Abstract
C linical decision support systems (CDSS) are software that provide direct aid to clinicians during the decision-making process 1 by retrieving patient characteristics , assessing patient information, and utilizing a clinical knowledge base to recommend possible treatment for the patient. 2,3 CDSS have been used in multiple fields for over 50 years 4 and have proven to be a useful invention for the improvement of clinical monitoring through computing. 5 CDSS can be divided into three categories: (1) focusing attention systems; (2) patient-specific recommendation systems; and (3) information management systems that critically analyze the information of each patient. 6 CDSS are an effective information technology that could help cause reduction in clinical errors and help clinicians make better decisions, thus resulting in an increase in the overall quality and efficiency of provided treatment. 7 Although the performance of the health care sector significantly improves with the adoption of CDSS, professionals are often unwilling to adopt these technologies and to use them when performing diagnoses. 3 Physician acceptance of clinical information technologies is necessary for the successful implementation of CDSS in a hospital setting, so the outcomes and antecedents of professional autonomy have a prominent impact on the adoption of CDSS. 8 Moreover, the increased integration of supercomputing science in the field of medicine is influencing the knowledge-sharing behavior of professionals and the conversion of data into knowledge; therefore, this integration has become crucial for achieving precision in personalized patient care and precision medicine. 9 These issues, which occur in both developed and underdeveloped countries, require immediate solutions. The implementation of CDSS can result in improved adherence to clinical guidelines for the prevention of a number of diseases. 10 CDSS can also prove to be an effective method for reducing analytical errors and for warning physicians regarding potentially harmful drug interactions. 11 Moreover, the decision-making Purpose: To assess the effectiveness of clinical decision support systems (CDSS) on the survival of natural teeth. Materials and Methods: The PubMed, ERIC, Google Scholar, and Medline databases were searched for full-text articles published between 2009 and 2018. Eight studies evaluating the use of CDSS for clinical decision-making were included in the systematic review. Results: CDSS were an effective technique for assisting clinicians in their daily practice. Conclusion: CDSS are effective and can be adopted in daily practice to assist clinicians in handling cases that require sound knowledge of the principles associated with the treatment.
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CITATION STYLE
Sayed, M. (2019). Effectiveness of Clinical Decision Support Systems for the Survival of Natural Teeth: A Community Guide Systematic Review. The International Journal of Prosthodontics, 32(4), 333–338. https://doi.org/10.11607/ijp.6162
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