Are Patient Safety Indicators Related to Widely Used Measures of Hospital Quality?

Context  Patient safety indicators (PSIs) are screening tools that use administrative data to identify potential complications of care and are being increasingly used as measures of hospital safety. It is unknown whether PSIs are related to standard quality metrics. Objective  To examine the relationship between select PSIs and measures of hospital quality. Design, Setting, and Participants  We used the 2003 MedPAR dataset to examine the performance of 4,504 acute-care hospitals on four medical PSIs among Medicare enrollees. Main Outcome Measures  We used bivariate and multivariate techniques to examine the relationship between PSI performance and quality scores from the Hospital Quality Alliance program, risk-adjusted mortality rates, and selection as a top hospital by US News & World Report. Results  We found inconsistent and usually poor associations among the PSIs and other hospital quality measures with the exception of “failure to rescue,” which was consistently associated with better performance on all quality measures tested. For example, hospitals in the top quartile of failure to rescue performance had a 0.9% better summary performance score in acute myocardial infarction (AMI) processes and a 22% lower mortality rate in AMI compared to hospitals in the bottom quartile of failure to rescue (p < 0.01 for both comparisons). Death in low mortality DRG, decubitus ulcer, and infection due to medical care generally had poor or often inverse relationships with the other quality measures. Conclusions  With the exception of failure to rescue, we found poor or inverse relationships between PSIs and other measures of healthcare quality. Whether the lack of relationship is due to the limitations of the PSIs is unknown, but suggests that PSIs need further validation before they are employed broadly.     

Will minimally invasive valve replacement ever really be important?

PURPOSE OF REVIEW: Most cardiac surgical centers worldwide have instituted some form of minimally invasive surgery into their operative armamentarium. However, skepticism still remains whether minimally invasive valve replacement will ever really be important. This review first addresses the definition of minimally invasive surgery and then analyzes the possible advantages and disadvantages of minimally invasive valvular surgery. RECENT FINDINGS: The nomenclature for minimally invasive surgery is ill defined. Minimally invasive valve replacement is a safe and effective procedure compared with total sternotomy. The advantages of minimally invasive valve replacement are the length of stay and disposition after discharge, postoperative bleeding, cosmesis, and postoperative pain, whereas the main disadvantage involves the operative times early in the learning curve. SUMMARY: Minimally invasive valve replacement is beneficial and will continue to evolve as an important treatment option for patients with valvular heart diseases.     

The New Medicaid Under PPACA What Will it Mean for General Internists?

The Patient Protection and Affordable Care Act (ACA) institutionalized Medicaid as a significant and permanent structure in the U.S. health care system. About half of the 32 million Americans expected to gain health insurance coverage under the ACA will be covered under Medicaid. While it is clear general internists will be significantly impacted by Medicaid-related health care reform provisions, its ultimate effect is unclear since these new opportunities also come with some new potential burdens. There are four main areas of impact for general internists to consider: (1) coverage expansions and reimbursement; (2) multiple payers and fragmented coverage; (3) primary care workforce and infrastructure capacity; and (4) delivery model changes.     

Which Are the Right Cells to be Used in a Bioartificial Liver?

Anno 2004 freshly isolated or cryopreserved porcine or human hepatocytes have been most frequently used as biocomponent in clinically applied bioartificial livers (BALs). Phase 1 studies of all biocomponent modalities showed safety, feasibility, and improvement of biochemical, neurological, and hemodynamic parameters. However, both the pilot-controlled clinical trial with C3A cells and the randomized larger clinical trial with cryopreserved porcine hepatocytes did not show significant improvement of survival by intention-to-treat analysis. Because of the xenotransplantation-related disadvantages of porcine cells and the shortage of primary human hepatocytes, other sources of biocomponents have to be explored. The future lies in the development of one or more human hepatocyte cell lines, which will have minimal immunogenicity, no risk of xeno-zoonosis, and the requested functionality and availability. Primary sources for the development of such human cell lines are liver-tumor-derived cell lines, immortalized fetal or adult hepatocytes, and stem cells of hepatic, hematopoietic, or embryonic origin. At present the most promising results for BAL application have been obtained by immortalization of human fetal liver cells by reconstitution of telomerase activity. However, in all cell types tested so far, the in vitro differentiation cannot be stimulated to such an extent that their functionality reaches that of primary human hepatocytes. More insight in differentiation-promoting factors and the influence of matrix and co-culture conditions is needed.     

The Promise of Machine Learning: When Will it be Delivered?

BackgroundThe real-life applications of machine learning clinical decision making is currently lagging behind its promise. One of the critics on machine learning is that it doesn't outperform more traditional statistical approaches in every problem.Methods and ResultsAuthors of “Predictive Abilities of Machine Learning Techniques May Be Limited by Dataset Characteristics: Insights From the UNOS Database” presented in the current issue of the Journal of Cardiac Failure that machine learning approaches do not provide significantly higher performance when compared to more traditional statistical approaches in predicting mortality following heart transplant. In this brief report, we provide an insight on the possible reasons for why machine learning methods do not outperform more traditional approaches for every problem and every dataset.ConclusionsMost of the performance-focused critics on machine learning are because the bar is set unfairly too high for machine learning. In most cases, machine learning methods provides at least as good results as traditional statistical methods do. It is normal for machine learning models to provide similar performance with linear models if the actual underlying input-outcome relationship is linear. Moreover, machine learning methods outperforms linear statistical models when the underlying input-output relationship is not linear and if the dataset is large enough and include predictors capturing that nonlinear relationship.     

Wireless endoscopy in 2020: Will it still be a capsule?

Currently,the major problem of all existing commercial capsule devices is the lack of control of movement.In the future,with an interface application,the clinician will be able to stop and direct the device into points of interest for detailed inspection/diagnosis,and therapy delivery.This editorial presents current commerciallyavailable new designs,European projects and delivery capsule and gives an overview of the progress required and progress that will be achieved-according to the opinion of the authors- in the next 5 year leading to 2020.     

Tissue Characterization by Ultrasound: What is Possible Now? What Will be Possible?

The purpose of this review is to discuss the principles of ultrasound tissue characterization. We describe gray scale analysis, backscatter techniques, real-time backscatter imaging, enhancement of abnormal tissue properties with contrast agents or liposomes, and use of acoustic microscopy. Ultrasound tissue characterization offers the promise of direct identification of abnormalities of the myocardium without relying on indirect manifestations such as abnormalities in cardiac function.