Outsourcing the hospital

The outsourcing of hospital services has become increasingly commonplace as way to control or reduce costs.
In the US, the need for outsourcing has intensified in recent years, in order to cope with cuts to Medicare after budget sequestration. This has intensified a backlog of pressure dating to the 1990s for healthcare reform and cost-effectiveness, which had already been driving hospitals to outsource.
On its part, Europe too has seen growth in the use of outsourcing over this period as a means to control healthcare spending. However, there are no European parallels to the relatively sweeping and immediate impact of the US budget sequestration.

Support functions typical outsourcing targets
Typically, the most common outsourcing targets for hospitals have consisted of support functions. These range from catering, housekeeping and laundry services to human resource management and IT.
Catering is among the areas where outsourcing is well established, and hospitals have become a key source of revenues. For US chain Au Bon Pain, hospitals account for more than 60 of its 280 outlets in the US. Its outlet at Long Island Jewish Medical Center is

Digital tomosynthesis – the promise of 3D mammograms

Digital tomosynthesis is a new, three-dimensional (3D) technology which promises to address key shortcomings of conventional mammography. It also offers a way to tackle some of the challenges faced by computed tomography (CT) and is under investigation for a variety of new medical and surgical applications.
The concept of digital tomosynthesis is clean and elegant. A 3D slice is made by superimposing (and retrospectively reconstructing) consecutive high-resolution images, taken from different angles, across an arc. The accompanying 2D images are also used for interpretation by radiologists.

Flat-panel technology, CT pave the way
Tomosynthesis was already known in the 1930s, as part of the family of geometric tomography techniques. However, the use of plain film meant that it was procedurally painstaking, since only one image could be acquired at a time. Even more problematic was the high dosage of radiation required to produce more imaging sections.
The emergence of computed tomography (CT) in the 1970s generated a new wave of excitement about tomosynthesis. However, progress remained dormant until the mid-1990s, when the advent of flat-panel digital detectors promised a means for tomosynthesis to acquire both technical traction and momentum.
One of the most important characteristics of flat-panel technology is the lack of distortion, since its geometry (rows and columns) is known. As a result, it is possible to interpolate reconstructions on the exact point in a tomographic layer, from which data has been recorded.
First-generation flat-panel tomosynthesis systems were, nevertheless, handicapped by speed. Experimental devices, even in the late 1990s, could only achieve four to five frames per second (FPS). However, flat panel technology has evolved since then, fuelled by increasingly sophisticated optoelectronics and back-end algorithms to interpret the data. As a result, it is now possible to acquire images at 20-30 FPS   with a radiation exposure similar to a chest X-Ray.

Different from CT

In spite of parallels, digital tomosynthesis and CT are two different techniques. Unlike the former, which typically consists of 15 images across a 15 degree arc, CT makes a full 360-degree rotation around a patient to acquire data for image reconstruction.
In digital tomosynthesis, the fewer data sets entail limited depth of field, and an inability to attain the very narrow slice widths of CT. However, given the digital processing of an image, one data set can provide for reconstruction of slices with both different depths and thicknesses; this not only saves time but radiation exposure requirements too.

Addressing limitations in slice width, but cost remains concern
Considerable efforts are underway to address the limits to slice width in digital tomosynthesis, especially in the form of more sophisticated detectors which allow higher in-plane resolution. The algorithms used to reconstruct tomosynthesis data are also more complex than CT. Together, both add to cost.

The Year of 3D Mammography
The application where digital tomosynthesis has drawn maximum attention is mammography. Indeed, digital tomosynthesis is now widely labelled as

Redefining telemedicine

In spite of fears in the early 2000s that telemedicine would be buried as a sideshow amidst the sweeping aspirations of eHealth, it now seems that both are headed their own ways, at different speeds. Indeed, while eHealth still grapples with issues like interoperability and standards, telemedicine has been establishing itself in niches ranging from rural healthcare and military medical care to robotics.
In 2000, the peer-reviewed

New generation mother & child care centres

A generic patient-centred environment fails to meet the needs of the entire patients

ProSim – Vital Signs Simulator

Digital breast tomosynthesis

Worldwide breast cancer is the most common female cancer; in the West one in eight women eventually develop the disease. However the mortality rate has steadily decreased in recent decades, in large part due to improved screening programmes and earlier detection. The current gold standard screening tool is mammography, but in 2011 the FDA approved the first Digital Breast Tomosynthesis (DBT) system, and this or similar systems are now available in a limited number of Western hospitals, generating studies to compare the effectiveness of the two imaging modalities.
Healthcare professionals are cognizant with the limitations of mammography, particularly for imaging dense breasts. X-rays of each breast from different angles can only provide a 2D image of a 3D structure, and normal breast tissue can thus mask a tumour. In addition false positive results augment both patient anxiety and hospital workload. And patients are well aware (even if many male health professionals are not) that the compression necessary for allowing the whole breast to be adequately viewed during mammography is not merely

LITERATURE ALERT: Implementing delirium screening in the ICU


Objective:
To review delirium screening tools available for use in the adult ICU and PICU, to review evidence-based delirium screening implementation, and to discuss common pitfalls encountered during delirium screening in the ICU.

Data Sources:

Review of delirium screening
literature and expert opinion

Results:

Over the past decade, tools specifically designed for use in critically ill adults and children have been developed and validated. Delirium screening has been effectively implemented across many ICU settings. Keys to effective implementation include addressing barriers to routine screening, multifaceted training such as lectures, case-based scenarios, one-on-one teaching, and real-time feedback of delirium screening, and interdisciplinary communication through discussion of a patient

Medical imaging: evolution and quality standards

Although many patients still associate the imaging department of a hospital with the frontiers of medicine, the discipline is nearly 120 years old.
The effort to set quality standards for modern CT and MRI systems are inspired by experience with older imaging technologies, especially X-rays. In general, safety issues remain the focus for lawmakers, while recognized professional organisations ensure that quality control efforts remain up to date with ever-changing technologies. Top professional bodies usually function in such capacities under a legislative umbrella. For example, the American College of Radiology (ACR) has a mandate from the US Medicare Improvements for Patients and Providers Act (MIPPA); it also seeks to ensure implementation of both safety and quality programs at the imaging facilities of accredited healthcare providers.

Roots in the 1890s
Medical imaging was born after the discovery of X-rays by German physicist Wilhelm R

Managing radiology risks

Risk management is an everyday part of a radiologist

Pattern recognition: unlocking the secrets of data

Pattern recognition consists of labelling data inputs and interpreting them according to a broad range of criteria, from classification and sequencing to regression and parsing.  At the most fundamental level, pattern recognition may be a basic definition of