11,973 research outputs found
The future of laboratory medicine - A 2014 perspective.
Predicting the future is a difficult task. Not surprisingly, there are many examples and assumptions that have proved to be wrong. This review surveys the many predictions, beginning in 1887, about the future of laboratory medicine and its sub-specialties such as clinical chemistry and molecular pathology. It provides a commentary on the accuracy of the predictions and offers opinions on emerging technologies, economic factors and social developments that may play a role in shaping the future of laboratory medicine
An Intelligent Data Mining System to Detect Health Care Fraud
The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice
The Bionic Radiologist: avoiding blurry pictures and providing greater insights
Radiology images and reports have long been digitalized. However, the potential of the more than 3.6 billion radiology
examinations performed annually worldwide has largely gone unused in the effort to digitally transform health care. The Bionic
Radiologist is a concept that combines humanity and digitalization for better health care integration of radiology. At a practical
level, this concept will achieve critical goals: (1) testing decisions being made scientifically on the basis of disease probabilities and
patient preferences; (2) image analysis done consistently at any time and at any site; and (3) treatment suggestions that are closely
linked to imaging results and are seamlessly integrated with other information. The Bionic Radiologist will thus help avoiding missed
care opportunities, will provide continuous learning in the work process, and will also allow more time for radiologists’ primary
roles: interacting with patients and referring physicians. To achieve that potential, one has to cope with many implementation
barriers at both the individual and institutional levels. These include: reluctance to delegate decision making, a possible decrease in
image interpretation knowledge and the perception that patient safety and trust are at stake. To facilitate implementation of the
Bionic Radiologist the following will be helpful: uncertainty quantifications for suggestions, shared decision making, changes in
organizational culture and leadership style, maintained expertise through continuous learning systems for training, and role
development of the involved experts. With the support of the Bionic Radiologist, disparities are reduced and the delivery of care is
provided in a humane and personalized fashion
BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer
For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice
Get screened: a pragmatic randomized controlled trial to increase mammography and colorectal cancer screening in a large, safety net practice
Abstract Background Most randomized controlled trials of interventions designed to promote cancer screening, particularly those targeting poor and minority patients, enroll selected patients. Relatively little is known about the benefits of these interventions among unselected patients. Methods/Design "Get Screened" is an American Cancer Society-sponsored randomized controlled trial designed to promote mammography and colorectal cancer screening in a primary care practice serving low-income patients. Eligible patients who are past due for mammography or colorectal cancer screening are entered into a tracking registry and randomly assigned to early or delayed intervention. This 6-month intervention is multimodal, involving patient prompts, clinician prompts, and outreach. At the time of the patient visit, eligible patients receive a low-literacy patient education tool. At the same time, clinicians receive a prompt to remind them to order the test and, when appropriate, a tool designed to simplify colorectal cancer screening decision-making. Patient outreach consists of personalized letters, automated telephone reminders, assistance with scheduling, and linkage of uninsured patients to the local National Breast and Cervical Cancer Early Detection program. Interventions are repeated for patients who fail to respond to early interventions. We will compare rates of screening between randomized groups, as well as planned secondary analyses of minority patients and uninsured patients. Data from the pilot phase show that this multimodal intervention triples rates of cancer screening (adjusted odds ratio 3.63; 95% CI 2.35 - 5.61). Discussion This study protocol is designed to assess a multimodal approach to promotion of breast and colorectal cancer screening among underserved patients. We hypothesize that a multimodal approach will significantly improve cancer screening rates. The trial was registered at Clinical Trials.gov NCT00818857http://deepblue.lib.umich.edu/bitstream/2027.42/78264/1/1472-6963-10-280.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78264/2/1472-6963-10-280.pdfPeer Reviewe
- …