Do trends in the reporting of quality measures on the nursing home compare web site differ by nursing home characteristics?

PURPOSE: This study examines the relationship between the first set of quality measures (QMs) published by the Centers for Medicare and Medicaid Services on the Nursing Home Compare Web site and five nursing home structural characteristics: ownership, chain affiliation, size, occupancy, and hospital-based versus freestanding status. DESIGN AND METHODS: Using robust linear regressions, we examined the values of the QMs at first publication and their change over the first five reporting periods, in relation to facility characteristics. RESULTS: There were significant baseline differences associated with these facility characteristics. Pain, physical restraints, and delirium exhibit a clear downward trend, with differences between the first QM reporting period and the fifth ranging from 12.7% to 46.0%. However, there were only minimal differences in trends associated with facility characteristics. This suggests that the relative position of facilities on these measures did not change much within this time period. The variation by facility type was larger for the short-stay QMs than for the long-stay measures. IMPLICATIONS: Those QMs that show an improvement exhibit it across all types of facilities, irrespective of initial quality levels. Although a number of alternatives may explain this positive trend, the trend itself suggests that report cards, to the extent that they are effective, are so for all facility types but only some QMs.     

Rapidly recurring massive pleural effusion as the initial presentation of sarcoidosis: A case report

Rationale:Sarcoidosis is a multisystem granulomatous disease with unknown etiology. It affects mainly the lungs, but it can affect almost any other organ. Nevertheless, pleural involvement with the development of pleural effusion is relatively rare. It is usually mild and responsive to treatment with systemic steroids. Here we present a case of rapidly recurring massive unilateral pleural effusion caused by sarcoidosis that was resistant to systemic steroids.Patient concerns:A 55-year-old lady presented with shortness of breath of 2-months duration. No other respiratory symptoms were reported. On physical examination, there were signs of left-sided pleural effusion, splenomegaly, and inguinal lymph nodes. These findings were confirmed by chest x-ray showing massive pleural effusion. Work up of the effusion revealed an exudative effusion with lymphocyte predominance. Pan-computed tomography scan revealed multiple thoracic, abdominal and inguinal lymphadenopathy; additionally, a left-sided pleural effusion and an enlarged spleen; that contained variable hypodense nodular lesions. Positron emission tomography-computed tomography showed intense uptake in the spleen and the lymph nodes. Inguinal lymph node biopsy showed non-necrotizing granulomatous inflammation. Due to suspicion of malignancy, left medical thoracoscopy was done, and biopsy of the parietal pleura showed nonspecific inflammation without evidence of malignancy or tuberculosis.Diagnosis:Sarcoidosis was diagnosed based on the finding of the non-necrotizing granulomatous inflammation with no evidence of malignancy or infection on several microbiological and pathological samples.Interventions:The patient was treated with repeated pleural fluid drainage. Steroids failed to prevent pleural effusion recurrence. Surgical left side pleurodesis was eventually performed.Outcomes:At more than 1 year follow up, the patient showed no recurrence of pleural effusion or development of any other symptoms.Lessons:Sarcoidosis may rarely present with massive pleural effusion, as this presentation is rare; it is imperative to rule out other causes of massive pleural effusion. Massive pleural effusion in sarcoidosis may be steroid-resistant. Pleurodesis may have a role in such a scenario.     

Identifying Patients with Group 3 Pulmonary Hypertension Associated with COPD or ILD Using an Administrative Claims Database

Lung - Group 3 pulmonary hypertension (PH) describes a subpopulation of patients with PH due to chronic lung disease and/or hypoxia, with chronic obstructive pulmonary disease (COPD) and...     

Forecasting Migraine Attacks and the Utility of Identifying Triggers

Purpose of Review

This review synthesizes the utility of measuring migraine triggers for the purpose of forecasting future headache attacks. The nature of forecasting models, headache triggers as inputs to such models, and how these trigger exposures can be measured for forecasting are reviewed. A critical evaluation of the existing forecasting models in the context of their potential application for preemptive treatment is considered.

Recent Findings

A substantial pool of candidate trigger factors could be considered in the creation of forecasting models. However, because mechanistic information about causal factors that precede a migraine attack is not well understood, and such factors are difficult to measure, empirical models that are based on trigger factors that are merely associated with the onset of headache activity are likely to be the focus of forecasting efforts in the near future. Of such factors, stress has considerable empirical support and has been used to successfully forecast future headache attacks within individuals over time. However, at present, existing models possess only modest levels of discrimination and lack strong resolution in generated predictions.

Summary

Current headache forecasting models represent an important first step in accurately predicting future headache activity. However, to utilize these models in a preemptive treatment paradigm where the risk of headache is treated prior to the actual experience of pain, these models must achieve greater precision with good calibration and generate predictions that are clinically actionable by individuals in their real-time home environments.

     

Biology‐Driven Gene‐Gene Interaction Analysis of Age‐Related Cataract in the eMERGE Network

Bioinformatics approaches to examine gene‐gene models provide a means to discover interactions between multiple genes that underlie complex disease. Extensive computational demands and adjusting for multiple testing make uncovering genetic interactions a challenge. Here, we address these issues using our knowledge‐driven filtering method, Biofilter, to identify putative single nucleotide polymorphism (SNP) interaction models for cataract susceptibility, thereby reducing the number of models for analysis. Models were evaluated in 3,377 European Americans (1,185 controls, 2,192 cases) from the Marshfield Clinic, a study site of the Electronic Medical Records and Genomics (eMERGE) Network, using logistic regression. All statistically significant models from the Marshfield Clinic were then evaluated in an independent dataset of 4,311 individuals (742 controls, 3,569 cases), using independent samples from additional study sites in the eMERGE Network: Mayo Clinic, Group Health/University of Washington, Vanderbilt University Medical Center, and Geisinger Health System. Eighty‐three SNP‐SNP models replicated in the independent dataset at likelihood ratio test P < 0.05. Among the most significant replicating models was rs12597188 (intron of CDH1)–rs11564445 (intron of CTNNB1). These genes are known to be involved in processes that include: cell‐to‐cell adhesion signaling, cell‐cell junction organization, and cell‐cell communication. Further Biofilter analysis of all replicating models revealed a number of common functions among the genes harboring the 83 replicating SNP‐SNP models, which included signal transduction and PI3K‐Akt signaling pathway. These findings demonstrate the utility of Biofilter as a biology‐driven method, applicable for any genome‐wide association study dataset.