scholarly journals Generic Model Base Design for Decision Support Systems in Revenue Management: Applications to Hotel and Health Care Sectors

10.5772/18080 ◽  
2011 ◽  
Author(s):  
Miguel Gutierrez ◽  
Alfonso Dura
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Revenue Management ◽  
Support Systems ◽  
Generic Model ◽  
Model Base ◽  
Base Design

scholarly journals Evaluation of User-Interface Alert Displays for Clinical Decision Support Systems for Sepsis

2018 ◽  
Vol 38 (4) ◽  
pp. 46-54 ◽  
Author(s):  
Devida Long ◽  
Muge Capan ◽  
Susan Mascioli ◽  
Danielle Weldon ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
User Interface ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Care Providers

BACKGROUND Hospitals are increasingly turning to clinical decision support systems for sepsis, a life-threatening illness, to provide patient-specific assessments and recommendations to aid in evidence-based clinical decision-making. Lack of guidelines on how to present alerts has impeded optimization of alerts, specifically, effective ways to differentiate alerts while highlighting important pieces of information to create a universal standard for health care providers. OBJECTIVE To gain insight into clinical decision support systems–based alerts, specifically targeting nursing interventions for sepsis, with a focus on behaviors associated with and perceptions of alerts, as well as visual preferences. METHODS An interactive survey to display a novel user interface for clinical decision support systems for sepsis was developed and then administered to members of the nursing staff. RESULTS A total of 43 nurses participated in 2 interactive survey sessions. Participants preferred alerts that were based on an established treatment protocol, were presented in a pop-up format, and addressed the patient’s clinical condition rather than regulatory guidelines. CONCLUSIONS The results can be used in future research to optimize electronic medical record alerting and clinical practice workflow to support the efficient, effective, and timely delivery of high-quality care to patients with sepsis. The research also may advance the knowledge base of what information health care providers want and need to improve the health and safety of their patients.

Strengthening Implementation of Guidelines at Primary Health Care

2016 ◽  
pp. 133-151 ◽  
Author(s):  
V. Horner ◽  
A. Coleman
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Health Care Providers ◽  
Support Systems ◽  
Dissemination Strategy ◽  
Primary Health ◽  
Health Decision ◽  
Care Information

Implementation of guidelines in the health system is a complex and considerable undertaking. After the health administration has developed guidelines, a dissemination strategy needs to be put in place. Dissemination involves distribution of printed guidelines booklets, training of health care providers, provision of the equipment needed for implementing the guidelines, improvements to facilities, and supervision and monitoring by managers. This chapter reports on the Basic Antenatal Care Information System (Bacis) study in South Africa which pertains to an e-health decision support systems that is intended as an aid for nurses and managers at primary health care. The Bacis program study is important because there are few published studies from developing countries on implementation of e-health decision support systems at primary health care and their effectiveness in improving care.

A Critical Analysis on Efficacy of Clinical Decision Support Systems in Health Care Domain

2011 ◽  
Vol 383-390 ◽  
pp. 4043-4050
Author(s):  
Mohammad Raza Perwez ◽  
Naveed Ahmad ◽  
Muhammad Sajid Javaid ◽  
Muhammad Ehsan ul Haq
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Rural Areas ◽  
Support Systems ◽  
Patient Treatment ◽  
Health Improvement ◽  
The World ◽  
Data Ware

Clinical Practice guidelines strongly relies on evidence based medical literature. In Health care domain decision support systems are playing a competent role in diagnosis and treatment from multiple diseases. Among different Hospitals all over the world the Information technology domain emphasis key roles in improvement of patient health care to great extent. The Concept of Data Mining (DM) and Decision Support systems (DSS) in medical domain provides an efficient mechanism to extract the multiple records of patient treatment diagnostics from previously stored records in Data base (DB) or Data Ware House (DWH) and compare these guidelines to perform strong analysis that results in efficient decision making. Along the previously mentioned techniques the era of Telemedicine has also being developed that results in generation of multiple techniques in diagnosis of multiple diseases and health improvement using Mobile Health care systems specially worth full for the rural areas where latest medical facilities are unavailable at the point of need. The required information in Database or in Data Ware House might be the historical data of patient or the health based summery of different patients in diverse stages. Now these days the emergence of distributed decision support systems in health care domain covers the health care treatment procedures in more comprehensive manner including surgical procedures and radiological treatment. In this paper we are going to analyze the multiple health care diagnosis procedures and treatment techniques using various decision support systems designed and implemented by various researchers all over the world and compare the effectiveness and efficiency of each decision support system in health care domain. Our research study is also helpful for physicians and health care practioners in analyzing multiple scenarios related to interesting pattern recognitions and intelligent decision making.

scholarly journals Cost and economic benefit of clinical decision support systems for cardiovascular disease prevention: a community guide systematic review

2017 ◽  
Vol 24 (3) ◽  
pp. 669-676 ◽  
Author(s):  
Verughese Jacob ◽  
Anilkrishna B Thota ◽  
Sajal K Chattopadhyay ◽  
Gibril J Njie ◽  
Krista K Proia ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Costs And Benefits ◽  
The Cost

Objective: This review evaluates costs and benefits associated with acquiring, implementing, and operating clinical decision support systems (CDSSs) to prevent cardiovascular disease (CVD). Materials and Methods: Methods developed for the Community Guide were used to review CDSS literature covering the period from January 1976 to October 2015. Twenty-one studies were identified for inclusion. Results: It was difficult to draw a meaningful estimate for the cost of acquiring and operating CDSSs to prevent CVD from the available studies (n = 12) due to considerable heterogeneity. Several studies (n = 11) indicated that health care costs were averted by using CDSSs but many were partial assessments that did not consider all components of health care. Four cost-benefit studies reached conflicting conclusions about the net benefit of CDSSs based on incomplete assessments of costs and benefits. Three cost-utility studies indicated inconsistent conclusions regarding cost-effectiveness based on a conservative $50,000 threshold. Discussion: Intervention costs were not negligible, but specific estimates were not derived because of the heterogeneity of implementation and reporting metrics. Expected economic benefits from averted health care cost could not be determined with confidence because many studies did not fully account for all components of health care. Conclusion: We were unable to conclude whether CDSSs for CVD prevention is either cost-beneficial or cost-effective. Several evidence gaps are identified, most prominently a lack of information about major drivers of cost and benefit, a lack of standard metrics for the cost of CDSSs, and not allowing for useful life of a CDSS that generally extends beyond one accounting period.

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