1.37 (GDM); 1.63 (GDM progressing to T2DM)]. Risk of overall major congenital (RR ≥ 1.17), major congenital circulatory (RR ≥ 1.19) or major congenital heart (RR ≥ 1.18) complications was greater in newborns of mothers with diabetes versus without. Mothers with T2DM had significantly higher risk (RR ≥ 1.36) of anaemia, depression, hypertension, infection, migraine, or cardiac, obstetrical or respiratory complications than non-diabetes patients. Mean medical costs were higher with all diabetes types, particularly T1DM ($27 531), than non-diabetes ($14 355). CONCLUSIONS: Complications and costs of healthcare were greater with diabetes, highlighting the need to optimize diabetes management in pregnancy.