Posted: January 17th, 2023

Critical Appraisal Evaluation Table

Critical Appraisal
Evaluation Table
Full citation of the selected article Article #1 Article #2 Article #3 Article #4
Campanella, P., Lovato, E., Marone, C., Fallacara, L., Mancuso, A., Ricciardi, W., & Specchia, M. L. (2015). The impact of electronic health records on healthcare quality: a systematic review and meta-analysis. The European Journal of Public Health, 26(1), 60-64. Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present, and future. Stroke and vascular neurology, 2(4), 230-243. Latifnejad, R. (2019). Critical appraisal of research evidence at a glance. Journal of Midwifery and Reproductive Health, 7(3), 1716-1717. Yu, K. H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature biomedical engineering, 2(10), 719.
Conceptual Framework
The study used a systematic review and meta-analysis design. The current study used a cross-sectional design. It used a cross-sectional case-control design. The study employed a systematic review design.
Design/Method
The study applied a systematic review design. The study was carried out by analyzing all the available research. A cross-sectional design was used in the current study. The study was carried out by analyzing information from the respondents. It used a transverse study design. The study was carried out on the basis of credibility of the responses due to the critical appraisal requirements. The study applied the use of transverse design. The reviewed analyzed data from the 48 articles that met the inclusion criteria.
Sample/Setting
The study involved 47 which met the inclusion criteria. There was no attrition rate in the review. 71 respondents were involved in the study. There was no attrition rate in the study. The study involved 121 respondents. There was no attrition rate in the study. 48 articles were selected for analysis. There was no attrition rate in the review.
Major Variables Studied
List and define dependent and independent variables The study comprised of independent variables including electronic health records and dependent variables including quality of healthcare. The study had independent variables including artificial intelligence and dependent variables including stroke. The study had independent variables including critical appraisal and dependent including research evidence. The study had independent variables including artificial intelligence and dependent quality of healthcare.
Measurement
Identify primary statistics used to answer clinical questions The study involved 47 which met the inclusion criteria from the 23, 398 citations identified. 71 respondents were involved in the study. The study involved 121 respondents. 48 articles were selected for analysis.
Data Analysis
Statistical or
qualitative
findings The data analysis from the 47 articles that met the inclusion criteria proved that electronic health records have a significant impact on patient outcomes. The study involved an analysis of information from the 71 respondents. The study comprised of an analysis of data received from 121 respondents. The study shows an analysis of 48 articles that met the inclusion criteria.
Findings and Recommendations
General findings and recommendations of the research The study found that electronic health records have a significant impact on health outcomes. The study recommends that further research is required in the field of electronic health records. The study indicated that artificial intelligence is important in the treatment of stroke. The study proposed further research on artificial intelligence in the health sector. Critical appraisal identified measures of assessing credible evidence in research. The study recommended the adoption of evidence-based research. The review shows the biomedical breakthroughs that have occurred due to the application of artificial intelligence. The study recommended that further reviews were required.
Appraisal
The study findings are reliable since they relied on systematic reviews. The reviews provided bias-free results which can be used in practical healthcare settings. The results can be implemented without any risk. The cross-sectional design of the study is reliable since it provides practical results. However, the study has weakness due to the few respondents involved. There is a high risk in applying the findings. The study involved 121 respondents and thus it had several weaknesses. There is a need to carry out more research to establish more findings since they bear a high risk currently. The review was effective in establishing the role of artificial intelligence in healthcare. More research is needed to establish the current results for implementation.
General Notes/Comments The systematic review presents the importance of reviews since it presents all the available research in electronic health records and their impact on health quality.

The article shows the significant progress of artificial intelligence in the past, present, and future. The critical appraisal was useful in identifying measures of assessing credible evidence. The review accounts for the significant progress made using artificial intelligence systems.

Levels of Evidence Table
Author and year of the selected article Article #1 Article #2 Article #3 Article #4
Campanella et al. (2015)

Jiang et al. (2017) Latifnejad (2019) Yu, Beam & Kohane (2018).
Study Design
The theoretical basis for the study
The research comprised of a systematic review. A transverse design was used in the study. It used a prevalence design. The study employed a systematic review design.
Sample/Setting
The number and
characteristics of
patients The study involved 47 which met the inclusion criteria. 71 respondents were involved in the study. The study involved 121 respondents. 48 articles were selected for analysis.
Evidence Level *
(I, II, or III)

Level I
Level III
Level III
Level III
Outcomes

The study found that electronic health records have a significant impact on health outcomes. The study indicated that artificial intelligence is important in the treatment of stroke. Critical appraisal identified measures of assessing credible evidence in research. The review shows the biomedical breakthroughs that have occurred due to the application of artificial intelligence.
General Notes/Comments The systematic review presents the importance of reviews since it presents all the available research in electronic health records and their impact on health quality.

The article shows the significant progress of artificial intelligence in the past, present, and future. The critical appraisal was useful in identifying measures of assessing credible evidence. The review accounts for the significant progress made using artificial intelligence systems.

Outcomes Synthesis Table
Author and year of the selected article Article #1 Article #2 Article #3 Article #4
Campanella et al. (2015)

Jiang et al. (2017) Latifnejad (2019) Yu, Beam & Kohane (2018).
Sample/Setting
The number and
characteristics of
patients The study involved 54 which met the inclusion criteria. 71 respondents were involved in the study. The study involved 121 respondents. 48 articles were selected for analysis.
Outcomes

The study found that electronic health records have a significant impact on health outcomes. The study indicated that artificial intelligence is important in the treatment of stroke. Critical appraisal identified measures of assessing credible evidence in research. The review shows the biomedical breakthroughs that have occurred due to the application of artificial intelligence.
Key Findings
The systematic review found that electronic health records had a significant impact on patient outcomes. The study found that stroke was easily treatable while using artificial intelligence. The critical appraise study found strategies for assessing credible evidence. The review presents the breakthroughs made using artificial intelligence systems.
Appraisal and Study Quality
The systematic review was established to have high quality since it was free from bias. The study involved various respondents who were representative of the research population.
The study used case-control design which was effective in validating the findings. The review shows all the available research making it free from bias.
General Notes/Comments The study suggested that electronic health records are crucial in supporting health outcomes.

The study praised the importance of artificial intelligence in the treatment of patients with stroke. The study established various methods of assessing credible evidence in research. The review is bias-free and thus the findings are reliable and credible.

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