1,721,029 research outputs found
Choosing Solvers in Decision Support Systems: A Neural Network Application in Resource-Constrained Project Scheduling
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Mathematical Programming and Heuristics for Patient Scheduling in Hospitals
No full textThe effective and efficient treatment of individual patients subject to scarce hospital resources is an increasingly important and challenging problem for decision makers to address. A recent study by the U.S. Bureau of Labor Statistics listed Registered Nursing among the top occupations in terms of job growth until the year 2022 (American Association of Colleges of Nursing (2015)). This growing demand can be explained in part by the large number of aging baby boomers with multi-morbid health conditions who typically require more treatments and longer length of stay in a variety of healthcare delivery settings (Vetrano et al. (2014)). Given the projected demand growth and reduced mobility of elderly patients, efficient operational research methods have to be developed and deployed for optimizing the process of scheduling the treatment of individual patients in highly resource constrained environments. We will henceforth denote this process as ‘patient scheduling' and provide a problem definition and a review of current approaches in the course of this chapter.</jats:p
Data-Driven Approaches for Developing Clinical Practice Guidelines
No full textThis chapter discusses clinical practice guidelines (CPGs) and their incorporation into healthcare IT (HIT) applications. CPGs provide guidance on treatment options based on evidence. This chapter provides a brief background on challenges in CPG development and adherence, and offers examples of data-driven approaches to improve usability of CPGs and their applications in HIT. A focus is given to clinical pathways, which translate CPG recommendations into actionable plans for patient management in community practices. Approaches for developing data-driven clinical pathways from electronic health record data are presented, including statistical, process mining, and machine learning algorithms. Further, efforts on using CPGs for decision support through visual analytics, and deployments of CPGs into mobile applications are described. Data-driven approaches can facilitate incorporation of practice-based evidence into CPG development after validation by clinical experts, potentially bridging the gap between available CPGs and changing clinical needs and workflow management.</jats:p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Understanding the Role of Social Media in Healthcare via Analytics: a Health Plan Perspective
No full textAn empirical study of opinion leader effects on mobile technology implementation by physicians in an American community health system
No full textThis study empirically examines the opinion leader effects on a mobile clinical information technology implementation by physicians in an American community health system using a fixed effect regression model. The model result suggests that the opinion leader effects are statistically significant during this information technology implementation process. Quantitatively, if opinion leaders increase their technology usage by 10 percent, the physicians who work closely with those opinion leaders would increase their technology usage by 3.5 percent, after controlling for physician individual-level fixed effects, time effects, working environment, and workload. This empirical result of opinion leader effects provides policy implications such as, if a healthcare system wants to promote a new information technology or a new mobile information technology implementation within their organization, they should leverage this opinion leader effects.</jats:p
Disruptive Digital Innovation in Healthcare Delivery: The Case for Patient Portals and Online Clinical Consultations
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