An Empiric Medicare Claims-Based Utilization Approach to Mitigating the Iodinated Contrast Shortage.
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ABSTRACT:
SUBMITTER: Duszak R
PROVIDER: S-EPMC9131464 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
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An Empiric Medicare Claims-Based Utilization Approach to Mitigating the Iodinated Contrast Shortage.
Duszak Richard R Hemingway Jennifer J Christensen Eric W EW Saindane Amit M AM Hughes Danny R DR Rula Elizabeth Y EY
Journal of the American College of Radiology : JACR 20220525 7
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Project description:Global shortage of iodinated contrast medium (ICM) is the latest health care ripple-effect from the COVID-19 pandemic. Some public hospitals in Australia have less than a week's supply. Strategies are, therefore, urgently needed to conserve ICM for those diagnostic tests and interventions, which are time-critical, and without which patients would suffer death or significant morbidity. A plan is also required to continue providing best possible care to patients in the worst-case scenario of exhausted ICM supplies. This document, by representatives from two major public hospitals, will provide some guidance that is tailored to the Australian context.
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Project description:The incidence of hypersensitivity reactions (HSRs) to iodinated contrast media (ICM) has risen over last years, representing an important health problem. HSRs to ICMs are classified into immediate reactions (IRs) and non-immediate reactions (NIRs) according to if they occur within 1 h or longer after ICM administration. The diagnosis of HSRs to ICM is complex as skin test (ST) sensitivity ranges widely, and drug provocation test (DPT) protocols are heterogeneous. In this manuscript, we describe the clinical characteristics of a series of patients confirmed as HSR to ICM and the diagnosis procedure carried out, looking into those cases confirmed as HSRs to multiple ICMs. For this purpose, we prospectively evaluated patients suggestive of HSRs to ICMs and classified them as IRs or NIRs. STs were carried out using a wide panel of ICMs, and in those with a negative ST, a single-blind placebo controlled DPT was performed with the culprit. If ST or DPT were positive, then tolerance was assessed with an alternative negative ST ICM. We included 101 cases (12 IRs and 89 NIRs) confirmed as allergic. Among them, 36 (35.64%) cases were allergic to more than one ICM (8 IRs and 28 NIRs). The most common ICM involved were iomeprol and iodixanol. Although not statistically significant, the percentage of patients reporting anaphylaxis was higher in patients allergic to multiple ICMs compared with patients allergic to a single ICM (50 vs. 25%). Likewise, the percentage of positive results in STs was higher in patients allergic to multiple ICMs compared with those allergic to a single ICM (for IR 62.5 vs. 25%, p > 0.05; and for NIR, 85.71 vs. 24.59%, p < 0.000). In cases allergic to more than one ICM, DPT with negative-ST ICM was positive in more than 60% (24/36) of cases. Therefore, allergy to multiple ICMs is common, associated to severe reactions in IRs, and confirmed frequently by positive STs. The allergological work-up should include DPT not only to establish the diagnosis but also to identify safe alternative ICM, even if ICM is structurally unrelated and ST is negative. More studies are needed to clarify mechanisms underlying cross-reactivity among ICMs.
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Project description:BackgroundDementia severity is unavailable in administrative claims data. We examined whether a claims-based frailty index (CFI) can measure dementia severity in Medicare claims.MethodsThis cross-sectional study included the National Health and Aging Trends Study Round 5 participants with possible or probable dementia whose Medicare claims were available. We estimated the Functional Assessment Staging Test (FAST) scale (range: 3 [mild cognitive impairment] to 7 [severe dementia]) using information from the survey. We calculated CFI (range: 0-1, higher scores indicating greater frailty) using Medicare claims 12 months prior to the participants' interview date. We examined C-statistics to evaluate the ability of the CFI in identifying moderate-to-severe dementia (FAST stage 5-7) and determined the optimal CFI cut-point that maximized both sensitivity and specificity.ResultsOf the 814 participants with possible or probable dementia and measurable CFI, 686 (72.2%) patients were ≥75 years old, 448 (50.8%) were female, and 244 (25.9%) had FAST stage 5-7. The C-statistic of CFI to identify FAST stage 5-7 was 0.78 (95% confidence interval: 0.72-0.83), with a CFI cut-point of 0.280, achieving the maximum sensitivity of 76.9% and specificity of 62.8%. Participants with CFI ≥0.280 had a higher prevalence of disability (19.4% vs 58.3%) and dementia medication use (6.0% vs 22.8%) and higher risk of mortality (10.7% vs 26.3%) and nursing home admission (4.5% vs 10.6%) over 2 years than those with CFI <0.280.ConclusionsOur study suggests that CFI can be useful in identifying moderate-to-severe dementia from administrative claims among older adults with dementia.
| S-EPMC10613007 | biostudies-literature
Project description:ObjectiveTo develop an empiric approach for evaluating the performance of physician peer groups based on patient-sharing in administrative claims data.Data sourcesSurveillance, Epidemiology and End Results-Medicare linked dataset.Study designApplying social network theory, we constructed physician peer groups for patients with breast cancer. Under different assumptions of key parameter values-minimum patient volume for physician inclusion and minimum number of patients shared between physicians for a connection-we compared agreement in group membership between split samples during 2004-2006 (T1) (reliability) and agreement in group membership between T1 and 2007-2009 (T2) (stability). We also compared the results with those derived from randomly generated groups and to hospital affiliation-based groups.Principal findingsThe sample included 142 098 patients treated by 43 174 physicians in T1 and 136 680 patients treated by 51 515 physicians in T2. We identified parameter values that resulted in a median peer group reliability of 85.2 percent (Interquartile range (IQR) [0 percent, 96.2 percent]) and median stability of 73.7 percent (IQR [0 percent, 91.0 percent]). In contrast, stability of randomly assigned peer groups was 6.2 percent (IQR [0 percent, 21.0 percent]). Median overlap of empirical groups with hospital groups was 32.2 percent (IQR [12.1 percent, 59.2 percent]).ConclusionsIt is feasible to construct physician peer groups that are reliable, stable, and distinct from both randomly generated and hospital-based groups.
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Project description:Current clinical CT contrast agents are mainly small molecular iodinated compounds, which often suffer from short blood pool retention for more comprehensive cardiovascular CT imaging and may cause contrast-induced nephropathy. In this work, we prepared polydisulfides containing a traditional iodinated CT contrast agent in order to optimize the pharmacokinetics of the agent and improve its safety. Initially acting as a macromolecular agent and achieving sharp blood vessel delineation, the polydisulfides can be reduced by endogenous thiols via disulfide-thiol exchange reaction to oligomers that can be readily excreted via renal filtration. Short polyethylene glycol (PEG) chain was also introduced to the polymers to further modify the in vivo properties of the agents. Strong and prolonged vascular enhancement has been generated with two new agents in mice (5-10 times higher blood pool enhancement than iodixanol). The polydisulfide agents gradually degraded and excreted via renal filtration. The gradual excretion process could prevent contrast-induced nephropathy. These results suggest that the biodegradable macromolecular CT contrast agents are promising safe and effective blood contrast agents for CT angiography and image-guided interventions.
| S-EPMC4142209 | biostudies-literature
Project description:ObjectivesTo assess the feasibility of using existing claims-based algorithms to identify community-dwelling Medicare beneficiaries with disability based solely on the conditions for which they are being treated, and improving on these algorithms by combining them in predictive models.Data sourceData on 12,415 community-dwelling fee-for-service Medicare beneficiaries who first responded to the Medicare Current Beneficiary Survey (MCBS) in 2003-2006.Study designLogistic regression models in which six claims-based disability indicators are used to predict self-reported disability. Receiver operating characteristic (ROC) curves were used to assess the performance of the predictive models.Principal findingsThe predictive performance of the regression-based models is better than that of the individual claims-based indicators. At a predicted probability threshold chosen to maximize the sum of sensitivity and specificity, sensitivity is 0.72 for beneficiaries age 65 or older and specificity is 0.65. For those under 65, sensitivity is 0.54 and specificity is 0.67. The findings also suggest ways to improve predictive performance for specific disability populations of interest to researchers.ConclusionsPredictive models that incorporate multiple claims-based indicators provide an improved tool for researchers seeking to identify people with disabilities in claims data.
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Project description:BackgroundThe accuracy of stroke diagnosis in administrative claims for a contemporary population of Medicare enrollees has not been studied. We assessed the validity of diagnostic coding algorithms for identifying stroke in the Medicare population by linking data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study to Medicare claims.Methods and resultsThe REGARDS Study enrolled 30 239 participants ≥45 years in the United States between 2003 and 2007. Stroke experts adjudicated suspected strokes, using retrieved medical records. We linked data for participants enrolled in fee-for-service Medicare to claims files from 2003 through 2009. Using adjudicated strokes as the gold standard, we calculated accuracy measures for algorithms to identify incident and recurrent strokes. We linked data for 15 089 participants, among whom 422 participants had adjudicated strokes during follow-up. An algorithm using primary discharge diagnosis codes for acute ischemic or hemorrhagic stroke (International Classification of Diseases, Ninth Revision, Clinical Modification codes: 430, 431, 433.x1, 434.x1, 436) had a positive predictive value of 92.6% (95% confidence interval, 88.8%-96.4%), a specificity of 99.8% (99.6%-99.9%), and a sensitivity of 59.5% (53.8%-65.1%). An algorithm using only acute ischemic stroke codes (433.x1, 434.x1, 436) had a positive predictive value of 91.1% (95% confidence interval, 86.6%-95.5%), a specificity of 99.8% (99.7%-99.9%), and a sensitivity of 58.6% (52.4%-64.7%).ConclusionsClaims-based algorithms to identify stroke in a contemporary Medicare cohort had high positive predictive value and specificity, supporting their use as outcomes for etiologic and comparative effectiveness studies in similar populations. These inpatient algorithms are unsuitable for estimating stroke incidence because of low sensitivity.
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