Nationally representative medical costs of diabetes by time since diagnosis

[Type 2 diabetes in Andalusia: Resources use and economic cost]

BACKGROUND AND OBJECTIVES

Previous studies that quantify the cost of type 2 diabetes (DM2) show very different results. We set out to define the profile of the patient with DM2 in Andalusia, analyze the use of health resources and quantify their economic cost during 2022.

PATIENTS AND METHODS

Multicenter, cross-sectional and descriptive study. Three hundred and eighty-five patients with DM2 from Andalusia (confidence level: 95%; error: 5%).

DATA ANALYZED

age, sex, attendance at primary care (PC), nursing, emergency and hospital specialty consultations; consumption of drugs in general and antidiabetics in particular, blood glucose strips, complementary tests and hospitalization days.

RESULTS

Mean age: 70.7 ± 12.44 years; 53.6% men. Care contacts: PC physician: 8.36 ± 4.69; nursing: 7.17 ± 12; hospital visits: 2.31 ± 2.38; emergencies: 1.71 ± 2.89; hospitalization days: 2.26 ± 6.46.

LABORATORY TESTS

3.79 ± 5.45 and 2.17 ± 3.47 Rx. Drugs consumed: 9.20 ± 3.94 (1.76 ± 0.90 antidiabetics). Blood glucose strips: 184 ± 488. Annual cost: 5171.05 €/patient/year (2228.36 € for hospital admissions, 1702.87 € for drugs and 1239.82 € for assistance and complementary tests).

CONCLUSIONS

The DM2 Andalusian is 71 years old, consumes 10 different drugs and treats DM2 with double therapy. He has been 20 attendances/year (75% in PC), 4 analyses, 2 X-rays and requires 2 days of hospitalization. Direct healthcare costs goes over 5000 €/year. This represents 41.66% of the budget of the Andalusian Ministry of Health and triples the average cost per habitant.

Early Education and Adult Health: Age 37 Impacts and Economic Benefits of the Child-Parent Center Preschool Program

This paper evaluates the long-term impacts of the Chicago Child-Parent Center (CPC) program, a comprehensive early childhood program launched in the 1960s, on the physical and mental health outcomes. This study follows a cohort of 1539 participants born in 1979-1980 and surveyed most recently at age 35-37 by employing a matched study design created by including all students who were enrolled in kindergarten classrooms in CPC school sites as well as entire kindergarten classrooms in a matched set of similar high-poverty schools. Using propensity score weighting that addresses potential issues with differential attrition and nonrandom treatment assignment, results reveal that CPC preschool participation is associated with significantly lower rates of adverse health outcomes such as smoking and diabetes. Further, evaluating the economic impacts of the preschool component of the program, the study finds a benefit-cost ratio in the range of 1.35 to 3.66 (net benefit: $3,896) indicating that the health benefits of the program by themselves offset the costs of the program even without considering additional benefits arising from increased educational attainment and reduced involvement in crime reported in earlier cost-benefit analyses. The findings are robust to corrections for multiple hypothesis testing, sensitivity analysis using a range of discount rates, and Monte Carlo analysis to account for uncertainty in outcomes.

Healthcare Costs of Diabetes and Microvascular and Macrovascular Disease in Individuals with Incident Type 2 Diabetes Mellitus: A Ten-Year Longitudinal Study

OBJECTIVE

The objective of this study was to estimate the incremental long-term costs associated with T2DM attributable to vascular diseases.

RESEARCH DESIGN AND METHODS

This retrospective cohort study identified newly diagnosed (incident) T2DM patients in 2007 (baseline to 01/01/2006) using the HealthCore Integrated Research Database, a repository of nationally representative claims data. Incident T2DM patients were 1:1 exact matched on age, gender and other factors of interest to non-DM patients, and followed until the earlier of 8 follow-up years or death. Patients with documented vascular disease diagnosis were identified during the study period. All-cause and T2DM/vascular disease-related annual healthcare costs were examined for each follow-up year.

RESULTS

The study included 13,883 individuals with T2DM and matched non-DM controls. Among individuals with T2DM, 11,792 (85%) had vascular disease versus 9251 (66.6%) non-T2DM between 01/01/2006 and 12/31/2015. Among T2DM patients, mean all-cause annual costs were greater than in non-T2DM patients ($13,806 vs $7,243, baseline, $21,745 vs $8,524, post-index year 1, $12,756-$14,793 vs $8,349-$9,940 years 2-8, p< 0.001), respectively. A similar trend was observed for T2DM/vascular disease-related costs (p< 0. 001). T2DM/vascular disease-related costs were largest during post-index year 1, accounting for the majority of all-cause cost difference between T2DM patients and matched non-DM controls. Incident T2DM individuals without vascular disease at any time had significantly lower costs compared to non-DM controls (p< 0. 001) between years 2-8 of follow-up.

CONCLUSION

Vascular disease increased the cost burden for individuals with T2DM. The cost impact of diabetes and vascular disease was highest in the year after diagnosis, and persisted for at least seven additional years, while the cost of T2DM patients without vascular disease trended lower than for matched non-DM patients. These data highlight potential costs that could be offset by earlier and more effective detection and management of T2DM aimed at reducing vascular disease burden.

Costs of people with diabetes in relation to average glucose control: an empirical approach controlling for year of onset cohorts

OBJECTIVE

To estimate the impact of glycaemic control and time since diabetes diagnosis on care costs incurred by people with type 2 diabetes mellitus (T2DM).

RESEARCH DESIGN AND METHODS

Random-effects linear regression models were run to test the impact of average glucose control (HbA1c) and time since diabetes diagnosis on total care spending in people with T2DM, adjusting for year of onset and other covariates. Two datasets were linked, Vektis (healthcare costs reimbursed by the Dutch mandatory health insurance) and Zodiac (clinical and sociodemographic data). The sample includes 22,612 observations, grouped in 5653 individuals from the Northern part of the Netherlands, covering 4 years (2008-2011).

RESULTS

A 1% point increase in HbA1c is associated with a 2.2% higher total care costs. However, when treatment modality is included, the results are modified. A 1% point increase (11 mol/mol) in HbA1c is significantly associated with 3.4% higher total care costs for individuals without glucose-lowering treatment. Being treated with insulin is significantly associated with an increase in costs of 30-38% for every additional percentage point of HbA1c, depending on the covariates included. Without controlling for year of onset, an additional year of diabetes duration relates to 2.6% higher care costs, while this is 4.9% controlling for year of onset. The effect of HbA1c and diabetes duration differs between types of costs.

CONCLUSION

HbA1c, insulin treatment and diabetes duration are the main drivers of increasing care costs. The results signal the relevance of controlling for HbA1c together with treatment modality, diabetes duration and year of diagnosis effects.

Racial and Ethnic Differences in Out-of-Pocket Expenses among Adults with Diabetes

BACKGROUND

Racial and ethnic minority groups have a higher prevalence of diabetes, increased risk for adverse complications, and worse health outcomes compared to Non-Hispanic Whites. Evidence suggests they also have higher healthcare expenses associated with diabetes care. Therefore, the objective of this study was to assess racial and ethnic differences in out-of-pocket (OOP) costs among a nationally representative sample of adults with diabetes.

METHODS

Cross-sectional study of 17,702 adults (aged ≥18 years) with diabetes from years 2002-2011 in the Medical Expenditure Panel Survey Household Component. The outcome was OOP expenditures, and the primary predictor was race/ethnicity. Descriptive statistics summarized the sample population. Unadjusted mean values were computed to compare OOP expenses over time. A two-part model was used to estimate adjusted incremental OOP expenses.

RESULTS

For the overall sample, OOP expenditures decreased significantly over time. In addition, compared to NHWs, racial and ethnic minority groups had significantly lower OOP costs per year when adjusted for sociodemographic characteristics, comorbid conditions, and time. NHBs paid $481 less than NHWs; Hispanics paid $591 less than NHWs; and individuals in the 'Other' racial/ethnic category paid nearly $645 less compared to NHWs (p < 0.001).

CONCLUSIONS

Racial/ethnic minority patients with diabetes had significantly less OOP expenses compared to NHWs, possibly due to differences in healthcare utilization. OOP expenses decreased significantly over time for all racial and ethnic groups. Additional research is needed to understand the factors associated with differences in OOP expenditures among racial groups.

Health service utilization and related costs attributable to diabetes

AIMS

To estimate the health service use and direct healthcare costs attributable to diabetes using best available data and methods.

METHODS

A nationally representative sample of adults aged ≥50 years was analysed (n=8107). Health service use in the previous 12 months included the number of general practitioner visits, outpatient department visits, hospital admissions, and accident and emergency department attendances. Multivariable negative binomial regression was used to estimate the associations between diabetes and frequency of visits. Average marginal effects were applied to unit costs for each health service and extrapolated to the total population, calculating the incremental costs associated with diabetes.

RESULTS

The prevalence of diabetes was 8.0% (95% CI: 7.4, 8.6). In fully adjusted models, diabetes was associated with additional health service use. Compared to those without diabetes, people with diabetes have, on average, 1.49 (95% CI: 1.10, 1.88) additional general practitioner visits annually. Diabetes was associated with an 87% increase in outpatient visits, a 52% increase in hospital admissions and a 33% increase in accident and emergency department attendances (P<0.001). The incremental cost of this additional service use, nationally, is an estimated €88,894,421 annually, with hospital admissions accounting for 67% of these costs.

CONCLUSION

Using robust methods, we identified substantially increased service use attributable to diabetes across the health system. Our findings highlight the urgent need to invest in the prevention and management of diabetes.

The Burden of Obesity on Diabetes in the United States: Medical Expenditure Panel Survey, 2008 to 2012

BACKGROUND

Diabetes is one of the most prevalent and costly chronic diseases in the United States.

OBJECTIVES

To analyze the risk of developing diabetes and the annual cost of diabetes for a US general population.

METHODS

Data from the Medical Expenditure Panel Survey, 2008 to 2012, were used to analyze 1) probabilities of developing diabetes and 2) annual total health care expenditures for diabetics. The age-, sex-, race-, and body mass index (BMI)-specific risks of developing diabetes were estimated by fitting an exponential survival function to age at first diabetes diagnosis. Annual health care expenditures were estimated using a generalized linear model with log-link and gamma variance function. Complex sampling designs in the Medical Expenditure Panel Survey were adjusted for. All dollar values are presented in 2012 US dollars.

RESULTS

We observed a more than 6 times increase in diabetes risks for class III obese (BMI ≥ 40 kg/m²) individuals compared with normal-weight individuals. Using age 50 years as an example, we found a more than 3 times increase in annual health care expenditures for those with diabetes ($13,581) compared with those without diabetes ($3,954). Compared with normal-weight (18.5 ≤ BMI < 25 kg/m²) individuals, class II obese (35 ≤ BMI < 40 kg/m²) and class III obese (BMI ≥ 40 kg/m²) individuals incurred an annual marginal cost of $628 and $756, respectively. The annual health care expenditure differentials between those with and without diabetes of age 50 years were the highest for individuals with class II ($12,907) and class III ($9,703) obesity.

CONCLUSIONS

This article highlights the importance of obesity on diabetes burden. Our results suggested that obesity, in particular, class II and class III (i.e., BMI ≥ 35 kg/m²) obesity, is associated with a substantial increase in the risk of developing diabetes and imposes a large economic burden.

Acculturation and Self-Management Perceptions Among Mexican American Adults With Type 2 Diabetes

Because type 2 diabetes (T2DM) is disproportionately high among Mexican Americans in the United States, this study examined how acculturation influences T2DM self-management, a critical component for disease outcome. Qualitative interviews of 24 low-income Mexican American patients with T2DM were matched to their biomedical and dietary data and degree of acculturation. Greater acculturation to the United States was associated with less favorable diabetes control, fiber density, leisure-time physical activity, and more physical disability. Health care professionals can improve their cultural competence by learning culturally appropriate foods and fostering a warm, caring manner with Mexican Americans to enhance their sense of well-being and compliance with T2DM recommendations.

Medical Care Costs Associated With Long-term Weight Maintenance Versus Weight Gain Among Patients With Type 2 Diabetes

OBJECTIVE

Weight loss is recommended for overweight patients with diabetes but avoidance of weight gain may be a more realistic goal. We calculated the 4-year economic impact of maintaining body weight versus gaining weight.

RESEARCH DESIGN AND METHODS

Among 8,154 patients with type 2 diabetes, we calculated weight change as the difference between the first body weight measure in 2010 and the last measure in 2013 and calculated mean glycated hemoglobin (A1C) from all measurements from 2010 to 2013. We created four analysis groups: weight change <5% and A1C <7%; weight gain ≥5% and A1C <7%; weight change <5% and A1C ≥7%; and weight gain ≥5% and A1C ≥7%. We compared change in medical costs between 2010 and 2013, adjusted for demographic and clinical characteristics.

RESULTS

Patients who maintained weight within 5% of baseline experienced a reduction in costs of about $400 regardless of A1C. In contrast, patients who gained ≥5% of baseline weight and had mean A1C ≥7% had an increase in costs of $1,473 (P < 0.001). Those who gained >5% of their baseline weight with mean A1C <7% had a modest increase in costs ($387, NS).

CONCLUSIONS

Patients who gained at least 5% of their baseline body weight and did not maintain A1C <7% over 4 years experienced a 14% increase in medical costs, whereas those who maintained good glycemic control had a mean cost increase of 3.3%. However, patients who maintained weight within 5% of baseline had costs that were ∼5% lower than baseline. Avoidance of weight gain may reduce costs in the long-term.

The Effects of Diagnostic Definitions in Claims Data on Healthcare Cost Estimates: Evidence from a Large-Scale Panel Data Analysis of Diabetes Care in Japan

BACKGROUND

Inaccurate estimates of diabetes-related healthcare costs can undermine the efficiency of resource allocation for diabetes care. The quantification of these costs using claims data may be affected by the method for defining diagnoses.

OBJECTIVES

The aims were to use panel data analysis to estimate diabetes-related healthcare costs and to comparatively evaluate the effects of diagnostic definitions on cost estimates.

RESEARCH DESIGN

Monthly panel data analysis of Japanese claims data.

SUBJECTS

The study included a maximum of 141,673 patients with type 2 diabetes who received treatment between 2005 and 2013.

MEASURES

Additional healthcare costs associated with diabetes and diabetes-related complications were estimated for various diagnostic definition methods using fixed-effects panel data regression models.

RESULTS

The average follow-up period per patient ranged from 49.4 to 52.3 months. The number of patients identified as having type 2 diabetes varied widely among the diagnostic definition methods, ranging from 14,743 patients to 141,673 patients. The fixed-effects models showed that the additional costs per patient per month associated with diabetes ranged from US$180 [95 % confidence interval (CI) 178-181] to US$223 (95 % CI 221-224). When the diagnostic definition excluded rule-out diagnoses, the diabetes-related complications associated with higher additional healthcare costs were ischemic heart disease with surgery (US$13,595; 95 % CI 13,568-13,622), neuropathy/extremity disease with surgery (US$4594; 95 % CI 3979-5208), and diabetic nephropathy with dialysis (US$3689; 95 % CI 3667-3711).

CONCLUSIONS

Diabetes-related healthcare costs are sensitive to diagnostic definition methods. Determining appropriate diagnostic definitions can further advance healthcare cost research for diabetes and its applications in healthcare policies.

The Hospitalization Costs of Diabetes and Hypertension Complications in Zimbabwe: Estimations and Correlations

Objective. Treating complications associated with diabetes and hypertension imposes significant costs on health care systems. This study estimated the hospitalization costs for inpatients in a public hospital in Zimbabwe. Methods. The study was retrospective and utilized secondary data from medical records. Total hospitalization costs were estimated using generalized linear models. Results. The median cost and interquartile range (IQR) for patients with diabetes, $994 (385-1553) mean $1319 (95% CI: 981-1657), was higher than patients with hypertension, $759 (494-1147) mean $914 (95% CI: 825-1003). Female patients aged below 65 years with diabetes had the highest estimated mean costs ($1467 (95% CI: 1177-1828)). Wound care had the highest estimated mean cost of all procedures, $2884 (95% CI: 2004-4149) for patients with diabetes and $2239 (95% CI: 1589-3156) for patients with hypertension. Age below 65 years, medical procedures (amputation, wound care, dialysis, and physiotherapy), the presence of two or more comorbidities, and being prescribed two or more drugs were associated with significantly higher hospitalization costs. Conclusion. Our estimated costs could be used to evaluate and improve current inpatient treatment and management of patients with diabetes and hypertension and determine the most cost-effective interventions to prevent complications and comorbidities.

Trends in health care expenditure in U.S. adults with diabetes: 2002-2011

OBJECTIVE

Direct medical cost of diabetes in the U.S. has been estimated to be 2.3 times higher relative to individuals without diabetes. This study examines trends in health care expenditures by expenditure category in U.S. adults with diabetes between 2002 and 2011.

RESEARCH DESIGN AND METHODS

We analyzed 10 years of data representing a weighted population of 189,013,514 U.S. adults aged ≥18 years from the Medical Expenditure Panel Survey. We used a novel two-part model to estimate adjusted mean and incremental medical expenditures by diabetes status, while adjusting for demographics, comorbidities, and time.

RESULTS

Relative to individuals without diabetes ($5,058 [95% CI 4,949-5,166]), individuals with diabetes ($12,180 [11,775-12,586]) had more than double the unadjusted mean direct expenditures over the 10-year period. After adjustment for confounders, individuals with diabetes had $2,558 (2,266-2,849) significantly higher direct incremental expenditures compared with those without diabetes. For individuals with diabetes, inpatient expenditures rose initially from $4,014 in 2002/2003 to $4,183 in 2004/2005 and then decreased continuously to $3,443 in 2010/2011, while rising steadily for individuals without diabetes. The estimated unadjusted total direct expenditures for individuals with diabetes were $218.6 billion/year and adjusted total incremental expenditures were approximately $46 billion/year.

CONCLUSIONS

Our findings show that compared with individuals without diabetes, individuals with diabetes had significantly higher health expenditures from 2002 to 2011 and the bulk of the expenditures came from hospital inpatient and prescription expenditures.

The Economic Costs of Type 2 Diabetes: A Global Systematic Review

BACKGROUND

There has been a widely documented and recognized increase in diabetes prevalence, not only in high-income countries (HICs) but also in low- and middle-income countries (LMICs), over recent decades. The economic burden associated with diabetes, especially in LMICs, is less clear.

OBJECTIVE

We provide a systematic review of the global evidence on the costs of type 2 diabetes. Our review seeks to update and considerably expand the previous major review of the costs of diabetes by capturing the evidence on overall, direct and indirect costs of type 2 diabetes worldwide that has been published since 2001. In addition, we include a body of economic evidence that has hitherto been distinct from the cost-of-illness (COI) work, i.e. studies on the labour market impact of diabetes.

METHODS

We searched PubMed, EMBASE, EconLit and IBSS (without language restrictions) for studies assessing the economic burden of type 2 diabetes published from January 2001 to October 2014. Costs reported in the included studies were converted to international dollars ($) adjusted for 2011 values. Alongside the narrative synthesis and methodological review of the studies, we conduct an exploratory linear regression analysis, examining the factors behind the considerable heterogeneity in existing cost estimates between and within countries.

RESULTS

We identified 86 COI and 23 labour market studies. COI studies varied considerably both in methods and in cost estimates, with most studies not using a control group, though the use of either regression analysis or matching has increased. Direct costs were generally found to be higher than indirect costs. Direct costs ranged from $242 for a study on out-of-pocket expenditures in Mexico to $11,917 for a study on the cost of diabetes in the USA, while indirect costs ranged from $45 for Pakistan to $16,914 for the Bahamas. In LMICs-in stark contrast to HICs-a substantial part of the cost burden was attributed to patients via out-of-pocket treatment costs. Our regression analysis revealed that direct diabetes costs are closely and positively associated with a country's gross domestic product (GDP) per capita, and that the USA stood out as having particularly high costs, even after controlling for GDP per capita. Studies on the labour market impact of diabetes were almost exclusively confined to HICs and found strong adverse effects, particularly for male employment chances. Many of these studies also took into account the possible endogeneity of diabetes, which was not the case for COI studies.

CONCLUSIONS

The reviewed studies indicate a large economic burden of diabetes, most directly affecting patients in LMICs. The magnitude of the cost estimates differs considerably between and within countries, calling for the contextualization of the study results. Scope remains large for adding to the evidence base on labour market effects of diabetes in LMICs. Further, there is a need for future COI studies to incorporate more advanced statistical methods in their analysis to account for possible biases in the estimated costs.

Increased cardiovascular disease, resource use, and costs before the clinical diagnosis of diabetes in veterans in the southeastern U.S

IMPORTANCE

Screening for diabetes might be more widespread if adverse associations with cardiovascular disease (CVD), resource use, and costs were known to occur earlier than conventional clinical diagnosis.

OBJECTIVE

The purpose of this study was to determine whether adverse effects associated with diabetes begin prior to clinical diagnosis.

DESIGN

Veterans with diabetes were matched 1:2 with controls by follow-up, age, race/ethnicity, gender, and VA facility. CVD was obtained from ICD-9 codes, and resource use and costs from VA datasets.

SETTING

VA facilities in SC, GA, and AL.

PARTICIPANTS

Patients with and without diagnosed diabetes.

MAIN OUTCOME MEASURES

Diagnosed CVD, resource use, and costs.

RESULTS

In this study, the 2,062 diabetic patients and 4,124 controls were 63 years old on average, 99 % male, and 29 % black; BMI was 30.8 in diabetic patients vs. 27.8 in controls (p<0.001). CVD prevalence was higher and there were more outpatient visits in Year -4 before diagnosis through Year +4 after diagnosis among diabetic vs. control patients (all p<0.01); in Year -2, CVD prevalence was 31 % vs. 24 %, and outpatient visits were 22 vs. 19 per year, respectively. Total VA costs/year/veteran were higher in diabetic than control patients from Year -4 ($4,083 vs. $2,754) through Year +5 ($8,347 vs. $5,700) (p<0.003) for each, reflecting underlying increases in outpatient, inpatient, and pharmacy costs (p<0.05 for each). Regression analysis showed that diabetes contributed an average of $1,748/year to costs, independent of CVD (p<0.001).

CONCLUSIONS AND RELEVANCE

VA costs per veteran are higher--over $1,000/year before and $2,000/year after diagnosis of diabetes--due to underlying increases in outpatient, inpatient, and pharmacy costs, greater number of outpatient visits, and increased CVD. Moreover, adverse associations with veterans' health and the VA healthcare system occur early in the natural history of the disease, several years before diabetes is diagnosed. Since adverse associations begin before diabetes is recognized, greater consideration should be given to systematic screening in order to permit earlier detection and initiation of preventive management. Keeping frequency of CVD and marginal costs in line with those of patients before diabetes is currently diagnosed has the potential to save up to $2 billion a year.

Supporting Practices to Adopt Registry-Based Care (SPARC): protocol for a randomized controlled trial

BACKGROUND

Diabetes is predicted to increase in incidence by 42% from 1995 to 2025. Although most adults with diabetes seek care from primary care practices, adherence to treatment guidelines in these settings is not optimal. Many practices lack the infrastructure to monitor patient adherence to recommended treatment and are slow to implement changes critical for effective management of patients with chronic conditions. Supporting Practices to Adopt Registry-Based Care (SPARC) will evaluate effectiveness and sustainability of a low-cost intervention designed to support work process change in primary care practices and enhance focus on population-based care through implementation of a diabetes registry.

METHODS

SPARC is a two-armed randomized controlled trial (RCT) of 30 primary care practices in the Virginia Ambulatory Care Outcomes Research Network (ACORN). Participating practices (including control groups) will be introduced to population health concepts and tools for work process redesign and registry adoption at a meeting of practice-level implementation champions. Practices randomized to the intervention will be assigned study peer mentors, receive a list of specific milestones, and have access to a physician informaticist. Peer mentors are clinicians who successfully implemented registries in their practices and will help champions in the intervention practices throughout the implementation process. During the first year, peer mentors will contact intervention practices monthly and visit them quarterly. Control group practices will not receive support or guidance for registry implementation. We will use a mixed-methods explanatory sequential design to guide collection of medical record, participant observation, and semistructured interview data in control and intervention practices at baseline, 12 months, and 24 months. We will use grounded theory and a template-guided approach using the Consolidated Framework for Implementation Research to analyze qualitative data on contextual factors related to registry adoption. We will assess intervention effectiveness by comparing changes in patient-level hemoglobin A1c scores from baseline to year 1 between intervention and control practices.

DISCUSSION

Findings will enhance our understanding of how to leverage existing practice resources to improve diabetes care in primary care practices by implementing and using a registry. SPARC has the potential to validate the effectiveness of low-cost implementation strategies that target practice change in primary care.

TRIAL REGISTRATION

NCT02318108.

Out-of-pocket expenditure on chronic non-communicable diseases in sub-Saharan Africa: the case of rural Malawi

In Sub-Saharan Africa (SSA) the disease burden of chronic non-communicable diseases (CNCDs) is rising considerably. Given weaknesses in existing financial arrangements across SSA, expenditure on CNCDs is often borne directly by patients through out-of-pocket (OOP) payments. This study explored patterns and determinants of OOP expenditure on CNCDs in Malawi. We used data from the first round of a longitudinal household health survey conducted in 2012 on a sample of 1199 households in three rural districts in Malawi. We used a two-part model to analyze determinants of OOP expenditure on CNCDs. 475 respondents reported at least one CNCD. More than 60% of the 298 individuals who reported seeking care incurred OOP expenditure. The amount of OOP expenditure on CNCDs comprised 22% of their monthly per capita household expenditure. The poorer the household, the higher proportion of their monthly per capita household expenditure was spent on CNCDs. Higher severity of disease was significantly associated with an increased likelihood of incurring OOP expenditure. Use of formal care was negatively associated with the possibility of incurring OOP expenditure. The following factors were positively associated with the amount of OOP expenditure: being female, Alomwe and household head, longer duration of disease, CNCDs targeted through active screening programs, higher socio-economic status, household head being literate, using formal care, and fewer household members living with a CNCD within a household. Our study showed that, in spite of a context where care for CNCDs should in principle be available free of charge at point of use, OOP payments impose a considerable financial burden on rural households, especially among the poorest. This suggests the existence of important gaps in financial protection in the current coverage policy.

The lifetime cost of diabetes and its implications for diabetes prevention

OBJECTIVE

To assess the cost implications of diabetes prevention, it is important to know the lifetime medical cost of people with diabetes relative to those without. We derived such estimates using data representative of the U.S. national population.

RESEARCH DESIGN AND METHODS

We aggregated annual medical expenditures from the age of diabetes diagnosis to death to determine lifetime medical expenditure. Annual medical expenditures were estimated by sex, age at diagnosis, and diabetes duration using data from 2006-2009 Medical Expenditure Panel Surveys, which were linked to data from 2005-2008 National Health Interview Surveys. We combined survival data from published studies with the estimated annual expenditures to calculate lifetime spending. We then compared lifetime spending for people with diabetes with that for those without diabetes. Future spending was discounted at 3% annually.

RESULTS

The discounted excess lifetime medical spending for people with diabetes was $124,600 ($211,400 if not discounted), $91,200 ($135,600), $53,800 ($70,200), and $35,900 ($43,900) when diagnosed with diabetes at ages 40, 50, 60, and 65 years, respectively. Younger age at diagnosis and female sex were associated with higher levels of lifetime excess medical spending attributed to diabetes.

CONCLUSIONS

Having diabetes is associated with substantially higher lifetime medical expenditures despite being associated with reduced life expectancy. If prevention costs can be kept sufficiently low, diabetes prevention may lead to a reduction in long-term medical costs.

Triggering factors of primary care costs in the years following type 2 diabetes diagnosis in Mexico

BACKGROUND AND AIMS

Diabetes represents a high epidemiological and economic burden worldwide. The cost of diabetes care increases slowly during early years, but it accelerates once chronic complications set in. There is evidence that adequate control may delay the onset of complications. Management of diabetes falls almost exclusively into primary care services until chronic complications appear. Therefore, primary care is strategic for reducing the expedited growth of costs. The objective of this study was to identify predictors of primary care costs in patients without complications in the years following diabetes diagnosis.

METHODS

Direct medical costs for primary care were determined from the perspective of public health services provider. Information was obtained from medical records of 764 patients. Microcosting and average cost techniques were combined. A generalized linear regression model was developed including characteristics of patients and facilities. Primary health care costs for different patient profiles were estimated.

RESULTS

The mean annual primary care cost was USD$465.1. Gender was the most important predictor followed by weight status, insulin use, respiratoty infections, glycemic control and dyslipidemia. A gap in costs was observed between genders; women make greater use of resources (42.1% on average). Such differences are reduced with obesity (18.1%), overweight (22.8%), respiratory infection (20.8%) and age >80 years (26.8%). Improving glycemic control shows increasing costs but at decreasing rates.

CONCLUSIONS

Modifiable factors (glycemic control, weight status and comorbidities) drive primary care costs the first 10 years. Those factors had a larger effect in costs for males than in for females.

Medical costs of CKD in the Medicare population

Estimates of the medical costs associated with different stages of CKD are needed to assess the economic benefits of interventions that slow the progression of kidney disease. We combined laboratory data from the National Health and Nutrition Examination Survey with expenditure data from Medicare claims to estimate the Medicare program's annual costs that were attributable to CKD stage 1-4. The Medicare costs for persons who have stage 1 kidney disease were not significantly different from zero. Per person annual Medicare expenses attributable to CKD were $1700 for stage 2, $3500 for stage 3, and $12,700 for stage 4, adjusted to 2010 dollars. Our findings suggest that the medical costs attributable to CKD are substantial among Medicare beneficiaries, even during the early stages; moreover, costs increase as disease severity worsens. These cost estimates may facilitate the assessment of the net economic benefits of interventions that prevent or slow the progression of CKD.

Screening for diabetes and prediabetes should be cost-saving in patients at high risk

OBJECTIVE

Although screening for diabetes and prediabetes is recommended, it is not clear how best or whom to screen. We therefore compared the economics of screening according to baseline risk.

RESEARCH DESIGN AND METHODS

Five screening tests were performed in 1,573 adults without known diabetes--random plasma/capillary glucose, plasma/capillary glucose 1 h after 50-g oral glucose (any time, without previous fast, plasma glucose 1 h after a 50-g oral glucose challenge [GCTpl]/capillary glucose 1 h after a 50-g oral glucose challenge [GCTcap]), and A1C--and a definitive 75-g oral glucose tolerance test. Costs of screening included the following: costs of testing (screen plus oral glucose tolerance test, if screen is positive); costs for false-negative results; and costs of treatment of true-positive results with metformin, all over the course of 3 years. We compared costs for no screening, screening everyone for diabetes or high-risk prediabetes, and screening those with risk factors based on age, BMI, blood pressure, waist circumference, lipids, or family history of diabetes.

RESULTS

Compared with no screening, cost-savings would be obtained largely from screening those at higher risk, including those with BMI >35 kg/m(2), systolic blood pressure ≥130 mmHg, or age >55 years, with differences of up to -46% of health system costs for screening for diabetes and -21% for screening for dysglycemia110, respectively (all P < 0.01). GCTpl would be the least expensive screening test for most high-risk groups for this population over the course of 3 years.

CONCLUSIONS

From a health economics perspective, screening for diabetes and high-risk prediabetes should target patients at higher risk, particularly those with BMI >35 kg/m(2), systolic blood pressure ≥130 mmHg, or age >55 years, for whom screening can be most cost-saving. GCTpl is generally the least expensive test in high-risk groups and should be considered for routine use as an opportunistic screen in these groups.

The effects of quality of care on costs: a conceptual framework

CONTEXT

The quality of health care and the financial costs affected by receiving care represent two fundamental dimensions for judging health care performance. No existing conceptual framework appears to have described how quality influences costs.

METHODS

We developed the Quality-Cost Framework, drawing from the work of Donabedian, the RAND/UCLA Appropriateness Method, reports by the Institute of Medicine, and other sources.

FINDINGS

The Quality-Cost Framework describes how health-related quality of care (aspects of quality that influence health status) affects health care and other costs. Structure influences process, which, in turn, affects proximate and ultimate outcomes. Within structure, subdomains include general structural characteristics, circumstance-specific (e.g., disease-specific) structural characteristics, and quality-improvement systems. Process subdomains include appropriateness of care and medical errors. Proximate outcomes consist of disease progression, disease complications, and care complications. Each of the preceding subdomains influences health care costs. For example, quality improvement systems often create costs associated with monitoring and feedback. Providing appropriate care frequently requires additional physician visits and medications. Care complications may result in costly hospitalizations or procedures. Ultimate outcomes include functional status as well as length and quality of life; the economic value of these outcomes can be measured in terms of health utility or health-status-related costs. We illustrate our framework using examples related to glycemic control for type 2 diabetes mellitus or the appropriateness of care for low back pain.

CONCLUSIONS

The Quality-Cost Framework describes the mechanisms by which health-related quality of care affects health care and health status-related costs. Additional work will need to validate the framework by applying it to multiple clinical conditions. Applicability could be assessed by using the framework to classify the measures of quality and cost reported in published studies. Usefulness could be demonstrated by employing the framework to identify design flaws in published cost analyses, such as omitting the costs attributable to a relevant subdomain of quality.

Diagnosed prevalence and health care expenditures of mental health disorders among dual eligible older people

PURPOSE

Little is known about mental health disorders (MHDs) and their associated health care expenditures for the dual eligible elders across long-term care (LTC) settings. We estimated the 12-month diagnosed prevalence of MHDs among dual eligible older adults in LTC and non-LTC settings and calculated the average incremental effect of MHDs on medical care, LTC, and prescription drug expenditures across LTC settings.

METHODS

Participants were fee-for-service dual eligible elderly beneficiaries from 7 states. We obtained their 2005 Medicare and Medicaid claims data and LTC program participation data from federal and state governments. We grouped beneficiaries into non-LTC, community LTC, and institutional LTC groups and identified enrollees with any of 5 MHDs (anxiety, bipolar, major depression, mild depression, and schizophrenia) using the International Classification of Diseases Ninth Revision codes associated with Medicare and Medicaid claims. We obtained medical care, LTC, and prescription drug expenditures from related claims.

RESULTS

Thirteen percent of all dual eligible elderly beneficiaries had at least 1 MHD diagnosis in 2005. Beneficiaries in non-LTC group had the lowest 12-month prevalence rates but highest percentage increase in health care expenditures associated with MHDs. Institutional LTC residents had the highest prevalence rates but lowest percentage increase in expenditures. LTC expenditures were less affected by MHDs than medical and prescription drug expenditures.

IMPLICATIONS

MHDs are prevalent among dual eligible older persons and are costly to the health care system. Policy makers need to focus on better MHD diagnosis among community-living elders and better understanding in treatment of MHDs in LTC settings.

Evaluating the impact of unmeasured confounding with internal validation data: an example cost evaluation in type 2 diabetes

The quantitative assessment of the potential influence of unmeasured confounders in the analysis of observational data is rare, despite reliance on the "no unmeasured confounders" assumption. In a recent comparison of costs of care between two treatments for type 2 diabetes using a health care claims database, propensity score matching was implemented to adjust for selection bias though it was noted that information on baseline glycemic control was not available for the propensity model. Using data from a linked laboratory file, data on this potential "unmeasured confounder" were obtained for a small subset of the original sample. By using this information, we demonstrate how Bayesian modeling, propensity score calibration, and multiple imputation can utilize this additional information to perform sensitivity analyses to quantitatively assess the potential impact of unmeasured confounding. Bayesian regression models were developed to utilize the internal validation data as informative prior distributions for all parameters, retaining information on the correlation between the confounder and other covariates. While assumptions supporting the use of propensity score calibration were not met in this sample, the use of Bayesian modeling and multiple imputation provided consistent results, suggesting that the lack of data on the unmeasured confounder did not have a strong impact on the original analysis, due to the lack of strong correlation between the confounder and the cost outcome variable. Bayesian modeling with informative priors and multiple imputation may be useful tools for unmeasured confounding sensitivity analysis in these situations. Further research to understand the operating characteristics of these methods in a variety of situations, however, remains.

Incremental Healthcare Expenditures Associated with Thyroid Disorders among Individuals with Diabetes

Objective. To estimate incremental healthcare expenditures associated with thyroid disorders among individuals with diabetes. Research Design and Methods. Cross-sectional study design with data on adults over 20 years of age with diabetes (N = 4, 490) from two years (2007 and 2009) of the Medical Expenditure Panel Survey (MEPS) was used. Ordinary least square regressions on log-transformed total expenditures and type of healthcare expenditures (inpatient, emergency room, outpatient, prescription drug, and other) were performed to estimate the incremental expenditures associated with thyroid disorders after controlling for demographic, socioeconomic, health status, lifestyle risk factors, macrovascular comorbid conditions (MCCs), and chronic conditions (CCs). Results. Among individuals with diabetes, those with thyroid disorders had significantly greater average annual total healthcare expenditures ($15,182) than those without thyroid disorders ($11,093). Individuals with thyroid disorders had 34.3% greater total healthcare expenditures compared to those without thyroid disorders, after controlling for demographic, socio-economic, and perceived health status. Furthermore, controlling for CCs and MCCs, this increase in expenditures was reduced to 21.4%. Conclusions. Among individuals with diabetes, thyroid disorders were associated with greater healthcare expenditures; such excess expenditures may be due to CCs and MCCs. Comanagement of CCs and reducing MCCs may be a pathway to reduce high healthcare expenditures.

Stratifying healthcare costs using the Diabetes Complication Severity Index

OBJECTIVE

We aim to determine whether healthcare costs for patients diagnosed with Type 2 Diabetes Mellitus (T2DM) are associated with the severity of diabetes complications as measured by the Diabetes Complication Severity Index (DCSI).

METHODS

Retrospective cohort analysis was performed on a 2007 primary care cohort of T2DM patients. The DCSI is a 13-point scale, which comprises 7 categories of complications and their severity levels. Healthcare cost data from 2008 and 2009 were used as primary outcome. Inpatient and outpatient costs incurred for services consumed by patients within the provider network were included. Generalized linear model with log-link and gamma distribution was used to predict healthcare costs.

RESULTS

Of the 59,767 T2DM patients, 2977 (5.0%) deaths occurred and 1336 (2.2%) were lost to follow up. Healthcare cost was strongly associated with increase in DCSI score. Compared to patients without complications, those with more complications (higher DCSI score) had an increased risk of higher healthcare costs. Risk ratio (RR) increased from 1.25 (95%CI: 1.19-1.32) for DCSI=1 to 1.61 (1.51-1.72) for DCSI=2; 2.10 (1.91-2.31) for DCSI=3; 2.52 (2.21-2.87) for DCSI=4 and 3.62 (3.09-4.25) for DCSI≥5. As a continuous score, a one-point increase in the DCSI was associated with a cost increase of 27% (95%CI: 1.25-1.29).

CONCLUSION

The DCSI score is a useful tool for predicting direct healthcare costs. The DCSI can be used to triage high-risk patients for more focused secondary prevention interventions at primary care level, in a bid to lower overall healthcare costs.

Neighborhoods, obesity, and diabetes--a randomized social experiment

BACKGROUND

The question of whether neighborhood environment contributes directly to the development of obesity and diabetes remains unresolved. The study reported on here uses data from a social experiment to assess the association of randomly assigned variation in neighborhood conditions with obesity and diabetes.

METHODS

From 1994 through 1998, the Department of Housing and Urban Development (HUD) randomly assigned 4498 women with children living in public housing in high-poverty urban census tracts (in which ≥40% of residents had incomes below the federal poverty threshold) to one of three groups: 1788 were assigned to receive housing vouchers, which were redeemable only if they moved to a low-poverty census tract (where <10% of residents were poor), and counseling on moving; 1312 were assigned to receive unrestricted, traditional vouchers, with no special counseling on moving; and 1398 were assigned to a control group that was offered neither of these opportunities. From 2008 through 2010, as part of a long-term follow-up survey, we measured data indicating health outcomes, including height, weight, and level of glycated hemoglobin (HbA(1c)).

RESULTS

As part of our long-term survey, we obtained data on body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) for 84.2% of participants and data on glycated hemoglobin level for 71.3% of participants. Response rates were similar across randomized groups. The prevalences of a BMI of 35 or more, a BMI of 40 or more, and a glycated hemoglobin level of 6.5% or more were lower in the group receiving the low-poverty vouchers than in the control group, with an absolute difference of 4.61 percentage points (95% confidence interval [CI], -8.54 to -0.69), 3.38 percentage points (95% CI, -6.39 to -0.36), and 4.31 percentage points (95% CI, -7.82 to -0.80), respectively. The differences between the group receiving traditional vouchers and the control group were not significant.

CONCLUSIONS

The opportunity to move from a neighborhood with a high level of poverty to one with a lower level of poverty was associated with modest but potentially important reductions in the prevalence of extreme obesity and diabetes. The mechanisms underlying these associations remain unclear but warrant further investigation, given their potential to guide the design of community-level interventions intended to improve health. (Funded by HUD and others.).

Cost-effectiveness of risk stratification for preventing type 2 diabetes using a multi-marker diabetes risk score

BACKGROUND

Personalized medicine requires diagnostic tests that stratify patients into distinct groups that may differentially benefit from targeted treatment approaches. This study compared the costs and benefits of two approaches for identifying those at high risk of developing type 2 diabetes for entry into a diabetes prevention program. The first approach identified high risk patients using impaired fasting glucose (IFG). The second approach used the PreDx Diabetes Risk Score (DRS) to further stratify IFG patients into high-risk and moderate-risk groups.

METHODS

A Markov model was developed to simulate the incidence and disease progression of diabetes and consequent costs and quality-adjusted life expectancy (QALY), comparing alternative approaches for identifying high-risk patients. We modeled direct medical costs, including the costs of the stratification testing, over a 10-year time horizon from a US payer perspective.

RESULTS

Stratification of IFG patients by the DRS method leads to improved identification and prevention among those at highest risk. At 5 years, the number needed to treat (NNT) in the IFG-only approach was 39 patients to prevent one case of diabetes compared to an NNT of 15 in the IFG + DRS approach. When compared to IFG alone, the IFG + DRS approach results in an incremental cost-effectiveness ratio (ICER) of $17,100/QALY gained at 5 years and would become cost saving in 10 years. In contrast and as compared to no stratification, the IFG-only approach would produce an ICER of $235,500/QALY gained at 5 years and $94,600/QALY gained at 10 years. The study findings are limited by the generalizability of the DRS validation study and uncertainty regarding the long-term effectiveness of diabetes prevention.

CONCLUSIONS

The analysis indicates that the cost-effectiveness of diabetes prevention can be improved by better identification of patients at highest risk for diabetes using the DRS.

Association between glycemic control and short-term healthcare costs among commercially insured diabetes patients in the United States

Abstract Objectives: Glycemic control, measured by HbA(1c), is well known to be a risk marker for long-term costly diabetes-related complications. The relationship between HbA(1c) and short-term costs is unclear. This study investigates how HbA(1c) is correlated to short-term diabetes-related medical expenses.

METHODS

Patients with diabetes with an HbA(1c) reading ≥6% between April and September 2007 were identified from a large US managed-care organization. Healthcare utilization data was obtained during the subsequent 12-month period. Multivariate analyses were performed to estimate the correlation between HbA(1c) and diabetes-related healthcare costs.

RESULTS

In all, 34,469 and 1,837 patients with type 2 and type 1 diabetes, respectively, were identified with an HbA(1c) reading ≥6% (mean HbA(1c): 7.4% and 7.9%). The majority of patients with type 1 diabetes were treated with insulin, while most patients with type 2 diabetes were treated with metformin. The multivariate analysis showed that several characteristics, including HbA(1c), significantly correlate with diabetes-related medical costs for both patients with type 1 and type 2 diabetes. A 1-percentage-point increase in HbA(1c) will, on average, lead to a 6.0% and 4.4% increase in diabetes-related medical costs for type 1 and type 2 diabetes, respectively. This corresponds to an annual cost increase of $445 and $250 for patients with type 1 and type 2 diabetes, respectively.

LIMITATIONS

Retrospective data analyses inherently associated with selection bias which can only partly be adjusted by statistical techniques. Furthermore, the study population is not necessarily representative of the general population and there can be isolated coding or data errors in the dataset.

CONCLUSIONS

These results suggest that tighter glycemic control is associated with short-term cost benefits for patients with diabetes. This supplements conventional wisdom that HbA(1c) affects risk of long-term complications and long-term costs.

Screening adults for pre-diabetes and diabetes may be cost-saving

OBJECTIVE

The economic costs of hyperglycemia are substantial. Early detection would allow management to prevent or delay development of diabetes and diabetes-related complications. We investigated the economic justification for screening for pre-diabetes/diabetes.

RESEARCH DESIGN AND METHODS

We projected health system and societal costs over 3 years for 1,259 adults, comparing costs associated with five opportunistic screening tests. All subjects had measurements taken of random plasma and capillary glucose (RPG and RCG), A1C, and plasma and capillary glucose 1 h after a 50 g oral glucose challenge test without prior fasting (GCT-pl and GCT-cap), and a subsequent diagnostic 75 g oral glucose tolerance test (OGTT).

RESULTS

Assuming 70% specificity screening cutoffs, Medicare costs for testing, retail costs for generic metformin, and costs for false negatives as 10% of reported costs associated with pre-diabetes/diabetes, health system costs over 3 years for the different screening tests would be GCT-pl $180,635; GCT-cap $182,980; RPG $182,780; RCG $186,090; and A1C $192,261; all lower than costs for no screening, which would be $205,966. Under varying assumptions, projected health system costs for screening and treatment with metformin or lifestyle modification would be less than costs for no screening as long as disease prevalence is at least 70% of that of our population and false-negative costs are at least 10% of disease costs. Societal costs would equal or exceed costs of no screening depending on treatment type.

CONCLUSIONS

Screening appears to be cost-saving compared to no screening from a health system perspective, and potentially cost-neutral from a societal perspective. These data suggest that strong consideration should be given to screening-with preventive management-and that use of GCTs may be cost-effective.

Physicians' perceptions of reimbursement as a barrier to comprehensive diabetes care

BACKGROUND

As the incidence of diabetes increases, there is growing concern about the adequacy of reimbursement levels for delivering comprehensive diabetes care.

OBJECTIVE

To investigate physicians' perceptions of the adequacy of reimbursement, as well as resources (eg, staff, facilities, materials), for their treatment of diabetic patients.

METHODS

A qualitative exploration using a Web-based survey of 300 physicians (200 primary care providers and 100 endocrinologists) and an online discussion group of 12 physicians, focusing on 10 services recommended by the American Diabetes Association that may be prone to underreimbursement. The 10 services were matched with 4 general diabetes care categories to assess the adequacy of care delivery.

RESULTS

The majority of physician study participants perceived that most of the 10 identified services are inadequately reimbursed-83% to 95% of physicians said Medicaid reimbursement was inadequate, 75% to 89% for Medicare reimbursement, and 67% to 86% for private insurance reimbursement-leading them to spend less time with each patient. This reduction in time was a limiting factor to providing comprehensive diabetes care. The survey also revealed differences between endocrinologists and primary care physicians; for example, medical nutrition therapy was offered by 50% of endocrinology practices compared with only 29.5% of primary care practices.

CONCLUSION

This study confirms previous findings that physicians perceive current reimbursement for diabetes care as too low, which limits their ability to perform all the tasks necessary to deliver comprehensive diabetes care.