scholarly journals A Fully Collaborative, Noteless Electronic Medical Record Designed to Minimize Information Chaos: Software Design and Feasibility Study (Preprint)

2020 ◽  
Author(s):  
Jackson Steinkamp ◽  
Abhinav Sharma ◽  
Wasif Bala ◽  
Jacob J Kantrowitz

BACKGROUND Clinicians spend large amounts of their workday using electronic medical records (EMRs). Poorly designed documentation systems contribute to the proliferation of out-of-date information, increased time spent on medical records, clinician burnout, and medical errors. Beyond software interfaces, examining the underlying paradigms and organizational structures for clinical information may provide insights into ways to improve documentation systems. In particular, our attachment to the <i>note</i> as the major organizational unit for storing unstructured medical data may be a cause of many of the problems with modern clinical documentation. Notes, as currently understood, systematically incentivize information duplication and information scattering, both within a single clinician’s notes over time and across multiple clinicians’ notes. Therefore, it is worthwhile to explore alternative paradigms for unstructured data organization. OBJECTIVE The aim of this study is to demonstrate the feasibility of building an EMR that does not use notes as the core organizational unit for unstructured data and which is designed specifically to disincentivize information duplication and information scattering. METHODS We used specific design principles to minimize the incentive for users to duplicate and scatter information. By default, the majority of a patient’s medical history remains the same over time, so users should not have to redocument that information. Clinicians on different teams or services mostly share the same medical information, so all data should be collaboratively shared across teams and services (while still allowing for disagreement and nuance). In all cases where a clinician must state that information has remained the same, they should be able to <i>attest</i> to the information without redocumenting it. We designed and built a web-based EMR based on these design principles. RESULTS We built a medical documentation system that does not use notes and instead treats the chart as a single, dynamically updating, and fully collaborative workspace. All information is organized by clinical topic or problem. Version history functionality is used to enable granular tracking of changes over time. Our system is highly customizable to individual workflows and enables each individual user to decide which data should be structured and which should be unstructured, enabling individuals to leverage the advantages of structured templating and clinical decision support as desired without requiring programming knowledge. The system is designed to facilitate real-time, fully collaborative documentation and communication among multiple clinicians. CONCLUSIONS We demonstrated the feasibility of building a non–note-based, fully collaborative EMR system. Our attachment to the <i>note</i> as the only possible atomic unit of unstructured medical data should be reevaluated, and alternative models should be considered.

1970 ◽  
Vol 09 (03) ◽  
pp. 149-160 ◽  
Author(s):  
E. Van Brunt ◽  
L. S. Davis ◽  
J. F. Terdiman ◽  
S. Singer ◽  
E. Besag ◽  
...  

A pilot medical information system is being implemented and currently is providing services for limited categories of patient data. In one year, physicians’ diagnoses for 500,000 office visits, 300,000 drug prescriptions for outpatients, one million clinical laboratory tests, and 60,000 multiphasic screening examinations are being stored in and retrieved from integrated, direct access, patient computer medical records.This medical information system is a part of a long-term research and development program. Its major objective is the development of a multifacility computer-based system which will support eventually the medical data requirements of a population of one million persons and one thousand physicians. The strategy employed provides for modular development. The central system, the computer-stored medical records which are therein maintained, and a satellite pilot medical data system in one medical facility are described.


2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Ashwin Belle ◽  
Raghuram Thiagarajan ◽  
S. M. Reza Soroushmehr ◽  
Fatemeh Navidi ◽  
Daniel A. Beard ◽  
...  

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.


1997 ◽  
Vol 3 (4) ◽  
pp. 179-187 ◽  
Author(s):  
Ben Stanberry

This paper reviews the principle of confidentiality and the rights of access by patients to their medical records. Confidentiality has been germane to the ethics of medical practice since the time of Hippocrates but the nature of the legal obligation of confidence does not have such a clear pedigree. The introduction of crossborder telemedical consultations presents a very real danger to maintaining the confidentiality of medical data. While both the common law and statute law can be used to prevent the unauthorized interception and disclosure of medical data and protect the patient's rights of access and ownership in the UK, it is the harmonization regime of the European Union that will bring comprehensive regulation and legal clarity to the protection of patients' rights within an increasingly international medical super-specialty'.


Author(s):  
Ya. Yu. Marunkevych

Suicidal behavior is one of the most pressing social and medical problems. At the same time, a number of important issues related to the suicidal behavior of schizophrenic patients, in particular gender features, remain insufficiently studied.The aim of the study – to learn the peculiarities of suicidal behavior of patients with paranoid schizophrenia taking into account the gender factor on the basis of a comparative analysis of medical records and direct clinical research.Materials and Methods. To study the peculiarities of suicidal behavior of patients with paranoid schizophrenia, taking into account the gender factor, a study of suicidal behavior was conducted by studying medical records of 407 men and 409 women and a clinical examination of 53 men and 49 women with paranoid schizophrenia.Results and Discussion. A relatively low prevalence of suicidal phenomena before the onset of schizophrenia: a suicidal ideation was found in 1.0 % of men and 1.5 % of women according to medical records and 5.7 % of men and 4.1 % of women according to the clinical examination, suicidal actions – in 1.5 % of women according to medical records. Installed that after the debut of schizophrenia, the suicidal activity of patients sharply increases: according to the analysis of medical documentation suicidal thoughts were found in 17.2 % of men and 18.8 % of women, according to the clinical survey – in 47.2 % of men and 20.4 % of women, suicide attempts were in 9.3% and 15.6%, respectively, and 26.4 %, respectively, versus 10.2 %. The significant severity of psychopathological symptoms of schizophrenia in patients with suicidal tendencies is established. The most closely associated with the presence of suicidal thoughts are negative symptoms and behavioral disorders (97.3 % among all patients, 95.7 % among men, 98.7 % among women according to the documentation analysis, 100.0 % according to the clinical survey). Suicidal actions are characterized by close association with negative symptoms.Conclusions. Patients with paranoid schizophrenia are characterized by high suicidal activity, both at the level of suicidal thoughts and at the level of suicidal actions.


2014 ◽  
Vol 8 (2) ◽  
pp. 13-24 ◽  
Author(s):  
Arkadiusz Liber

Introduction: Medical documentation ought to be accessible with the preservation of its integrity as well as the protection of personal data. One of the manners of its protection against disclosure is anonymization. Contemporary methods ensure anonymity without the possibility of sensitive data access control. it seems that the future of sensitive data processing systems belongs to the personalized method. In the first part of the paper k-Anonymity, (X,y)- Anonymity, (α,k)- Anonymity, and (k,e)-Anonymity methods were discussed. these methods belong to well - known elementary methods which are the subject of a significant number of publications. As the source papers to this part, Samarati, Sweeney, wang, wong and zhang’s works were accredited. the selection of these publications is justified by their wider research review work led, for instance, by Fung, Wang, Fu and y. however, it should be noted that the methods of anonymization derive from the methods of statistical databases protection from the 70s of 20th century. Due to the interrelated content and literature references the first and the second part of this article constitute the integral whole.Aim of the study: The analysis of the methods of anonymization, the analysis of the methods of protection of anonymized data, the study of a new security type of privacy enabling device to control disclosing sensitive data by the entity which this data concerns.Material and methods: Analytical methods, algebraic methods.Results: Delivering material supporting the choice and analysis of the ways of anonymization of medical data, developing a new privacy protection solution enabling the control of sensitive data by entities which this data concerns.Conclusions: In the paper the analysis of solutions for data anonymization, to ensure privacy protection in medical data sets, was conducted. the methods of: k-Anonymity, (X,y)- Anonymity, (α,k)- Anonymity, (k,e)-Anonymity, (X,y)-Privacy, lKc-Privacy, l-Diversity, (X,y)-linkability, t-closeness, confidence Bounding and Personalized Privacy were described, explained and analyzed. The analysis of solutions of controlling sensitive data by their owner was also conducted. Apart from the existing methods of the anonymization, the analysis of methods of the protection of anonymized data was included. In particular, the methods of: δ-Presence, e-Differential Privacy, (d,γ)-Privacy, (α,β)-Distributing Privacy and protections against (c,t)-isolation were analyzed. Moreover, the author introduced a new solution of the controlled protection of privacy. the solution is based on marking a protected field and the multi-key encryption of sensitive value. The suggested way of marking the fields is in accordance with Xmlstandard. For the encryption, (n,p) different keys cipher was selected. to decipher the content the p keys of n were used. The proposed solution enables to apply brand new methods to control privacy of disclosing sensitive data.


2022 ◽  
pp. 431-454
Author(s):  
Pinar Kirci

To define huge datasets, the term of big data is used. The considered “4 V” datasets imply volume, variety, velocity and value for many areas especially in medical images, electronic medical records (EMR) and biometrics data. To process and manage such datasets at storage, analysis and visualization states are challenging processes. Recent improvements in communication and transmission technologies provide efficient solutions. Big data solutions should be multithreaded and data access approaches should be tailored to big amounts of semi-structured/unstructured data. Software programming frameworks with a distributed file system (DFS) that owns more units compared with the disk blocks in an operating system to multithread computing task are utilized to cope with these difficulties. Huge datasets in data storage and analysis of healthcare industry need new solutions because old fashioned and traditional analytic tools become useless.


2020 ◽  
pp. 239-254
Author(s):  
David W. Dorsey

With the rise of the internet and the related explosion in the amount of data that are available, the field of data science has expanded rapidly, and analytic techniques designed for use in “big data” contexts have become popular. These include techniques for analyzing both structured and unstructured data. This chapter explores the application of these techniques to the development and evaluation of career pathways. For example, data scientists can analyze online job listings and resumes to examine changes in skill requirements and careers over time and to examine job progressions across an enormous number of people. Similarly, analysts can evaluate whether information on career pathways accurately captures realistic job progressions. Within organizations, the increasing amount of data make it possible to pinpoint the specific skills, behaviors, and attributes that maximize performance in specific roles. The chapter concludes with ideas for the future application of big data to career pathways.


2019 ◽  
Vol 34 (s1) ◽  
pp. s43-s43
Author(s):  
Sonia Haris ◽  
Naveen Anaswara ◽  
Venugopal Poovathumparambil

Introduction:In August 2018, Kerala, India witnessed its worst flood in over a century. With the support of the national health mission, Operation Navajeevan, a public-private partnership between the district health administration and local hospitals was established in Kozhikode to provide medical aid to flood victims. This study identifies prerequisites, describes challenges, and depicts the epidemiology of patients seen in these camps.Aim:1.Identify prerequisites and medical needs/challenges faced by medical relief camps in a flood-affected region2.Formulate protocols to avoid duplication of services3.Prepare an ideal PPP emergency medical camp modelMethods:A control center with drugs and a logistics unit was set up at the district administration to monitor and supervise various camps. A mobile medical documentation format was created to record the details of each camp. Cases of patients seen at these camps were compiled and later analyzed. The medical officer sent reports from each camp to the control center each day to specify the daily difficulties faced by each camp. Mobile ICUs were kept on standby to respond in the event of emergent circumstances or surge demands. Transfer protocol and treatment guidelines were formulated and standardized.Results:Over two weeks, approximately 40,000 patients were seen in 280 medical camps. Major medical issues included exacerbation of chronic illnesses due to loss of medications (18,490), acute respiratory infections (7,451), psychiatric illnesses (5,327), trauma (3,736), skin infection (792), tropical fever (498), acute gastroenteritis (394), and ACS (17). Of the cases of fever, 137 people had leptospirosis. Major challenges included a lack of training in disaster management and failure of documentation systems.Discussion:A well-organized control center, improved training in disaster medicine, and reliable documentation systems are crucial for coordinating medical camps in disaster areas. Public-private partnerships offer a model for providing medical relief in disaster settings.


2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Cícero A. Silva ◽  
Gibeon S. Aquino ◽  
Sávio R. M. Melo ◽  
Dannylo J. B. Egídio

The aging of the world’s population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients’ health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario.


BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e032551 ◽  
Author(s):  
Graham Powell ◽  
John Logan ◽  
Victor Kiri ◽  
Simon Borghs

ObjectiveTo assess the evolution of antiepileptic drug (AED) treatment patterns and seizure outcomes in England from 2003 to 2016.Design, setting and participantsRetrospective cohort study of electronic medical records from Clinical Practice Research Datalink and National Health Service Digital Hospital Episode Statistics databases. Patients newly diagnosed with epilepsy were identified and followed until end of data availability. Three eras were defined starting 1 April 2003 (first National Institute for Health and Care Excellence (NICE) guideline); 1 September 2007 (Standard and New Antiepileptic Drugs publication); and 1 January 2012 (second NICE guideline).Outcome measuresTime from diagnosis to first AED; AED sequence; time from first AED to first 1-year remission period (no new AED attempts and no seizure-related healthcare events); time from first AED to refractoriness (third AED attempt regardless of reason); Kaplan-Meier analysis of time-to-event variables.Results4388 patients were included (mean follow-up: 6.8, 4.2 and 1.7 years by era). 84.6% of adults (≥16 years), 75.5% of children (<16) and 89.1% of elderly subgroup (65+) received treatment within 1 year; rates were generally stable over time. Treatment trends included reduced use of carbamazepine (adult first line, era 1: 34.9%; era 3: 10.7%) and phenytoin, earlier line and increased use of levetiracetam (adult first line, era 1: 2.6%; era 3: 26.2%) and lamotrigine (particularly in adults and elderly subgroup), and a larger number of different AEDs used. Valproate use shifted somewhat to later lines. Rates of 1-year remission within 2 years of starting treatment increased in adults (era 1: 71.9%; era 3: 81.4%) and elderly (era 1: 76.1%; era 3: 81.7%). Overall, 55.5% of patients relapsed after achieving 1-year remission. Refractoriness rates remained stable over time (~26% of adults within 5 years).ConclusionTreatment trends often were not aligned with era-relevant guidance. However, our results suggest a slight improvement in epilepsy treatment outcomes over the 13-year period.


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