scholarly journals Cost of installing and operating an electronic clinical decision support system for maternal health care: case of Tanzania rural primary health centres

2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Happiness Pius Saronga ◽  
Maxwell Ayindenaba Dalaba ◽  
Hengjin Dong ◽  
Melkizedeck Leshabari ◽  
Rainer Sauerborn ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Maternal Health ◽  
Clinical Decision Support ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Primary Health ◽  
Primary Health Centres ◽  
Health Centres ◽  
Electronic Clinical Decision Support

scholarly journals Cost-Effectiveness of Clinical Decision Support System in Improving Maternal Health Care in Ghana

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0125920 ◽  
Author(s):  
Maxwell Ayindenaba Dalaba ◽  
Patricia Akweongo ◽  
Raymond Akawire Aborigo ◽  
Happiness Pius Saronga ◽  
John Williams ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Cost Effectiveness ◽  
Maternal Health ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Maternal Health Care

scholarly journals District nurses’ experiences of using a clinical decision support system and an assessment tool at elderly care units in primary health care: a qualitative study

2021 ◽  
Vol 22 ◽  
Author(s):  
Annica Lagerin ◽  
Lena Törnkvist ◽  
Johan Fastbom ◽  
Lena Lundh
Keyword(s):  
Older Adults ◽  
Health Care ◽  
Primary Health Care ◽  
Decision Support ◽  
Clinical Decision Support System ◽  
Elderly Care ◽  
Medication Use ◽  
Clinical Decision ◽  
Primary Health ◽  
District Nurses

Abstract Aim: The present study aimed to describe the experience of district nurses (DNs) in using a clinical decision support system (CDSS) and the safe medication assessment (SMA) tool during patient visits to elderly care units at primary health care centres. Background: In Swedish primary health care, general practitioners (GPs) prescribe and have the responsibility to regularly review older adults’ medications, while DN (nurses specialised in primary health care) play an important role in assessing older adults’ ability to manage their medications, detecting potential drug-related problems and communicating with patients and GPs about such problems. In a previous feasibility study, we found that DNs who use a combination of a CDSS and the SMA tool identified numerous potentially harmful or dangerous factors and took a number of nursing care actions to improve the safety and quality of patients’ medication use. In telephone interviews, patients indicated that they were positive towards the assessment and interventions. Methods: Individual interviews with seven DNs who worked at six different primary health care centres in Region Stockholm were carried out in 2018. In 2019, an additional group interview was conducted with two of the seven DNs so they could discuss and comment on preliminary findings. Qualitative content analysis was used to analyse the interview transcripts. Findings: Using the tools, the DNs could have a natural conversation about medication use with older adults. They could get a clear picture of the older adults’ medication use and thus obtain information that could facilitate collaboration with GPs about this important component of health care for older adults. However, for the tools to be used in clinical practice, some barriers would have to be overcome, such as the time-consuming nature of using the tools and the lack of established routines for interprofessional collaboration regarding medication discussions.

Advanced Issues of Health Informatics and Clinical Decision Support System in Global Health Care

2018 ◽  
pp. 153-170 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Global Health ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Health Informatics ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Global Health Care

This chapter indicates the advanced issues of health informatics; the advanced issues of Clinical Decision Support System (CDSS); CDSS and Computerized Physician Order Entry (CPOE); the false positive alerts in CDSS; and CDSS and biomedical engineering. Health informatics and CDSS are the advanced health care technologies with the support of many technological fields. Health informatics and CDSS apply various computerized devices to provide enhanced health-related outcomes in terms of problem solving, analytical thinking, and decision making. Health informatics and CDSS help clinicians and health care providers to make complex information useful in supporting clinical decisions, thus delivering the best standard of care for each patient. The chapter argues that utilizing health informatics and CDSS has the potential to increase health outcomes and reach strategic goals in global health care.

Artificial intelligence-based clinical decision-support system improves cancer treatment and patient satisfaction.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18303-e18303
Author(s):  
Zuochao Wang ◽  
Zhonghe Yu ◽  
Xuejing Zhang
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Treatment Options ◽  
Clinical Decision ◽  
Diagnostic Model ◽  
Consultation System

e18303 Background: Traditional diagnostic model for cancer heavily relies on physicians and their teams’ knowledge. However, under this diagnostic model, patients’ source of information is quite limited. Cancer patients usually fill with negative emotion. Lack of knowledge to the disease and treatment options further leads to less confidence to their treatment outcome. Methods: In order to improve their faith in getting proper treatment and the hope for surviving the deadly disease, we has introduced an artificial intelligence based clinical decision-support system, the Watson for Oncology (WFO), since May-2018. WFO is developed by IBM, it assesses information from a patient’s medical record, evaluates medical evidence, and displays potential treatment options. Our oncologist can then apply their own expertise to identify the most appropriate treatment options. We have generated a new 7-step consultation system with the help of WFO. That include 1: introduce the WFO to patients, 2: patients express their demands and expectations, 3: the oncologist presents patient’s medical condition, 4: discussion with other members in the consultation team, 5: input patients’ information into WFO system and review treatment options, 6: discuss and finalize treatment options with patients, 7: feedbacks form patients after consultation. 70 patients who were hospitalized from May-2018 to Dec-2018 were divided into two groups, 50 patients volunteered to be assigned to the new 7-step consultation system and 20 patients stayed with the traditional diagnostic method to find them treatment options. All patients were followed up by questionnaire. Results: The results showed that patients in the 7-step consultation group presented significantly higher satisfaction rate towards treatment options, confidence level to their health care workers, and willingness to follow the treatment option when compared to patients in the traditional diagnostic group. Conclusions: The WFO assisted 7-step consultation system not only provides a more efficient way to find treatment options, but also improves patients’ understanding to their disease and possible side effects towards the treatment. Most importantly, patients build stronger confidence with their health care team and are willing to believe they will benefit from the treatment plans.

Sign in / Sign up

Export Citation Format

Share Document