The Effects of Clinical Decision Support Systems on Medication Safety: An Overview

Jia, Pengli; Zhang, Longhao; Chen, Jingjing; Zhao, Pujing; Zhang, Mingming

doi:10.1371/journal.pone.0167683

Cited by 96 publications

(90 citation statements)

References 47 publications

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“…As regards our second research question, namely to understand the advantages and disadvantages of CDSS use, we found that current CDSSs could potentially improve services within the healthcare system, time to decision, and health-related quality of life for patients; and reduce both healthcare costs and medical error rates [8,12]. However, as with any healthcare innovation, CDSSs should be rigorously assessed before dissemination into clinical practice, i.e., corroborate that indeed it improves clinical care or patient outcomes.…”

Section: Discussionmentioning

confidence: 99%

“…A CDSS has two principal action areas: (i) clinical decision-making and (ii) medical education [7]. Currently, CDSSs are used in many medical areas to improve healthcare system services [8], decision timing [8], and health-related quality of life for patients [8]; such systems can reduce both healthcare costs [8-10] and medical error rates [11][12][13]. CDSSs have potential benefits and drawbacks in implementation and use in clinical practice, specifically in oncology [14].…”

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confidence: 99%

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Clinical Decision Support Systems in Breast Cancer: A Systematic Review

Mazo

Kearns

Mooney

et al. 2020

Cancers

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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.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Clinical Decision Support Systems in Breast Cancer: A Systematic Review

Mazo

Kearns

Mooney

et al. 2020

Cancers

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“…Outside the scope of oncology, several reviews reported positive effects of CDSSs on process outcomes. The review of Jia et al assessed the effects of CDSSs on medication prescription, medication dose and other drug related outcomes [37]. This study reported that CDSSs significantly impact medication administration in 108 out 143 studies included [37].…”

Section: Agreements and Disagreements With Literaturementioning

confidence: 99%

“…The review of Jia et al assessed the effects of CDSSs on medication prescription, medication dose and other drug related outcomes [37]. This study reported that CDSSs significantly impact medication administration in 108 out 143 studies included [37]. The review of Bright et al assessed CDSSs with a broad scope in healthcare [38].…”

Section: Agreements and Disagreements With Literaturementioning

confidence: 99%

The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review

Klarenbeek¹,

Weekenstroo²,

Sedelaar³

et al. 2020

Cancers

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Background: To deal with complexity in cancer care, computerized clinical decision support systems (CDSSs) are developed to support quality of care and improve decision-making. We performed a systematic review to explore the value of CDSSs using automated clinical guidelines, Artificial Intelligence, datamining or statistical methods (higher level CDSSs) on the quality of care in oncology. Materials and Methods: The search strategy combined synonyms for 'CDSS' and 'cancer.' Pubmed, Embase, The Cochrane Library, Institute of Electrical and Electronics Engineers, Association of Computing Machinery digital library and Web of Science were systematically searched from January 2000 to December 2019. Included studies evaluated the impact of higher level CDSSs on process outcomes, guideline adherence and clinical outcomes. Results: 11,397 studies were selected for screening, after which 61 full-text articles were assessed for eligibility. Finally, nine studies were included in the final analysis with a total population size of 7985 patients. Types of cancer included breast cancer (63.1%), lung cancer (27.8%), prostate cancer (4.1%), colorectal cancer (3.1%) and other cancer types (1.9%). The included studies demonstrated significant improvements of higher level CDSSs on process outcomes and guideline adherence across diverse settings in oncology. No significant differences were reported for clinical outcomes. Conclusion: Higher level CDSSs seem to improve process outcomes and guidelines adherence but not clinical outcomes. It should be noticed that the included studies primarily focused on breast and lung cancer. To further explore the impact of higher level CDSSs on quality of care, high-quality research is required.

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“…Although periodic medication review can lead to prevention of PIP [15,16], there is no consensus on what such a review should comprise. In recent years, it has become apparent that Clinical Decision Support Systems (CDSSs) can provide support in medication reviews and could possibly reduce medication-related errors [17][18][19]. CDSSs could therefore contribute in improving quality of care and outcomes in older patients.…”

Section: Introductionmentioning

confidence: 99%

Medication in older patients reviewed multiple ways (MORE) study

et al. 2019

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Background Polypharmacy in older patients can lead to potentially inappropriate prescribing. The risk of the latter calls for effective medication review to ensure proper medication usage and safety. Objective Provide insight on the similarities and differences of medication review done in multiple ways that may lead to future possibilities to optimize medication review. Setting This study was conducted in Zuyderland Medical Centre, the second largest teaching hospital in the Netherlands. Method This descriptive study compares the quantity and content of remarks identified by medication review performed by a geriatrician, outpatient pharmacist, and Clinical Decision Support System. The content of remarks is categorized in seven categories of possible pharmacotherapeutic problems: 'indication without medication', 'medication without indication', 'contra-indication/interaction/side-effect', 'dosage problem', 'double medication', 'incorrect medication' and 'therapeutic drug monitoring'. Main outcome measure Number and content of remarks on medication review. Results The Clinical Decision Support System (1.8 ± 0.8 vs. 0.9 ± 0.9, p < 0.001) and outpatient pharmacist (1.8 ± 0.8 vs. 0.9 ± 0.9, p = 0.045) both noted remarks in significantly more categories than the geriatricians. The Clinical Decision Support System provided more remarks on 'double medication', 'dosage problem' and 'contraindication/interaction/side effects' than the geriatrician (p < 0.050), while the geriatrician did on 'medication without indication' (p < 0.001). The Clinical Decision Support System noted significantly more remarks on 'contraindication/interaction/side effects' and 'therapeutic drug monitoring' than the outpatient pharmacist, whereas the outpatient pharmacist reported more on 'indication without medication' and 'medication without indication' than the Clinical Decision Support System (p ≤ 0.007). Conclusion Medication review performed by a geriatrician, outpatient pharmacist, and Clinical Decision Support System provides different insights and should be combined to create a more comprehensive report on medication profiles.

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The Effects of Clinical Decision Support Systems on Medication Safety: An Overview

Cited by 96 publications

References 47 publications

Clinical Decision Support Systems in Breast Cancer: A Systematic Review

Clinical Decision Support Systems in Breast Cancer: A Systematic Review

The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review

Medication in older patients reviewed multiple ways (MORE) study

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