Impact of Proteinuria and Kidney Function Decline on Health Care Costs and Resource Utilization in Adults With IgA Nephropathy in the United States: A Retrospective Analysis.

Rationale & Objective: Among patients with IgA nephropathy (IgAN), proteinuria and decline in kidney function may be associated with increased economic burden. This study aimed to provide current information on the epidemiology and economic burden of IgAN in the United States. Study Design: Retrospective cohort study. Setting & Study Population: Overall, 9,984 patients in the Optum's Market Clarity database identified by the presence of at least 2 natural language processing-derived IgAN signs and disease and symptoms terms; 813 with linked claims data included in a health care resource utilization/cost subcohort. Predictor: High-risk proteinuria (≥1 g/d), chronic kidney disease (CKD) stage. Outcomes: Standardized prevalence, health care resource utilization, costs. Analytical Approach: Descriptive statistics for categorical and continuous variables. Direct standardization for prevalence estimation. Generalized linear models for health care resource utilization/costs, reported as per-patient-per-month (PPPM) costs in 2020 US dollars. Results: The estimated standardized US prevalence of IgAN (2016-2020) was 329.0 per 1,000,000 persons. High-risk proteinuria (≥1 vs <1 g/d) was associated with a higher mean PPPM number of outpatient visits (3.49 vs 1.74; P = 0.01) and pharmacy claims (3.79 vs 2.41; P = 0.01), contributing to higher mean total costs PPPM ($3,732 vs $1,457; P = 0.01). Furthermore, higher CKD stage was also associated with higher health care resource utilization (number of outpatient visits PPPM, number of pharmacy claims PPPM, proportion of patients with inpatient visits and emergency department visits; P < 0.001) and mean total cost PPPM (from $2,111 CKD stage 1 to $10,703 CKD stage 5/kidney failure; P < 0.001). Limitations: Generalizability outside of the catchment group for the database, missing data/errors inherent in retrospective database studies, relatively small sample size, use of Optum Market Clarity standardized pricing algorithms, exclusion of out-of-pocket costs. Conclusions: Health care resource utilization and costs were higher for IgAN patients with high-risk proteinuria and worsening kidney function. Treatments that reduce proteinuria and slow CKD disease progression may reduce the economic burden associated with IgAN. Plain-Language Summary: Immunoglobulin A nephropathy (IgAN) is a rare kidney disease. Over time, the kidneys may leak protein into the urine (proteinuria). IgAN can lead to kidney failure. Because IgAN is rare, it is hard to know how many people have it. This study used electronic health records to estimate the number of patients with IgAN in the United States, describe the characteristics of patients, and understand their treatments and the costs. The number of patients with IgAN increased between 2016 and 2020. The researchers think this is because doctors learned more about IgAN. Patients with severe disease used more health care resources and had higher costs. The authors believe treatments that slow kidney damage may reduce the cost of treating IgAN.

Effectiveness of a multistate quality improvement campaign in reducing risk of surgical site infections following hip and knee arthroplasty.

BACKGROUND: Quality improvement (QI) campaigns appear to increase use of evidence-based practices, but their effect on health outcomes is less well studied. OBJECTIVE: To assess the effect of a multistate QI campaign (Project JOINTS, Joining Organizations IN Tackling SSIs) that used the Institute for Healthcare Improvement's Rapid Spread Network to promote adoption of evidence-based surgical site infection (SSI) prevention practices. METHODS: We analysed rates of SSI among Medicare beneficiaries undergoing hip and knee arthroplasty during preintervention (May 2010 to April 2011) and postintervention (November 2011 to September 2013) periods in five states included in a multistate trial of the Project JOINTS campaign and five matched comparison states. We used generalised linear mixed effects models and a difference-in-differences approach to estimate changes in SSI outcomes. RESULTS: 125 070 patients underwent hip arthroplasty in 405 hospitals in intervention states, compared with 131 787 in 525 hospitals in comparison states. 170 663 patients underwent knee arthroplasty in 397 hospitals in intervention states, compared with 196 064 in 518 hospitals in comparison states. After the campaign, patients in intervention states had a 15% lower odds of developing hip arthroplasty SSIs (OR=0.85, 95% CI 0.75 to 0.96, p=0.01) and a 12% lower odds of knee arthroplasty SSIs than patients in comparison states (OR=0.88, 95% CI 0.78 to 0.99, p=0.04). CONCLUSIONS: A larger reduction of SSI rates following hip and knee arthroplasty was shown in intervention states than in matched control states.

Surgical Site Infections: Volume-Outcome Relationship and Year-to-Year Stability of Performance Rankings.

BACKGROUND: Surgical site infection (SSI) rates are publicly reported as quality metrics and increasingly used to determine financial reimbursement. OBJECTIVE: To evaluate the volume-outcome relationship as well as the year-to-year stability of performance rankings following coronary artery bypass graft (CABG) surgery and hip arthroplasty. RESEARCH DESIGN: We performed a retrospective cohort study of Medicare beneficiaries who underwent CABG surgery or hip arthroplasty at US hospitals from 2005 to 2011, with outcomes analyzed through March 2012. Nationally validated claims-based surveillance methods were used to assess for SSI within 90 days of surgery. The relationship between procedure volume and SSI rate was assessed using logistic regression and generalized additive modeling. Year-to-year stability of SSI rates was evaluated using logistic regression to assess hospitals' movement in and out of performance rankings linked to financial penalties. RESULTS: Case-mix adjusted SSI risk based on claims was highest in hospitals performing <50 CABG/year and <200 hip arthroplasty/year compared with hospitals performing ≥200 procedures/year. At that same time, hospitals in the worst quartile in a given year based on claims had a low probability of remaining in that quartile the following year. This probability increased with volume, and when using 2 years' experience, but the highest probabilities were only 0.59 for CABG (95% confidence interval, 0.52-0.66) and 0.48 for hip arthroplasty (95% confidence interval, 0.42-0.55). CONCLUSIONS: Aggregate SSI risk is highest in hospitals with low annual procedure volumes, yet these hospitals are currently excluded from quality reporting. Even for higher volume hospitals, year-to-year random variation makes past experience an unreliable estimator of current performance.

Objective Sepsis Surveillance Using Electronic Clinical Data.

OBJECTIVE: To compare the accuracy of surveillance of severe sepsis using electronic health record clinical data vs claims and to compare incidence and mortality trends using both methods. DESIGN: We created an electronic health record-based surveillance definition for severe sepsis using clinical indicators of infection (blood culture and antibiotic orders) and concurrent organ dysfunction (vasopressors, mechanical ventilation, and/or abnormal laboratory values). We reviewed 1,000 randomly selected medical charts to characterize the definition's accuracy and stability over time compared with a claims-based definition requiring infection and organ dysfunction codes. We compared incidence and mortality trends from 2003-2012 using both methods. SETTING: Two US academic hospitals. PATIENTS: Adult inpatients. RESULTS: The electronic health record-based clinical surveillance definition had stable and high sensitivity over time (77% in 2003-2009 vs 80% in 2012, P=.58) whereas the sensitivity of claims increased (52% in 2003-2009 vs 67% in 2012, P=.02). Positive predictive values for claims and clinical surveillance definitions were comparable (55% vs 53%, P=.65) and stable over time. From 2003 to 2012, severe sepsis incidence imputed from claims rose by 72% (95% CI, 57%-88%) and absolute mortality declined by 5.4% (95% CI, 4.6%-6.7%). In contrast, incidence using the clinical surveillance definition increased by 7.7% (95% CI, -1.1% to 17%) and mortality declined by 1.7% (95% CI, 1.1%-2.3%). CONCLUSIONS: Sepsis surveillance using clinical data is more sensitive and more stable over time compared with claims and can be done electronically. This may enable more reliable estimates of sepsis burden and trends.

The utility of claims data for infection surveillance following anterior cruciate ligament reconstruction.

OBJECTIVE: To explore the feasibility of identifying anterior cruciate ligament (ACL) allograft implantations and infections using claims. DESIGN: Retrospective cohort study. METHODS: We identified ACL reconstructions using procedure codes at 6 health plans from 2000 to 2008. We then identified potential infections using claims-based indicators of infection, including diagnoses, procedures, antibiotic dispensings, specialty consultations, emergency department visits, and hospitalizations. Patients' medical records were reviewed to determine graft type, validate infection status, and calculate sensitivity and positive predictive value (PPV) for indicators of ACL allografts and infections. RESULTS: A total of 11,778 patients with codes for ACL reconstruction were identified. After chart review, PPV for ACL reconstruction was 96% (95% confidence interval [CI], 94%-97%). Of the confirmed ACL reconstructions, 39% (95% CI, 35%-42%) used allograft tissues. The deep infection rate after ACL reconstruction was 1.0% (95% CI, 0.7%-1.4%). The odds ratio of infection for allografts versus autografts was 0.41 (95% CI, 0.19-0.78). Sensitivity of individual claims-based indicators for deep infection after ACL reconstruction ranged from 0% to 75% and PPV from 0% to 100%. Claims-based infection indicators could be combined to enhance sensitivity or PPV but not both. CONCLUSIONS: While claims data accurately identify ACL reconstructions, they poorly distinguish between allografts and autografts and identify infections with variable accuracy. Claims data could be useful to monitor infection trends after ACL reconstruction, with different algorithms optimized for different surveillance goals.