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Relevant bibliographies by topics / Medical records Medical writing

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Academic literature on the topic 'Medical records Medical writing'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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Journal articles on the topic "Medical records Medical writing"

1

Pagano, Michael P., and David Mair. "Writing Medical Records." Journal of Technical Writing and Communication 16, no. 4 (October 1986): 331–41. http://dx.doi.org/10.2190/wy9t-634e-v2jt-jdvq.

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A study was undertaken both to evaluate how medical students are taught to write patient records and to examine the writing done by doctors. Typical medical records, written by medical doctors, were also evaluated. A single questionnaire was sent to eighty-four medical school professors, twenty law school faculty, and five practicing attorneys. The questionnaire asked how medical records were used and what the legal implications were in authoring a patient record. The medical professionals were also asked how their schools taught medical writing. The questionnaire pointed out that most medical schools teach less than ten hours of medical writing in their curricula and that patient records are not written with an understanding of the various audiences, purposes, and uses for medical documents. Two radiology reports are discussed in terms of their clarity and usefulness for medical and extra-medical readers. The study concludes that medical students should be taught a composing process so that they will understand the audience, purpose, and use for the patient records they write.

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McCalman, Janet. "Writing the Women's-Hospital History with Medical Records." Health and History 1, no. 2/3 (1999): 132. http://dx.doi.org/10.2307/40111339.

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Ou, Hui, Xiaoyan Tan, and Ling Li. "Case Analysis on Writing Standards of Medical Records." Chinese Medical Record English Edition 1, no. 8 (August 2013): 347–49. http://dx.doi.org/10.3109/23256176.2013.842719.

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Nurhayati, Yunita Wisda Tumarta Arif, and Ahmad Yusron Yunizar. "Rancang Bangun Website Rekam Medis Elektronik di Fasilitas Pelayanan Kesehatan Praktik Dokter." Infokes: Jurnal Ilmiah Rekam Medis dan Informatika Kesehatan 10, no. 2 (September 28, 2020): 49–54. http://dx.doi.org/10.47701/infokes.v10i2.1033.

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Electronic medical records record electronic medical records which contain personal data, demographic data, social data, clinical / medical data. Processing of medical record documents at doctor's practice health facilities is still done manually, starting from patient registration, writing examination history, and storing medical record documents. One of the efforts to overcome these obstacles is by building an Electronic Medical Record website. The website development method uses the development life cycle system. Medical records are processed from input patient data, diagnostic data, action data, drug data, officer data, registration data, examination data. Then the data is processed to produce reports, including patient data, and examination data. The electronic medical record website used can simplify the processing of medical record data.

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Ratnawati, Ratnawati. "Analysis The Level of Compliance of Hospital Human Resources in Writing The Status of Inpatient Medical Record Dr Sayidiman Hospital and The Influences Factors." Journal for Quality in Public Health 3, no. 2 (May 12, 2020): 423–33. http://dx.doi.org/10.30994/jqph.v3i2.92.

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The quality of medical records in hospitals also determines the quality of service, completeness of writing Medical Records documents correctly and correctly is very important. The purpose of this study was to analyze the level of compliance of hospital human resources in writing the status of the inpatient Medical Record Dr. Sayidiman Magetan Regional Hospital and the factors that influence it. The design of this study was an observational quantitative study with a cross section approach with the focus of the research directed to be analyzing the level of compliance of hospital human resources in writing the status of the inpatient Medical Record Dr Sayidiman Magetan Regional Hospital and the factors that influenced it with a sample of 192 respondents taken with the Simple Random Sampling technique. The findings found that most of the respondents have high motivation that is 144 respondents (75%). Most of the respondents care to write in the medical record that is 160 respondents (83.3%). Most of the respondents have a high appreciation of 136 respondents (70.8%). Most of the respondents did not comply doing medical record writing of 107 respondents (55.7%). Based on the Linear Regression analysis the motivation variable on compliance p-value 0.015 <0.05, the variable concern for compliance p-value 0.025 <0.05 then H0 is rejected so there is the influence of motivation and concern for compliance with medical record writing by health professionals in Regional General Hospital Dr. Sayidiman Magetan. Linear regression variable rewards for compliance shows that the p-value of 0.665> 0.05 then H0 is accepted so it is concluded that there is no effect of rewards on compliance with writing medical records by health professionals at the Dr Sayidiman Magetan Regional General Hospital. It is expected that respondents can comply to fill out medical records so that the delivery of care to passion can be well integrated

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Cahyaharnita, Rezky Ami. "Synchronization of Electronic Medical Record Implementation Guidelines in National E-Health Strategies." SOEPRA 5, no. 2 (April 2, 2020): 209. http://dx.doi.org/10.24167/shk.v5i2.2430.

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Medical records are made in writing, complete and clear or electronically. Medical records are the basis of medical services to patients. Paper medical records increase the amount of paper waste in Indonesia. A national e-health strategy is a comprehensive approach to efforts in the national health sector. Electronic medical records are more effective because of better time management. The formulation of the problem in this article covers the reasons, criteria, and implementation of electronic medical records. The research method used is descriptive qualitative research with a statute approach. The criteria for a good electronic medical record are integrated data from various sources, data collected at the service point, and supporting service providers in decision making. The expected electronic medical record is to be integrated with the health service facility information system program without neglecting the confidentiality aspect. Therefore, the government needs to make regulations on the technical implementation of electronic medical records.

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Berutu, Chris Anggi Natalia, Yanti Agustina, and Sonya Airini Batubara. "KEKUATAN HUKUM PEMBUKTIAN REKAM MEDIS KONVESIONAL DAN ELEKTRONIK BERDASARKAN HUKUM POSITIF INDONESIA." Jurnal Hukum Samudra Keadilan 15, no. 2 (December 21, 2020): 305–17. http://dx.doi.org/10.33059/jhsk.v15i2.2686.

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Medical records are files containing patient records, which are made chronological time. There are two types of medical records and in general have been regulated in Permenkes Number 269 / MENKES / PER / III / 2008 concerning Medical Records, namely conventional medical records and electronic medical records. One of the benefits of medical records is as evidence in the law enforcement process. This type of research is normative juridical research and is analytical descriptive in nature. The data source used in this research is secondary data, which is obtained from books, journals, expert opinions and others. The data collection technique used is to collect data in this study through documentation studies in the form of data collection from literature or scientific writing in accordance with the object under study. Data analysis is data obtained and then analyzed qualitatively. From the study it is concluded that the difference in the strength of evidence lies in the non-fulfillment of the requirements of electronic medical records as written / letter evidence, in accordance with the Criminal Code Book 4, Concerning Evidence and Expiration, Second Chapter on Evidence by Writing and KUHAP Article 184 paragraph (1) letter c and d, as well as Articles 187 and 188 paragraph (2) letter b. This means that conventional medical records can be used as original written evidence, whereas electronic medical records cannot. The cause of the difference is because both the Criminal Code and the Criminal Procedure Code, the power of written evidence, is only in writing, in the form of original letters and / or authentic deeds. The data used are (1) primary data in the form of statutory regulations, results of interviews with hospitals and courts, (2) secondary data through literature studies of various laws and regulations and books / journals to obtain expert opinion. The results of this research are expected to be published through (1) scientific articles in Accredited National Journals and (2) teaching materials in Law courses at the Faculty of Law at Prima Indonesia University.

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Garrett, L. E., W. E. Hammond, and W. W. Stead. "The Effects of Computerized Medical Records on Provider Efficiency and Quality of Care." Methods of Information in Medicine 25, no. 03 (July 1986): 151–57. http://dx.doi.org/10.1055/s-0038-1635467.

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SummaryTo study the effect of computerized medical records on the efficiency of providers and the quality of care, 245 patient visits were randomly assigned to manual (134 visits) or computerized (111 visits) records during the implementation of a comprehensive medical information system, TMR, in the renal clinic of the Durham VA Medical Center. Data were collected on the time required for the providers to perform their various functions in the clinic. With the exception of prescription writing, the computerized records resulted in significant reductions in the time required for the physicians to obtain data from and enter data into the record (p <0.01). A similar time reduction was noted for the nursing pre-interview (p <0.001) when the computerized records were employed. With the inclusion of the time required for clerical computer data entry, no overall difference in person hours per visit was noted. The clinician’s utilization of the recorded data was significantly better (p <0.001) for the computerized records. Significant reductions in medication errors were also noted (p <0.01).

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Gosanti, Ayunda Zilul, and Ernawaty Ernawaty. "Analisis Kelengkapan Penulisan Soap, KIE, dan ICD X pada Rekam Medis di Poli Umum dan KIA-KB Puskesmas X Surabaya." Jurnal Administrasi Kesehatan Indonesia 5, no. 2 (January 2, 2018): 139. http://dx.doi.org/10.20473/jaki.v5i2.2017.139-144.

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Based on the standart that Public Health Center “X” completeness of SOAP, KIE, and ICD X must be 100%. The aim of research was to analyze how the completeness of writing SOAP, KIE, and ICD X inGeneral Poly and Health of Mother and Child Family Planning Public Health Center “X”. This study was descriptive research with 500 medical records that consist of 260 for January and 240 for February as sample and they taken by random sampling. The result showed that completeness of SOAP, KIE, and ICD X on January in General Poly were 48% and decrease on February became 45,8%.While Health Mother and Child Family Planning Poly showed that completeness on January were 97,8% and increase on February became 98,6%. The incompleteness of medical records can be influenced by several factors is compliance the health workers who responsible in filling the medical records and they have multi job in Public Health Center “X” also the patient was increase. To minimize the incompleteness of SOAP, KIE, and ICD X, medical staff needs to expose by socialization of medical record to remember their responsibilty of their job description.Keywords : Completeness, medical record, Public Health Center

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Fananca, Muhammad Andy, Aliyadi Aliyadi, and Dwiyono Ariyadi. "RANCANG BANGUN APLIKASI REKAM MEDIS BAGI PASIEN UNIT KESEHATAN KAMPUS BERBASIS WEB (Studi Kasus: Universitas Muhammadiyah Ponorogo)." KOMPUTEK 4, no. 2 (October 28, 2020): 73. http://dx.doi.org/10.24269/jkt.v4i2.536.

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To improve health care and processing data for medical records at the Muhammadiyah Ponorogo University campus health unit, a modern medical record information system is needed. The current medical record-recording process in the Muhammadiyah University campus medical unit of Ponorogo is still done by hand, which is by writing in a book and a patient's treatment card. This is running less optimal because an official has to retrieve and retrieve the data that will be needed in a patient's books and treatment cards, so it takes little time and space. The aim of this study is to develop an existing medical record system, becoming a web-based modern medical record system for patients to record clearly and more efficiently. The study begins with observation, study literature, and then follows the design method using the waterfall model, the context diagram design, the flow diagram (DFD), entity relathionship diagram (erd), system interface design and application testing. With the design of this application for medical records, it is hoped to be beneficial and can improve health care at UKK Muhammadiyah University Ponorogo. The design of this medical record application is still in short supply, and few improvements and innovations that the age has developed need to be made.

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

1

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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2

Lukman, Heryawan. "A Computer-mediated Support for Writing Medical Notes with Coder's Perspective." Kyoto University, 2020. http://hdl.handle.net/2433/259072.

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付記する学位プログラム名: デザイン学大学院連携プログラム
Kyoto University (京都大学)
0048
新制・課程博士
博士(情報学)
甲第22804号
情博第734号
新制||情||125(附属図書館)
京都大学大学院情報学研究科社会情報学専攻
(主査)教授黒田知宏, 教授吉川正俊, 教授緒方広明
学位規則第4条第1項該当

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3

Cheng, Leung Wai-lin Winnie. "An evaluation of a laboratory report writing unit for medical laboratory science students." Click to view the E-thesis via HKUTO, 1989. http://sunzi.lib.hku.hk/HKUTO/record/B38626500.

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Mak, Kwok-kei. "A survey of the perceptions of impact factor among gastrointestinal researchers /." View the Table of Contents & Abstract, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31540788.

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5

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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6

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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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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Books on the topic "Medical records Medical writing"

1

Writing in the health professions. New York: Pearson Longman, 2005.

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1949-, Mair David Clare, and Fischer Pamela C, eds. Writing and reading mental health records: Issues and analysis in professional writing and science rhetoric. 2nd ed. Mahwah, N.J: L. Erlbaum Associates, 1995.

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Reynolds, John Frederick. Writing and reading mental health records: Issues and analysis. Newbury Park: Sage Publications, 1992.

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Sherry, Borcherding, ed. The OTA's guide to documentation: Writing SOAP notes. 3rd ed. Thorofare, NJ: SLACK, 2013.

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Milazzo, Vickie L. How to detect tampering in a medical record. Houston, Tex: Medical-Legal Consulting Institute, 1997.

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Milazzo, Vickie L. How to detect tampering in a medical record. Houston, Tex: Medical-Legal Consulting Institute, 1998.

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Alex, Jacocks M., ed. Communicating effectively in medical records: A guide for physicians. Newbury Park, Calif: Sage Publications, 1992.

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Writing S.O.A.P. notes. Philadelphia: F.A. Davis, 1990.

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Kettenbach, Ginge. Writing S.O.A.P. notes. Philadelphia: F.A. Davis, 1990.

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Sherry, Borcherding, and Borcherding Sherry, eds. Documentation manual for occupational therapy: Writing SOAP notes. 3rd ed. Thorofare, NJ: SLACK, 2012.

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Book chapters on the topic "Medical records Medical writing"

1

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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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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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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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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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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Taylor, Robert B. "Getting Started in Medical Writing." In Medical Writing, 1–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70126-4_1.

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Taylor, Robert B. "How to Write a Grant Proposal." In Medical Writing, 261–88. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70126-4_10.

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Taylor, Robert B. "How to Write a Report of a Research Study." In Medical Writing, 289–315. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70126-4_11.

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Conference papers on the topic "Medical records Medical writing"

1

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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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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Kim, Joong Il, Bong Mun Jang, Dong Hoon Han, Keon Ho Yang, Won-Suk Kang, Haijo Jung, and Hee-Joung Kim. "Applying XDS for sharing CDA-based medical records." In Medical Imaging, edited by Steven C. Horii and Osman M. Ratib. SPIE, 2006. http://dx.doi.org/10.1117/12.652037.

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Yao, Yehong, Chenghao Zhang, Jianyong Sun, Jin Jin, and Jianguo Zhang. "Integrated secure solution for electronic healthcare records sharing." In Medical Imaging, edited by Steven C. Horii and Katherine P. Andriole. SPIE, 2007. http://dx.doi.org/10.1117/12.709156.

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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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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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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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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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Reports on the topic "Medical records Medical writing"

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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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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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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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Gattrell, William, Paul Farrow, Elizabeth Costigan, Catherine Sheard, Richard White, and Christopher Winchester. Professional medical writing support increases the impact of articles reporting randomized controlled trials. Oxford PharmaGenesis Ltd, April 2016. http://dx.doi.org/10.21305/ismpp2016.001.

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Gattrell, William, Paul Farrow, Elizabeth Costigan, Catherine Sheard, Richard White, and Christopher Winchester. Professional medical writing support increases the impact of articles reporting randomized controlled trials. Oxford PharmaGenesis Ltd, April 2016. http://dx.doi.org/10.21305/ismpp2016.002.

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