ABSTRACT A lot amounts of data i.e information that related to make wonders with work is called as 'BIG DATA' Last two decades big data treated as a special interest and had a lot potentiality because of hidden features in it. To generate, store, and analyze big data with an aim to improve the services they provide in multiple no of small & large scale industries. As we are considering the health care industry for this big data is providing multiple opportunities like records of patients, inflow & outflow of the hospitals. It also generates a significant portion of big data relevant to public healthcare in biomedical research. In order to derive meaningful information analysis & proper management of data is required. In the haystack seeking solution in big data will be quickly analyzable just like finding a needle. in big data analysis various challenges associated with each step of handling big data surpassed by using high-end computing solutions. for improving public health healthcare providers provide relevant solutions & to systematically generate and analyze big data requirements to be fully loaded with efficient infrastructure. in big data can change the game by opening new avenues for modern healthcare with an efficient management, analysis, and interpretation. vigorous instructions are given by the various industries like public sectors followed by healthcare for the betterment of services and as well as financial upgrades. by taking the revolution in healthcare industry we can accommodate personnel medicine included by therapies in strong integration manner. Keywords: Healthcare, Biomedical Research, Big Data Analytics, Internet of Things, Personalized Medicine, Quantum Computing Cite this Article: Krishnachaitanya.Katkam and Harsh Lohiya, Patient Centric Management Analysis and Future Prospects in Big Data Healthcare, International Journal of Computer Engineering and Technology (IJCET), 13(3), 2022, pp. 76-86.

This data accompanies the following publication: Title: Data and systems for medication-related text classification and concept normalization from Twitter: Insights from the Social Media Mining for Health (SMM4H) 2017 shared task Journal: Journal of the American Medical Informatics Association (JAMIA) The evaluation data (in addition to the training data) was used for the SMM4H-2017 shared tasks, co-located with AMIA-2017 (Washington DC).

For the period from 2016 to 2020, the natural science and medical & health sciences were the two academic fields in which Greek scientific publications were cited the most. These fields both saw around 313,000 publications during the four year period, with engineering & technology fields seeing 152,000 citations over the same period.

Abstract Celebrating the 25 years of existence of the Journal Ciência & Saúde Coletiva (C&SC), this paper analyzed 375 documents published between 2000-2019 as an integral part of the editorial of collective oral health. The production analysis aimed to understand how oral health core appears in publications and how it could have contributed to knowledge on the population’s health-disease, specific public policies, education, and management of oral health services in the SUS. The process employed bibliometric and documental analysis. We could show the authors’ territorial distribution, their extensive collaboration network, and the dimension of citations in publications, including the international plan. The Brazilian states most present in the publications were São Paulo and Minas Gerais, followed by authors from Pernambuco, Rio Grande do Sul, and Santa Catarina. Citations were more frequent in Brazil (85.14%), followed by the United States (2.31%), Portugal (1.34%), and Australia (1.34%). We concluded that, despite the limitations, the C&SC showed unequivocally a powerful instrument for the dissemination of scientific production from the perspective of collective oral health, enabling the exchange of information and facilitating the integration between researchers and enabling a path to its consolidation.

Objective: To quantify data sharing policy compliance at the BMJ by analysing the rate of data sharing practices, and investigate attitudes and examine barriers towards data sharing. Design: Observational study. Setting: The BMJ research archive. Participants: 160 randomly sampled BMJ research articles, excluding meta-analysis and systematic reviews. Main outcome measures: Percentages of research articles that indicated the availability of their raw datasets in their data sharing statements and those that provided their datasets upon request. Results: Fifty out of 160 (31%) research articles indicated the availability of their datasets. Twelve used publicly available data and the remaining 38 were sent email requests to access their datasets. Only 1 publicly available dataset could be accessed and only 6 out of 38 shared their data via e-mail. So only 7/160 research articles shared their datasets, 4.4% (95% confidence interval: 1.8% to 8.8%). Conclusions: Despite the BMJ's strong data sharing policy, sharing rates are low. Possible explanations for low data sharing rates could be: the wording of the BMJ data sharing policy, which leaves room for individual interpretation and possible loopholes; that our email requests ended up in researchers spam folders; and, that researchers are not rewarded in the scientific community for sharing their data. It might be time for a more effective data sharing policy and better incentives for health and medical researchers to share their data.

International Journal of Contemporary Medical Research Abstract & Indexing - ResearchHelpDesk - International Journal of Contemporary Medical Research - IJCMR, an official publication of International Society for Contemporary Medical Research (Registered under Government of India, Society Registration Act No - 21, 1860), is a peer reviewed, international, print and online, open access journal with MONTHLY (since January, 2016) publication. It is a multidisciplinary journal to provide a forum for the presentation and criticism of original, innovative and thought provocative ideas in medical and allied specialties. IJCMR publishes new, challenging and radical ideas, so long as they are coherent and clearly expressed. The types of article accepted include original articles, review articles, case reports, and letters to the editor. Clinical microbiology relevant immunology, pathophysiology, genetics, epidemiological, and genomics studies are also welcome. International Journal of Contemporary Medical Research is an internationally targeted official publication. All articles have to be original articles that have not been published elsewhere or are being considered for publication in other journals. All articles submitted will be peer reviewed by experts. Receipt of the manuscript will be acknowledged by email. Every effort will be made to complete the review process within 2 weeks and communicated to the corresponding author. Papers should be submitted to ijcmr.journal@gmail.com. The Editorial board will strive for the quality of the journal and will also index the journal in various indexing bodies and the information will be updated on the journal website from time to time. We welcome all your submissions. I hope you will consider IJCMR for your next submission. Periodicity of the journal - Quarterly (Since inception to 2015 June (Volume 2; Issue 2) Bimonthly (Since 2015 July (Volume 2; Issue 3)) Monthly (Since January 2016 (Volume 3; Issue 1)) Scope of Journal The journal covers all aspects of medical sciences from genes to humans. Articles reporting clinical observations, experimental studies and theoretical concepts are all welcome, and especially welcome high quality review articles from distinguished authors, and original articles reporting new findings in medical and allied sciences. The journal covers technical and clinical studies related to health, ethical and social issues in the fields of Science and allied specialties. Articles with clinical interest and implications will be given preference. Journal editors, welcome thought provoking papers on areas listed above. Decisions about papers will be communicated to authors within 3 weeks of submission. IJCMR publishes original research work that contributes significantly to further the scientific knowledge and research in Medical, Dental, Pharmaceutical Sciences etc.. and aims to provide a platform to researchers to publish their articles. It comprises peer- reviewed articles as its core material which includes original research papers, case reports and review articles as well. We encourage the submission of manuscripts that cross disciplines and also studies that address universal problems of human health. Fields Anesthesiology, Anatomy, Animal Research, Ayurveda, Sidha & Unani (All Branches) Biochemistry, Biotechnology, Cardiology, Community, Dermatology, Dentistry (All Branches), Education, Emergency Medicine, Endocrinology, Ethics, Ear Nose and Throat, Forensic, Gastroenterology, Genetics, Haematology, Health Management and Policy, Homeopathy, Immunology and Infectious Diseases, Intensive Care, Internal Medicine, Microbiology, Health Management and Policy, Immunology and Infectious Diseases, Intensive Care, Internal Medicine, Microbiology, Nephrology / Renal, Neurology and Neuro-Surgery, Nutrition, Oncology, Orthopaedics, Ophthalmology, Obstetrics and Gynaecology, Paediatrics and Neonatology, Pharmacology, Pharmacy (All branches) Physiology, Pathology, Plastic Surgery, Psychiatry/Mental Health, Rehabilitation, Radiology, Statistics, Surgery, Yoga and alternative therapies.

Background This bibliometric analysis examines the top 50 most-cited articles on COVID-19 complications, offering insights into the multifaceted impact of the virus. Since its emergence in Wuhan in December 2019, COVID-19 has evolved into a global health crisis, with over 770 million confirmed cases and 6.9 million deaths as of September 2023. Initially recognized as a respiratory illness causing pneumonia and ARDS, its diverse complications extend to cardiovascular, gastrointestinal, renal, hematological, neurological, endocrinological, ophthalmological, hepatobiliary, and dermatological systems. Methods Identifying the top 50 articles from a pool of 5940 in Scopus, the analysis spans November 2019 to July 2021, employing terms related to COVID-19 and complications. Rigorous review criteria excluded non-relevant studies, basic science research, and animal models. The authors independently reviewed articles, considering factors like title, citations, publication year, journal, impact fa..., A bibliometric analysis of the most cited articles about COVID-19 complications was conducted in July 2021 using all journals indexed in Elsevier’s Scopus and Thomas Reuter’s Web of Science from November 1, 2019 to July 1, 2021. All journals were selected for inclusion regardless of country of origin, language, medical speciality, or electronic availability of articles or abstracts. The terms were combined as follows: (“COVID-19†OR “COVID19†OR “SARS-COV-2†OR “SARSCOV2†OR “SARS 2†OR “Novel coronavirus†OR “2019-nCov†OR “Coronavirus†) AND (“Complication†OR “Long Term Complication†OR “Post-Intensive Care Syndrome†OR “Venous Thromboembolism†OR “Acute Kidney Injury†OR “Acute Liver Injury†OR “Post COVID-19 Syndrome†OR “Acute Cardiac Injury†OR “Cardiac Arrest†OR “Stroke†OR “Embolism†OR “Septic Shock†OR “Disseminated Intravascular Coagulation†OR “Secondary Infection†OR “Blood Clots† OR “Cytokine Release Syndrome†OR “Paediatric Inflammatory Multisystem Syndrome†OR “Vaccine..., , # Data of top 50 most cited articles about COVID-19 and the complications of COVID-19

This dataset contains information about the top 50 most cited articles about COVID-19 and the complications of COVID-19. We have looked into a variety of research and clinical factors for the analysis.

Description of the data and file structure

The data sheet offers a comprehensive analysis of the selected articles. It delves into specifics such as the publication year of the top 50 articles, the journals responsible for publishing them, and the geographical region with the highest number of citations in this elite list. Moreover, the sheet sheds light on the key players involved, including authors and their affiliated departments, in crafting the top 50 most cited articles.

Beyond these fundamental aspects, the data sheet goes on to provide intricate details related to the study types and topics prevalent in the top 50 articles. To enrich the analysis, it incorporates clinical data, capturing...

Please cite the following paper when using this dataset:N. Thakur, "Twitter Big Data as a Resource for Exoskeleton Research: A Large-Scale Dataset of about 140,000 Tweets from 2017–2022 and 100 Research Questions", Journal of Analytics, Volume 1, Issue 2, 2022, pp. 72-97, DOI: https://doi.org/10.3390/analytics1020007AbstractThe exoskeleton technology has been rapidly advancing in the recent past due to its multitude of applications and diverse use cases in assisted living, military, healthcare, firefighting, and industry 4.0. The exoskeleton market is projected to increase by multiple times its current value within the next two years. Therefore, it is crucial to study the degree and trends of user interest, views, opinions, perspectives, attitudes, acceptance, feedback, engagement, buying behavior, and satisfaction, towards exoskeletons, for which the availability of Big Data of conversations about exoskeletons is necessary. The Internet of Everything style of today’s living, characterized by people spending more time on the internet than ever before, with a specific focus on social media platforms, holds the potential for the development of such a dataset by the mining of relevant social media conversations. Twitter, one such social media platform, is highly popular amongst all age groups, where the topics found in the conversation paradigms include emerging technologies such as exoskeletons. To address this research challenge, this work makes two scientific contributions to this field. First, it presents an open-access dataset of about 140,000 Tweets about exoskeletons that were posted in a 5-year period from 21 May 2017 to 21 May 2022. Second, based on a comprehensive review of the recent works in the fields of Big Data, Natural Language Processing, Information Retrieval, Data Mining, Pattern Recognition, and Artificial Intelligence that may be applied to relevant Twitter data for advancing research, innovation, and discovery in the field of exoskeleton research, a total of 100 Research Questions are presented for researchers to study, analyze, evaluate, ideate, and investigate based on this dataset.

Data mining and analytics in healthcare management : applications and tools is a book. It was written by David L. Olson and published by : Springer in 2023.

Data collection statistics.

This dataset identifies data from publications underlying the Open Science Health Barometer on clinical trials and observational studies. The website ‘https://barometredelascienceouverte.esr.gouv.fr/sante’ offers a global view of the results of the Open Science Health Barometer. This dataset lists clinical trials and observational studies present in the clinicaltrials.org or EUCTR registers and which have been conducted, at least in part, in France. Details of the method are set out in ‘https://barometredelascienceouverte.esr.gouv.fr/a-propos/methodologie’ (https://barometredelascienceouverte.esr.gouv.fr/a-propos/methodologie) The data are available in csv format:https://storage.gra.cloud.ovh.net/v1/AUTH_32c5d10cb0fe4519b957064a111717e3/bso_dump/bso-clinical-trials_20221209.csv.gz and in jsonl format (json lines): HTTPS://STORAGE.GRA.CLOUD.OVH.NET/V1/AUTH_32C5D10CB0FE4519B957064A111717E3/BSO_DUMP/BSO-CLINICAL-TRIALS_20221209.JSONL.GZ The jsonl file contains richer than the csv file. ISRCTN: identifier in the ISRCTN registry NCTId: NCT identifier in clinicaltrials.gov WHO: who Identifier (WHO) Acronym: test Acronym all_sources: sources used (clinicaltrials and/or EUCTR) delay_first_results_completion: number of days between the end of the trial (complete) and the first reporting date (publication in a journal or submission of a summary) delay_start_completion: number of days between start and end of the trial design_allocation: randomised/non-randomised enrollment_count: number of participants EudraCT: EudraCT identifier

The data collected through the APGAR test aimed to measure family functions and changes in a postmodern context. Over three years, this study has been conducted to 77 individuals, 71 of whom were adults while the remaining 6 were underage people. These participants belong to 37 families from different social strata in the city of Quito-Ecuador, which were selected through convenience and non-probabilistic sampling. The APGAR design used a modification of the work [1], extrapolated to the Ecuadorian context. The data has been collected, cleaned, and unified in a single file in a CSV structured format and without missing values. The participants’ personal information has been concealed to guarantee their identity remains anonymous. Additionally, those who participated in the project have given their consent for the use of their information for academic purposes, which include: scientific journals, presentations, and digital academic repositories. The structured data, within the file, has a distribution in the form of rows and columns. Each row (instance) represents an APGAR test executed on an individual, while the columns represent the different variables (attributes) of the dataset. Each APGAR test has metadata collected during the process. The metadata corresponding to the informative data of the individuals are located in attributes 1 to 7 of the dataset and their description is as follows. • Person_ID: Identifier of each individual who participated in the APGAR test. Discrete quantitative variable. • Year: Data collection year. Discrete quantitative variable. • Family_ID: Unique identifier of each family. Discrete quantitative variable. • Age: Participant age in years. Discrete quantitative variable. • Familiar_Rol: Self-identification of the role played by the individual in the family. Nominal qualitative variable with open categories. Seven different classes were identified: father, mother, son, daughter, nephew, grandmother, and stepfather. • Gender: Self-identification of the individual's gender. Nominal qualitative variable with open categories. Two classes were identified: male and female. • Location: Geographical location of the family home. Nominal qualitative variable with closed categories determined by the official zones that make up the metropolitan district of Quito. Nineteen classes were identified in total. In the Ecuadorian context, a person is of legal age if he has reached an age equal to or greater than 18 years. Therefore, in order to discern these two segments of subpopulations within the family, the design of two different question types for the APGAR tests was required. The Questions (Qi) for adults were: • Q1: I am satisfied with the help I receive from my family when I have a problem or need. • Q2: I am satisfied with the participation that my family gives me and allows me. • Q3: I am satisfied with how my family accepts and supports my desire to undertake new activities. • Q4: I am satisfied with how my family expresses affection and responds to my emotions, such as anger, sadness, love, etc. • Q5: I am satisfied with how we share in my family: a) time to be together, b) spaces in the house, c) money. The Questions (Qi) for underage people were: • Q1: When I am worried about anything, I can ask my family for help. • Q2: I like how my family talks and shares their problems with me. • Q3: I like how my family allows me to do the new things I want to do. • Q4: I like what my family does when I am happy, sad, angry, etc. • Q5: I like how my family and I spend time together. On the other hand, for each question, 5 possible answers were designed with different weights based on a linear symmetric likert scale, and with the same ratings for adults and underage people. The Likert scale weighted Answers (Ai), offered for the participants were: • A1: Never (0 Points) • A2: Almost Never (1 Point) • A3: Sometimes (2 Points) • A4: Almost Always (3 Points) • A5: Always (4 Points) Variables 8 to 32 correspond to the execution of the APGAR test, per se, and were coded in the form of a tuple, Question-Answer (Qi-Aj). The ‘i’ value identifies the 5 types of questions, while the ‘j’ index determines the 5 types of answers. All the tuples Qi-Aj were encoded through a boolean variable (0/1). Where ‘0’ indicates the absence of a value in the tuple and ‘1’ the presence of a value in the tuple. All the APGAR tests were taken in Spanish since it is the official language of Ecuador, and then transcribed into English. Although the data has been collected by using the APGAR test to measure family functions and their changes in the postmodern context, it is important to note that the collected data could be used for other different purposes.

This is the raw data for the manuscript "Knowledge syntheses in medical education: A bibliometric analysis" by Maggio, Costello, Norton, Driessen, and Artino. The data contain the citations, including the DOI and PMID, for all 963 knowledge syntheses included in the study. This study has also been published in a peer reviewed journal:

Maggio LA, Costello JA, Norton C, Driessen EW, Artino Jr AR. Knowledge syntheses in medical education: A bibliometric analysis. Perspectives on Medical Education. 2020 Oct 22:1-9.

The abstract for the study is as follows:

Purpose This bibliometric analysis maps the landscape of knowledge syntheses in medical education. It provides scholars with a roadmap for understanding where the field has been and where it might go in the future. In particular, this analysis details the venues in which knowledge syntheses are published, the types of syntheses conducted, citation rates they produce, and altmetric attention they garner.

Method In 2020, the authors conducted a bibliometric analysis of knowledge syntheses published in 14 core medical education journals from 1999 to 2019. To characterize the studies, metadata was extracted from Pubmed, Web of Science, Altmetrics Explorer, and Unpaywall.

Results The authors analyzed 963 knowledge syntheses representing 3.1% of total articles published (n=30,597). On average, 45.9 knowledge syntheses were published annually (SD=35.85, Median=33), and there was an overall 2,620% increase in the number of knowledge syntheses published from 1999 to 2019. The journals each published, on average, a total of 68.8 knowledge syntheses (SD=67.2, Median=41) with Medical Education publishing the most (n=189; 19%). Twenty-one knowledge synthesis types were identified; the most prevalent types were systematic reviews (n=341; 35.4%) and scoping reviews (n=88; 9.1%). Knowledge syntheses were cited an average of 53.80 times (SD=107.12, Median=19) and received a mean Altmetric Attention Score of 14.12 (SD=37.59, Median=6).

Conclusions There has been considerable growth in knowledge syntheses in medical education over the past 20 years, contributing to medical education’s evidence base. Beyond this increase in volume, researchers have introduced methodological diversity in these publications, and the community has taken to social media to share knowledge syntheses. Implications for the field, including the impact of synthesis types and their relationship to knowledge translation, are discussed.

PubMed comprises more than 26 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

This is the post-processed mobile air monitoring data, with the methods described in the science journal publication. This dataset is associated with the following publication: Brantley, H., G. Hagler, S. Herndon, P. Massoli, M. Bergin, and A. Russell. Characterization of Spatial Air Pollution Patterns Near a Large Railyard Area in Atlanta, Georgia. International Journal of Environmental Research and Public Health. Molecular Diversity Preservation International, Basel, SWITZERLAND, 16(4): 535, (2019).

Type and use of health data investigated across included studies.

Journal of Dermatological Science Acceptance Rate - ResearchHelpDesk - The Journal of Dermatological Science accepts online submissions only. EES is a web-based submission and review system. Authors may submit manuscripts and track their progress through the system to publication. Reviewers can download manuscripts and submit their opinions to the editor. Editors can manage the whole submission/review/revise/publish process. The Journal of Dermatological Science publishes high quality peer-reviewed manuscripts covering the entire scope of dermatology, from molecular studies to clinical investigations. Laboratory and clinical studies which provide new information will be reviewed expeditiously and published in a timely manner. The Editor and his Editorial Board especially encourage the publication of research based on a process of bilateral feedback between the clinic and the laboratory, in which incompletely understood clinical phenomena are examined in the laboratory and the knowledge thus acquired is directly reapplied in the clinic. This continuous feedback will refine and expand our understanding of both clinical and scientific domains. Although the Journal is the official organ of the Japanese Society for Investigative Dermatology, it serves as an international forum for the work of all dermatological scientists. With an internationally renowned Editorial Board, the Journal maintains high scientific standards in the evaluation and publication of manuscripts. The Journal also publishes invited reviews, commentaries, meeting announcements and book reviews. Letters to the Editor reporting new results or even negative scientific data, if they contribute to advances in dermatology are encouraged. Letters to the Editor should be less than 1000 words with up to 2 figures or tables. Abstracting and Indexing Science Citation Index Web of Science Embase BIOSIS Citation Index PubMed/Medline Abstracts on Hygiene and Communicable Diseases Elsevier BIOBASE Biological Abstracts BIOSIS Previews Chemical Abstracts Current Awareness in Biological Sciences Current Contents Embase Index Veterinarius Inpharma Weekly Medical and Surgical Dermatology PharmacoEconomics and Outcomes News Protozoological Abstracts Reactions Weekly Review of Medical and Veterinary Entomology Review of Aromatic and Medicinal Plants Review of Medical and Veterinary Mycology Sugar Industry Abstracts Veterinary Bulletin Wheat, Barley and Triticale Abstracts Abstracts of Mycology Horticultural Science Abstracts Review of Agricultural Entomology CABI Information Cancerlit Global Health Inside Conferences ISI Science Citation Index MANTIS Social SciSearch TOXFILE BIOSIS Toxicology SIIC Data Bases Elsevier BIOBASE Current Contents - Clinical Medicine Scopus

✅ Advances in Nursing Science ISSN - ResearchHelpDesk - Advances in Nursing Science - Consistently ranked as one of the most-read and most assigned journals by faculties of graduate programs in nursing, Advances in Nursing Science (ANS) is intellectually challenging, innovative, and progressive, and features articles from a wide range of scholarly traditions. The journal particularly encourages works that speak to the need for global sustainability and that take an intersectional approach, recognizing class, color, sexual and gender identity, and other dimensions of human experience related to health. Articles in ANS are peer-reviewed and chosen for their pioneering perspectives and for their significance in contributing to the evolution of the discipline of nursing. RG Journal Impact: 0.53 * *This value is calculated using ResearchGate data and is based on average citation counts from work published in this journal. The data used in the calculation may not be exhaustive. RG Journal impact history 2018 / 2019 0.53 2017 0.10 2016 0.24 2015 0.32 2009 0.30 2008 0.39 2007 0.70 2006 0.75 2005 0.83 2004 0.80 2003 0.99 2002 0.75 2001 0.69 2000 0.54 Additional details Cited half-life 0.00 Immediacy index 0.07 Eigenfactor 0.00 Article influence 0.33 Website description Advances in Nursing Science website Other titles Advances in nursing science, Advances in nursing science ISSN 0161-9268 OCLC 4064666 Material type Periodical, Internet resource Document type Journal / Magazine / Newspaper, Internet Resource

Indian journal of public health Acceptance Rate - ResearchHelpDesk - Indian Journal of Public Health is a peer-reviewed international journal published Quarterly by the Indian Public Health Association. It is indexed/abstracted by the major international indexing systems like Index Medicus/MEDLINE, SCOPUS, PUBMED, etc. The journal allows free access (Open Access) to its contents and permits authors to self-archive the final accepted version of the articles. The journal’s full text is available online at www.ijph.in. Abstracting and Indexing Information The journal is registered with the following abstracting partners: Baidu Scholar, CNKI (China National Knowledge Infrastructure), EBSCO Publishing's Electronic Databases, Ex Libris – Primo Central, Google Scholar, Hinari, Infotrieve, National Science Library, ProQuest, TdNet, Wanfang Data The journal is indexed with, or included in, the following: DOAJ, Emerging Sources Citation Index, Indian Science Abstracts, IndMed, MEDLINE/Index Medicus, Scimago Journal Ranking, SCOPUS, Web of Science

Electronic medical records (EMRs) have great potential to improve healthcare processes and outcomes. They are increasingly available in Nigeria, as in many developing countries. The impact of their introduction has not been well studied. We sought to synthesize the evidence from primary studies of the effect of EMRs on data quality, patient-relevant outcomes and patient satisfaction. We identified and examined five original research articles published up to May 2023 in the following medical literature databases: PUBMED/Medline, EMBASE, Web of Science, African Journals Online and Google Scholar. Four studies examined the influence of the introduction of or improvements in the EMR on data collection and documentation. The pooled percentage difference in data quality after introducing or improving the EMR was 142% (95% CI: 82% to 203%, p-value < 0.001). There was limited heterogeneity in the estimates (I2 = 0%, p-heterogeneity = 0.93) and no evidence suggestive of publication bias. The 5th study assessed patient satisfaction with pharmacy services following the introduction of the EMR but neither had a comparison group nor assessed patient satisfaction before EMR was introduced. We conclude that the introduction of EMR in Nigerian healthcare facilities meaningfully increased the quality of the data.