Table 2 PRISMA 2009 Checklist- Big Data Write-up
From: The power of big data mining to improve the health care system in the United Arab Emirates
Section/topic | # | Checklist item | Reported on page # |
|---|---|---|---|
TITLE | |||
Title | 1 | Systematic review for “Big data & health care system.” | |
ABSTRACT | |||
Structured summary | 2 | Research method limited to secondary data through a published journal on “PubMed” website was done, and limitation of the studies to the keyword “Big data mining and Healthcare” was done. The period was selected between January 2016 and September 2020, limited to English language and free full text | Supplementary file – Microsoft Excel |
INTRODUCTION | |||
Rationale | 3 | Many studies describe the importance of harvesting big data in different sectors, including health care; however, the authors did not locate a single research within the context of the United Arab Emirates (UAE). Therefore, the authors are verifying the applicabilities of various studies finding within the UAE health sector. The motivation for this systematic review is to provide new researchers insights into the field of big data usage in health care systems, together with its associated challenges, or as a guide for researchers interested in exploring the opportunities and solving the challenges of big data implementation in emerging countries such as the UAE. Thus the following research questions are designed, which this paper aims to answer: With RQ1, we can investigate the role of big data usage in improving health care systems and its’ industry. Moreover, RQ2 allows us to find the existing solutions to enhance the quality of care services in health care systems using big data. RQ3, on the other hand, gives an insight into how various challenges can be mitigated to enhance the implementation of big data technologies in health care systems | Supplementary file – Microsoft Excel |
Objectives | 4 | This research study aims to gain further insight using a systematic approach to review the role and effectiveness of big data in the area of health care within the UAE. The objectives of the study using PRISMA are: •RQ1: What is big data's role in the health care system? •RQ2: What are the potential opportunities to enhance quality-of-care services through integrating big data in the health care system? •RQ3: How to best understand the challenges of implementing and using big data technologies? | Supplementary file – Microsoft Excel |
METHODS | |||
Protocol and registration | 5 | The research was done through a single web engine, “PubMed” and all the collection criteria like language, full free text, and period were entered through the website and the keywords | Supplementary file – Microsoft Excel |
Eligibility criteria | 6 | Studies were included in qualitative studies, published journal from January 2016 to September 2020, limited to English language, full free text | Supplementary file – Microsoft Excel |
Information sources | 7 | The database was “PubMed”, no authored as contacted as the study limited to full free text only | Supplementary file – Microsoft Excel |
Search | 8 | The search was done through the website” PubMed” through keywords (Big data and Healthcare), which resulted in thousands of studies that were irrelevant to the research aim and objective. Then the keywords were more specified to (Mining bigdata and Healthcare), restricted to the English language and time (2016–2020) resulted in 685 reviews | Supplementary file – Microsoft Excel |
Study selection | 9 | A systematic review of the studies was conducted, and the articles were judged according to their objectives, the approach of the description methodology and study design, use of authentic data sources, validity and reliability of the study method, analysis, consideration of the ethical issues, comprehensive description of finding and outcomes, the appropriateness of the tools used for data mining, the suitability of the qualitative methodology, use of valid research designs, and clearly stated findings of the research | Supplementary file – Microsoft Excel |
Data collection process | 10 | The search was done through the website” PubMed” through keywords (Big data and Healthcare), which resulted in thousands of studies that were irrelevant to the research aim and objective. Then the keywords were more specified to (Mining bigdata and Healthcare), restricted to the English language and time (2016–2020) resulting in 685 reviews Then scanning of the abstract was done to check the relevant studies relevant to the objective was highlighted for further screening. Sixty-seven studies at the first stage were included, and the rest were excluded. Then a quick review of the studies was done and checked if it was relevant to the study aim and objective. Quantitative studies, and interview were excluded as well. Studies that highlight a different tool for data mining are excluded as well. This resulted in exhaustive studies, which included 22 reviews | Supplementary file – Microsoft Excel |
Data items | 11 | List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made | Supplementary file – Microsoft Excel |
Risk of bias in individual studies | 12 | Describe methods used for assessing the risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis | Supplementary file – Microsoft Excel |
Summary measures | 13 | State the principal summary measures (e.g., risk ratio, the difference in means) | Supplementary file – Microsoft Excel |
Synthesis of results | 14 | Describe the methods of handling data and combining results of studies, if done, including measures of consistency (e.g., I2) for each meta-analysis | Supplementary file – Microsoft Excel |