Claims-based Index Research Articles

Association of CHA2DS2-VASc and HAS-BLED to frailty and frail outcomes: From the TREAT-AF study

Morbidity and mortality associated with high CHA2DS2-VASc and HAS-BLED scores is not specific to atrial fibrillation (AF). Frailty could be an important contributor to this morbidity and mortality while being mechanistically independent from AF. We sought to evaluate the association of stroke and bleeding risk to noncardiovascular frail events and the association of stroke prevention therapy to outcomes in frail patients with AF. Using the TREAT-AF (The Retrospective Evaluation and Assessment of Therapies in AF) study from the Veterans Health Administration, we identified patients with newly diagnosed AF from 2004 to 2014. Baseline frailty was identified using a previously validated claims-based index requiring ≥2 of 12 ICD-9 diagnoses. Logistic regressions modeled the association between CHA2DS2-VASc and modified HAS-BLED and frailty. Cox proportional hazard regressions were used to evaluate the association between CHA2DS2-VASc and modified HAS-BLED and a composite of noncardiovascular frail events (fractures, urinary tract infections, bacterial pneumonia, or dehydration). We also evaluated the association of oral anticoagulant (OAC) use with stroke, bleeding, and 1-year mortality in frail patients and non-frail patients. In 213,435 patients (age 70 ± 11; 98% male; CHA2DS2-VASc 2.4 ± 1.7) with AF, 8,498 (4%) were frail. CHA2DS2-VASc > 0 and HAS-BLED > 0 were strongly associated with frailty (odds ratio [OR] 13.3 (95% CI: 11.6-15.2) for CHA2DS2-VASc 4+ and OR 13.4 (10.2-17.5) for HAS-BLED 3+). After adjusting for covariates, CHA2DS2-VASc, and HAS-BLED > 0 were associated with higher risk of non-cardiovascular frail events (hazard ratio [HR] 2.1 (95% CI: 2.0-2.2) for CHA2DS2-VASc 4+ and HR 1.4 (95% CI: 1.3-1.5) for HAS-BLED 3+). In frail patients, OAC use was associated with significantly lower risk of 1-year mortality (HR 0.82; 95% CI 0.72-0.94, P=.0031) but did not reach significance for risk of stroke (HR 0.80; 95% CI 0.55-1.18, P=.26) or major bleeding (HR 1.08; 95% CI 0.93-1.25, P=.34). High CHA2DS2-VASc and HAS-BLED scores are strongly associated with frailty. However, in frail patients, OAC use was associated with reduction in 1-year mortality. For this challenging clinical population with competing risks of frailty and frail events, focused prospective studies are needed to support clinical decision-making. Until then, careful evaluation of frailty should inform shared decision-making.

Annals for Hospitalists - September 2021.

Annals for Hospitalists - September 2021.

Patient Characteristics and Indicators of Treatment Initiation with Repository Corticotropin Injection in Patients with Rheumatoid Arthritis: A Claims Database Analysis.

Repository corticotropin injection (RCI) is indicated as adjunctive, short-term therapy in selected patients with RA. To characterize RCI users and identify predictors of RCI initiation in RA, we compared preindex characteristics, treatment patterns, comorbidities, healthcare resource utilization (HCRU), and costs for patients who had initiated RCI treatment (RCI cohort) versus patients with no RCI claims and ≥ 1 targeted synthetic or biologic disease-modifying antirheumatic drugs (ts/bDMARD) claim (non-RCI ts/bDMARD cohort). We analyzed pharmacy and medical claims data from a large commercial and Medicare supplemental administrative database. Inclusion criteria were age ≥ 18 years, ≥ 1 inpatient or ≥ 2 outpatient claims with RA diagnosis (January 1, 2007–December 31, 2018), and 12-month continuous medical and pharmacy coverage preindex. Results from baseline cohort comparisons informed multiple logistic regression analysis. Compared with the non-RCI ts/bDMARD cohort (n = 162,065), the RCI cohort (n = 350) had a greater proportion of patients with higher Charlson comorbidity index (CCI) scores; higher mean claims-based index of RA severity and CCI scores; greater frequency of almost all comorbidities; higher use of nontraditional DMARDs, glucocorticoids, and opioids; higher all-cause HCRU; and higher medical and total costs. By multivariable analysis, the most significant predictors of RCI initiation were intermittent glucocorticoid use at any dose (odds ratio [OR] 1.67), extended-use glucocorticoids at medium (OR 2.03) and high doses (OR 2.99), nontraditional DMARD use (OR 2.09), anemia (OR 1.39), and renal disease (OR 2.45). Before RCI initiation, patients had more severe RA, higher comorbidity burden, greater use of glucocorticoids and opioids, and higher HCRU compared with non-RCI initiators. The most significant predictors for starting RCI in patients with RA were intermittent use of glucocorticoids at any dose, extended-use high-dose glucocorticoids, use of nontraditional DMARDs, and comorbid anemia and renal disease.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40744-020-00272-x.

Relationship of a Claims-Based Frailty Index to Annualized Medicare Costs: A Cohort Study.

Medicare uses the Centers for Medicare & Medicaid Services Hierarchical Condition Category (CMS-HCC) model to predict patients' annualized Medicare costs in value-based payment programs. The CMS-HCC model does not include measures of frailty, and prior research shows that it systematically underpredicts costs for frail Medicare beneficiaries. To determine whether a claims-based frailty index can improve Medicare cost prediction. Retrospective cohort study. Medicare Current Beneficiary Survey linked to Medicare claims, 2006 to 2013. 16535 community-dwelling, fee-for-service beneficiaries representing 26705 patient-years. Patient frailty status was classified using a validated claims-based frailty index. The association between the frailty index and annualized Medicare costs was examined, and regression methods were used to compare observed Medicare costs versus predictions based on the standard CMS-HCC model with and without the frailty index. Mean costs were $5724 for the 8910 patients classified as robust (46.4% of patient-years), $12462 for the 8405 prefrail patients (41.6%), $26239 for the 2215 mildly frail patients (9.6%), and $44586 for the 593 patients classified as moderately to severely frail (2.5%). The frailty index addition to the CMS-HCC model predicted on average an additional $2712, $7915, and $16449 in costs for prefrail, mildly frail, and moderately to severely frail patients, respectively, beyond the CMS-HCC model alone. On average, the model with the frailty index addition resulted in more accurate predictions of costs for patients at all 4 levels of frailty. However, observed costs remained more widely distributed than predictions from the enhanced model at all levels of frailty. The claims-based index is a proxy for frailty and is likely less accurate than an in-person examination. The CMS-HCC model with the frailty index addition is an improvement over current Medicare cost prediction. None.

Health Care Effect of Disease-Modifying Antirheumatic Drug Use on Patients with Rheumatoid Arthritis.

Disease-modifying antirheumatic drugs (DMARDs) are recommended as the standard of care for patients with rheumatoid arthritis (RA) due to their ability to reduce pain and disability; however, DMARD use is low in some subgroups of the RA population. To identify characteristics associated with DMARD use in the overall cohort of patients with RA and newly diagnosed RA patients. This retrospective observational study used claims from a large national health plan. Use of DMARDs was measured according to the Healthcare Effectiveness Data and Information Set (HEDIS) as the proportion of patients with RA receiving DMARDs. Following HEDIS measure technical specifications, we identified patients aged 18-89 years with continuous enrollment during 2014 (measurement year) with ≥ 2 claims for RA outpatient visits and/or discharges on different dates between January and November 2014. Additionally, we identified a subset of patients newly diagnosed with RA in 2014 based on absence of any claims for RA or DMARDs in 2013. Descriptive analyses and bivariate associations were used to compare demographic and clinical characteristics of patients with RA with or without DMARD use in 2014. Health care resource utilization (HCRU) and costs were compared in 2014 for patients enrolled in Medicare Advantage Prescription Drug (MAPD) plans during both 2014 and 2015. Regression models were used to evaluate patient and provider characteristics associated with DMARD use in 2014 and the effect on HCRU and costs. Among the 33,880 patients identified with RA in 2014, most patients received a DMARD (75.2%); 29.4% of patients newly diagnosed with RA had been treated with DMARDs in 2014. Patients with DMARD use, on average, were younger (aged 67 years ± 10.7 vs. 69 years ± 10.7) and healthier (Deyo-Charlson Comorbidity Index [DCCI] 2.4 ± 1.9 vs. 2.6 ± 2.1) and included a greater proportion of women (75.9% vs. 71.0%) than those with no DMARD use (P < 0.0001). Use of DMARDs (P < 0.0001) was associated with 14.5% fewer hospitalizations and 18.0% fewer emergency department visits. Although total costs increased by 15.0% with use of DMARDs, when the cost of DMARDs was excluded, the total cost decreased by 13.7% (P < 0.0001). Female gender (32.2%), higher claims-based index for RA severity score (47.0%), higher RxRisk-V score (26.7%), visit to a rheumatologist (34.3%), and use of glucocorticoids (17.7%) increased the odds of DMARD use (P < 0.0001). Use of certain classes of medication, such as nonsteroidal anti-inflammatory drugs (12.3%), opioids (19.5%), antidepressants (20.0%), muscle relaxants (12.5%), and anticonvulsants (15.5%), were associated with lower use of DMARDs (P < 0.0001). We found significant differences in demographic and clinical characteristics between patients with and without DMARD use, which can potentially inform treatment decisions regarding DMARD use as deemed necessary by the provider. Future research should investigate the reasons for lack of treatment. This study was supported by funding from Eli Lilly to Humana as a collaborative research project involving employees of both companies. Boytsov, Saverno, Zhang, and Gaich are employees of Eli Lilly. Nair, Bhattacharya, Abbott, and Dixon are employees of Humana, which received funding from Eli Lilly to complete this research.

Severity indices in rheumatoid arthritis: A systematic review.

To identify tools designed to evaluate the severity of patients with rheumatoid arthritis (RA) in order to use them in the investigation of prognostic markers in early arthritis. We conducted a systematic review of studies that developed/validated an index for RA disease severity. They were analyzed using the COSMIN checklist to assess their methodological quality. In addition, all the variables included were evaluated for their clarity of definition, feasibility and probability of being present in each outcome during the first 2 years of the disease course. To estimate redundancy, variables were grouped by domains. After reviewing 3,519 articles, 3 studies were included. The first study, the PAS, assessed whether current and lifetime treatment with disease-modifying antirheumatic drugs and/or biologics accurately predicted RA severity, as measured by the patient-reported PAS. Treatment variables did not fully distinguish patients in the highest and lowest quartiles of PAS scores. Another severity index, the Claims-Based Index for RA Severity (CIRAS), included the variables age, sex, Felty's syndrome, number of rehabilitation and rheumatology visits, test for inflammatory markers, number of chemistry panels/platelet counts ordered and rheumatoid factor test. The correlation was low (r=0.56) with an index previously validated by the same research group, the RA medical records-based index of severity (RARBIS), with Disease Activity Score-C-reactive protein (DAS28-PCR) (r=0.07) and Multidimensional Health Assessment Questionnaire (MD-HAQ) (r=0.008). Finally, the RARBIS, used to validate the CIRAS, was devised as an RA severity index based on medical records. It includes as domains surgery, radiology, extra-articular manifestations, clinical and laboratory variables, previously chosen by an expert panel. RARBIS had a weak correlation with treatment intensity (r=0.35) and with DAS28 (r=0.41). There is no index to assess the severity of RA based on the course of the first 2 years of follow-up that is adapted to the current strategy of therapeutic management of this disease. Therefore, we believe it is reasonable to develop a new ad hoc severity index for patients with early arthritis.

Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare

BackgroundThere is systemic undercoding of medical comorbidities within administrative claims in the Department of Veterans Affairs (VA). This leads to bias when applying claims-based risk adjustment indices to compare outcomes between VA and non-VA settings. Our objective was to compare the accuracy of a medication-based risk adjustment index (RxRisk-VM) to diagnostic claims-based indices for predicting mortality. MethodsWe modified the RxRisk-V index (RxRisk-VM) by incorporating VA and Medicare pharmacy and durable medical equipment claims in Veterans dually-enrolled in VA and Medicare in 2012. Using the concordance (C) statistic, we compared its accuracy in predicting 1 and 3-year all-cause mortality to the following models: demographics only, demographics plus prescription count, or demographics plus a diagnostic claims-based risk index (e.g., Charlson, Elixhauser, or Gagne). We also compared models containing demographics, RxRisk-VM, and a claims-based index. ResultsIn our cohort of 271,184 dually-enrolled Veterans (mean age = 70.5 years, 96.1% male, 81.7% non-Hispanic white), RxRisk-VM (C = 0.773) exhibited greater accuracy in predicting 1-year mortality than demographics only (C = 0.716) or prescription counts (C = 0.744), but was less accurate than the Charlson (C = 0.794), Elixhauser (C = 0.80), or Gagne (C = 0.810) indices (all P < 0.001). Combining RxRisk-VM with claims-based indices enhanced its accuracy over each index alone (all models C ≥ 0.81). Relative model performance was similar for 3-year mortality. ConclusionsThe RxRisk-VM index exhibited a high level of, but slightly less, accuracy in predicting mortality in comparison to claims-based risk indices. ImplicationsIts application may enhance the accuracy of studies examining VA and non-VA care and enable risk adjustment when diagnostic claims are not available or biased. Level of evidenceLevel 3.

Validation of the JEN frailty index in the National Long-Term Care Survey community population: identifying functionally impaired older adults from claims data

BackgroundUse of a claims-based index to identify persons with physical function impairment and at risk for long-term institutionalization would facilitate population health and comparative effectiveness research. The JEN Frailty Index [JFI] is comprised of diagnosis domains representing impairments and multimorbid clusters with high long-term institutionalization [LTI] risk. We test the index’s discrimination of activities-of-daily-living [ADL] dependency and 1-year LTI and mortality in a nationally representative sample of over 12,000 Medicare beneficiaries, and compare long-term community survival stratified by ADL and JFI.Methods2004 U.S. National Long-Term Care Survey data were linked to Medicare, Minimum Data Set, Veterans Health Administration files and vital statistics. ADL dependencies, JFI score, age and sex were measured at baseline survey. ADL and JFI groups were cross-tabulated generating likelihood ratios and classification statistics. Logistic regression compared discrimination (areas under receiver operating characteristic curves), multivariable calibration and accuracy of the JFI and, separately, ADLs, in predicting 1-year outcomes. Hall-Wellner bands facilitated contrasts of JFI- and ADL-stratified 5-year community survival.ResultsLikelihood ratios rose evenly across JFI risk categories. Areas under the curves of functional dependency at ≥3 and ≥ 2 for JFI, age and sex models were 0.807 [95% c.i.: 0.795, 0.819] and 0.812 [0.801, 0.822], respectively. The area under the LTI curve for JFI and age (0.781 [0.747, 0.815]) discriminated less well than the ADL-based model (0.829 [0.799, 0.860]). Community survival separated by JFI strata was comparable to ADL strata.ConclusionsThe JEN Frailty Index with demographic covariates is a valid claims-based measure of concurrent activities-of-daily-living impairments and future long-term institutionalization risk in older populations lacking functional information.

Severity Indices in Rheumatoid Arthritis: A Systematic Review

ObjectiveTo identify tools designed to evaluate the severity of patients with rheumatoid arthritis (RA) in order to use them in the investigation of prognostic markers in early arthritis. MethodsWe conducted a systematic review of studies that developed/validated an index for RA disease severity. They were analysed using the COSMIN checklist to assess their methodological quality. In addition, all the variables included were evaluated for their clarity of definition, feasibility and probability of being present in each outcome during the first 2 years of the disease course. To estimate redundancy, variables were grouped by domains. ResultsAfter reviewing 3519 articles, 3 studies were included. The first study, the PAS, assessed whether current and lifetime treatment with disease-modifying antirheumatic drugs and/or biologics accurately predicted RA severity, as measured by the patient-reported PAS. Treatment variables did not fully distinguish patients in the highest and lowest quartiles of PAS scores. Another severity index, the Claims-Based Index for RA Severity (CIRAS), included the variables age, sex, Felty's syndrome, number of rehabilitation and rheumatology visits, test for inflammatory markers, number of chemistry panels/platelet counts ordered and rheumatoid factor test. The correlation was low (r=0.56) with an index previously validated by the same research group, the RA medical records-based index of severity (RARBIS), with Disease Activity Score-C-reactive protein (DAS28-PCR) (r=0.07) and Multidimensional Health Assessment Questionnaire (MD-HAQ) (r=0.008). Finally, the RARBIS, used to validate the CIRAS, was devised as an RA severity index based on medical records. It includes as domains surgery, radiology, extra-articular manifestations, clinical and laboratory variables, previously chosen by an expert panel. RARBIS had a weak correlation with treatment intensity (r=0.35) and with DAS28 (r=0.41). ConclusionThere is no index to assess the severity of RA based on the course of the first 2 years of follow-up that is adapted to the current strategy of therapeutic management of this disease. Therefore, we believe it is reasonable to develop a new ad hoc severity index for patients with early arthritis.

Registry-based stroke research in Taiwan: past and future.

Stroke registries are observational databases focusing on the clinical information and outcomes of stroke patients. They play an important role in the cycle of quality improvement. Registry data are collected from real-world experiences of stroke care and are suitable for measuring quality of care. By exposing inadequacies in performance measures of stroke care, research from stroke registries has changed how we manage stroke patients in Taiwan. With the success of various quality improvement campaigns, mortality from stroke and recurrence of stroke have decreased in the past decade. After the implementation of a nationwide stroke registry, researchers have been creatively expanding how they use and collect registry data for research. Through the use of the nationwide stroke registry as a common data model, researchers from many hospitals have built their own stroke registries with extended data elements to meet the needs of research. In collaboration with information technology professionals, stroke registry systems have changed from web-based, manual submission systems to automated fill-in systems in some hospitals. Furthermore, record linkage between stroke registries and administrative claims databases or other existing databases has widened the utility of registry data in research. Using stroke registry data as the reference standard, researchers have validated several algorithms for ascertaining the diagnosis of stroke and its risk factors from claims data, and have also developed a claims-based index to estimate stroke severity. By making better use of registry data, we believe that we will provide better care to patients with stroke.

Economic Burden and Treatment Patterns of Cycling between Conventional Synthetic Disease-modifying Antirheumatic Drugs Among Biologic-treated Patients with Rheumatoid Arthritis

PurposeTo assess the economic outcomes and treatment patterns among patients with rheumatoid arthritis (RA) who used 1, 2, or 3 or more conventional synthetic disease-modifying antirheumatic drugs (DMARDs) before receiving a biologic therapy. MethodsAdult patients with ≥2 RA diagnoses (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 714.xx) on different dates, ≥1 claim for a conventional synthetic DMARD, and ≥1 claim for a biologic DMARD were identified from a large commercial claims database. The initiation date of the first biologic DMARD was defined as the index date. Based on the number of distinct conventional synthetic DMARDs initiated between the first RA diagnosis and the index date, patients were classified into 3 cohorts: those who used 1, 2, or 3 or more conventional synthetic DMARDs. Baseline characteristics were measured 6 months preindex date and compared between the 3 cohorts. All-cause health care costs (in 2014 US$) were compared during the follow-up period (12 months postbiologic initiation) using multivariable gamma models adjusting for baseline characteristics. Time to discontinuation of the index biologic DMARD and time to switching to a new DMARD were compared using multivariable Cox proportional hazards models. FindingsThe 1, 2, and 3 or more conventional synthetic DMARD cohorts included 6215; 3227; and 976 patients, respectively. At baseline, patients in the 3 or more conventional synthetic DMARD cohort had the least severe RA, as indicated by the lowest claims-based index for RA severity score (1 vs 2 vs 3 or more = 6.1 vs 5.9 vs 5.8). During the study period, there was a significant association between number of conventional synthetic DMARDs and higher all-cause total health care costs (adjusted mean difference, 1 vs 2: $772; P < 0.001; 2 vs 3 or more: $2390; P < 0.001). The all-cause medical and pharmacy costs were also significantly higher with the increasing number of conventional synthetic DMARDs. Patients who cycled more conventional synthetic DMARDs were also more likely to switch treatment after biologic initiation (1 vs 2: adjusted hazard ratio = 0.89; P = 0.005; 2 vs 3 or more: adjusted hazard ratio = 0.89; P = 0.087). There were no differences in index biologic discontinuation between the 3 cohorts. ImplicationsPatients with RA who cycled more conventional synthetic DMARDs had increased economic burden in the 12 months following biologic initiation and were more likely to switch therapy. These results highlight the importance of timely switching to biologic DMARDs for the treatment of RA.

An external validation study reporting poor correlation between the claims-based index for rheumatoid arthritis severity and the disease activity score.

IntroductionWe conducted an external validation study to examine the correlation of a previously published claims-based index for rheumatoid arthritis severity (CIRAS) with disease activity score in 28 joints calculated by using C-reactive protein (DAS28-CRP) and the multi-dimensional health assessment questionnaire (MD-HAQ) physical function score.MethodsPatients enrolled in the Brigham and Women’s Hospital Rheumatoid Arthritis Sequential Study (BRASS) and Medicare were identified and their data from these two sources were linked. For each patient, DAS28-CRP measurement and MD-HAQ physical function scores were extracted from BRASS, and CIRAS was calculated from Medicare claims for the period of 365 days prior to the DAS28-CRP measurement. Pearson correlation coefficient between CIRAS and DAS28-CRP as well as MD-HAQ physical function scores were calculated. Furthermore, we considered several additional pharmacy and medical claims-derived variables as predictors for DAS28-CRP in a multivariable linear regression model in order to assess improvement in the performance of the original CIRAS algorithm.ResultsIn total, 315 patients with enrollment in both BRASS and Medicare were included in this study. The majority (81%) of the cohort was female, and the mean age was 70 years. The correlation between CIRAS and DAS28-CRP was low (Pearson correlation coefficient = 0.07, P = 0.24). The correlation between the calculated CIRAS and MD-HAQ physical function scores was also found to be low (Pearson correlation coefficient = 0.08, P = 0.17). The linear regression model containing additional claims-derived variables yielded model R2 of 0.23, suggesting limited ability of this model to explain variation in DAS28-CRP.ConclusionsIn a cohort of Medicare-enrolled patients with established RA, CIRAS showed low correlation with DAS28-CRP as well as MD-HAQ physical function scores. Claims-based algorithms for disease activity should be rigorously tested in distinct populations in order to establish their generalizability before widespread adoption.

Comparing a medical records-based and a claims-based index for measuring comorbidity in patients with lung or colon cancer.

Ascertaining comorbid conditions in cancer patients is important for research and clinical quality measurement, and is particularly important for understanding care and outcomes for older patients and those with multi-morbidity. We compared the medical records-based ACE-27 index and the claims-based Charlson index in predicting receipt of therapy and survival for lung and colon cancer patients. We calculated the Charlson index using administrative data and the ACE-27 score using medical records for Veterans Affairs patients diagnosed with stage I/II non-small cell lung or stage III colon cancer from January 2003 to December 2004. We compared the proportion of patients identified by each index as having any comorbidity. We used multivariable logistic regression to ascertain the predictive power of each index regarding delivery of guideline-recommended therapies and two-year survival, comparing the c-statistic and the Akaike information criterion (AIC). Overall, 97.2% of lung and 90.9% of colon cancer patients had any comorbidity according to the ACE-27 index, versus 59.5% and 49.7%, respectively, according to the Charlson. Multivariable models including the ACE-27 index outperformed Charlson-based models when assessing receipt of guideline-recommended therapies, with higher c-statistics and lower AICs. Neither index was clearly superior in prediction of two-year survival. The ACE-27 index measured using medical records captured more comorbidity and outperformed the Charlson index measured using administrative data for predicting receipt of guideline-recommended therapies, demonstrating the potential value of more detailed comorbidity data. However, the two indices had relatively similar performance when predicting survival.

The role of rheumatoid arthritis (RA) flare and cumulative burden of RA severity in the risk of cardiovascular disease

ObjectiveTo examine the role of rheumatoid arthritis (RA) flare, remission and RA severity burden in cardiovascular disease (CVD).MethodsIn a population-based cohort of patients with RA without CVD (age ≥30 years;...

SAT0138 Cumulative Burden of Rheumatoid Arthritis Disease Severity Impacts Cardiovascular Disease Risk

BackgroundRheumatoid arthritis (RA) disease severity is linked to unfavorable cardiovascular disease (CVD) outcomes. Cumulative measures of RA disease burden on CVD have not been well-studied and could be used to...

Derivation of severity index for rheumatoid arthritis and its association with healthcare outcomes

Objectives:To develop a claims-based severity index for rheumatoid arthritis (RA) using the Veterans Health Administration (VHA) database.Methods:Adult patients with at least two RA diagnoses 2 months apart were identified between 10/1/2008–09/30/2009. Patients were required to have at least 12 months continuous health plan enrollment before and after the index date (first RA diagnosis date) for an overall study period of 10/1/2007–09/30/2010. A severity index for rheumatoid arthritis (SIFRA, a proprietary algorithm of SIMR, Inc. [STATinMED Research]) was developed by calculating a weighted sum of 34 RA-related indicators assessed by an expert Delphi panel of six rheumatologists, including laboratory, clinical, and functional status, extra-articular manifestations, surgical history, and medications, during a 1-year pre-index period. Separate SIFRA versions were derived for patients with and without laboratory information. Correlations between SIFRA and previously validated claims-based indexes for RA severity (CIRAS), and other traditional comorbidity indexes were calculated during the pre-index period. The relationship between SIFRA and follow-up healthcare outcomes was also examined using histograms.Results:The Spearman’s rank correlations between SIFRA and CIRAS were 0.525 for SIFRA without and 0.539 with laboratory data. The correlations between SIFRA and the Charlson Comorbidity Index (CCI) (0.1503 without, 0.1135 with laboratory data), Elixhauser Index (ELIX) (0.105 without, 0.079 with laboratory data), and Chronic Disease Score (CDS) (0.255 without, 0.239 with laboratory data) were low. Histograms showed that patients in the upper tercile of SIFRA incurred $9123 more all-cause and $1326 more RA-related healthcare costs during the 1-year post-index period than patients in the lower tercile. Using SIFRA in combination with CCI, CDS, or ELIX significantly increased the percentage of variation explained in outcomes measures.Limitations:Patients in the VHA database may not represent typical RA patients since the database generally contains older, economically disadvantaged men with a high disease burden. Validity of the score is indirectly based on disease activity score 28 (DAS28), which measures disease activity rather than severity.Conclusions:SIFRA was found to have moderate correlations with the previously validated CIRAS score, and demonstrated evidence of being a significant determinant of total and RA-related healthcare costs for RA patients. This study suggests that SIFRA could be an important methodological tool to control for severity in RA-related outcomes research. The algorithm can be applied to any claims dataset.

Rheumatoid Arthritis Disease Severity Indices in Administrative Databases: A Systematic Review

We aimed to systematically review rheumatoid arthritis (RA) disease severity indices for use in administrative healthcare databases. We also provide an overview of alternative methods to control for RA disease severity in administrative database research. We conducted a systematic review of studies that developed/validated an index for RA disease severity using variables in administrative databases, and compared the convergent validity/reliability of the index with a standard measure of RA severity. After reviewing 539 articles, 2 studies were included. The claims-based index for RA severity (CIRAS) was developed in one study. Components of the CIRAS included tests for inflammatory markers, number of chemistry panels/platelet counts ordered, rheumatoid factor test, number of rehabilitation and rheumatology visits, and Felty's syndrome. The CIRAS correlated moderately well with a previously validated RA medical records-based index of severity. The second study assessed whether current and lifetime treatment with disease-modifying antirheumatic drugs and/or biologics accurately predicted RA severity, as measured by the patient-reported Patient Activity Scale (PAS). Treatment variables did not fully distinguish patients in the highest and lowest quartiles of PAS scores (67.2% correctly classified). Two claims-based indices of RA severity were identified but have some limitations for routine use. A concerted effort from experts in the field is needed to define, develop, and validate a widely applicable measure of RA disease severity for administrative database research.

Development of a health care utilisation data-based index for rheumatoid arthritis severity: a preliminary study

IntroductionHealth care utilisation ('claims') databases contain information about millions of patients and are an important source of information for a variety of study types. However, they typically do not contain information about disease severity. The goal of the present study was to develop a health care claims index for rheumatoid arthritis (RA) severity using a previously developed medical records-based index for RA severity (RA medical records-based index of severity [RARBIS]).MethodsThe study population consisted of 120 patients from the Veteran's Administration (VA) Health System. We previously demonstrated the construct validity of the RARBIS and established its convergent validity with the Disease Activity Score (DAS28). Potential claims-based indicators were entered into a linear regression model as independent variables and the RARBIS as the dependent variable. The claims-based index for RA severity (CIRAS) was created using the coefficients from models with the highest coefficient of determination (R2) values selected by automated modelling procedures. To compare our claims-based index with our medical records-based index, we examined the correlation between the CIRAS and the RARBIS using Spearman non-parametric tests.ResultsThe forward selection models yielded the highest model R2 for both the RARBIS with medications (R2 = 0.31) and the RARBIS without medications (R2 = 0.26). Components of the CIRAS included tests for inflammatory markers, number of chemistry panels and platelet counts ordered, rheumatoid factor, the number of rehabilitation and rheumatology visits, and Felty's syndrome diagnosis. The CIRAS demonstrated moderate correlations with the RARBIS with medication and the RARBIS without medication sub-scales.ConclusionWe developed the CIRAS that showed moderate correlations with a previously validated records-based index of severity. The CIRAS may serve as a potentially important tool in adjusting for RA severity in pharmacoepidemiology studies of RA treatment and complications using health care utilisation data.

Risk adjustment in claims-based research: The search for efficient approaches

Claims-based indices of comorbidity and severity, as well as other measures derived from routinely collected administrative data, are developed and tested. The extent to which risk adjustments using claims can be improved-by adding information from one well-known measure based on chart review and patient examination (the American Society of Anesthesiologists' (ASA) Physical Status score) is also examined. Readmissions and mortality after three common surgical procedures are the outcomes studied using multiple logistic regression. Claims-based measures of comorbidity, derived both from-hospital discharge abstracts at the time of surgery and from hospitalizations in the 6 months before surgery, provided reasonably good predictions of postsurgical readmissions and mortality. In the most complete logistic regression models, the Somers' D yx measure of fit (a rank correlation coefficient) ranged from 0.23 to 0:38 for readmissions and from 0.46 to 0.72 for mortality. In 5 out of 6 cases, these predictions were not improved by including the prospectively-collected ASA Physical Status score. Such difficulties in improving risk adjustment by more intensive data collection are discussed in terms of their research implications.