Exploring kidney dialysis costs in the United States: a scoping review.

AIMS: The increasing prevalence of end-stage renal disease (ESRD) in the United States (US) represents a considerable economic burden due to the high cost of dialysis treatment. This review examines data from real-world studies to identify cost drivers and explore areas where dialysis costs could be reduced. METHODS: We identified and synthesized evidence published from 2016-2023 reporting direct dialysis costs in adult US patients from a comprehensive literature search of MEDLINE, Embase, and grey literature sources (e.g. US Renal Data System reports). RESULTS: Most identified data related to Medicare expenditures. Overall Medicare spending in 2020 was $29B for hemodialysis and $2.8B for peritoneal dialysis (PD). Dialysis costs accounted for almost 80% of total Medicare expenditures on ESRD beneficiaries. Private insurance payers consistently pay more for dialysis; for example, per person per month spending by private insurers on outpatient dialysis was estimated at $10,149 compared with Medicare spending of $3,364. Dialysis costs were higher in specific high-risk patient groups (e.g. type 2 diabetes, hepatitis C). Spending on hemodialysis was higher than on PD, but the gap in spending between PD and hemodialysis is closing. Vascular access costs accounted for a substantial proportion of dialysis costs. LIMITATIONS: Insufficient detail in the identified studies, especially related to outpatient costs, limits opportunities to identify key drivers. Differences between the studies in methods of measuring dialysis costs make generalization of these results difficult. CONCLUSIONS: These findings indicate that prevention of or delay in progression to ESRD could have considerable cost savings for Medicare and private payers, particularly in patients with high-risk conditions such as type 2 diabetes. More efficient use of resources is needed, including low-cost medication, to improve clinical outcomes and lower overall costs, especially in high-risk groups. Widening access to PD where it is safe and appropriate may help to reduce dialysis costs.

Previous papers have studied the cost of treating patients who need dialysis for kidney failure. We reviewed these costs and looked for patterns. Dialysis was the most expensive part of treatment for people with kidney disease who have Medicare. Dialysis with private insurance was much more expensive than with Medicare. People with diabetes experienced higher costs of dialysis than those without diabetes. Dialysis in a hospital costs more than dialysis at home. There are opportunities to reduce the cost of dialysis that should be explored further, such as more use of low-cost medication that can prevent the worsening of kidney disease and reduce the need for dialysis.

Drug-drug interaction potential among patients with nonmetastatic castration-resistant prostate cancer (nmCRPC) treated with novel androgen receptor inhibitors.

BACKGROUND: Nonmetastatic castration-resistant prostate cancer (nmCRPC) patients are often older and use concurrent medications that increase the potential for drug-drug interactions (pDDIs). This study assessed pDDI prevalence in real-world nmCRPC patients treated with apalutamide, darolutamide, or enzalutamide. RESEARCH DESIGN AND METHODS: Castrated prostate cancer patients without metastases prior to androgen receptor inhibitor initiation were identified retrospectively via Optum Clinformatics Data Mart claims data (8/2019-3/2021). The top 100 concomitant medications were assessed for pDDIs. RESULTS: Among 1,515 patients (mean age: 77 ± 8 years; mean Charlson Comorbidity Index: 3 ± 3), 340 initiated apalutamide, 112 darolutamide, and 1,063 enzalutamide. Common concomitant medication classes were cardiovascular (80%) and central nervous system (52%). Two-thirds of the patients received ≥5 concomitant medications; 30 (30/100 medications) pDDIs were identified for apalutamide and enzalutamide each and 2 (2/100 medications) for darolutamide. Most pDDIs had risk ratings of C or D, but four for apalutamide were rated X. Approximately 58% of the patients on apalutamide, 5% on darolutamide, and 54% on enzalutamide had ≥1 identified pDDI. CONCLUSIONS: Results showed a higher frequency of pDDIs in patients receiving apalutamide and enzalutamide vs darolutamide. The impact of these could not be determined retrospectively. DDI risk should be carefully evaluated when discussing optimal therapy for patients with nmCRPC.

Adverse events and costs among non-metastatic castration-resistant prostate cancer patients.

BACKGROUND: Limited real-world evidence exists on the economic burden of adverse events (AEs) to the healthcare system among patients with non-metastatic castration-resistant prostate cancer (nmCRPC) treated with second-generation androgen receptor antagonists (ARAs). Current data is needed to understand real-world clinical event rates among ARAs and the cost of these events. OBJECTIVES: Describe the incidence of non-central nervous system (CNS)-related AEs and CNS-related AEs among nmCRPC patients treated in the United States with second-generation ARAs (apalutamide and enzalutamide) and evaluate healthcare resource utilization (HCRU) and costs for these patients. METHODS AND STUDY DESIGN: This was a retrospective observational cohort study using claims data from Optum Clinformatics Data Mart to identify adult males with prostate cancer, castration, no metastases, and >1 claim for apalutamide or enzalutamide. The study was conducted from January 2017 to March 2020, with a patient index identification period from January 2018 to December 2019. AEs were classified as CNS-related or non-CNS-related. RESULTS: Of 605 patients (156 apalutamide and 449 enzalutamide), most were ≥65 years (94%) and had ≥1 non-CNS-related AE (55%). Many had ≥1 CNS-related AE (32%). Pain (12%) and arthralgia (11%) were the most frequently reported non-CNS-related AEs. Fatigue/asthenia (14%) and dizziness (7%) were the most frequently reported CNS-related AEs. Among patients with versus without non-CNS-related AEs, 34% versus 8% had emergency room (ER) events, and 25% versus 2% had inpatient events. Among patients with versus without CNS-related AEs, 41% versus 14% had ER events, and 38% versus 4% had inpatient events. Adjusted per-patient per-year cost (in 2020 USD) differences were significant between patients with and without non-CNS-related AEs ($30,765, p = 0.0018) and between patients with and without CNS-related AEs ($40,689, p = 0.0017). CONCLUSION: There is significant HCRU and cost burden among nmCRPC patients treated with ARAs developing AEs, highlighting the need for treatments with improved tolerability. Additional studies are warranted to include recently approved agents.

Risk of chronic kidney disease in patients with acute kidney injury following a major surgery: a US claims database analysis.

Background: Acute kidney injury (AKI) is a common complication after major surgery. This study assessed the risk of developing or worsening of chronic kidney disease (CKD) and other clinical outcomes in patients experiencing AKI after major surgery. Methods: This retrospective observational study used Optum's de-identified Clinformatics Data Mart Database to investigate cardiorenal outcomes in adult patients at the first AKI event following major surgery. The primary outcome was CKD stage ≥3; secondary outcomes included myocardial infarction (MI), stroke, heart failure, all-cause hospitalization, end-stage kidney disease, need for dialysis or kidney transplant and composite measures. Follow-up was up to 3 years. Additionally, the effect of intercurrent events on the risk of clinical outcomes was assessed. Results: Of the included patients (N = 31 252), most were male (61.9%) and White (68.9%), with a median age of 72 years (interquartile range 64-79). The event rates were 25.5 events/100 patient-years (PY) for CKD stage ≥3, 3.1 events/100 PY for end-stage kidney disease, 3.0 events/100 PY for dialysis and 0.1 events/100 PY for kidney transplants. Additionally, there were 6.9 events/100 PY for MI, 8.7 events/100 PY for stroke and 49.8 events/100 PY for all-cause hospitalization during follow-up. Patients with AKI relapses as intercurrent events were more likely to develop CKD stage ≥3 than those with just one AKI event after major surgery. Conclusion: This analysis demonstrated that patients experiencing AKI following major surgery are at high risk of developing severe CKD or worsening of pre-existing CKD and other cardiorenal clinical outcomes such as MI and stroke.

Estimated Prevalence and Testing for Albuminuria in US Adults at Risk for Chronic Kidney Disease.

Importance: Albuminuria testing is crucial for guiding evidence-based treatments to mitigate chronic kidney disease (CKD) progression and cardiovascular morbidity, but it is widely underutilized among persons with or at risk for CKD. Objective: To estimate the extent of albuminuria underdetection from lack of testing and evaluate its association with CKD treatment in a large US cohort of patients with hypertension or diabetes. Design, Setting, and Participants: This cohort study examined adults with hypertension or diabetes, using data from the 2007 to 2018 National Health and Nutrition Examination Surveys (NHANES) and the Optum deidentified electronic health record (EHR) data set of diverse US health care organizations. Analyses were conducted from October 31, 2022, to May 19, 2023. Main Outcomes and Measures: Using NHANES as a nationally representative sample, a logistic regression model was developed to estimate albuminuria (urine albumin-creatinine ratio ≥30 mg/g). This model was then applied to active outpatients in the EHR from January 1, 2017, to December 31, 2018. The prevalence of albuminuria among those with and without albuminuria testing during this period was estimated. A multivariable logistic regression was used to examine associations between having albuminuria testing and CKD therapies within the subsequent year (prescription for angiotensin-converting enzyme inhibitor [ACEi] or angiotensin II receptor blocker [ARB], prescription for sodium-glucose cotransporter 2 inhibitor [SGLT2i], and blood pressure control to less than 130/80 mm Hg or less than 140/90 mm Hg on the latest outpatient measure). Results: The total EHR study population included 192 108 patients (mean [SD] age, 60.3 [15.1] years; 185 589 [96.6%] with hypertension; 50 507 [26.2%] with diabetes; mean [SD] eGFR, 84 [21] mL/min/1.73 m2). There were 33 629 patients (17.5%) who had albuminuria testing; of whom 11 525 (34.3%) had albuminuria. Among 158 479 patients who were untested, the estimated albuminuria prevalence rate was 13.4% (n = 21 231). Thus, only 35.2% (11 525 of 32 756) of the projected population with albuminuria had been tested. Albuminuria testing was associated with higher adjusted odds of receiving ACEi or ARB treatment (OR, 2.39 [95% CI, 2.32-2.46]), SGLT2i treatment (OR, 8.22 [95% CI, 7.56-8.94]), and having blood pressure controlled to less than 140/90 mm Hg (OR, 1.20 [95% CI, 1.16-1.23]). Conclusions and Relevance: In this cohort study of patients with hypertension or diabetes, it was estimated that approximately two-thirds of patients with albuminuria were undetected due to lack of testing. These results suggest that improving detection of CKD with albuminuria testing represents a substantial opportunity to optimize care delivery for reducing CKD progression and cardiovascular complications.

Prescription of guideline-directed medical therapies in patients with diabetes and chronic kidney disease from the CURE-CKD Registry, 2019-2020.

AIM: Guideline-directed medical therapy (GDMT) is designed to improve clinical outcomes. The study aim was to assess GDMT prescribing rates and prescribing-persistence predictors in patients with diabetes and chronic kidney disease (CKD) from the Center for Kidney Disease Research, Education, and Hope Registry. MATERIALS AND METHODS: Data were obtained from adults ≥18 years old with diabetes and CKD between 1 January 2019 and 31 December 2020 (N = 39 158). Baseline and persistent (≥90 days) prescriptions for GDMT, including angiotensin converting enzyme (ACE) inhibitor/angiotensin receptor blocker (ARB), sodium-glucose cotransporter-2 (SGLT2) inhibitor and glucagon-like peptide 1 (GLP-1) receptor agonist were assessed. RESULTS: The population age (mean ± SD) was 70 ± 14 years, and 49.6% (n = 19 415) were women. Baseline estimated glomerular filtration rate (2021 CKD-Epidemiology Collaboration creatinine equation) was 57.5 ± 23.0 ml/min/1.73 m2 and urine albumin/creatinine 57.5 mg/g (31.7-158.2; median, interquartile range). Baseline and ≥90-day persistent prescribing rates, respectively, were 70.7% and 40.4% for ACE inhibitor/ARB, 6.0% and 5.0% for SGLT2 inhibitors, and 6.8% and 6.3% for GLP-1 receptor agonist (all p < .001). Patients lacking primary commercial health insurance coverage were less likely to be prescribed an ACE inhibitor/ARB [odds ratio (OR) = 0.89; 95% confidence interval (CI) 0.84-0.95; p < .001], SGLT2 inhibitor (OR 0.72; 95% CI 0.64-0.81; p < .001) or GLP-1 receptor agonist (OR 0.89; 95% CI 0.80-0.98; p = .02). GDMT prescribing rates were lower at Providence than UCLA Health. CONCLUSIONS: Prescribing for GDMT was suboptimal and waned quickly in patients with diabetes and CKD. Type of primary health insurance coverage and health system were associated with GDMT prescribing.

Poor adherence to clinical practice guidelines: A call to action for increased albuminuria testing in patients with type 2 diabetes.

We describe the substantial shortfall in adherence to guideline-recommended albumin-to-creatinine ratio (uACR) testing for people in the United States with type 2 diabetes. Poor compliance with current guidelines leads to delays in diagnosis-and treatment- of chronic kidney disease, which adversely affects clinical outcomes and contributes to incremental economic burden.

Unmet needs and opportunities for optimal management of patients with type 2 diabetes and chronic kidney disease.

This brief report utilizes EHR data from a large US health system to summarize unmet needs in patients with type 2 diabetes and chronic kidney disease and identifies areas of opportunity to optimize management within this patient population from treatment, screening and monitoring, and health care resource use perspectives.

Clinical characteristics and disease outcomes in non-diabetic chronic kidney disease: retrospective analysis of a US healthcare claims database.

BACKGROUND: The observational, real-world evidence FLIEDER study aimed to describe patient clinical characteristics and investigate clinical outcomes in non-diabetic patients with chronic kidney disease (CKD) using data collected from routine clinical practice in the United States. METHODS: Between 1 January, 2008-31 December, 2018, individuals aged ≥ 18 years, with non-diabetic, stage 3-4 CKD were indexed in the Optum® Clinformatics® Data Mart US healthcare claims database using International Classification of Diseases-9/10 codes for CKD or by laboratory values (estimated glomerular filtration rate [eGFR] 15-59 mL/min/1.73 m2). The primary outcomes were hospitalization for heart failure, a composite kidney outcome of end-stage kidney disease/kidney failure/need for dialysis and worsening of CKD stage from baseline. The effects of the intercurrent events of a sustained post-baseline decline in eGFR ≥ 30%, ≥ 40%, and ≥ 57% on the subsequent risk of the primary outcomes were also assessed. RESULTS: In the main study cohort (N = 504,924), median age was 75.0 years, and 60.5% were female. Most patients (94.7%) had stage 3 CKD at index. Incidence rates for hospitalization for heart failure, the composite kidney outcome, and worsening of CKD stage from baseline were 4.0, 10.3, and 4.4 events/100 patient-years, respectively. The intercurrent event analysis demonstrated that a relative decline in kidney function from baseline significantly increased the risk of cardiorenal events. CONCLUSIONS: This real-world study highlights that patients with non-diabetic CKD are at high risk of serious adverse clinical outcomes, and that this risk is amplified in patients who experienced greater post-baseline eGFR decline.

Descriptive study of the economic burden among patients with type 2 diabetes mellitus, chronic kidney disease, and chronic kidney disease and type 2 diabetes mellitus in a large US commercially insured population.

BACKGROUND: Chronic kidney disease (CKD) is a major public health concern that affects 37 million adults in the United States. It is well known that CKD presents a large economic burden, especially in the Medicare population. However, studies of the economic burden of CKD in younger populations are scarce. In particular, there is a gap in understanding how the presence of type 2 diabetes mellitus (T2DM) affects the burden of CKD in commercially insured populations. OBJECTIVE: To describe the economic and health care resource utilization (HCRU) burden of CKD within 3 patient groups (T2DM only, CKD only, and CKD and T2DM) aged 45-64 years overall and by Kidney Disease Improving Global Outcomes (KDIGO) CKD estimated glomerular filtration rate-based stage categories. METHODS: A descriptive, observational retrospective cohort study was conducted using administrative medical and pharmacy claims integrated with laboratory results data available in the HealthCore Integrated Research Database from January 1, 2017, to December 31, 2019. Three mutually exclusive groups of commercially insured patients aged 45-64 years were identified: T2DM only, CKD only, and CKD and T2DM. All-cause and disease-specific HCRU and costs in total, by medical and pharmacy benefits and across all places of service, were described for each of these groups 12 months after index date. For the CKD only and CKD and T2DM groups, costs were also described by KDIGO CKD stage. RESULTS: The CKD and T2DM group (n = 13,052) had numerically higher 12-month post-index all-cause and CKD/T2DM-related HCRU across all places of service. Mean 12-month all-cause costs for this group were $35,649, whereas costs for the CKD only group (n = 7,876) were $25,010 and costs for the T2DM only group (n = 120,364) were $16,121. Costs also tended to increase as CKD stage increased, with the greatest increases beginning at KDIGO stage 3b and higher. Mean 12-month all-cause costs for the CKD and T2DM group ranged from $29,993 to $41,222 for stages 1 to 3a and from $46,796 to $119,944 for stages 3b to 5. CONCLUSIONS: Commercially insured patients aged 45-64 years with CKD, especially those who also have T2DM, present a substantial burden in terms of elevated HCRU and costs. Costs tend to increase across KDIGO CKD stages and increase most rapidly at stage 3b and later. Therefore, there is an opportunity to reduce the burden of CKD in this population by investing in interventions to prevent or delay CKD disease progression. DISCLOSURES: HealthCore, Inc, received funding to perform this research, as well as funding from multiple pharmaceutical companies to perform various research studies outside of the submitted work. Mr Crowe and Dr Willey are employees of HealthCore, Inc., a wholly owned subsidiary of Elevance Health, Inc. Ms Chung was an employee of HealthCore, Inc., a wholly owned subsidiary of Elevance Health, Inc, at the time of study performance. Ms Chung and Dr Willey are shareholders of Elevance Health, Inc. Dr Kong, Dr Singh, Mr Farej, Dr Elliot, and Dr Williamson are employees of Bayer US, LLC. Dr Singh is a shareholder of Bayer US, LLC.

CKD Progression and Economic Burden in Individuals With CKD Associated With Type 2 Diabetes.

Rationale & Objective: To evaluate progression patterns and associated economic outcomes, using estimated glomerular filtration rate (eGFR) and urine albumin-creatinine ratio (UACR) based on the Kidney Disease: Improving Global Outcomes (KDIGO) risk categories, among patients with type 2 diabetes (T2D) and chronic kidney disease (CKD). Study Design: Patients with T2D and moderate- or high-risk CKD were selected from the Optum electronic health records database (January 2007-December 2019). Progression patterns and post-progression economic outcomes were assessed. Setting & Participants: Adults with T2D and CKD in clinical settings. Predictor: Baseline KDIGO risk categories. Outcomes: Progression to a more severe KDIGO risk category; healthcare resource utilization and medical costs. Analytical Approach: Progression probability was estimated using cumulative incidence. Healthcare resource utilization and costs were compared across progression groups. Results: Of 269,187 patients (mean age 65.6 years) with T2D and CKD of moderate or high baseline risk, 18.9% progressed to the very high-risk category within 5 years. Among moderate-risk patients, 17.8% of CKD stage G1-A2, 44.0% of stage G2-A2, and 61.3% of stage G3a-A1 patients progressed to a higher KDIGO risk category. Among high-risk patients, 63.9% of stage G3b-A1/G3a-A2 and 56.0% of stage G2-A3 patients progressed to very high risk. Within the same eGFR stage, a higher UACR stage was associated with 4- to 7-times higher risk of progressing to very high risk and faster eGFR decline. Nonprogressors had lower annual medical costs ($16,924) than patients who progressed from moderate risk to high risk ($22,117, P < 0.05), from high risk to very high risk ($32,204, P < 0.05), and from moderate risk to very high risk ($35,092, P < 0.05). Limitations: Infrequent lab testing might have caused lags in identifying progression; medical costs were calculated using unit costs. Conclusions: Patients with T2D and CKD of moderate or high risk per KDIGO risk categories had high probabilities of progression, incurring a substantial economic burden. The results highlight the value of UACR in CKD management.

Prescription Patterns of Cardiovascular- and Kidney-Protective Therapies Among Patients With Type 2 Diabetes and Chronic Kidney Disease.

OBJECTIVE: To assess the prevalence and correlates of prescription of sodium-glucose cotransporter 2 inhibitors (SGLT2i) and/or glucagon-like peptide 1 receptor agonists (GLP1-RA) in individuals with type 2 diabetes mellitus (T2DM) with and without chronic kidney disease (CKD). RESEARCH DESIGN AND METHODS: This was a cross-sectional analyses of SGLT2i and GLP1-RA prescriptions from 1 January 2019 to 31 December 2020 in the Veterans Health Administration System. The likelihood of prescriptions was examined by the presence or absence of CKD and by predicted risks of atherosclerotic cardiovascular disease (ASCVD) and end-stage kidney disease (ESKD). RESULTS: Of 1,197,880 adults with T2DM, SGLT2i and GLP1-RA were prescribed to 11% and 8% of patients overall, and to 12% and 10% of those with concomitant CKD, respectively. In adjusted models, patients with severe albuminuria were less likely to be prescribed SGLT2i or GLP1-RA versus nonalbuminuric patients with CKD, with odds ratios (ORs) of 0.91 (95% CI 0.89, 0.93) and 0.97 (0.94, 1.00), respectively. Patients with a 10-year ASCVD risk >20% (vs. <5%), had lower odds of SGLT2i use (OR 0.66 [0.61, 0.71]) and GLP1-RA prescription (OR 0.55 [0.52, 0.59]). A 5-year ESKD risk >5%, compared with <1%, was associated with lower likelihood of SGLT2i prescription (OR 0.63 [0.59, 0.67]) but higher likelihood of GLP1-RA prescription (OR 1.53 [1.46, 1.61]). CONCLUSIONS: Among a large cohort of patients with T2DM, prescription of SGLT2i and GLP1-RA was low in those with CKD. We observed a "risk-treatment paradox," whereby patients with higher risk of adverse outcomes were less likely to receive these therapies.

Development of clinical prediction models for renal and cardiovascular outcomes and mortality in patients with type 2 diabetes and chronic kidney disease using time-varying predictors.

AIMS: To develop a set of prediction models for end-stage kidney disease (ESKD), cardiovascular outcomes, and mortality in patients with type 2 diabetes (T2D) and chronic kidney disease (CKD) using commonly measured clinical variables. METHODS: We studied 1432 participants with T2D and CKD enrolled in the Chronic Renal Insufficiency Cohort, followed for a median period of 7 years. We used Cox proportional-hazards models to model the six outcomes (ESKD, stroke, myocardial infarction (MI), congestive heart failure (CHF), death before ESKD, and all-cause mortality). We internally evaluated these models using concordance and calibration measures. RESULTS: The newly developed six prediction models included 15 predictors: age at diabetes diagnosis, sex, blood pressure, body mass index, hemoglobin A1c, high density lipoprotein cholesterol, urine protein-to-creatinine ratio, estimated glomerular filtration rate, smoking status, and history of stroke, MI, CHF, ESKD, and amputation. The resulting models demonstrated good/strong discrimination (cross-validation C-index range: 0.70 to 0.90) and calibration. CONCLUSIONS: This study provided an internally validated and useful tool for predicting individual adverse outcomes and mortality in patients with T2D and CKD. These models may inform optimal use of targeted health interventions.

CKD Prevalence Among Patients With and Without Type 2 Diabetes: Regional Differences in the United States.

RATIONALE & OBJECTIVE: Regional variation in chronic kidney disease (CKD) prevalence in patients with or without type 2 diabetes mellitus (T2DM) has not been well characterized. STUDY DESIGN: Spatial and temporal comparative analysis. SETTING & PARTICIPANTS: MarketScan databases were used to identify patients with CKD overall and subgroups of patients with CKD with and without T2DM in the United States. OUTCOMES: Spatial patterns in CKD prevalence based on year, regional clusters of CKD between years, and characteristics of patients in high-prevalence states. ANALYTICAL APPROACH: Geomapping was used to visualize the state-level data of CKD prevalence generated from 2013 to 2018. We used univariate local indicators of spatial association (LISA) to evaluate geographic differences in prevalence, differential LISA for changes in CKD prevalence over time, and the χ2 test to identify patient characteristics in the top-20th percentile states for the prevalence of CKD. RESULTS: In univariate LISA, low-low clusters, in which a state has a low CKD prevalence and the surrounding states have a below-average CKD prevalence, were observed in the northwest region throughout the study period, regardless of the T2DM status, indicating a consistently low prevalence of CKD clustered in these areas. High-high clusters were observed, regardless of the T2DM status, in the southeast region in more recent years, suggesting an increased CKD prevalence in this region. LIMITATIONS: Health care insurance enrollment might not have been representative of the United States; the estimates were based on claims data that likely underestimated the true prevalence. CONCLUSIONS: Geographic disparities in CKD prevalence appear increasingly magnified, with an increase in the southeastern region of the United States. This increase is especially problematic because patients with CKD in high-prevalence states experience a greater likelihood of chronic conditions than those in the rest of the United States.

Medical costs for managing chronic kidney disease and related complications in patients with chronic kidney disease and type 2 diabetes.

OBJECTIVE: To provide cost estimates for chronic kidney disease (CKD) management and major CKD complications among patients with CKD and type 2 diabetes (T2D). STUDY DESIGN: A retrospective cohort study of 52,599 adults with CKD and T2D using Optum Clinformatics claims data from 2014 to 2019. METHODS: Medical costs associated with CKD management, renal replacement therapies (RRTs), major CKD complications (eg, myocardial infarction, stroke, heart failure, atrial fibrillation, and hyperkalemia), and death were estimated using generalized estimating equations adjusting for baseline demographics, complications, and medical costs. Costs for CKD management, RRT, and major CKD complications were assessed in 4-month cycles. Mortality costs were assessed in the month before death. RESULTS: The estimated 4-month CKD management costs ranged from $7725 for stage I to II disease to $11,879 for stage V (without RRT), with high additional costs for dialysis and kidney transplantation ($87,538 and $124,271, respectively). The acute event costs were $31,063 for heart failure, $21,087 for stroke, and $21,016 for myocardial infarction in the first 4 months after the incident event, which all decreased substantially in subsequent 4-month cycles. The acute event costs of atrial fibrillation and hyperkalemia were $30,500 and $31,212 with hospitalization, and $5162 and $1782 without. The costs associated with cardiovascular-related death, renal-related death, and death from other causes were $17,031, $12,605, and $9900, respectively. CONCLUSIONS: Management of CKD and its complications incurs high medical costs for patients with CKD and T2D. Results from this study can be used to quantify the economic profile of emerging treatments and inform decision-making.

Quantifying the economic burden of unintended pregnancies due to drug-drug interactions with hormonal contraceptives from the United States payer perspective.

Background: In the United States of America (USA), nearly 10 million women use oral contraceptives (OCs). Concomitant administration of certain medications can result in contraceptive failure, and consequently unintended pregnancies due to drug-drug interactions (DDIs). The objective of this analysis was to estimate the economic impact of unintended pregnancies due to DDIs among women of reproductive age using an OC alone or in combination with an enzyme inducer co-medication in the USA from a payer perspective. Methods: A Markov model using a cohort of 1,000 reproductive-age women was developed to estimate costs due to contraceptive failure for OC alone versus OC with concomitant enzyme inducer drugs. All women were assumed to begin an initial state, continuing until experiencing an unintended pregnancy. Unintended pregnancies could result in birth, induced abortion, spontaneous abortion, or ectopic pregnancy. The cohort was analyzed over a time horizon of 1 year with a cycle length of 1 month. Estimates of costs and probabilities of unintended pregnancy outcomes were obtained from the literature. Probabilities from the Markov cohort trace was used to estimate number of pregnancy outcomes. Results: On average, enzyme inducers resulted in 20 additional unintended pregnancies with additional unadjusted and adjusted costs median (range) of USD136,304 (USD57,436-USD320,093) and USD65,146 (USD28,491-USD162,635), respectively. The major component of the direct cost is attributed to the cost of births. Considering the full range of events, DDIs with enzyme inducers could result in 16-25 additional unintended pregnancies and total unadjusted and adjusted costs ranging between USD46,041 to USD399,121 and USD22,839 to USD202,788 respectively. Conclusion: The direct costs associated with unintended pregnancies due to DDIs may be substantial and are potentially avoidable. Greater awareness of DDI risk with oral contraceptives among payers, physicians, pharmacists and patients may reduce unintended pregnancies in at-risk populations.

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.

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

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

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

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

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

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