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Background Higher ultrafiltration (UF) rates are associated with numerous adverse cardiovascular outcomes among individuals receiving maintenance hemodialysis. We undertook this study to investigate the association of UF rate and incident atrial fibrillation in a large, nationally representative US cohort of incident, older hemodialysis patients. Methods We used the US Renal Data System linked to the records of a large dialysis provider to identify individuals ≥67 years of age initiating hemodialysis between January 2006 and December 2011. We applied an extended Cox model as a function of a time-varying exposure to compute adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of delivered UF rate and incident atrial fibrillation. Results Among the 15 414 individuals included in the study, 3177 developed atrial fibrillation. In fully adjusted models, a UF rate >13 mL/h/kg (versus ≤13 mL/h/kg) was associated with a higher hazard of incident atrial fibrillation [adjusted HR 1.19 (95% CI 1.07–1.30)]. Analyses using lower UF rate thresholds (≤10 versus >10 mL/h/kg and ≤8 versus >8 mL/h/kg, separately) yielded similar results. Analyses specifying the UF rate as a cubic spline (per 1 mL/h/kg) confirmed an approximately linear dose–response relationship between the UF rate and the risk of incident atrial fibrillation: risk began at UF rates of ~6 mL/h/kg and the magnitude of this risk flattened, but remained elevated, at rates ≥9 mL/h/kg. Conclusion In this observational study of older individuals initiating hemodialysis, higher UF rates were associated with higher incidences of atrial fibrillation.

Background: Heart failure (HF) after kidney transplantation is a significant but understudied problem. Pretransplant dialysis modality could influence incident HF risk through differing cardiac stressors. However, whether pretransplant dialysis modality is associated with the development of posttransplant HF is unknown. Methods: We used the US Renal Data System to assemble a cohort of 27,701 patients who underwent their first kidney transplant in the USA between the years 2005 and 2012 and who had Medicare fee-for-service coverage for >6 months preceding their transplant date. Patients with any HF diagnosis prior to transplant were excluded. Detailed baseline patient characteristics and comorbidities were abstracted. The outcome of interest was de novo posttransplant HF. Pretransplant dialysis modality was defined as the dialysis modality used at the time of transplant. We conducted time-to-event analyses using Cox regression. Death was treated as a competing risk in the study’s primary analysis. Graft failure was included as a time-varying covariate. Results: Among eligible patients, 81% were treated with hemodialysis prior to transplant, and hemodialysis patients were more likely to be male, had a shorter dialysis vintage, and had more diabetes and vascular disease diagnoses. When adjusted for all available demographic and clinical data, pretransplant treatment with hemodialysis (vs. peritoneal dialysis) was associated with a 19% increased risk in de novo posttransplant HF, with sub-distribution HR 1.19 (95% CI: 1.09–1.29). Conclusions: Our results suggest that choice of pretransplant dialysis modality may impact the development of posttransplant HF.

Despite accumulating evidence of cardiorenal benefits from sodium–glucose cotransporter 2 (SGLT2) inhibitors, prescription of agents in this drug class may be limited by concerns regarding adverse effects and interdisciplinary care coordination. To investigate these potential barriers, we performed a cross-sectional study of SGLT2 inhibitor prescriptions in 2017 in 3,779 adults with type 2 diabetes and proteinuric chronic kidney disease from a nationwide database. Only 173 (5%) of these patients received an SGLT2 inhibitor in 2017. Younger age, renin-angiotensin-aldosterone system inhibitor prescription, and higher estimated glomerular filtration rate were associated with SGLT2 inhibitor prescription. Primary care providers were responsible for the majority of the prescriptions. Continued efforts should be made to track and improve SGLT2 inhibitor use in indicated populations.

Background Whether fracture rates, overall and by fracture site, vary by cause of kidney failure in patients receiving dialysis is unknown. Methods Using the US Renal Data System, we compared fracture rates across seven causes of kidney failure in patients who started dialysis between 1997 and 2014. We computed unadjusted and multivariable adjusted proportional sub-distribution hazard models, with fracture events (overall, and by site) as the outcome and immunoglobulin A nephropathy as the reference group. Kidney transplantation and death were competing events. Results Among 491 496 individuals, with a median follow-up of 2.0 (25%, 75% range 0.9–3.9) years, 62 954 (12.8%) experienced at least one fracture. Patients with diabetic nephropathy, vasculitis or autosomal polycystic kidney disease (ADPKD) had the highest (50, 46 and 40 per 1000 person-years, respectively), and patient with lupus nephritis had the lowest (20 per 1000 person-years) fracture rates. After multivariable adjustment, diabetic nephropathy [hazard ratio (HR) 1.43, 95% confidence interval 1.33–1.53], ADPKD (HR 1.37, 1.26–1.48), vasculitis (HR 1.22, 1.09–1.34), membranous nephropathy (HR 1.16, 1.02–1.30) and focal segmental glomerulosclerosis (FSGS) (HR 1.13, 1.02–1.24) were associated with a significantly higher, and lupus nephritis with a significantly lower (HR 0.85, 0.71–0.98) fracture hazard. The hazards for upper extremity and lower leg fractures were significantly higher in diabetic nephropathy, ADPKD, FSGS and membranous nephropathy, while the hazard for vertebral fracture was significantly higher in vasculitis. Our findings were limited by the lack of data on medication use and whether fractures were traumatic or non-traumatic, among other factors. Conclusions Fracture risk, overall and by fracture site, varies by cause of end-stage kidney disease. Future work to determine underlying pathogenic mechanisms contributing to differential risks might inform more tailored treatment strategies. Our study was limited by lack of data regarding numerous potential confounders or mediators including medications and measures or bone biomarkers.

AIMS –: To determine the association with cardiovascular (CV) outcomes of sodium glucose cotransporter-2 (SGLT-2) inhibitors compared with dipeptidyl peptidase-4 (DPP-4) inhibitors in patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD). MATERIALS AND METHODS –: We conducted a population-based cohort study of new users of SGLT-2 inhibitors and DPP-4 inhibitors with T2DM and CKD using data from Optum Clinformatics DataMart. We assembled three cohorts: T2DM/no CKD, T2DM/CKD 1–2, and T2DM/ CKD 3a. Study outcomes were 1) time to first heart failure (HF) hospitalization; and 2) time to a composite CV endpoint comprised of non-fatal myocardial infarction (MI) or stroke. After inverse probability of treatment weighting, we used proportional hazards regression to estimate hazard ratios (HR) and 95% confidence intervals (CI). RESULTS –: New users of SGLT-2 inhibitors versus of DPP-4 inhibitors had lower risks of HF hospitalization in the T2DM/no CKD (HR, 0.76; 95% CI, 0.70, 0.82) and T2DM/CKD 1–2 (HR, 0.63; 95% CI, 0.48, 0.84), but no significant association was present in the T2DM/CKD 3a cohort. Compared with prescription of DPP-4 inhibitors, SGLT-2 inhibitors were associated with lower risks of non-fatal MI or stroke of 23% (HR, 0.77; 95% CI, 0.70, 0.85) in the T2DM/no CKD cohort, but no significant associations were present in the T2DM/CKD 1–2 and T2DM/CKD 3a cohorts. CONCLUSIONS –: Incident prescription of SGLT-2 inhibitors was associated with lower risks of HF hospitalization but not with non-fatal MI or stroke despite suggesting benefit, relative to prescription of DPP-4 inhibitor across different stages of CKD.

Though acute kidney injury (AKI) is often multifactorial, investigators are now emphasizing the specific contribution of nephrotoxins. This study examines the epidemiology of nephrotoxin exposure and nephrotoxin-associated AKI among children undergoing congenital heart surgery (CHS). This is a retrospective cohort study of children admitted following CHS between June 1, 2014, and September 30, 2014. Nephrotoxins were defined according to the Nephrotoxic Injury Negated by Just-in-time-Action (NINJA) collaborative; high nephrotoxin exposure was defined as receipt of ≥ 3 nephrotoxins concurrently. AKI was diagnosed according to KDIGO creatinine criteria. Severe AKI was defined as KDIGO stage ≥ 2. Poisson models were used to compute adjusted relative risk (aRR) of high nephrotoxin exposure for AKI. One hundred fifty-four children (median age 20.4 months, IQR 2.3–59.5) were included. One hundred thirty-one (85.1%) received at least one nephrotoxin; 32 (20.8%) received ≥ 3 nephrotoxins. The most commonly administered medications were ketorolac (n = 74, 48.1%), aspirin (n = 62, 40.3%), ibuprofen (n = 51, 33.1%), vancomycin (n = 39, 25.3%), piperacillin/tazobactam (n = 35, 22.7%), and enalapril (n = 14, 9.1%). AKI occurred more commonly in those exposed to ≥ 3 nephrotoxins (62.5 vs. 50.8%); this was not statistically significant after adjusting for confounders (aRR = 1.2, 95% CI 0.9–1.7). Severe AKI was similar between those with and without high nephrotoxin exposure (21.9 vs. 19.7%, p = 0.78). Nephrotoxin use is common following pediatric CHS. While we found no association between high nephrotoxin exposure and AKI, this may be related to the multifactorial nature of AKI in this population. For many common nephrotoxins, less injurious agents exist and nephrotoxin exposure may represent a modifiable risk factor for AKI.

The incidence of hip fracture in patients with end-stage renal disease (ESRD) is considerably higher than that in the general age- and sex-matched population. Although medical therapy for chronic kidney disease mineral bone disorder (CKD-MBD) has changed considerably over the last decade, rates of hip fracture in the entire ESRD population have not been well-characterized. Herein, we evaluated temporal trends in rates of hip fracture, in-hospital mortality, and costs of associated hospital stay in ESRD. We identified hospitalizations for hip fracture from 2003 to 2011 using the Nationwide Inpatient Sample, a representative national database inclusive of all ages and payers. We incorporated data from the United States Renal Data System and the US Census to calculate population-specific rates. Between 2003 and 2011, we identified 47,510 hip fractures in the ESRD population. The overall rate of hip fracture was 10.04/1000 person-years. The rate was 3.73/1000 person-years in patients aged less than 65 years, and 20.97/1000 person-years in patients aged 65 or older. Age- and sex-standardized rates decreased by 12.6% from 2003 (10.23/1000 person-years; 95% confidence interval [CI], 7.99/1000 to 12.47/1000) to 2011 (8.94/1000 person-years; 95% CI, 7.12/1000 to 10.75/1000). Hip fracture rates over time were virtually identical in patients aged less than 65 years; however, rates decreased by 15.3% among patients aged 65 years or older; rates declined more rapidly in older women compared with older men (p for interaction = 0.047). In-hospital mortality rate after hip fracture operation declined by 26.7% from 2003 (8.6%; 95% CI, 6.8 to 10.4) to 2011 (6.3%; 95% CI, 4.9 to 7.7). In ESRD, age- and sex-standardized hip fracture rates and associated in-hospital mortality have declined substantially over the last decade. © 2017 American Society for Bone and Mineral Research.

Importance Seroprevalence studies complement data on detected cases and attributed deaths in assessing the cumulative spread of the SARS-CoV-2 virus. Objective To estimate seroprevalence of SARS-CoV-2 antibodies in patients receiving dialysis and adults in the US in January 2021 before the widespread introduction of COVID-19 vaccines. Design, setting, and participants This cross-sectional study used data from the third largest US dialysis organization (US Renal Care), which has facilities located nationwide, to estimate SARS-CoV-2 seroprevalence among US patients receiving dialysis. Remainder plasma (ie, plasma that would have otherwise been discarded) of all patients receiving dialysis at US Renal Care facilities from January 1 to 31, 2021, was tested for SARS-CoV-2 antibodies. Patients were excluded if they had a documented dose of SARS-CoV-2 vaccination or if a residence zip code was missing from electronic medical records. Crude seroprevalence estimates from this sample (January 2021) were standardized to the US adult population using the 2018 American Community Survey 1-year estimates and stratified by age group, sex, self-reported race/ethnicity, neighborhood race/ethnicity composition, neighborhood income level, and urban or rural status. These data and case detection rates were then compared with data from a July 2020 subsample of patients who received dialysis at the same facilities. Exposures Age, sex, race/ethnicity, and region of residence as well as neighborhood race/ethnicity composition, poverty, population density, and urban or rural status. Main outcomes and measures The spike protein receptor-binding domain total antibody assay (Siemens Healthineers; manufacturer-reported sensitivity of 100% and specificity of 99.8%) was used to estimate crude SARS-CoV-2 seroprevalence in the unweighted sample, and then the estimated seroprevalence rates for the US dialysis and adult populations were calculated, adjusting for age, sex, and region. Results A total of 21 464 patients (mean [SD] age, 63.1 [14.2] years; 12 265 men [57%]) were included in the unweighted sample from January 2021. The patients were disproportionately older (aged 65-79 years, 7847 [37%]; aged ≥80 years, 2668 [12%]) and members of racial/ethnic minority groups (Hispanic patients, 2945 [18%]; non-Hispanic Black patients, 4875 [29%]). Seroprevalence of SARS-CoV-2 antibodies was 18.9% (95% CI, 18.3%-19.5%) in the sample, with a seroprevalence of 18.7% (95% CI, 18.1%-19.2%) standardized to the US dialysis population, and 21.3% (95% CI, 20.3%-22.3%) standardized to the US adult population. In the unweighted sample, younger persons (aged 18-44 years, 25.9%; 95% CI, 24.1%-27.8%), those who self-identified as Hispanic or living in Hispanic neighborhoods (25.1%; 95% CI, 23.6%-26.4%), and those living in the lowest-income neighborhoods (24.8%; 95% CI, 23.2%-26.5%) were among the subgroups with the highest seroprevalence. Little variability was observed in seroprevalence by geographic region, population density, and urban or rural status in the January 2021 sample (largest regional difference, 1.2 [95% CI, 1.1-1.3] higher odds of seroprevalence in residents of the Northeast vs West). Conclusions and relevance In this cross-sectional study of patients receiving dialysis in the US, fewer than 1 in 4 patients had evidence of SARS-CoV-2 antibodies 1 year after the first case of SARS-CoV-2 infection was detected in the US. Results standardized to the US population indicate similar prevalence of antibodies among US adults. Vaccine introduction to younger individuals, those living in neighborhoods with a large population of racial/ethnic minority residents, and those living in low-income neighborhoods may be critical to disrupting the spread of infection.

We compared prospective risk adjustment models for adjusting patient panels at the San Francisco Department of Public Health. We used 4 statistical models (linear regression, two-part model, zero-inflated Poisson, and zero-inflated negative binomial) and 4 subsets of predictor variables (age/gender categories, chronic diagnoses, homelessness, and a loss to follow-up indicator) to predict primary care visit frequency. Predicted visit frequency was then used to calculate patient weights and adjusted panel sizes. The two-part model using all predictor variables performed best (R = 0.20). This model, designed specifically for safety net patients, may prove useful for panel adjustment in other public health settings.

Patients with end-stage renal disease (ESRD) are at a high risk for hip fracture. Little is known about the risk for, and consequences of, hip fracture among patients with non-dialysis-requiring chronic kidney disease (CKD). We examined the incidence of hip fracture, in-hospital mortality, length of stay, and costs among patients with ESRD, non-dialysis-requiring CKD, and normal or near normal kidney function. Using the Healthcare Cost and Utilization Project's Nationwide Inpatient Sample, a nationally representative database, we identified hospitalizations for hip fracture in 2010. We incorporated data from the United States Renal Data System (USRDS) and the US census to calculate population-specific rates. Age-standardized incidence of hip fracture was highest among patients with ESRD (3.89/1000 person-years), followed by non-dialysis-requiring CKD (1.81/1000 persons) and patients with normal or near normal kidney function (1.18/1000 persons). In-hospital mo rtality (odds ratio [OR] = 1.69, 95% confidence interval [CI] 1.46 to 1.96), lengths of stay (median [10th, 90th percentiles] 5 [3 to 11] versus 5 [3 to 10] days) and costs (median $14,807 versus $13,314) were significantly higher in patients with non-dialysis-requiring CKD relative to patients with normal or near normal kidney function. In summary, non-dialysis-requiring CKD is associated with higher age-standardized rates of hip fracture and post-hip fracture mortality and higher resource utilization. © 2016 American Society for Bone and Mineral Research.

Background Little is known about the trends in the incidence and outcomes of patients with end-stage renal disease (ESRD) attributed to human immunodeficiency virus-associated nephropathy (HIVAN). We sought to define relative incidence among ESRD patients, changes in mortality among patients with ESRD attributed to HIVAN, as well as changes in the excess mortality experienced by patients with ESRD attributed to HIVAN compared with otherwise similar ESRD patients with non-HIVAN causes. Methods We used the US Renal Data System to identify all individuals with reported HIVAN who initiated treatment for ESRD between 1989 and 2011. We plotted their counts and proportions among all incident ESRD patients and tabulated their characteristics across years. We then compared mortality within the HIVAN group across years using Cox regression. In addition, we studied the trends in relative mortality of HIVAN patients versus those with ESRD not reported as HIVAN. Results Overall, 14 719 individuals with HIVAN-ESRD were recorded, with significant reductions in recent years (893 in 2006; 525 in 2011). Compared with patients initiating dialysis between 1989 and 1992, mortality declined by 40% (HR = 0.60; 95% CI, 0.55-0.65) and 64% (HR = 0.36; 95% CI, 0.32-0.40) for patients initiating dialysis in 1999/2000 and 2009-11, respectively. The adjusted excess mortality of HIVAN-ESRD patients versus incident ESRD patients from other causes was >5-fold in 1989-92 (HR = 5.21; 95% CI, 4.84-5.60); this excess mortality has subsequently declined but remained at almost 3-fold in recent years (e.g. HR = 2.58; 95% CI, 2.37-2.80, 2009-11 incidence cohort). Conclusions Concurrent with the increasing availability of highly active antiretroviral therapy (HAART), both the incidence of ESRD due to HIVAN and the mortality of such patients have decreased substantially. However, HIVAN patients reaching ESRD continue to experience substantial excess mortality compared with other ESRD patients even in the current era of modern HAART.

India is experiencing an alarming rise in the burden of non-communicable diseases, but data on the incidence of chronic kidney disease (CKD) are sparse. Using the Center for Cardiometabolic Risk Reduction in South Asia surveillance study (a population-based survey of Delhi and Chennai, India) we estimated overall, and age-, sex-, city-, and diabetes-specific prevalence of CKD, and defined the distribution of the study population by the Kidney Disease Improving Global Outcomes (KDIGO) classification scheme. The likelihood of cardiovascular events in participants with and without CKD was estimated by the Framingham and Interheart Modifiable Risk Scores. Of 12,271 participants, 80% had complete data on serum creatinine and albuminuria. The prevalence of CKD and albuminuria, age standardized to the World Bank 2010 world population, were 8.7% (95% confidence interval: 7.9 to 9.4%) and 7.1% (6.4 to 7.7%) respectively. Nearly 80% of patients with CKD had an abnormally high hemoglobin A1c (5.7 and above). Based on KDIGO guidelines, 6.0, 1.0, and 0.5% of study participants are at moderate, high, or very high risk for experiencing CKD-associated adverse outcomes. The cardiovascular risk scores placed a greater proportion of patients with CKD in the high-risk categories for experiencing cardiovascular events, when compared with participants without CKD. Thus one in 12 persons living in two of India’s largest cities have evidence of CKD, with features that put them at high risk for adverse outcomes.

Purpose Heparin is commonly used to anticoagulate the hemodialysis (HD) circuit. Despite the bleeding risk, no American standards exist for its administration. We identified correlates and quantified sources of variance in heparin dosing for HD. Methods We performed a cross-sectional study of patients aged 67 years or older who underwent HD with heparin on one of two randomly chosen days in 2008 at a national chain of dialysis facilities. Using a mixed effects model with random intercept for facility and fixed patient and facility characteristics, we examined heparin dosing at patient and facility levels. Results The median heparin dose among the 17 722 patients treated in 1366 facilities was 4000 (25th–75th percentile: 2625–6000) units. In multivariable-adjusted analyses, higher weight, longer session duration, catheter use, and dialyzer reuse were significantly associated with higher heparin dose. Dose also varied considerably among census divisions. Of the overall variance in dose, 21% was due to between-facility differences, independent of facilities' case mix, geography, size, or rurality; 79% was due to differences at the patient level. The patient and facility characteristics in our model explained only 25% of the variance at the patient level. Conclusions Despite the lack of standards for heparin administration, we noted patterns of use, including weight-based and time-dependent dosing. Most of the variance was at the patient level; however, only a quarter of it could be explained. The high amount of unexplained variance suggests that factors other than clinical need are driving heparin dosing and that there is likely room for more judicious dosing of heparin. Copyright © 2014 John Wiley & Sons, Ltd.

Coronary artery disease is a major cause of morbidity and mortality in the kidney transplant population. We compared the long-term outcomes of coronary artery bypass graft (CABG) surgery with percutaneous coronary intervention (PCI) for multivessel coronary disease in a contemporary cohort of US kidney transplant recipients. From the U.S. Renal Data System, we identified all adult kidney transplant patients with ≥6 months of Medicare A+B undergoing first recorded multivessel coronary revascularization from 1997 to 2009. The associations of CABG versus PCI with death and the composite of death or myocardial infarction (MI) were compared using proportional hazards regression. Of the 2272 patients included in the study, 1594 underwent CABG and 678 underwent PCI. The estimated 5-year survival rate was 55% [95% confidence interval (CI) 53% to 57%] following coronary revascularization, with no significant association between revascularization type and death [adjusted hazard ratio (aHR) = 1.08; CI 0.94-1.23] or the composite of death or MI (aHR = 1.07; CI 0.96-1.18). Separate propensity score-matched analyses yielded similar results. In this analysis of kidney transplant recipients undergoing multivessel coronary revascularization, we found no difference between CABG and PCI in terms of survival or the composite of death and MI.

The incidence of hip fracture in patients with end-stage renal disease (ESRD) is considerably higher than that in the general age- and sex-matched population. Although medical therapy for chronic kidney disease mineral bone disorder (CKD-MBD) has changed considerably over the last decade, rates of hip fracture in the entire ESRD population have not been well-characterized. Herein, we evaluated temporal trends in rates of hip fracture, in-hospital mortality, and costs of associated hospital stay in ESRD. We identified hospitalizations for hip fracture from 2003 to 2011 using the Nationwide Inpatient Sample, a representative national database inclusive of all ages and payers. We incorporated data from the United States Renal Data System and the US Census to calculate population-specific rates. Between 2003 and 2011, we identified 47,510 hip fractures in the ESRD population. The overall rate of hip fracture was 10.04/1000 person-years. The rate was 3.73/1000 person-years in patients aged less than 65 years, and 20.97/1000 person-years in patients aged 65 or older. Age- and sex-standardized rates decreased by 12.6% from 2003 (10.23/1000 person-years; 95% confidence interval [CI], 7.99/1000 to 12.47/1000) to 2011 (8.94/1000 person-years; 95% CI, 7.12/1000 to 10.75/1000). Hip fracture rates over time were virtually identical in patients aged less than 65 years; however, rates decreased by 15.3% among patients aged 65 years or older; rates declined more rapidly in older women compared with older men (p for interaction = 0.047). In-hospital mortality rate after hip fracture operation declined by 26.7% from 2003 (8.6%; 95% CI, 6.8 to 10.4) to 2011 (6.3%; 95% CI, 4.9 to 7.7). In ESRD, age- and sex-standardized hip fracture rates and associated in-hospital mortality have declined substantially over the last decade. © 2017 American Society for Bone and Mineral Research.

Background The development of acute kidney injury (AKI) after cardiac surgery is associated with significant mortality, morbidity, and cost. The last decade has seen major changes in the complexity of cardiac surgical candidates and in the number and type of cardiac surgical procedures being performed. Methods Using data from the Nationwide Inpatient Sample, we determined the annual rates of AKI, AKI requiring dialysis (AKI-D), and inpatient mortality after cardiac surgery in the United States in the years 1999 through 2008. Results Inpatient mortality with AKI and AKI-D decreased from 27.9% and 45.9%, respectively, in 1999 to 12.8% and 35.3%, respectively, in 2008. Compared with 1999, the odds of AKI and AKI-D in 2008, adjusted for demographic and clinical factors, were 3.30 (95% confidence interval [CI]: 2.89 to 3.77) and 2.23 (95% CI: 1.78 to 2.80), respectively. Corresponding adjusted odds of death associated with AKI and AKI-D were 0.31 (95% CI: 0.26 to 0.36) and 0.47 (95% CI: 0.34 to 0.65.) Taken together, the attributable risks for death after cardiac surgery associated with AKI and AKI-D increased from 30% and 5%, respectively, in 1999 to 47% and 14%, respectively, in 2008. Conclusions In sum, despite improvements in individual patient outcomes over the decade 1999 to 2008, the population contribution of AKI and AKI-D to inpatient mortality after surgery increased over the same period.

Non-VA services may provide an important alternative to veterans affairs (VA) services for VA patients who are eligible for Medicare coverage, especially in areas with poor geographic access to the VA. As Medicare and the VA are legally prohibited from billing each other for services provided to dually eligible veterans, cost-shifting may occur, especially as the population ages and increasingly more veterans become Medicare eligible. It is of strong interest to understand which VA patients are also obtaining services outside of the VA and how their outside utilization responds to the allocation of VA resources. That is, where access to VA services becomes more limited, do dually eligible veterans increasingly turn to the Medicare sector for their care (substitution), or do they actually receive fewer Medicare services, e.g., due to fewer VA referrals (complementarity)? Veterans 65 and older use Medicare for their medical care (Borowsky and Cowper 1999; Wright et al. 1999; Weeks et al. 2005, 2006), but only one previous study, limited to elderly veterans in northern New England (Weeks et al. 2005), has examined use of Medicare for behavioral health care among dually eligible veterans. The question of cost-shifting and substitution is particularly interesting for veterans with mental health and substance abuse (MH/SA) disorders. The prevalence of mental disorders is generally higher in the VA than in other health care systems, with approximately 29 percent of veterans having at least one MH/SA disorder (Hankin et al. 1999; Piette, Baisden, and Moos 1999). Psychiatric comorbidities are common as well. Although the VA is sometimes viewed as a “provider of last resort” for medical care, due to its limited choice of providers and lack of resources, the limitations of Medicare coverage on behavioral health care (Ettner 1997), in conjunction with the wide array of services provided by VA in this area, makes the VA an indispensable source of care for many veterans with behavioral health problems. The VA operates the largest mental health service delivery system in the nation, servicing over 900,000 veterans annually at a cost of more than $2.5 billion. Special emphasis programs target populations including the severely mentally ill, the homeless, and those with posttraumatic stress disorder (PTSD) and SA problems. Furthermore, the VA provides more comprehensive prescription drug coverage than Medicare, so patients have a strong financial incentive to receive pharmacotherapy from VA providers. Yet, the greater relative distance to VA versus Medicare providers may impede some veterans from taking advantage of VA's unique MH/SA services. Proximity to care has been shown to influence medical utilization in the general population (Nemet and Bailey 2000; Shahain et al. 2000; Arcury et al. 2005) as well as in the VA (Mooney et al. 2000; Fortney et al. 2005). For mental health care, earlier studies found that VA patients living further from VA facilities used fewer VA resources (Fortney et al. 1995, 1998; Rosenheck and Stolar 1998; Druss and Rosenheck 2000), but were unable to determine whether the reduction in the use of VA services was offset by increased Medicare utilization. Another paper found that rural veterans experience changes in policy that restrict access to SA services more dramatically than urban veterans, without substituting private-sector care (Wallace et al. 2007). Similarly, studies have identified a role of distance to provider in determining treatment patterns of Medicare patients with psychiatric conditions (Ettner and Hermann 1997; Ettner 1999; Ettner, Hermann, and Tang 1999), but did not look at crossover between the VA and Medicare among patients who had a choice between the two. A recent study showed that dual eligibles who lived farther from VA hospitals were less likely to rely on VA health care, particularly inpatient care (Hynes et al. 2007). However, this study focused on patient characteristics and did not examine behavioral health care. This research uses a national linked VA-Medicare database to examine health care sector choices among VA patients diagnosed with MH/SA disorders who are dually eligible for Medicare. We focus on the effects of geographic proximity to care on utilization of services in each sector. Our goal is to establish whether veterans with more limited geographic access to VA behavioral health services reduce their utilization of these services and whether their use of Medicare behavioral health services increases or decreases concomitantly. This issue has important policy implications regarding allocation of MH/SA resources within the VA system. If Medicare behavioral health care serves as a substitute for VA care, then an understanding of the nature of the cost-shifting involved is important information for VA managers in their budget allocation decisions. If Medicare services are complementary to VA services, then the VA may need to increase its outreach efforts to identify veterans who are in need of behavioral care but not receiving it.

The Patient Safety Indicators (PSIs), developed by the Agency for Healthcare Research and Quality, are useful screening tools for highlighting areas in which quality should be further investigated and providing useful benchmarks for tracking progress.Our objectives were to: 1) provide a descriptive analysis of the incidence of PSI events from 2001 to 2004 in the Veterans Health Administration (VA); 2) examine trends in national PSI rates at the hospital discharge level over time; and 3) assess whether hospital characteristics (eg, teaching status, number of beds, and degree of quality improvement implementation) and baseline safety-related hospital performance predict future hospital safety-related performance.We examined changes in risk-adjusted PSI rates at the discharge level, calculated the correlation between hospitals' risk-adjusted PSI rates in 2001 with subsequent years, and developed generalized linear models to examine predictors of hospitals' 2004 risk-adjusted PSI rates.Risk-adjusted rates of 2 of the 15 PSIs demonstrated significant trends over time. Rates of iatrogenic pneumothorax increased over time, whereas rates of failure to rescue decreased. Most PSIs demonstrated consistent rates over time. After accounting for patient and hospital characteristics, hospitals' baseline risk-adjusted PSI rates were the most important predictors of their 2004 risk-adjusted rates for 8 PSIs.The PSIs are useful tools for tracking and monitoring patient safety events in the VA. Future research should investigate whether trends reflect better or worse care or increased attention to documenting patient safety events.

Although difficulties in applying risk-adjustment measures to mental health populations are increasingly evident, a model designed specifically for patients with psychiatric disorders has never been developed.Our objective was to develop and validate a case-mix classification system, the "PsyCMS," for predicting concurrent and future mental health (MH) and substance abuse (SA) healthcare costs and utilization.Subjects included 914,225 veterans who used Veterans Administration (VA) healthcare services during fiscal year 1999 (FY99) with any MH/SA diagnosis (International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] codes 290.00-312.99, 316.00-316.99).We derived diagnostic categories from ICD-CM codes using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition definitions, clinical input, and empiric analyses. Weighted least-squares regression models were developed for concurrent (FY99) and prospective (FY00) MH/SA costs and utilization. We compared the predictive ability of the PsyCMS with several case-mix systems, including adjusted clinical groups, diagnostic cost groups, and the chronic illness and disability payment system. Model performance was evaluated using R-squares and mean absolute prediction errors (MAPEs).Patients with MH/SA diagnoses comprised 29.6% of individuals seen in the VA during FY99. The PsyCMS accounted for a distinct proportion of the variance in concurrent and prospective MH/SA costs (R=0.11 and 0.06, respectively), outpatient MH/SA utilization (R=0.25 and 0.07), and inpatient MH/SA utilization (R=0.13 and 0.05). The PsyCMS performed better than other case-mix systems examined with slightly higher R-squares and lower MAPEs.The PsyCMS has clinically meaningful categories, demonstrates good predictive ability for modeling concurrent and prospective MH/SA costs and utilization, and thus represents a useful method for predicting mental health costs and utilization.

To examine how service accessibility measured by geographic distance affects service sector choices for veterans who are dually eligible for veterans affairs (VA) and Medicare services and who are diagnosed with mental health and/or substance abuse (MH/SA) disorders.Primary VA data sources were the Patient Treatment (acute care), Extended Care (long-term care), and Outpatient Clinic files. VA cost data were obtained from (1) inpatient and outpatient cost files developed by the VA Health Economics and Resource Center and (2) outpatient VA Decision Support System files. Medicare data sources were the denominator, Medicare Provider Analysis Review (MEDPAR), Provider-of-Service, Outpatient Standard Analytic and Physician/Supplier Standard Analytic files. Additional sources included the Area Resource File and Census Bureau data.We identified dually eligible veterans who had either an inpatient or outpatient MH/SA diagnosis in the VA system during fiscal year (FY)'99. We then estimated one- and two-part regression models to explain the effects of geographic distance on both VA and Medicare total and MH/SA costs.Results provide evidence for substitution between the VA and Medicare, demonstrating that poorer geographic access to VA inpatient and outpatient clinics decreased VA expenditures but increased Medicare expenditures, while poorer access to Medicare-certified general and psychiatric hospitals decreased Medicare expenditures but increased VA expenditures.As geographic distance to VA medical facility increases, Medicare plays an increasingly important role in providing mental health services to veterans.

Background Providers use risk-adjustment systems to help manage healthcare costs. Typically, ordinary least squares (OLS) models on either untransformed or log-transformed cost are used. We examine the predictive ability of several statistical models, demonstrate how model choice depends on the goal for the predictive model, and examine whether building models on samples of the data affects model choice. Methods Our sample consisted of 525,620 Veterans Health Administration patients with mental health (MH) or substance abuse (SA) diagnoses who incurred costs during fiscal year 1999. We tested two models on a transformation of cost: a Log Normal model and a Square-root Normal model, and three generalized linear models on untransformed cost, defined by distributional assumption and link function: Normal with identity link (OLS); Gamma with log link; and Gamma with square-root link. Risk-adjusters included age, sex, and 12 MH/SA categories. To determine the best model among the entire dataset, predictive ability was evaluated using root mean square error (RMSE), mean absolute prediction error (MAPE), and predictive ratios of predicted to observed cost (PR) among deciles of predicted cost, by comparing point estimates and 95% bias-corrected bootstrap confidence intervals. To study the effect of analyzing a random sample of the population on model choice, we re-computed these statistics using random samples beginning with 5,000 patients and ending with the entire sample. Results The Square-root Normal model had the lowest estimates of the RMSE and MAPE, with bootstrap confidence intervals that were always lower than those for the other models. The Gamma with square-root link was best as measured by the PRs. The choice of best model could vary if smaller samples were used and the Gamma with square-root link model had convergence problems with small samples. Conclusion Models with square-root transformation or link fit the data best. This function (whether used as transformation or as a link) seems to help deal with the high comorbidity of this population by introducing a form of interaction. The Gamma distribution helps with the long tail of the distribution. However, the Normal distribution is suitable if the correct transformation of the outcome is used.

Background Impaired kidney function is an established predictor of mortality after acute nonvariceal upper gastrointestinal bleeding (ANVUGIB); however, which factors are associated with mortality after ANVUGIB among patients undergoing dialysis is unknown. We examined the associations among demographic characteristics, dialysis-specific features, and comorbid conditions with short-term mortality after ANVUGIB among patients on dialysis. Methods Design: Retrospective cohort study. Setting: United States Renal Data System (USRDS), a nation-wide registry of patients with end-stage renal disease. Participants: All ANVUGIB episodes identified by validated algorithms in Medicare-covered patients between 2003 and 2007. Measurements: Demographic characteristics and comorbid conditions from 1 year of billing claims prior to each bleeding event. We used logistic regression extended with generalized estimating equations methods to model the associations among risk factors and 30-day mortality following ANVUGIB events. Results From 2003 to 2007, we identified 40,016 eligible patients with 50,497 episodes of ANVUGIB. Overall 30-day mortality was 10.7% (95% CI: 10.4-11.0). Older age, white race, longer dialysis vintage, peritoneal dialysis (vs. hemodialysis), and hospitalized (vs. outpatient) episodes were independently associated with a higher risk of 30-day mortality. Most but not all comorbid conditions were associated with death after ANVUGIB. The joint ability of all factors captured to discriminate mortality was modest (c=0.68). Conclusions We identified a profile of risk factors for 30-day mortality after ANVUGIB among patients on dialysis that was distinct from what had been reported in non-dialysis populations. Specifically, peritoneal dialysis and more years since initiation of dialysis were independently associated with short-term death after ANVUGIB.