How Well Do Computerised Decision Support Systems Cover Nursing Standards of Practice? A Literature Review

The use of computerized decision support systems (DSS) in nursing practice is increasing. However, research about who uses DSS, where are they implemented, and how they are linked with standards of nursing is limited. This paper presents evidence on users and settings of DSS implementation, along with specific nursing standards of practice that are facilitated by such DSS. We searched six bibliographic databases using relevant terms and identified 28 studies, each evaluating a unique DSS. Of these, 24 were used by registered nurses and 19 were implemented in short-term care units. Most of the DSS were found to facilitate nursing standards of assessment and intervention, however, outcome identification and evaluation were the least included standards. These findings not only highlight gaps in systems but also offer opportunities for further research development in this area.

Integrating Information Visualization and Dimensionality Reduction: A pathway to Bridge the Gap between Natural and Artificial Intelligence

By importing some natural abilities from human thinking into the design of computerized decision support systems, a cross-cutting trend of intelligent systems has emerged, namely, the synergetic integration between natural and artificial intelligence. While natural intelligence provides creative, parallel, and holistic thinking, its artificial counterpart is logical, accurate, able to perform complex and extensive calculations, and tireless. In the light of such integration, two concepts are important: controllability and interpretability. The former is defined as the ability of computerized systems to receive feedback and follow users’ instructions, while the latter refers to human-machine communication. A suitable alternative to simultaneously involve these two concepts—and then bridging the gap between natural and artificial intelligence—is bringing together the fields of dimensionality reduction (DimRed) and information visualization (InfoVis).

Users’ Assessement of the Visualization with Gauges of a Guideline-Based Decision Support System Output: A Qualitative Study of Focus Groups

Computerized decision support systems (CDSSs) are still poorly routinely implemented in clinical practices mainly because of usability problems related to the technology interface. We previously proposed to use gauges to visualize the output of a guideline-based CDSS applied to malnutrition and pressure ulcer management in nursing homes. This interface was assessed by four focus groups including 16 healthcare professionals with expertise in geriatrics. A USE-like questionnaire was distributed. Participants considered the dashboard-with-gauges visualization was useful (94%), easy to use (63%), easy to learn (88%), and 88% thought they could be satisfied with it. However, concerns were expressed about the difficulty to follow up multiple healthcare problems.

A Survey on Weapon Target Allocation Models and Applications

In Command and Control (C2), Threat Evaluation (TE) and Weapon Target Allocation (WTA) are two key components. To build an automated system in this area after modeling Threat Evaluation and Weapon Target Allocation processes, solving these models and finding the optimal solution are further important issues. This setting demands instantaneous operational planning and decision making under inherent severe stress conditions. The associated responsibilities are usually divided among a number of operators and also computerized decision support systems that aid these operators during the decision making process. In this Chapter, the literature in the area of WTA system with the emphasis on the modeling and solving methods are surveyed.

Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review

Background Computerized decision support systems (CDSSs) are software programs that support the decision making of practitioners and other staff. Other reviews have analyzed the relationship between CDSSs, practitioner performance, and patient outcomes. These reviews reported positive practitioner performance in over half the articles analyzed, but very little information was found for patient outcomes. Objective The purpose of this review was to analyze the relationship between CDSSs, practitioner performance, and patient medical outcomes. PubMed, CINAHL, Embase, Web of Science, and Cochrane databases were queried. Methods Articles were chosen based on year published (last 10 years), high quality, peer-reviewed sources, and discussion of the relationship between the use of CDSS as an intervention and links to practitioner performance or patient outcomes. Reviewers used an Excel spreadsheet (Microsoft Corporation) to collect information on the relationship between CDSSs and practitioner performance or patient outcomes. Reviewers also collected observations of participants, intervention, comparison with control group, outcomes, and study design (PICOS) along with those showing implicit bias. Articles were analyzed by multiple reviewers following the Kruse protocol for systematic reviews. Data were organized into multiple tables for analysis and reporting. Results Themes were identified for both practitioner performance (n=38) and medical outcomes (n=36). A total of 66% (25/38) of articles had occurrences of positive practitioner performance, 13% (5/38) found no difference in practitioner performance, and 21% (8/38) did not report or discuss practitioner performance. Zero articles reported negative practitioner performance. A total of 61% (22/36) of articles had occurrences of positive patient medical outcomes, 8% (3/36) found no statistically significant difference in medical outcomes between intervention and control groups, and 31% (11/36) did not report or discuss medical outcomes. Zero articles found negative patient medical outcomes attributed to using CDSSs. Conclusions Results of this review are commensurate with previous reviews with similar objectives, but unlike these reviews we found a high level of reporting of positive effects on patient medical outcomes.

Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes: Systematic Review (Preprint)

BACKGROUND Computerized decision support systems (CDSSs) are software programs that support the decision making of practitioners and other staff. Other reviews have analyzed the relationship between CDSSs, practitioner performance, and patient outcomes. These reviews reported positive practitioner performance in over half the articles analyzed, but very little information was found for patient outcomes. OBJECTIVE The purpose of this review was to analyze the relationship between CDSSs, practitioner performance, and patient medical outcomes. PubMed, CINAHL, Embase, Web of Science, and Cochrane databases were queried. METHODS Articles were chosen based on year published (last 10 years), high quality, peer-reviewed sources, and discussion of the relationship between the use of CDSS as an intervention and links to practitioner performance or patient outcomes. Reviewers used an Excel spreadsheet (Microsoft Corporation) to collect information on the relationship between CDSSs and practitioner performance or patient outcomes. Reviewers also collected observations of participants, intervention, comparison with control group, outcomes, and study design (PICOS) along with those showing implicit bias. Articles were analyzed by multiple reviewers following the Kruse protocol for systematic reviews. Data were organized into multiple tables for analysis and reporting. RESULTS Themes were identified for both practitioner performance (n=38) and medical outcomes (n=36). A total of 66% (25/38) of articles had occurrences of positive practitioner performance, 13% (5/38) found no difference in practitioner performance, and 21% (8/38) did not report or discuss practitioner performance. Zero articles reported negative practitioner performance. A total of 61% (22/36) of articles had occurrences of positive patient medical outcomes, 8% (3/36) found no statistically significant difference in medical outcomes between intervention and control groups, and 31% (11/36) did not report or discuss medical outcomes. Zero articles found negative patient medical outcomes attributed to using CDSSs. CONCLUSIONS Results of this review are commensurate with previous reviews with similar objectives, but unlike these reviews we found a high level of reporting of positive effects on patient medical outcomes.

What are the Effects of Computerized Decision Support Systems on Practitioner Performance and Patient Outcomes

Background Computerized decision support systems (CDSS) are software programs that support the decision making of practitioners and other staff. Other reviews have analyzed the relationship between CDSS, practitioner performance, and patient outcomes. These reviews reported positive practitioner performance in over half the articles analyzed, but very little information was found for patient outcomes. The purpose of this review was to analyze the relationship between CDSS, practitioner performance, and patient medical outcomes. PubMed, CINAHL, and Cochrane databases were queried.Methods 27 articles were chosen based on year published (last ten years), high quality source, and discussion of the relationship between the use of CDSS as an intervention and links to practitioner performance or patient outcomes. Reviewers used an Excel spreadsheet to collect information on the relationship between CDSS and practitioner performance or patient outcomes. Reviewers also collected observations of participants, intervention, comparison with control group, and outcomes (PICO) along with those showing implicit bias. Articles were analyzed by multiple reviewers following the Kruse Protocol for systematic reviews. Data were organized into multiple tables for analysis and reporting.Results Fourteen articles (52%) discussed positive practitioner performance, three articles (11%) found no difference in practitioner performance, ten articles (37%) did not discuss practitioner performance. Zero articles reported negative practitioner performance. Fifteen articles (56%) discussed positive patient medical outcomes, two articles (7%) found no statistically significant difference in medical outcomes between intervention and control groups, and ten articles (37%) did not discuss medical outcomes. Zero articles found negative patient medical outcomes.Conclusions Results of this review are commensurate with previous reviews with similar objectives, but unlike these reviews we found significant positive reporting of a positive effect on patient medical outcomes. Our findings support adoption of decision support systems.

Penerapan Metode Analytic Hirerarchy Process (AHP) Untuk Pemilihan Kabid Pendapatan Badan Keuangan Daerah Kota Padangsidempuan

Proposing and voting kabid income BKD city of Padang Sidempuan is done through a series of process. The selection process can be done by observing the variety of considerations of various elements of the assessment. So that decision-makers can be easier in your selections so very necessary computerized decision support systems. In developing decision support system used method of Analitycal Hierarchy Process (AHP) by making a matrix comparison of paired and matrix of criteria so that retrieved the value of the total in use as a base in perengkingan. The input data retrieved from secondary data contained in the assessment of the achievements of the work of employees (PPKP). In PPKP element assessed consists of two components, namely the employment Target employees (SKP) and Work Behavior (PK). AHP method to be performed on the body of the Regional city of Padang Sidempuan Finance this is a work Behavior (PK), with 6 criteria i.e. orientation service, integrity, commitment, discipline, cooperation, and leadership. Candidates will be assessed the Kabid consists of 4 employees. The results obtained from the process by using AHP method was obtained that information from the four candidate kabid, then candidate A kabid is the most viable candidate due to A gain the most value from other candidates i.e. 0.330715 or 33.07%.