Medical expenditure trajectory and HbA1c progression prior to and after clinical diagnosis of type 2 diabetes in a commercially insured population in the USA.

INTRODUCTION: Medical expenditures of individuals with type 2 diabetes escalate before clinical diagnosis. How increases in medical expenditures are related to glucose levels remains unclear. We examined changes in HbA1c and medical expenditures in years prior to and shortly after type 2 diabetes diagnosis. RESEARCH DESIGN AND METHODS: Using insurance claims and laboratory test results from a commercially insured population in the USA, we built three (2014, 2015, 2016) longitudinal cohorts with type 2 diabetes up to 10 years before and 2 years after the diagnosis (index year). We identified diabetes diagnosis using International Classification of Diseases, Ninth Revision and Tenth Revision codes and antidiabetic medication use. We ran two individual fixed regression models with annual total medical expenditures and average HbA1c values as dependent variables and number of years from diagnosis as the main independent variable and examined the risk-adjusted movement of the outcomes. RESULTS: Our study included 9847 individuals (83 526 person-years). Medical expenditures and HbA1c levels increased before and peaked at the diagnosis year. Medical expenditures were $8644 lower 10 years and $5781 lower 1 year before diagnosis compared with the index year. HbA1c was 12.18 mmol/mol (1.11 percentage points) and 3.49 mmol/mol (0.32 percentage points) lower, respectively. Average annual increases in medical expenditures and HbA1c values over the prediagnosis period were $318 and 0.97 mmol/mol (0.09 percentage points), respectively. CONCLUSIONS: Medical expenditures and HbA1c values followed similar trajectories before and after diabetes diagnosis. Our results can inform economic evaluations of programs and policies aimed at preventing type 2 diabetes.

A New Type 2 Diabetes Microsimulation Model to Estimate Long-Term Health Outcomes, Costs, and Cost-Effectiveness.

OBJECTIVES: This study aimed to develop a microsimulation model to estimate the health effects, costs, and cost-effectiveness of public health and clinical interventions for preventing/managing type 2 diabetes. METHODS: We combined newly developed equations for complications, mortality, risk factor progression, patient utility, and cost-all based on US studies-in a microsimulation model. We performed internal and external validation of the model. To demonstrate the model's utility, we predicted remaining life-years, quality-adjusted life-years (QALYs), and lifetime medical cost for a representative cohort of 10 000 US adults with type 2 diabetes. We then estimated the cost-effectiveness of reducing hemoglobin A1c from 9% to 7% among adults with type 2 diabetes, using low-cost, generic, oral medications. RESULTS: The model performed well in internal validation; the average absolute difference between simulated and observed incidence for 17 complications was < 8%. In external validation, the model was better at predicting outcomes in clinical trials than in observational studies. The cohort of US adults with type 2 diabetes was projected to have an average of 19.95 remaining life-years (from mean age 61), incur $187 729 in discounted medical costs, and accrue 8.79 discounted QALYs. The intervention to reduce hemoglobin A1c increased medical costs by $1256 and QALYs by 0.39, yielding an incremental cost-effectiveness ratio of $9103 per QALY. CONCLUSIONS: Using equations exclusively derived from US studies, this new microsimulation model achieves good prediction accuracy in US populations. The model can be used to estimate the long-term health impact, costs, and cost-effectiveness of interventions for type 2 diabetes in the United States.

Estimating costs of diabetes complications in people <65 years in the U.S. using panel data.

AIMS: To estimate the cost of diabetes complications in the United States (U.S.). METHODS: We constructed longitudinal panel data using one of the largest claims databases in the U.S. for privately insured Type 1 (T1DM) and type 2 (T2DM) diabetes patients with a follow-up time of one to ten years. Complication costs were estimated both in years of the first occurrence and in subsequent years, using individual fixed-effects models. All costs were in 2016 dollars. RESULTS: 47,166 people with T1DM and 608,237 with T2DM were included in our study. Aside from organ transplants, which were rare, the estimated average costs for the top three most costly conditions in the first vs. subsequent years were: end stage renal disease ($73,534 vs. $97,431 for T1DM; $94,231 vs. $98,981 for T2DM), congestive heart failure ($41,681 vs. $14,855 for T1DM; $31,202 vs. $7062 for T2DM), and myocardial infarction ($40,899 vs. $9496 for T1DM; $45,251 vs. $8572 for T2DM). For both diabetes types, retinopathy and neuropathy tend to have the lowest cost estimates. CONCLUSIONS: Our study provides the latest and most comprehensive cost estimates for a broad set of diabetes complications needed to evaluate the long-term cost-effectiveness of interventions for preventing and managing diabetes.

Current and projected future economic burden of Parkinson's disease in the U.S.

Parkinson's disease (PD) is one of the world's fastest growing neurological disorders. Much is unknown about PD-associated economic burdens in the United States (U.S.) and other high-income nations. This study provides a comprehensive analysis of the economic burdens of PD in the U.S. (2017) and projections for the next two decades. Multiple data sources were used to estimate the costs of PD, including public and private administrative claims data, Medicare Current Beneficiary Survey, Medical Expenditure Panel Survey, and a primary survey (n = 4,548) designed for this study. We estimated a U.S. prevalence of approximately one million individuals with diagnosed Parkinson's disease in 2017 and a total economic burden of $51.9 billion. The total burden of PD includes direct medical costs of $25.4 billion and $26.5 billion in indirect and non-medical costs, including an indirect cost of $14.2 billion (PWP and caregiver burden combined), non-medical costs of $7.5 billion, and $4.8 billion due to disability income received by PWPs. The Medicare program bears the largest share of excess medical costs, as most PD patients are over age 65. Projected PD prevalence will be more than 1.6 million with projected total economic burden surpassing $79 billion by 2037. The economic burden of PD was previously underestimated. Our findings underscore the substantial burden of PD to society, payers, patients, and caregivers. Interventions to reduce PD incidence, delay disease progression, and alleviate symptom burden may reduce the future economic burden of PD.

Identifying High-Cost Medicare Beneficiaries: Impact of Neighborhood Socioeconomic Disadvantage.

The objective of this observational longitudinal study of Maryland fee-for-service Medicare beneficiaries (2015-2016) was to investigate whether using data on neighborhood socioeconomic disadvantage in addition to individual clinical risk data improves identification of high-cost Medicare beneficiaries. Neighborhood socioeconomic disadvantage is measured using the Area Deprivation Index (ADI), a validated composite measure based on publically-available US census data (2011-2015) for Maryland census block groups. Hierarchical Condition Categories (HCC) score, health care utilization, and spending were obtained from Centers for Medicare & Medicaid Services Chronic Condition Warehouse beneficiary file and Part A and Part B claims data (2015). Total cost of care (TCOC) was calculated for 2016. Descriptive and multivariate analyses were performed to examine the relationship of residency in neighborhoods with high ADI and subsequent year health care spending. Among 615,637 Maryland Medicare fee-for-service beneficiaries, those living in neighborhoods with the greatest disadvantage vs. the least disadvantage incur significantly greater costs in the subsequent year (ADI Quintile 5 $12,439 versus Quintile 1 $8920, P < .001). Clinical risk exacerbates this disparity. Among beneficiaries in the highest HCC score quintile, costs are 27% ($5458, P < .001) higher among beneficiaries in the highest compared with the lowest ADI quintiles without risk adjustment and 24% ($4599, P < .001) higher with risk adjustment. Several sensitivity analyses found the relationship between ADI and TCOC robust. Association between neighborhood socioeconomic disadvantage and health care cost is most pronounced among the most clinically complex Maryland Medicare beneficiaries. Using ADI in combination with HCC score may facilitate more precise targeting of care management resources.

The Economic Burden of Elevated Blood Glucose Levels in 2017: Diagnosed and Undiagnosed Diabetes, Gestational Diabetes Mellitus, and Prediabetes.

OBJECTIVE: This study was conducted to update national estimates of the economic burden of undiagnosed diabetes, prediabetes, and gestational diabetes mellitus (GDM) in the United States for year 2017 and provide state-level estimates. Combined with published estimates for diagnosed diabetes, these updated statistics provide a detailed picture of the economic costs associated with elevated blood glucose levels. RESEARCH DESIGN AND METHODS: This study estimated medical expenditures exceeding levels occurring in the absence of diabetes or prediabetes and the indirect economic burden associated with reduced labor force participation and productivity. Data sources analyzed included Optum medical claims for ∼5.8 million commercially insured patients continuously enrolled from 2013 to 2015, Medicare Standard Analytical Files containing medical claims for ∼2.8 million Medicare patients in 2014, and the 2014 Nationwide Inpatient Sample containing ∼7.1 million discharge records. Other data sources were the U.S. Census Bureau, Centers for Disease Control and Prevention, and Centers for Medicare & Medicaid Services. RESULTS: The economic burden associated with diagnosed diabetes (all ages), undiagnosed diabetes and prediabetes (adults), and GDM (mothers and newborns) reached nearly $404 billion in 2017, consisting of $327.2 billion for diagnosed diabetes, $31.7 billion for undiagnosed diabetes, $43.4 billion for prediabetes, and nearly $1.6 billion for GDM. Combined, this amounted to an economic burden of $1,240 for each American in 2017. Annual burden per case averaged $13,240 for diagnosed diabetes, $5,800 for GDM, $4,250 for undiagnosed diabetes, and $500 for prediabetes. CONCLUSIONS: Updated statistics underscore the importance of reducing the burden of prediabetes and diabetes through better detection, prevention, and treatment.

Economic Costs Attributable to Diabetes in Each U.S. State.

OBJECTIVE: To estimate direct medical and indirect costs attributable to diabetes in each U.S. state in total and per person with diabetes. RESEARCH DESIGN AND METHODS: We used an attributable fraction approach to estimate direct medical costs using data from the 2013 State Health Expenditure Accounts, 2013 Behavioral Risk Factor Surveillance System, and the Centers for Medicare & Medicaid Services' 2013-2014 Minimum Data Set. We used a human capital approach to estimate indirect costs measured by lost productivity from morbidity (absenteeism, presenteeism, lost household productivity, and inability to work) and premature mortality, using the 2008-2013 National Health Interview Survey, 2013 daily housework value data, 2013 mortality data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research, and mean wages from the 2014 Bureau of Labor Statistics. Costs were adjusted to 2017 U.S. dollars. RESULTS: The estimated median state economic cost was $5.9 billion, ranging from $694 million to $55.5 billion, in total and $18,248, ranging from $15,418 to $30,915, per person with diabetes. The corresponding estimates for direct medical costs were $2.8 billion (range $0.3-22.9) and $8,544 (range $6,591-12,953) and for indirect costs were $3.0 billion (range $0.4-32.6) and $9,672 (range $7,133-17,962). In general, the estimated state median indirect costs resulting from morbidity were larger than costs from mortality both in total and per person with diabetes. CONCLUSIONS: Economic costs attributable to diabetes were large and varied widely across states. Our comprehensive state-specific estimates provide essential information needed by state policymakers to monitor the economic burden of the disease and to better plan and evaluate interventions for preventing type 2 diabetes and managing diabetes in their states.

Future Health and Economic Impact of Comprehensive Tobacco Control in DoD: A Microsimulation Approach.

Background: Tobacco use is a major concern to the Military Health System of the Department of Defense (DoD). The 2011 DoD Health Related Behavior Survey reported that 24.5% of active duty personnel are current smokers, which is higher than the national estimate of 20.6% for the civilian population. Overall, it is estimated that tobacco use costs the DoD $1.6 billion a year through related medical care, increased hospitalization, and lost days of work, among others. Methods: This study evaluated future health outcomes of Tricare Prime beneficiaries aged 18-64 yr (N = 3.2 million, including active duty and retired military members and their dependents) and the potential economic impact of initiatives that DoD may take to further its effort to transform the military into a tobacco-free environment. Our analysis simulated the future smoking status, risk of developing 25 smoking-related diseases, and associated medical costs for each individual using a Markov Chain Monte Carlo microsimulation model. Data sources included Tricare administrative data, national data such as Centers for Disease Control and Prevention mortality data and National Cancer Institute's cancer registry data, as well as relative risks of diseases obtained from a literature review. Findings: We found that the prevalence of active smoking among the Tricare Prime population will decrease from about 24% in 2015 to 18% in 2020 under a status quo scenario. However, if a comprehensive tobacco control initiative that includes a 5% price increase, a tighter clean air policy, and an intensified media campaign were to be implemented between 2016 and 2020, the prevalence of smoking could further decrease to 16%. The near 2 percentage points reduction in smoking prevalence represents an additional 81,240 quitters and translates to a total lifetime medical cost savings (in 2016 present value) of $968 million, with 39% ($382 million) attributable to Tricare savings. Discussion: A comprehensive tobacco control policy within the DoD could significantly decrease the prevalence and lifetime medical cost of tobacco use. If the smoking prevalence among Prime beneficiaries could reach the Healthy People 2020 goal of 12%, through additional measures, the lifetime savings could mount to $2.08 billion. To achieve future savings, DoD needs to pay close attention to program design and implementation issues of any additional tobacco control initiatives.

Geographic Variation in Antidiabetic Agent Adherence and Glycemic Control Among Patients with Type 2 Diabetes.

BACKGROUND: Medication nonadherence is an imperative public health concern. Among patients with type 2 diabetes mellitus (T2DM), poor adherence to antidiabetic agents is strongly associated with suboptimal glycemic control. Poor adherence and hyperglycemia greatly increase diabetes-related morbidity and mortality. At a national level, diabetes drug adherence using average proportion of days covered (PDC) is estimated to range between 36% and 81%, with an estimated range for diabetes control between 38% and 47%. At a state level no such studies exist. OBJECTIVE: To estimate the level of medication adherence to antidiabetic agents and of diabetes control, and their association among patients with T2DM receiving medication treatment at the state and the Metropolitan Statistical Area (MSA) levels among the populations covered by commercial insurance, Medicare, or Medicaid. METHODS: The study population included adults with T2DM aged ≥18 years who were identified using ICD-9-CM code 250.xx, who received diabetes medication, and who were covered by private insurance, Medicare, or Medicaid in each state, the District of Columbia, and the top 50 MSAs. Medication adherence was measured by average PDC and the percentage of population that had a PDC ≥ 80%. Diabetes control was identified using ICD-9-CM diagnosis codes. Patients who were not diagnosed with uncontrolled diabetes (250.x2 and 250.x3) were identified as being under control. The administrative claims databases used for this study included the 2012 medical and pharmacy claims from a large U.S. health plan, the complete 2011 Medicare Standard Analytical File linked with Part D claims, and the 2008 Mini-Medicaid Analytic eXtract (Mini-Max). Medication adherence and diabetes control were adjusted for age and sex to allow comparison across insurance coverage, states, and MSAs. RESULTS: For an insured patient population with T2DM that received diabetic drug treatment, average PDC was 79%. However, 35% of patients did not achieve an adherence of at least 80% of PDC. In addition, at least 40% of patients did not have their diabetes under control. Across insurance types, we found that patients insured with Medicare had relatively high average PDC and adherence levels (83% and 71%) in comparison with the commercially insured population (77% and 60%) and Medicaid patients (75% and 57%). In contrast, commercially insured patients had relatively better diabetes control (69%) than those insured with Medicare and Medicaid (54% and 53%, respectively). At a state level, we found that commercially insured and Medicare populations have relatively smaller geographic variation in drug adherence than the Medicaid population. CONCLUSIONS: This study identified gaps in T2DM drug adherence and pinpointed geographic areas that lag in terms of diabetes drug adherence or diabetes control and would benefit from implementing strategies to increase drug adherence.

The economic burden of elevated blood glucose levels in 2012: diagnosed and undiagnosed diabetes, gestational diabetes mellitus, and prediabetes.

OBJECTIVE: To update estimates of the economic burden of undiagnosed diabetes, prediabetes, and gestational diabetes mellitus in 2012 in the U.S. and to present state-level estimates. Combined with published estimates for diagnosed diabetes, these statistics provide a detailed picture of the economic costs associated with elevated glucose levels. RESEARCH DESIGN AND METHODS: This study estimated health care use and medical expenditures in excess of expected levels occurring in the absence of diabetes or prediabetes. Data sources that were analyzed include Optum medical claims for ∼4.9 million commercially insured patients who were continuously enrolled from 2010 to 2012, Medicare Standard Analytical Files containing medical claims for ∼2.6 million Medicare patients in 2011, and the 2010 Nationwide Inpatient Sample containing ∼7.8 million hospital discharge records. The indirect economic burden includes reduced labor force participation, missed workdays, and reduced productivity. State-level estimates reflect geographic variation in prevalence, risk factors, and prices. RESULTS: The economic burden associated with diagnosed diabetes (all ages) and undiagnosed diabetes, gestational diabetes, and prediabetes (adults) exceeded $322 billion in 2012, consisting of $244 billion in excess medical costs and $78 billion in reduced productivity. Combined, this amounts to an economic burden exceeding $1,000 for each American in 2012. This national estimate is 48% higher than the $218 billion estimate for 2007. The burden per case averaged $10,970 for diagnosed diabetes, $5,800 for gestational diabetes, $4,030 for undiagnosed diabetes, and $510 for prediabetes. CONCLUSIONS: These statistics underscore the importance of finding ways to reduce the burden of prediabetes and diabetes through prevention and treatment.

Injuries among children with autism spectrum disorder.

OBJECTIVE: We compared risk of injury among children with autism spectrum disorder (ASD) to those without ASD, adjusting for demographic and clinical characteristics. METHODS: We used claims data from 2001 to 2009 from a commercial health plan in the United States. A validated ASD case identification algorithm identified 33,565 children (ages 0-20 years) with ASD and 138,876 children without. Counting process models tested the association between ASD status and injury episodes with separate regressions run for children during different age periods. RESULTS: Unadjusted results demonstrated that children with ASD had a 12% greater injury risk than children without ASD (hazard ratio [HR] = 1.119; P < .001). After including demographic variables, the HR was 1.03 (P < .05); after controlling for co-occurring conditions, such as seizures, depression, etc, HR decreased to 0.889 (P < .001). For the age period analysis, HR values were as follows: for 0 to 2 years, HR 1.141; 3 to 5 years, HR 1.282; 6 to 10 years, HR not significant; and 11 to 20 years, HR 0.634 (P < .05 for all significant results). CONCLUSIONS: Children with ASD have more injuries than children without ASD. After controlling for demographic factors and co-occurring conditions, children with ASD are at lower risk of injury, suggesting that co-occurring conditions or the ways these conditions interact with ASD is related to injuries. Clinicians should understand that injury risk in children with ASD may be driven by co-occurring conditions. Treating these conditions could thus decrease injury risk as well as have other benefits. Injury prevention interventions are especially warranted for younger children with ASD and those with seizures, depression, visual impairment, or attention-deficit disorders.

Projected supply of and demand for oncologists and radiation oncologists through 2025: an aging, better-insured population will result in shortage.

PURPOSE: The American Society of Clinical Oncology (ASCO) published a study in 2007 that anticipated a shortage of oncologists by 2020. This study aims to update and better assess the market for chemotherapy and radiation therapy and the impact of health reform on capacity of and demand for oncologists and radiation oncologists. METHODS: The supply of oncologists and radiation oncologists, by age, sex, and specialty, was projected through 2025 with an input-output model. The Medical Expenditure Panel Survey, commercial claims, and Medicare claims were analyzed to determine patterns of use by patient characteristics such as age, sex, health insurance coverage, cancer site, physician specialty, and service type. Patterns of use were then applied to the projected prevalence of cancer, using data from the SEER Program of the National Cancer Institute. RESULTS: Beginning in 2012, 16,347 oncologists and radiation oncologists were active and supplying 15,190 full-time equivalents (FTEs) of patient care. Without consideration of the Affordable Care Act (ACA), overall demand for oncologist services is projected to grow 40% (21,255 FTEs), whereas supply may grow only 25% (18,997 FTEs), generating a shortage of 2,258 FTEs in 2025. When fully implemented, the ACA could increase the demand for oncologists and radiation oncologists by 500,000 visits per year, increasing the shortage to 2,393 FTEs in 2025. CONCLUSION: Anticipated shortages are largely consistent with the projections of the ASCO 2007 workforce study but somewhat more delayed. The ACA may modestly exacerbate the shortage. Unless oncologist productivity can be enhanced, the anticipated shortage will strain the ability to provide quality cancer care.

Does a claims diagnosis of autism mean a true case?

The purpose of this study was to validate autism spectrum disorder cases identified through claims-based case identification algorithms against a clinical review of medical charts. Charts were reviewed for 432 children who fell into one of the three following groups: (a) more than or equal to two claims with an autism spectrum disorder diagnosis code (n = 182), (b) one claim with an autism spectrum disorder diagnosis code (n = 190), and (c) those who had no claims for autism spectrum disorder but had claims for other developmental or neurological conditions (n = 60). The algorithm-based diagnoses were compared with documented autism spectrum disorders in the medical charts. The algorithm requiring more than or equal to two claims for autism spectrum disorder generated a positive predictive value of 87.4%, which suggests that such an algorithm is a valid means to identify true autism spectrum disorder cases in claims data.

Cost of illness for neuromuscular diseases in the United States.

INTRODUCTION: We conducted a comprehensive study of the costs associated with amyotrophic lateral sclerosis (ALS), Duchenne muscular dystrophy (DMD). and myotonic dystrophy (DM) in the U.S. METHODS: We determined the total impact on the U.S. economy, including direct medical costs, nonmedical costs, and loss of income. Medical costs were calculated using a commercial insurance database and Medicare claims data. Nonmedical and indirect costs were determined through a survey of families registered with the Muscular Dystrophy Association. RESULTS: Medical costs were driven by outpatient care. Nonmedical costs were driven by the necessity to move or adapt housing for the patient and paid caregiving. Loss of income correlated significantly with the amount of care needed by the patient. CONCLUSIONS: We calculated the annual per-patient costs to be $63,693 for ALS, $50,952 for DMD, and $32,236 for DM. Population-wide national costs were $1,023 million (ALS), $787 million (DMD), and $448 million (DM).

Simulation of quitting smoking in the military shows higher lifetime medical spending more than offset by productivity gains.

Despite the documented benefits of quitting smoking, studies have found that smokers who quit may have higher lifetime medical costs, in part because of increased risk for medical conditions, such as type 2 diabetes, brought on by associated weight gain. Using a simulation model and data on 612,332 adult smokers in the US Department of Defense's TRICARE Prime health plan in 2008, we estimated that cessation accompanied by weight gain would increase average life expectancy by 3.7 years, and that the average lifetime reduction in medical expenditures from improved health ($5,600) would be offset by additional expenditures resulting from prolonged life ($7,300). Results varied by age and sex: For females ages 18-44 at time of cessation, there would be net savings of $1,200 despite additional medical expenditures from prolonged life. Avoidance of weight gain after quitting smoking would increase average life expectancy by four additional months and reduce mean extra spending resulting from prolonged life by $700. Overall, the average net lifetime health care cost increase of $1,700 or less per ex-smoker would be modest and, for employed people, more than offset by even one year's worth of productivity gains. These results boost the case for smoking cessation programs in the military in particular, along with not selling cigarettes in commissaries or at reduced prices.

Health care use and costs for participants in a diabetes disease management program, United States, 2007-2008.

INTRODUCTION: The Disease Management Association of America identifies diabetes as one of the chronic conditions with the greatest potential for management. TRICARE Management Activity, which administers health care benefits for US military service personnel, retirees, and their dependents, created a disease management program for beneficiaries with diabetes. The objective of this study was to determine whether participation intensity and prior indication of uncontrolled diabetes were associated with health care use and costs for participants enrolled in TRICARE's diabetes management program. METHODS: This ongoing, opt-out study used a quasi-experimental approach to assess program impact for beneficiaries (n = 37,370) aged 18 to 64 living in the United States. Inclusion criteria were any diabetes-related emergency department visits or hospitalizations, more than 10 diabetes-related ambulatory visits, or more than twenty 30-day prescriptions for diabetes drugs in the previous year. Beginning in June 2007, all participants received educational mailings. Participants who agreed to receive a baseline telephone assessment and telephone counseling once per month in addition to educational mailings were considered active, and those who did not complete at least the baseline telephone assessment were considered passive. We categorized the diabetes status of each participant as "uncontrolled" or "controlled" on the basis of medical claims containing diagnosis codes for uncontrolled diabetes in the year preceding program eligibility. We compared observed outcomes to outcomes predicted in the absence of diabetes management. Prediction equations were based on regression analysis of medical claims for a historical control group (n = 23,818) that in October 2004 met the eligibility criteria for TRICARE's program implemented June 2007. We conducted regression analysis comparing historical control group patient outcomes after October 2004 with these baseline characteristics. RESULTS: Per-person total annual medical savings for program participants, calculated as the difference between observed and predicted outcomes, averaged $783. Active participants had larger reductions in inpatient days and emergency department visits, larger increases in ambulatory visits, and larger increases in receiving retinal examinations, hemoglobin A1c tests, and urine microalbumin tests compared with passive participants. Participants with prior indication of uncontrolled diabetes had higher per-person total annual medical savings, larger reduction in inpatient days, and larger increases in ambulatory visits than did participants with controlled diabetes. CONCLUSION: Greater intensity of participation in TRICARE's diabetes management program was associated with lower medical costs and improved receipt of recommended testing. That patients who were categorized as having uncontrolled diabetes realized greater program benefits suggests diabetes management programs should consider indication of uncontrolled diabetes in their program candidate identification criteria.

Disease management 360 degrees: a scorecard approach to evaluating TRICARE's programs for asthma, congestive heart failure, and diabetes.

OBJECTIVE: To assess the effect of TRICARE's asthma, congestive heart failure, and diabetes disease management programs using a scorecard approach. EVALUATION MEASURES: Patient healthcare utilization, financial, clinical, and humanistic outcomes. Absolute measures were translated into effect size and incorporated into a scorecard. RESEARCH DESIGN: Actual outcomes for program participants were compared with outcomes predicted in the absence of disease management. The predictive equations were established from regression models based on historical control groups (n = 39,217). Z scores were calculated for the humanistic measures obtained through a mailed survey. DATA COLLECTION METHODS: Administrative records containing medical claims, patient demographics and characteristics, and program participation status were linked using an encrypted patient identifier (n = 57,489). The study time frame is 1 year prior to program inception through 2 years afterward (October 2005-September 2008). A historical control group was identified with the baseline year starting October 2003 and a 1-year follow-up period starting October 2004. A survey was administered to a subset of participants 6 months after baseline assessment (39% response rate). RESULTS: Within the observation window--24 months for asthma and congestive heart failure, and 15 months for the diabetes program--we observed modest reductions in hospital days and healthcare cost for all 3 programs and reductions in emergency visits for 2 programs. Most clinical outcomes moved in the direction anticipated. CONCLUSIONS: The scorecard provided a useful tool to track performance of 3 regional contractors for each of 3 diseases and over time.

Outcomes and lessons learned from evaluating TRICARE's disease management programs.

OBJECTIVE: To share outcomes and lessons learned from an evaluation of disease management (DM) programs for asthma, congestive heart failure (CHF), and diabetes for TRICARE patients. STUDY DESIGN: Multiyear evaluation of participants in voluntary, opt-out DM programs. Patient-centered programs, administered by 3 regional contractors, provide phone-based consultations with a care manager, educational materials, and newsletters. The study sample consisted of 23,793 asthma, 4092 CHF, and 29,604 diabetes patients with at least 6 months' tenure in the program. METHODS: Medical claims were analyzed to quantify program effect on healthcare utilization, medical costs, and clinical outcomes. Multivariate regression analysis with an historical control group was used to predict patient outcomes in the absence of DM. The difference between actual and predicted DM patient outcomes was attributed to the program. A patient survey collected data on program satisfaction and perceived usefulness of program information and services. RESULTS: Modest improvements in patient outcomes included reduced inpatient days and medical costs, and (with few exceptions) increased percentages of patients receiving appropriate medications and tests. Annual per patient reductions in medical costs were $453, $371, and $783 for asthma, CHF, and diabetes program participants, respectively. The estimated return on investment was $1.26 per $1.00 spent on DM services. CONCLUSION: Findings suggest that the DM programs more than pay for themselves, in addition to improving patient health and quality of life. Lessons learned in program design, implementation, effectiveness, and evaluation may benefit employers contemplating DM, DM providers, and evaluators of DM programs.

The economic burden of diabetes.

New research provides revised comprehensive estimates that suggest that the U.S. national economic burden of pre-diabetes and diabetes reached $218 billion in 2007. This estimate includes $153 billion in higher medical costs and $65 billion in reduced productivity. The average annual cost per case is $2,864 for undiagnosed diabetes, $9,975 for diagnosed diabetes ($9,677 for type 2 and $14,856 for type 1), and $443 for pre-diabetes (medical costs only). For each American, regardless of diabetes status, this burden represents a cost of approximately $700 annually. These results underscore the urgency of better understanding how prevention and treatment strategies may or may not help reduce costs.

Medical cost associated with prediabetes.

In this article, we estimate national health care resource use and medical costs in 2007 associated with prediabetes (PD), defined as either fasting plasma glucose between 100 and 125 or oral glucose tolerance test between 140 and 200. We use Poisson regression with medical claims for an adult population continuously insured between 2004 and 2006 to analyze patterns of health care resource use by PD status. Combining rate ratios that reflect health care use patterns with national PD prevalence rates from the National Health and Nutrition Examination Survey, we calculate etiological fractions to estimate the portion of national health resource use associated with PD. The findings suggest that PD is associated with statistically higher rates of ambulatory visits for hypertension; endocrine, metabolic, and renal complications; and general medical conditions. PD is associated with a slight increase in visit rates for neurological symptoms, peripheral vascular disease, and cardiovascular disease, but the increase is not statistically significant. There is no indication that PD is associated with an increase in emergency visits and inpatient days. Extrapolating these patterns to the 57 million adults with PD in 2007 suggests that national annual medical costs of PD exceed $25 billion, or an additional $443 for each adult with PD. PD is associated with excessive use of ambulatory services for comorbidities known to be related to diabetes. Our findings strengthen the business case for lifestyle interventions to prevent diabetes by adding additional economic benefits that potentially can be achieved by preventing or delaying PD.