Relevant bibliographies by topics / Medical records Medical records Medical informatics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Medical records Medical records Medical informatics'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Medical records Medical records Medical informatics"

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Tange, Huibert J., Arie Hasman, Pieter F. de Vries Robbé, and Harry C. Schouten. "Medical narratives in electronic medical records." International Journal of Medical Informatics 46, no. 1 (August 1997): 7–29. http://dx.doi.org/10.1016/s1386-5056(97)00048-8.

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Lian, Ping, Kangmei Chong, Xinhai Zhai, and Yi Ning. "The quality of medical records in teleconsultation." Journal of Telemedicine and Telecare 9, no. 1 (February 1, 2003): 35–41. http://dx.doi.org/10.1258/135763303321159675.

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We collected and examined the medical records from telemedicine cases dealt with by the telemedicine centre of Shanghai Hospital No. 85. This centre handles the second largest number of teleconsultations in the entire network. There were 658 telemedicine cases in total. The medical records included the patient record in 599 cases (91%), transmitted images in 392 cases (60%), the consultant's opinion in 595 cases (90%) and a video-recording of the teleconsultation in 203 cases (31%). The quality of patient records was reviewed and found to be acceptable in 58% of cases. In total, 1794 radiology images (85% of all images) were transmitted via the telemedicine network. The consultant considered 352 of them (20%) to be unreadable on the screen (i.e. 80% of radiology images were considered to be acceptable). For optimum performance of telemedicine, the patient record and associated images should be delivered in advance and the relevant parts of the patient record should be available during a teleconsultation. Three aspects of the management of the medical records for teleconsultations are particularly important: multimedia collection, standardization of patient/record identification and classification, and information management.
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Gabrieli, Elmer R. "Automated medical office records." Journal of Medical Systems 11, no. 1 (February 1987): 59–68. http://dx.doi.org/10.1007/bf00992600.

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Md Zali, Mastura, Saiful Farik Mat Yatin, Mohd Razilan Abdul Kadir, Siti Noraini Mohd Tobi, Nurul Hanis Kamarudin, and Nik Nurul Emyliana Nik Ramlee. "Managing Medical Records in Specialist Medical Centres." International Journal of Engineering & Technology 7, no. 3.7 (July 4, 2018): 232. http://dx.doi.org/10.14419/ijet.v7i3.7.16358.

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A collection of facts about a patient’s life and health history of past and present illnesses and treatments is known as medical records. The health professionals were contributing to record the patient’s care. The responsibility in managing daily records that produced by each of department is by the Medical Records Department. It is a department under clinical support services with activities including managing of patient records, patient information production, management of medical reports, and hospital statistics. This article aims to discuss the challenge associated with managing medical records in the organization and how to handle and manage it with the records management as a tool to mitigate risk. Therefore, it is likely to prompt further research by addressing existing gaps towards improving service delivery that can contribute to the body of knowledge in the field of records management and archives generally.
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Quantin, Catherine, David-Olivier Jaquet-Chiffelle, Gouenou Coatrieux, Eric Benzenine, and François-André Allaert. "Medical record search engines, using pseudonymised patient identity: An alternative to centralised medical records." International Journal of Medical Informatics 80, no. 2 (February 2011): e6-e11. http://dx.doi.org/10.1016/j.ijmedinf.2010.10.003.

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Hawthorne, Kisha Hortman, and Lorraine Richards. "Personal health records: a new type of electronic medical record." Records Management Journal 27, no. 3 (November 20, 2017): 286–301. http://dx.doi.org/10.1108/rmj-08-2016-0020.

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Purpose This paper examines existing research on the topic of personal health records (PHRs). Areas covered include PHR/patient portal, recordkeeping, preservation planning, access and provider needs for future reuse of health information. Patient and physician PHR use and functionality, as well as adoption facilitators and barriers, are also reviewed. Design/methodology/approach The paper engages in a review of relevant literature from a variety of subject domains, including personal information management, medical informatics, medical literature and archives and records management literature. Findings The review finds that PHRs are extensions of electronic records. In addition, it finds a lack of literature within archives and records management that may lead to a less preservation-centric examination of the new PHR technologies that are desirable for controlling the lifecycle of these important new records-type. Originality/value Although the issues presented by PHRs are issues that can best be solved with the use of techniques from records management, there is no current literature related to PHRs in the records management literature, and that offered in the medical informatics literature treats the stewardship aspects of PHRs as insurmountable. This paper offers an introduction to the aspects of PHRs that could fruitfully be examined in archives and records management.
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Yasunaga, Hideo, Tomoaki Imamura, Shintaro Yamaki, and Hiroyoshi Endo. "Computerizing medical records in Japan." International Journal of Medical Informatics 77, no. 10 (October 2008): 708–13. http://dx.doi.org/10.1016/j.ijmedinf.2008.03.005.

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Trimmer, Ken, Leigh W. Cellucci, Carla Wiggins, and William Woodhouse. "Electronic Medical Records." International Journal of Healthcare Information Systems and Informatics 4, no. 3 (July 2009): 55–68. http://dx.doi.org/10.4018/jhisi.2009070104.

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Bassøe, C. F., and J. E. Rasmussen. "Semantic Analysis of Medical Records." Methods of Information in Medicine 32, no. 01 (1993): 66–72. http://dx.doi.org/10.1055/s-0038-1634897.

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Abstract:A program (LogStory) is described that was developed for the automatic semantic analysis of clinical narratives, stored in a computerized problem-oriented medical record (PROMED). The diagnoses were written in a free-text format during consultation, and later collected into diagnostic classes, e.g., diseases. A lexical parser automatically created dictionaries from the clinical narrative associated with each disease. Automatic (fuzzy) set operations were performed on the words associated with each class. The manifestations of 16 diseases were automatically extracted by pairwise operations on the word sets. The correlation between diseases and corresponding signs, symptoms and treatment was highly significant (p <0.001). Applying the difference operation on diseases with disjunct sets of clinical findings allowed the recovery of disease-specific knowledge. The evolution of a disease was accounted for, and the system was able to generalize its findings. The PROMED-LogStory concept enables the processing of natural language and may be a powerful tool for knowledge acquisition and clinical research.
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Murphy, Cynthia A., Kelly Merriman, Cindy Zabka, Marcella Penick, and Precy Villamayor. "Patient-Entered Electronic Healthcare Records With Electronic Medical Record Integration." CIN: Computers, Informatics, Nursing 26, no. 5 (September 2008): 302. http://dx.doi.org/10.1097/01.ncn.0000304828.47262.6c.

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Dissertations / Theses on the topic "Medical records Medical records Medical informatics"

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Gregory, Judith. "Sorcerer's apprentice : creating the electronic health record, re-inventing medical records and patient care /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2000. http://wwwlib.umi.com/cr/ucsd/fullcit?p9992380.

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Kirkham, David Andrew. "Patient-held medical records : a thermodynamic perspective." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296769.

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Song, Lihong. "Medical concept embedding with ontological representations." HKBU Institutional Repository, 2019. https://repository.hkbu.edu.hk/etd_oa/703.

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Learning representations of medical concepts from the Electronic Health Records (EHRs) has been shown effective for predictive analytics in healthcare. The learned representations are expected to preserve the semantic meanings of different medical concepts, which can be treated as features and thus benefit a variety of applications. Medical ontologies have also been explored to be integrated with the EHR data to further enhance the accuracy of various prediction tasks in healthcare. Most of the existing works assume that medical concepts under the same ontological category should share similar representations, which however does not always hold. In particular, the categorizations in the categorical medical ontologies were established with various factors being considered. Medical concepts even under the same ontological category may not follow similar occurrence patterns in the EHR data, leading to contradicting objectives for the representation learning. In addition, these existing works merely utilize the categorical ontologies. Actually, it has been noticed that ontologies containing multiple types of relations are also available. However, studies rarely make use of the diverse types of medical ontologies. In this thesis research, we propose three novel representation learning models for integrating the EHR data and medical ontologies for predictive analytics. To improve the interpretability and alleviate the conflicting objective issue between the EHR data and medical ontologies, we propose techniques to learn medical concepts embeddings with multiple ontological representations. To reduce the reliance on labeled data, we treat the co-occurrence statistics of clinical events as additional training signals, which help us learn good representations even with few labeled data. To leverage the various domain knowledge, we also consider multiple medical ontologies (CCS, ATC and SNOMED-CT) and propose corresponding attention mechanisms so as to take the best advantage of the medical ontologies with better interpretability. Our proposed models can achieve the final medical concept representations which align better with the EHR data. We conduct extensive experiments, and our empirical results prove the effectiveness of the proposed methods. Keywords: Bio/Medicine, Healthcare-AI, Electronic Health Record, Representation Learning, Machine Learning Applications
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Pagano, Michael Pro. "Communicating healthcare information : an analysis of medical records /." Full-text version available from OU Domain via ProQuest Digital Dissertations, 1990.

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Sethi, Iccha. "Clinician Decision Support Dashboard: Extracting value from Electronic Medical Records." Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/41894.

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Medical records are rapidly being digitized to electronic medical records. Although Electronic Medical Records (EMRs) improve administration, billing, and logistics, an open research problem remains as to how doctors can leverage EMRs to enhance patient care. This thesis describes a system that analyzes a patientâ s evolving EMR in context with available biomedical knowledge and the accumulated experience recorded in various text sources including the EMRs of other patients. The aim of the Clinician Decision Support (CDS) Dashboard is to provide interactive, automated, actionable EMR text-mining tools that help improve both the patient and clinical care staff experience. The CDS Dashboard, in a secure network, helps physicians find de-identified electronic medical records similar to their patient's medical record thereby aiding them in diagnosis, treatment, prognosis and outcomes. It is of particular value in cases involving complex disorders, and also allows physicians to explore relevant medical literature, recent research findings, clinical trials and medical cases. A pilot study done with medical students at the Virginia Tech Carilion School of Medicine and Research Institute (VTC) showed that 89% of them found the CDS Dashboard to be useful in aiding patient care for doctors and 81% of them found it useful for aiding medical students pedagogically. Additionally, over 81% of the medical students found the tool user friendly. The CDS Dashboard is constructed using a multidisciplinary approach including: computer science, medicine, biomedical research, and human-machine interfacing. Our multidisciplinary approach combined with the high usability scores obtained from VTC indicated the CDS Dashboard has a high potential value to clinicians and medical students.
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Steiner, Bridget Anne. "Electronic medical record implementation in nursing practice a literature review of the factors of success /." Thesis, Montana State University, 2009. http://etd.lib.montana.edu/etd/2009/steiner/SteinerB0509.pdf.

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This is a review of the current literature to discern what factors need to be present in an electronic medical record (EMR) implementation in order for it to be successful for nurses. An extensive literature search was performed by using databases CINAHL, MEDLINE, and Health Reference Center for primary sources of research that specifically addressed EMR implementation and nursing. A coding scheme was developed and applied to each article for analysis. It was found that fit of the EMR with nurse functions, education, and positive nurse attitude were the three most common factors associated with successful EMR implementation for nurses. Lack of computer system quality, lack of fit of the EMR with nurse functions, and time requirements of its use were most commonly associated with lack of success.
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Win, Khin Than. "The application of the FMEA risk assessment technique to electronic health record systems." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20050822.093730/index.html.

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Van, der Westhuizen Eldridge Welner. "A framework for personal health records in online social networking." Thesis, Nelson Mandela Metropolitan University, 2012. http://hdl.handle.net/10948/d1012382.

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Since the early 20th century, the view has developed that high quality health care can be delivered only when all the pertinent data about the health of a patient is available to the clinician. Various types of health records have emerged to serve the needs of healthcare providers and more recently, patients or consumers. These health records include, but are not limited to, Personal Health Records, Electronic Heath Records, Electronic Medical Records and Payer-Based Health Records. Payer-Based Health Records emerged to serve the needs of medical aids or health care plans. Electronic Medical Records and Electronic Health Records were targeted at the healthcare provider market, whereas a gap developed in the patient market. Personal Health Records were developed to address the patient market, but adoption was slow at first. The success of online social networking reignited the flame that Personal Health Records needed and online consumer-based Personal Health Records were developed. Despite all the various types of health records, there still seems to be a lack of meaningful use of personal health records in modern society. The purpose of this dissertation is to propose a framework for Personal Health Records in online social networking, to address the issue of a lack of a central, accessible repository for health records. In order for a Personal Health Record to serve this need it has to be of meaningful use. The capability of a PHR to be of meaningful use is core to this research. In order to determine whether a Personal Health Record is of meaningful use, a tool is developed to evaluate Personal Health Records. This evaluation tool takes into account all the attributes that a Personal Health Record which is of meaningful use should comprise of. Suitable ratings are allocated to enable measuring of each attribute. A model is compiled to facilitate the selection of six Personal Health Records to be evaluated. One of these six Personal Health Records acts as a pilot site to test the evaluation tool in order to determine the tool’s utility and effect improvements. The other five Personal Health Records are then evaluated to measure their adherence to the attributes of meaningful use. These findings, together with a literature study on the various types of health records and the evaluation tool, inform the building blocks used to present the framework. It is hoped that the framework for Personal Health Records in online social networking proposed in this research, may be of benefit to provide clear guidance for the achievement of a central or integrated, accessible repository for health records through the meaningful use of Personal Health Records.
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Spinks, Karolyn Annette. "The impact of the introduction of a pilot electronic health record system on general practioners' work practices in the Illawarra." Access electronically, 2006. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060712.153053/index.html.

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Erdil, Nadiye Özlem. "Systems analysis of electronic health record adoption in the U.S. healthcare system." Diss., Online access via UMI:, 2009.

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Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2009.
Includes bibliographical references.
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Books on the topic "Medical records Medical records Medical informatics"

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Informatics in medical imaging. Boca Raton: CRC Press, 2012.

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International Council on Medical and Care Compunetics, ed. Medical and care compunetics 6. Amsterdam: IOS Press, 2010.

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Slee, Vergil N. The endangered medical record: Ensuring its integrity in the age of informatics. St. Paul, Minn: Triaga Press, 2000.

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F, Bria William, ed. Digital communication in medical practice. London: Springer, 2009.

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Research, Institute for Career. Careers in health information technology: Medical records specialists. [Chicago, Ill.]: Institute for Career Research, 2003.

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Kloss, Linda. Implementing health information governance: Lessons from the field. Chicago, Ill: American Health Information Management Association, 2015.

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American Health Information Management Association, ed. Pocket glossary of health information management and technology. Chicago, Illinois: AHiMA, American Health Information Management Association, 2012.

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Health information technology: Hearing before the Subcommittee on Technology, Innovation, and Competitiveness of the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Ninth Congress, first session, June 30, 2005. Washington: U.S. G.P.O., 2011.

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Pocket glossary of health information management and technology. Chicago, Illinois: AHiMA, American Health Information Management Association, 2014.

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United States. Congress. House. Committee on Energy and Commerce. Subcommittee on Health. Legislative proposals to promote electronic health records and a smarter information system: Hearing before the Subcommittee on Health of the Committee on Energy and Commerce, House of Representatives, One Hundred Ninth Congress, second session, March 16, 2006. Washington: U.S. G.P.O., 2006.

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Book chapters on the topic "Medical records Medical records Medical informatics"

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Park, Seung L., Anil V. Parwani, and Liron Pantanowitz. "Electronic Medical Records." In Practical Informatics for Cytopathology, 121–27. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9581-9_13.

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Schatz, Bruce R., and Richard B. Berlin. "Medical Records for Health Systems." In Health Informatics, 115–33. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-452-4_7.

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Staccini, P., C. Daniel, T. Dart, and O. Bouhaddou. "Sharing Data and Medical Records." In Medical Informatics, e-Health, 315–48. Paris: Springer Paris, 2013. http://dx.doi.org/10.1007/978-2-8178-0478-1_13.

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Devarakonda, Murthy V., and Neil Mehta. "Cognitive Computing for Electronic Medical Records." In Health Informatics, 555–77. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20765-0_32.

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DesRoches, Catherine M., and Paola D. Miralles. "Meaningful Use of Health Information Technology: What Does it Mean for Practicing Physicians?" In Electronic Medical Records, 1–14. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-606-1_1.

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Priebe, Cedric J., and Eric Rose. "Workflow Automation with Electronic Medical Records." In Informatics in Primary Care, 152–65. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4613-0069-4_10.

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Huang, Hen-Hsen, Chia-Chun Lee, and Hsin-Hsi Chen. "Mining Professional Knowledge from Medical Records." In Brain Informatics and Health, 152–63. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09891-3_15.

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Draper, Ronald J. "Electronic Patient Records: Usability vs Security, with Special Reference to Mental Health Records." In Personal Medical Information, 151–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59023-8_12.

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van der Lei, J., R. F. Westerman, and B. M. Th Mosseveld. "Critiquing based on automated medical records: An evaluation of HYPERCRITIC." In Medical Informatics Europe ’90, 369–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-51659-7_70.

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Weber-Jahnke, Jens H., and Fieran Mason-Blakley. "On the Safety of Electronic Medical Records." In Foundations of Health Informatics Engineering and Systems, 177–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32355-3_11.

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Conference papers on the topic "Medical records Medical records Medical informatics"

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Villamor, Dennis Andrew R., Christian E. Pulmano, and Maria Regina Justina E. Estuar. "Understanding Adoption of Electronic Medical Records." In ICMHI 2020: 2020 4th International Conference on Medical and Health Informatics. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3418094.3418109.

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Boudreau, T., M. Davis, L. Delery, J. Korbich, S. Lambert, E. Vogel, B. Tawney, and R. Bennett. "Electronic medical records: a multidimensional analysis." In s and Information Engineering Design Symposium. IEEE, 2005. http://dx.doi.org/10.1109/sieds.2005.193281.

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Gloria, Chrismatovanie. "Compliance with Complete Filling of Patient's Medical Record at Hospital: A Systematic Review." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.04.29.

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ABSTRACT Background: The health information system, especially medical records in hospitals must be carried out accurately and completely. Medical records are important as evidence for the courts, education, research, and policy makers. This study aimed to investigate the factors affecting the compliance with completeness of filling patient’s medical re­cords at hospitals. Subjects and Methods: A systematic review was conducted by searching from Pro­Quest, Scopus, and National journals using keywords medical records, filling of medical records, and non- compliance filling medical records. The abstracts and full-text arti­cles published between 2014 to 2019 were selected for this review. A total of 62,355 arti­cles were conducted screening of eligibility criteria. The data were reported using PRIS­MA flow chart. Results: Eleven articles consisting of eight articles using observational studies and three articles using experimental studies met the eligible criteria. There were two articles analyzed systematically from the United States and India, two articles reviewed literature from the United States and England, and seven articles were analyzed statis­tically from Indonesia, America, Australia, and Europe. Six articles showed the sig­nificant results of the factors affecting non-compliance on the medical records filling at the Hospitals. Conclusion: Non-compliance with medical record filling was found in the hospitals under study. Health professionals are suggested to fill out the medical record com­pletely. The hos­pital should enforce compliance with complete medical record fill­ing by health professionals. Keywords: medical record, compliance, hospital Correspondence: Chrismatovanie Gloria. Hospital Administration Department, Faculty Of Public Health, Uni­­ver­sitas Indonesia, Depok, West Java. Email: chrismatovaniegloria@gmail.com. Mo­­­­bi­le: +628132116­1896 DOI: https://doi.org/10.26911/the7thicph.04.29
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Reategui, Ruth, Sylvie Ratte, Estefania Bautista-Valarezo, and J. F. Beltran-Valdivieso. "A network-based analysis of medical information extracted from electronic medical records." In 2020 XLVI Latin American Computing Conference (CLEI). IEEE, 2020. http://dx.doi.org/10.1109/clei52000.2020.00007.

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Tseng, Tzu-Wei, Cheng-Yi Yang, and Chien-Tsai Liu. "Designing Privacy Information Protection of Electronic Medical Records." In 2016 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2016. http://dx.doi.org/10.1109/csci.2016.0022.

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Paun, D., D. Sauciuc, O. Stan, O. Iosif, C. Dehelean, and L. Miclea. "Medical information system based on electronic healthcare records." In 2010 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR 2010). IEEE, 2010. http://dx.doi.org/10.1109/aqtr.2010.5520713.

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Milanova, Mariofanna, Roumen Kountchev, Vladimir Todorov, and Roumiana Kountcheva. "New Method for Lossless Compression of Medical Records." In 2008 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2008. http://dx.doi.org/10.1109/isspit.2008.4775649.

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Limsopatham, Nut, Craig Macdonald, and Iadh Ounis. "Learning to combine representations for medical records search." In SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2484028.2484177.

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Dube, Sibusisiwe, Siqabukile Sihwa, Thambo Nyathi, and Khulekani Sibanda. "QR Code Based Patient Medical Health Records Transmission: Zimbabwean Case." In InSITE 2015: Informing Science + IT Education Conferences: USA. Informing Science Institute, 2015. http://dx.doi.org/10.28945/2233.

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In Zimbabwe the health care delivery system is hierarchical and patient transfer from the lower level to the next higher level health care facility involves patients carrying their physical medical record card. A medical record card holds information pertaining to the patient’s medical history, pre-existing allergies, medical health conditions, prescribed medication the patient is currently taking among other details. Recording such patient information on a medical health card renders it susceptible to tempering, loss, and misinterpretation as well as susceptible to breaches in confidentiality. In this paper, we propose the application of Quick Response (QR) codes to secure and transmit this sensitive patient information from one level of the health care delivery system to another. Other security methods such as steganography could be used, but in this paper we propose the use of QR codes owing to the high proliferation of mobile phones in the country, high storage capacity, flexibility, ease of use and their capability to maintain data integrity as well as storage of data in any format.
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Lu, Qiuhao, Nisansa de Silva, Sabin Kafle, Jiazhen Cao, Dejing Dou, Thien Huu Nguyen, Prithviraj Sen, Brent Hailpern, Berthold Reinwald, and Yunyao Li. "Learning Electronic Health Records through Hyperbolic Embedding of Medical Ontologies." In BCB '19: 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3307339.3342148.

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Reports on the topic "Medical records Medical records Medical informatics"

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Gallegos, J., V. Hamilton, T. Gaylor, K. McCurley, and T. Meeks. Information integrity and privacy for computerized medical patient records. Office of Scientific and Technical Information (OSTI), September 1996. http://dx.doi.org/10.2172/392809.

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W, Nedra, Laura B. Strange, Sara M. Kennedy, Katrina D. Burson, and Gina L. Kilpatrick. Completeness of Prenatal Records in Community Hospital Charts. RTI Press, February 2018. http://dx.doi.org/10.3768/rtipress.2018.rr.0032.1802.

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We describe the completeness of prenatal data in maternal delivery records and the prevalence of selected medical conditions and complications among patients delivering at community hospitals around Atlanta, Georgia. Medical charts for 199 maternal-infant dyads (99 infants in normal newborn nurseries and 104 infants in newborn intensive care nurseries) were identified by medical records staff at 9 hospitals and abstracted on site. Ninety-eight percent of hospital charts included prenatal records, but over 20 percent were missing results for common laboratory tests and prenatal procedures. Forty-nine percent of women had a pre-existing medical condition, 64 percent had a prenatal complication, and 63 percent had a labor or delivery complication. Missing prenatal information limits the usefulness of these records for research and may result in unnecessary tests or procedures or inappropriate medical care.
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Uecker, S. A., and J. A. Borovies. Digitizing Marine Corps Medical Records. Fort Belvoir, VA: Defense Technical Information Center, February 2006. http://dx.doi.org/10.21236/ada491972.

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Seybold, Patricia. Who Owns Your Medical Records. Boston, MA: Patricia Seybold Group, July 2009. http://dx.doi.org/10.1571/psgp07-08-09cc.

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Fletcher, Chadwick B. Implementation of an Electronic Medical Records System. Fort Belvoir, VA: Defense Technical Information Center, May 2008. http://dx.doi.org/10.21236/ada493828.

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Baker, Laurence, Kate Bundorf, and Daniel Kessler. Expanding Patients' Property Rights In Their Medical Records. Cambridge, MA: National Bureau of Economic Research, October 2014. http://dx.doi.org/10.3386/w20565.

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Gardner, J. W., P. J. Amoroso, J. K. Grayson, J. Helmkamp, and B. H. Jones. Hospitalizations Due to Injury: Inpatient Medical Records Data. Fort Belvoir, VA: Defense Technical Information Center, January 1999. http://dx.doi.org/10.21236/ada376530.

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Ramaiah, Mala, Eswaran Subrahmanian, Ram D. Sriram, and Bettijoyce B. Lide. Workflow and electronic health records in small medical practices. Gaithersburg, MD: National Institute of Standards and Technology, 2010. http://dx.doi.org/10.6028/nist.ir.7732.

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Novakoski, William L. Leveraging Technology: Using Voice Recognition to Improve Medical Records Production at Walter Reed Army Medical Center. Fort Belvoir, VA: Defense Technical Information Center, August 1999. http://dx.doi.org/10.21236/ada420777.

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Dranove, David, Craig Garthwaite, Bingyang Li, and Christopher Ody. Investment Subsidies and the Adoption of Electronic Medical Records in Hospitals. Cambridge, MA: National Bureau of Economic Research, October 2014. http://dx.doi.org/10.3386/w20553.

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