Abstract
Breast cancer is the most frequently diagnosed cancer in women, with more than 2.1 million new diagnoses worldwide every year. Personalised treatment is critical to optimising outcomes for patients with breast cancer. A major advance in medical practice is the incorporation of Clinical Decision Support Systems (CDSSs) to assist and support healthcare staff in clinical decision-making, thus improving the quality of decisions and overall patient care whilst minimising costs. The usage and availability of CDSSs in breast cancer care in healthcare settings is increasing. However, there may be differences in how particular CDSSs are developed, the information they include, the decisions they recommend, and how they are used in practice. This systematic review examines various CDSSs to determine their availability, intended use, medical characteristics, and expected outputs concerning breast cancer therapeutic decisions, an area that is known to have varying degrees of subjectivity in clinical practice. Utilising the methodology of Kitchenham and Charter, a systematic search of the literature was performed in Springer, Science Direct, Google Scholar, PubMed, ACM, IEEE, and Scopus. An overview of CDSS which supports decision-making in breast cancer treatment is provided along with a critical appraisal of their benefits, limitations, and opportunities for improvement.
Highlights
Breast cancer is one of the most common types of cancer in European countries and the second leading cause of cancer death
The research questions are: (i) to identify and critically appraise what Clinical Decision Support Systems (CDSSs) are being used in breast cancer treatment and their targeted outcomes; (ii) to evaluate, based on the literature, the advantages and disadvantages of using CDSSs in breast cancer treatment; (iii) to evaluate the effects on patients’ lives as a consequence of CDSS use
There, we present an analysis of the available CDSSs for breast cancer treatment taking into account their target outcomes, input, method, results, main users, available format, access path, clinical question and dataset(s), among others
Summary
Breast cancer is one of the most common types of cancer in European countries and the second leading cause of cancer death. A breast cancer diagnosis impacts upon the health, lifestyle, work and family lives of affected individuals [3]. It carries with it a risk of severe morbidity and mortality, but side-effects of treatments that can leave physical and psycho-social complications that extend beyond treatment completion. An additional burden due to this disease can be economic hardship caused by loss of working hours and healthcare costs [4]. Breast cancer clinicians need accurate tools to help guide clinical decisions to improve patient prognosis, survival and quality of life whilst reducing associated healthcare costs [4]
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