Relevant bibliographies by topics / Medical records

Academic literature on the topic 'Medical records'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Medical records"

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R, Abinandana, and Srinivasa Reddy P. "Medical Records- a Legal Perspective." JOURNAL OF CLINICAL AND BIOMEDICAL SCIENCES 08, no. 4 (December 15, 2018): 109–12. http://dx.doi.org/10.58739/jcbs/v08i4.7.

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A medical record is a document containing chronologically written account of a patient’s examina-tion and treatment. A medical record apart from case sheet includes investigatory reports, investigatory samples, referral letter, discharge summary etc. Every registered medical practitioner is supposed to main-tain the proper medical report of his / her patient. The Indian government has laid down certain guidelines as to properly preserve the records. As a component of good medical practice it is necessary to maintain the medical records anticipating the litigation anytime. Key words: Medical records, Documentation, Electronic medical records, Medico legal report.
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Carpenter, Iain, Mala Bridgelal Ram, Giles P. Croft, and John G. Williams. "Medical records and record-keeping standards." Clinical Medicine 7, no. 4 (August 1, 2007): 328–31. http://dx.doi.org/10.7861/clinmedicine.7-4-328.

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Reddy, BH Srinivas, Dr J. N. Rao Dr.J.N.Rao, and Dr B. V. Subrahmanyam Dr.B.V.Subrahmanyam. "Medical Records –Boon Or Bane." Paripex - Indian Journal Of Research 2, no. 2 (January 15, 2012): 238–39. http://dx.doi.org/10.15373/22501991/feb2013/84.

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Minda Kusumah, Raden, and Jessica Putri Meyliyan. "Review Of Returning Medical Records In Outpatient Medical Record." KESANS : International Journal of Health and Science 1, no. 1 (October 30, 2021): 6–12. http://dx.doi.org/10.54543/kesans.v1i1.3.

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In returning the outpatient medical record file to thesection of the Medical Record Unit, Assembling there was a delay. This is because the return of medical record files has not been carried out according to Standard Operating Procedures, as a result, causing delays in the reporting system. The method used is qualitative using a descriptive approach. Data collection techniques by observation, interviews and literature study. This study aims to determine the return of former medical records of outpatients at Dayeuhkolot Health Center. The results of the study prove that the delay in returning outpatient medical record files at the Dayeuhkolot Health Center with presentations during the 1 week study amounted to 63 or 22% of 285 medical record files. Efforts have been made to disseminate information to all officers related to the efforts made by the person in charge of COVID-19 patients in returning medical record files on time.
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Cahalane, Seamus, James Deeny, and John O'Connell. "Medical Records." Books Ireland, no. 133 (1989): 115. http://dx.doi.org/10.2307/20626192.

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Nilegaonkar, Sujit, and PadmajS Kulkarni. "Medical records." Indian Journal of Medical and Paediatric Oncology 41, no. 1 (2020): 47. http://dx.doi.org/10.4103/ijmpo.ijmpo_49_20.

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TAN, S. Y. "Medical Records." Family Practice News 41, no. 14 (September 2011): 62–63. http://dx.doi.org/10.1016/s0300-7073(11)70788-5.

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Lane, Vic, and Peter Hayward. "Medical records." Lancet 353, no. 9149 (January 1999): 330. http://dx.doi.org/10.1016/s0140-6736(05)74890-x.

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Tan, S. Y. "Medical Records." Internal Medicine News 44, no. 12 (July 2011): 68. http://dx.doi.org/10.1016/s1097-8690(11)70632-1.

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Michael, Robin. "Paperless Medical Records." Australian Medical Record Journal 19, no. 4 (December 1989): 149–54. http://dx.doi.org/10.1177/183335838901900404.

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Flinders Medical Centre (FMC) in South Australia has a storage problem. The space available for filing existing medical records is full, while the demand for additional storage continues its linear growth. The hospital plans to use this “crisis” as an opportunity to review the entire basis for the management of the medical record and pilot an optical disk system as a precursor to paperless medical records. There are many constraints to this objective, but many advantages if the scheme proves successful. Michael describes the events which precipitated this project and outlines the steps in FMC's planned progression to a paperless record. (AMRJ, 1989, 19(4), 149–154).
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Dissertations / Theses on the topic "Medical records"

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Chang, Jaime. "Medication concepts, records, and lists in electronic medical record systems." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35551.

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Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2006.
Includes bibliographical references.
A well-designed implementation of medication concepts, records, and lists in an electronic medical record (EMR) system allows it to successfully perform many functions vital for the provision of quality health care. A controlled medication terminology provides the foundation for decision support services, such as duplication checking, allergy checking, and drug-drug interaction alerts. Clever modeling of medication records makes it easy to provide a history of any medication the patient is on and to generate the patient's medication list for any arbitrary point in time. Medication lists that distinguish between description and prescription and that are exportable in a standard format can play an essential role in medication reconciliation and contribute to the reduction of medication errors. At present, there is no general agreement on how to best implement medication concepts, records, and lists. The underlying implementation in an EMR often reflects the needs, culture, and history of both the developers and the local users. survey of a sample of medication terminologies (COSTAR Directory, the MDD, NDDF Plus, and RxNorm) and EMR implementations of medication records (OnCall, LMR, and the Benedum EMR) reveals the advantages and disadvantages of each. There is no medication system that would fit perfectly in every single context, but some features should strongly be considered in the development of any new system.
(cont.) A survey of a sample of medication terminologies (COSTAR Directory, the MDD, NDDF Plus, and RxNorm) and EMR implementations of medication records (OnCall, LMR, and the Benedum EMR) reveals the advantages and disadvantages of each. There is no medication system that would fit perfectly in every single context, but some features should strongly be considered in the development of any new system.
by Jaime Chang.
S.M.
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SadegiI, Nava, and Nava SadegiI. "Advances in Electronic Medical Records: Iris Medical." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/625141.

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Iris Medical is a SaaS platform for EMTs and Paramedics. We have streamlined the patient care report system, allowing our users to quickly, accurately, and safely input patient information. Our application reduces the need to take an ambulance out of service. With our software, our customers will be able to cut costs and save lives by reducing the time needed to take response units out of service and by increasing the validity, speed, and accuracy of patient data input. Our tablet software is lightweight and intuitive, providing data collection and analytics tools for use in any emergency response setting G ranging from traditional ambulance units in established markets, to less developed medical operations in emerging markets. The following thesis explains Iris Medical's business plan along with a step by step lead on revenue generation and growth.
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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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Rudin, Robert (Robert Samuel). "Making medical records more resilient." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41567.

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Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 72-77).
Hurricane Katrina showed that the current methods for handling medical records are minimally resilient to large scale disasters. This research presents a preliminary model for measuring the resilience of medical records systems against public policy goals and uses the model to illuminate the current state of medical record resilience. From this analysis, three recommendations for how to make medical records more resilient are presented. The recommendations are: 1) Federal and state governments should use the preliminary resilience model introduced here as the basis for compliance requirements for electronic medical record technical architectures. 2) Regional Health Information Organizations (RHIOs) should consider offering services in disaster management to healthcare organizations. This will help RHIOs create sustainable business models. 3) Storage companies should consider developing distributed storage solutions based on Distributed Hash Table (DHT) technology for medical record storage. Distributed storage would alleviate public concerns over privacy with centralized storage of medical records. Empirical evidence is presented demonstrating the performance of DHT technology using a prototype medical record system.
by Robert Rudin.
S.M.
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Domańska, Jeżyna. "Rethinking interfaces to medical records." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372066.

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Ba-Dhfari, Thamer Omer Faraj. "Hypothesis formulation in medical records space." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/hypothesis-formulation-in-medical-records-space(cfbc207f-89df-49f4-988b-d5c0204b84c5).html.

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Patient medical records are a valuable resource that can be used for many purposes including managing and planning for future health needs as well as clinical research. Health databases such as the clinical practice research datalink (CPRD) and many other similar initiatives can provide researchers with a useful data source on which they can test their medical hypotheses. However, this can only be the case when researchers have a good set of hypotheses to test on the data. Conversely, the data may have other equally important areas that remain unexplored. There is a chance that some important signals in the data could be missed. Therefore, further analysis is required to make such hidden areas become more obvious and attainable for future exploration and investigation. Data mining techniques can be effective tools in discovering patterns and signals in large-scale patient data sets. These techniques have been widely applied to different areas in medical domain. Therefore, analysing patient data using such techniques has the potential to explore the data and to provide a better understanding of the information in patient records. However, the heterogeneity and complexity of medical data can be an obstacle in applying data mining techniques. Much of the potential value of this data therefore goes untapped. This thesis describes a novel methodology that reduces the dimensionality of primary care data, to make it more amenable to visualisation, mining and clustering. The methodology involves employing a combination of ontology-based semantic similarity and principal component analysis (PCA) to map the data into an appropriate and informative low dimensional space. The aim of this thesis is to develop a novel methodology that provides a visualisation of patient records. This visualisation provides a systematic method that allows the formulation of new and testable hypotheses which can be fed to researchers to carry out the subsequent phases of research. In a small-scale study based on Salford Integrated Record (SIR) data, I have demonstrated that this mapping provides informative views of patient phenotypes across a population and allows the construction of clusters of patients sharing common diagnosis and treatments. The next phase of the research was to develop this methodology and explore its application using larger patient cohorts. This data contains more precise relationships between features than small-scale data. It also leads to the understanding of distinct population patterns and extracting common features. For such reasons, I applied the mapping methodology to patient records from the CPRD database. The study data set consisted of anonymised patient records for a population of 2.7 million patients. The work done in this analysis shows that methodology scales as O(n) in ways that did not require large computing resources. The low dimensional visualisation of high dimensional patient data allowed the identification of different subpopulations of patients across the study data set, where each subpopulation consisted of patients sharing similar characteristics such as age, gender and certain types of diseases. A key finding of this research is the wealth of data that can be produced. In the first use case of looking at the stratification of patients with falls, the methodology gave important hypotheses; however, this work has barely scratched the surface of how this mapping could be used. It opens up the possibility of applying a wide range of data mining strategies that have not yet been explored. What the thesis has shown is one strategy that works, but there could be many more. Furthermore, there is no aspect of the implementation of this methodology that restricts it to medical data. The same methodology could equally be applied to the analysis and visualisation of many other sources of data that are described using terms from taxonomies or ontologies.
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Stephen, Reejis 1977. "Context identification in electronic medical records." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28760.

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Thesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2004.
Includes bibliographical references (leaves 66-67).
In order to automate data extraction from electronic medical documents, it is important to identify the correct context of the extracted information. Context in medical documents is provided by the layout of documents, which are partitioned into sections by virtue of a medical culture instilled through common practice and the training of physicians. Unfortunately, formatting and labeling is inconsistently adhered to in practice and human experts are usually required to identify sections in medical documents. A series of experiments tested the hypothesis that section identification independent of the label on sections could be achieved by using a neural network to elucidate relationships between features of sections (like size, position from start of the document) and the content characteristic of certain sections (subject-specific strings). Results showed that certain sections can be reliably identified using two different methods, and described the costs involved. The stratification of documents by document type (such as History and Physical Examination Documents or Discharge Summaries), patient diagnoses and department influenced the accuracy of identification. Future improvements suggested by the results in order to fully outline the approach were described.
by Reejis Stephen.
S.M.
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Grim, Nancy R. "Protecting the confidentiality of medical records used in medical research an assessment of the adequacy of federal law /." Instructions for remote access. Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only, 2001. http://www.kutztown.edu/library/services/remote_access.asp.

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Thesis (M.P.A.)--Kutztown University of Pennsylvania, 2001.
Source: Masters Abstracts International, Volume: 45-06, page: 2942. Typescript. Abstract precedes thesis as preliminary leaves. Includes bibliographical references (leaves 78-81).
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Turk, Carrie. "Stages of concern for implementing the electronic medical records." Menomonie, WI : University of Wisconsin--Stout, 2007. http://www.uwstout.edu/lib/thesis/2007/2007turkc.pdf.

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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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Books on the topic "Medical records"

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American Health Information Management Association, ed. Documentation for medical records. Chicago, Ill: American Health Information Management Association, 2009.

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Royal College of General Practitioners. Library and Informaton Service. Medical records. Edited by Smith Robin Ridsdill. London: The College, 1987.

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Novak, Mary Ann. Hillcrest Medical Center: Beginning medical transcription course. 3rd ed. Cincinnati, OH: South-Western Pub. Co., 1991.

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A, Baldwin John, Acheson E. D. 1926-, and Graham W. J, eds. Textbook of medical record linkage. Oxford: Oxford University Press, 1987.

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Huffman, Edna K. Medical record management. 9th ed. Berwyn, Ill: Physicians' Record Co., 1990.

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Rita, Finnegan, Price Elizabeth 1914-, and American Medical Record Association, eds. Medical record management. 8th ed. Berwyn, Ill: Physicians' Record Co., 1985.

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McQuade, J. Stanley. Reading medical records. Durham, N.C: Carolina Academic Press, 2012.

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Division, United States General Accounting Office Human Resources. [Medical records control]. Washington, D.C: General Accounting Office, Human Resources Division, 1994.

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Skolnik, Neil S., ed. Electronic Medical Records. Totowa, NJ: Humana Press, 2011. http://dx.doi.org/10.1007/978-1-60761-606-1.

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Institute, Pennsylvania Bar. Mastering medical records. [Mechanicsburg, Pa.]: Pennsylvania Bar Institute, 2011.

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Book chapters on the topic "Medical records"

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Annas, George J. "Medical Records." In The Rights of Patients, 160–74. Totowa, NJ: Humana Press, 1992. http://dx.doi.org/10.1007/978-1-4612-0397-1_10.

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Eisenberg, Ronald L. "Medical Records." In Radiology and the Law, 128–31. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4612-2040-4_19.

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Slappendel, R. J., and F. J. van Sluijs. "Medical records." In Medical History and Physical Examination in Companion Animals, 32–48. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0459-3_5.

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Nundy, Samiran, Atul Kakar, and Zulfiqar A. Bhutta. "Medical Records." In How to Practice Academic Medicine and Publish from Developing Countries?, 429–40. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5248-6_45.

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AbstractThe term of Medical Records is vast and vaguely defined. It encompasses, but is not necessarily limited to, the admission sheet, history sheet, progress of a patient as well as the charts of his or her vital parameters, intake–output data, medications given, referrals, and discharge summary. Medical certificates, birth certificates, Medico-legal case sheets also fall into this purview.
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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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Sulkes, Stephen B. "Electronic Medical Records." In Health Care for People with Intellectual and Developmental Disabilities across the Lifespan, 335–43. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-18096-0_29.

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Kuperman, Gilad J., Reed M. Gardner, and T. Allan Pryor. "Medical Records Functions." In Computers and Medicine, 82–91. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3070-0_8.

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Nokeri, Tshepo Chris. "Medical Records Categorization." In Artificial Intelligence in Medical Sciences and Psychology, 131–44. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8217-5_8.

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Jennings, Todd A. "Electronic Medical Records." In Legal Nurse Consulting Principles and Practices, 213–28. 4th edition. | Abingdon, Oxon [UK] ; New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429283642-9.

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Sharma, Shashikant, and Saurabh Singh. "Medical Records Unit." In Planning & Designing Health Care Facilities in Developing Countries, 176–80. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9780367460884-30.

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Conference papers on the topic "Medical records"

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Tominanto, Mr, Eko Purwanto, and Novita Yuliani. "Outpatient Electronic Medical Records." In International Conference on Applied Science and Engineering (ICASE 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icase-18.2018.39.

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"Medical Relation Extraction from Electronic Medical Records." In WCSE 2022 Spring Event: 2022 9th International Conference on Industrial Engineering and Applications. WCSE, 2022. http://dx.doi.org/10.18178/wcse.2022.04.177.

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Tache, Irina Andra, Monica Dragoicea, Elena-Simona Apostol, and Ciprian-Octavian Truica. "Text Mining of Medical Records." In 2019 E-Health and Bioengineering Conference (EHB). IEEE, 2019. http://dx.doi.org/10.1109/ehb47216.2019.8969943.

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Bossen, Claus, Lotte Groth Jensen, and Flemming Witt. "Medical secretaries' care of records." In the ACM 2012 conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2145204.2145341.

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Ringenberg, Tatiana R., and Julia M. Taylor. "Semantic anonymization of medical records." In 2014 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2014. http://dx.doi.org/10.1109/smc.2014.6974119.

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Plaisant, Catherine, Daniel Heller, Jia Li, Ben Shneiderman, Rich Mushlin, and John Karat. "Visualizing medical records with LifeLines." In CHI98: ACM Conference on Human Factors and Computing Systems. New York, NY, USA: ACM, 1998. http://dx.doi.org/10.1145/286498.286513.

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Yellamma, Pachipala, Sai Siva Kathera, D. S. V. S. U. S. S. N. Sarma, and Yasaswin Palukuri. "Centralised Concurrency of Medical Records." In 2023 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2023. http://dx.doi.org/10.1109/icict57646.2023.10134315.

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Voorhees, Ellen M. "The TREC Medical Records Track." In BCB'13: ACM-BCB2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2506583.2506624.

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Assentoft, Joergen E., Arne Andreasen, Asbjorn M. Drewes, and B. O. Kristensen. "Noise filtering on echocardiographic records." In Medical Imaging VI, edited by Murray H. Loew. SPIE, 1992. http://dx.doi.org/10.1117/12.59436.

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Cohen, Simona, Flora Gilboa, and Uri Shani. "PACS and electronic health records." In Medical Imaging 2002, edited by Eliot L. Siegel and H. K. Huang. SPIE, 2002. http://dx.doi.org/10.1117/12.467019.

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Reports on the topic "Medical records"

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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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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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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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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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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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