The primary care counsellor's support systems

Author(s):  
Valerie Garrett
Keyword(s):  
2021 ◽  
Author(s):  
Hector Acosta-Garcia ◽  
Ingrid Ferrer-López ◽  
Juan Ruano-Ruiz ◽  
Bernardo Santos-Ramos ◽  
Teresa Molina-López

Abstract Background Computerized clinical decision support systems are used by clinicians at the point-of-care to improve quality of healthcare processes (prescribing error prevention, adherence to clinical guidelines...) and clinical outcomes (preventive, therapeutic, and diagnostics). Attempts to summarize results of computerized clinical decision support systems to support prescription in primary care have been challenging, and most systematic reviews and meta-analyses failed due to an extremely high degree of heterogeneity present among the included primary studies. The aim of our study will be to synthesize the evidence, considering all methodological factors that could explain these differences, and to build an evidence and gap map to identify important remaining research questions. Methods A literature search will be conducted from January 2010 onwards in Medline, Embase, The Cochrane Library and Web of Science databases. Two reviewers will independently screen all citations, full-text and abstract data. The study methodological quality and risk of bias will be appraised using appropriate tools if applicable. A flow diagram with the screened studies will be presented, and all included studies will be displayed using interactive evidence and gap maps. Results will be reported in accordance with recommendations from The Campbell Collaboration on the development of evidence and gap maps. Discussion Evidence behind computerized clinical decision support systems to support prescription use in primary care, has so far been difficult to be synthesized. Evidence and gap maps represent an innovative approach that has emerged and is increasingly being used to address a broader research question, where multiple types of intervention and outcomes reported may be evaluated. Broad inclusion criteria have been chosen with regards to study designs, in order to collect all available information. Regarding the limitations we will only include English and Spanish language studies from the last 10 years, we will not perform a grey literature search, and we will not carry out a meta-analysis due to the predictable heterogeneity of available studies. Systematic Review registration: This study is registered in Open Science Framework https://bit.ly/2RqKrWp


BMJ ◽  
1999 ◽  
Vol 319 (7220) ◽  
pp. 1281-1281 ◽  
Author(s):  
B. C Delaney ◽  
D. A Fitzmaurice ◽  
A. Riaz ◽  
F D R. Hobbs

Author(s):  
Taku Harada ◽  
Taiju Miyagami ◽  
Kotaro Kunitomo ◽  
Taro Shimizu

Diagnosis is one of the crucial tasks performed by primary care physicians; however, primary care is at high risk of diagnostic errors due to the characteristics and uncertainties associated with the field. Prevention of diagnostic errors in primary care requires urgent action, and one of the possible methods is the use of health information technology. Its modes such as clinical decision support systems (CDSS) have been demonstrated to improve the quality of care in a variety of medical settings, including hospitals and primary care centers, though its usefulness in the diagnostic domain is still unknown. We conducted a scoping review to confirm the usefulness of the CDSS in the diagnostic domain in primary care and to identify areas that need to be explored. Search terms were chosen to cover the three dimensions of interest: decision support systems, diagnosis, and primary care. A total of 26 studies were included in the review. As a result, we found that the CDSS and reminder tools have significant effects on screening for common chronic diseases; however, the CDSS has not yet been fully validated for the diagnosis of acute and uncommon chronic diseases. Moreover, there were few studies involving non-physicians.


2019 ◽  
Vol 161 ◽  
pp. 441-448
Author(s):  
Guardian Yoki Sanjaya ◽  
Lutfan Lazuardi ◽  
Mubasysyir Hasanbasri ◽  
Hari Kusnanto

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