Improving pathway compliance and clinician performance by using information technology.

Int J Med Inform

Philipps-Universität Marburg, Institut für Medizinische Informatik, Bunsenstrasse 3, 35037 Marburg, Germany.

Published: May 2007

To deliver patient-specific advice at the time and place of a consultation is an important contribution to improving clinician performance. Using computer-based decision support on the basis of clinical pathways is a promising strategy to achieve this goal. Thereby integration of IT applications into the clinical workflow is a core precondition for success. User acceptance and usability play a critical role: additional effort has to be balanced with enough benefit for the users and interaction design and evaluation should be handled as an intertwined, continuous process. Experiences from routine use of an online surgical pathway at Marburg University Medical Center show that it is possible to successfully address this issue by seamlessly integrating patient-specific pathway recommendations with documentation tasks which have to be done anyway, by substantially reusing entered data to accelerate routine tasks (e.g. by automatically generating orders and reports), and by continuously and systematically monitoring pathway conformance and documentation quality.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ijmedinf.2006.07.006DOI Listing

Publication Analysis

Top Keywords

clinician performance
8
improving pathway
4
pathway compliance
4
compliance clinician
4
performance technology
4
technology deliver
4
deliver patient-specific
4
patient-specific advice
4
advice time
4
time place
4

Similar Publications

Accurate survival prediction of patients with long-bone metastases is challenging, but important for optimizing treatment. The Skeletal Oncology Research Group (SORG) machine learning algorithm (MLA) has been previously developed and internally validated to predict 90-day and 1-year survival. External validation showed promise in the United States and Taiwan.

View Article and Find Full Text PDF

Background: PROTECT ( Platform Randomised evaluation of clinical Outcomes using novel TEChnologies to optimise antimicrobial Therapy) has brought together a team of researchers to design a platform trial to rapidly evaluate and adopt into care multiple diagnostic technologies, bringing immediate benefit to patients. Rapid diagnostic tests will be used to identify patients at risk of deterioration from severe infection, before they become critically unwell. The platform will assess their comparative clinical effectiveness and cost-effectiveness relative to current standard of care.

View Article and Find Full Text PDF

Background: Revision hip and knee arthroplasty volume continues to rise, and total femur replacement (TFR) remains a key salvage option in patients with extensive bone loss. Prior research has demonstrated mixed results of this procedure, and this study aimed to characterize the outcomes of nononcologic TFR in one of the largest single-center modern series.

Methods: A retrospective analysis was conducted on 23 nononcologic TFR procedures performed on 22 patients between 2012 and 2021.

View Article and Find Full Text PDF

Background: Large Language Models (LLMs) such as ChatGPT are gaining attention for their potential applications in healthcare. This study aimed to evaluate the diagnostic sensitivity of various LLMs in detecting hip or knee osteoarthritis (OA) using only patient-reported data collected via a structured questionnaire, without prior medical consultation.

Methods: A prospective observational study was conducted at an orthopaedic outpatient clinic specialized in hip and knee OA treatment.

View Article and Find Full Text PDF

Background: Depression is being increasingly acknowledged as an important risk factor contributing to coronary heart disease (CHD). Currently, there is no predictive model specifically designed to evaluate the risk of coronary heart disease among individuals with depression. We aim to develop a machine learning (ML) model that will analyze risk factors and forecast the probability of coronary heart disease in individuals suffering from depression.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!