Speech Recognition Technology: Improving Speed and Accuracy of Emergency Medical Services Documentation to Protect Patients

Because hospital errors, such as mistakes in documentation, cause one in six deaths each year in the United States, the accuracy of health records in the emergency medical services (EMS) must be improved. One possible solution is to incorporate speech recognition (SR) software into current tools used by EMS first responders. The purpose of this research was to determine if SR software could increase the efficiency and accuracy of EMS documentation to improve the safety of patients of EMS. An initial review of the literature on the performance of current SR software demonstrated that this software was not 99% accurate, and therefore, errors in the medical documentation produced by the software could harm patients. The literature review also identified weaknesses of SR software that could be overcome so that the software would be accurate enough for use in EMS settings. These weaknesses included the inability to differentiate between similar phrases and the inability to filter out background noise. To find a solution, an analysis of natural language processing algorithms showed that the bag-of-words post processing algorithm has the ability to differentiate between similar phrases. This algorithm is best suited for SR applications because it is simple yet effective compared to machine learning algorithms that required a large amount of training data. The findings suggested that if these weaknesses of current SR software are solved, then the software would potentially increase the efficiency and accuracy of EMS documentation. Further studies should integrate the bag-of-words post processing method into SR software and field test its accuracy in EMS settings

Speech Recognition Technology: Improving Speed and Accuracy of Emergency Medical Services Documentation to Protect Patients

Because hospital errors, such as mistakes in documentation, cause one sixth of the deaths each year in the United States, the accuracy of health records in the emergency medical services (EMS) must be improved. One possible solution is to incorporate speech recognition (SR) software into current tools used by EMS first responders. The purpose of this research was to determine if SR software could increase the efficiency and accuracy of EMS documentation to improve the safety for patients of EMS. An initial review of the literature on the performance of current SR software demonstrated that this software was not 99% accurate and therefore, errors in the medical documentation produced by the software could harm patients. The literature review also identified weaknesses of SR software that could be overcome so that the software would be accurate enough for use in EMS settings. These weaknesses included the inability to differentiate between similar phrases and the inability to filter out background noise. To find a solution, an analysis of natural language processing algorithms showed that the bag-of-words post processing algorithm has the ability to differentiate between similar phrases. This algorithm is the best suited for SR applications because it is simple yet effective compared to machine learning algorithms that required a large amount of training data. The findings suggested that if these weaknesses of current SR software are solved, then the software would potentially increase the efficiency and accuracy of EMS documentation. Further studies should integrate the bag-of-words post processing method into SR software and field test its accuracy in EMS settings.https://scholarscompass.vcu.edu/uresposters/1273/thumbnail.jp

The digital scribe.

Current generation electronic health records suffer a number of problems that make them inefficient and associated with poor clinical satisfaction. Digital scribes or intelligent documentation support systems, take advantage of advances in speech recognition, natural language processing and artificial intelligence, to automate the clinical documentation task currently conducted by humans. Whilst in their infancy, digital scribes are likely to evolve through three broad stages. Human led systems task clinicians with creating documentation, but provide tools to make the task simpler and more effective, for example with dictation support, semantic checking and templates. Mixed-initiative systems are delegated part of the documentation task, converting the conversations in a clinical encounter into summaries suitable for the electronic record. Computer-led systems are delegated full control of documentation and only request human interaction when exceptions are encountered. Intelligent clinical environments permit such augmented clinical encounters to occur in a fully digitised space where the environment becomes the computer. Data from clinical instruments can be automatically transmitted, interpreted using AI and entered directly into the record. Digital scribes raise many issues for clinical practice, including new patient safety risks. Automation bias may see clinicians automatically accept scribe documents without checking. The electronic record also shifts from a human created summary of events to potentially a full audio, video and sensor record of the clinical encounter. Digital scribes promisingly offer a gateway into the clinical workflow for more advanced support for diagnostic, prognostic and therapeutic tasks

Improving Patient Safety and Hospital Service Quality Through Electronic Medical Record: A Systematic Review

ABSTRACT To understand the Electronic medical records (EMR) role in improving patient safety and hospital’s service quality. Articles that included and assessed for the eligibility in this review was an article that show an effect of patient’ safety, and product quality in hospital in correlation on using EMR. The most important function of EMR implementation is to improve patient safety in hospital, in addition to reducing cost. EMR reduce excess cost of Hospital Acquired Condition (HAC) by 16%, reduce death due to HAC by 34%. Doctor and nurse’s belief that the quality of patient data is better when EMR are easier to use and suit with their dialy routine. EMR can improve patient safety, but its use require some skills in technology so it won’t turn to harm patients’ safety. The implementation EMR requires the ability of skilled human resources in using technologies, computer and programs

From a simple EHR to the market lead: what technologies to add

Electronic health records (EHRs) can store, capture, and present patient data in an organized way that improves physicians’ workflow and patient care. This makes EHRs key to addressing many of today’s health care challenges. An interdisciplinary review and qualitative study of artificial intelligence, machine learning, natural language processing, and real-time location services in health care was conducted. The results show that in an industry where digitization is key, several recommendations can be made to leverage these technologies in ways that can improve current systems and help EHR vendors become the market lead

User-Centered Design of a Speech-Based Application to Support Caregivers

The shortage of skilled nursing personnel is – among other reasons – due to the low attractiveness of the profession, comprising high workloads and atypical working hours. Studies show that speech-based documentation systems increase documentation efficiency and satisfaction of physicians. This paper describes the development process of a speech-based application to support nurses, according to the user-centered design approach. User requirements were collected based on interviews (n=6) as well as observations (n=6) in three institutions and were evaluated by means of qualitative content analysis. A prototype of the derived system architecture was implemented. Based on a usability test (n=3), further potentials for improvement were determined. The resulting application enables nurses to dictate personal notes, share them with colleagues and transmit notes to the existing documentation system. We conclude that the user-centered approach ensures the extensive consideration of the nursing staff’s requirements and shall be continued for further development

Electronic Health Records (EHR)

Electronic Health Records are electronic versions of patients’ healthcare records. An electronic health record gathers, creates, and stores the health record electronically. The electronic health record has been slow to be adopted by healthcare providers. The federal government has recently passed legislation requiring the use of electronic records or face monetary penalties. The electronic health record will improve clinical documentation, quality, healthcare utilization tracking, billing and coding, and make health records portable. The core components of an electronic health record include administrative functions, computerized physician order entry, lab systems, radiology systems, pharmacy systems, and clinical documentation. HL7 is the standard communication protocol technology that an electronic health record utilizes. Implementation of software, hardware, and IT networks are important for a successful electronic health record project. The benefits of an electronic health record include a gain in healthcare efficiencies, large gains in quality and safety, and lower healthcare costs for consumers. Electronic health record challenges include costly software packages, system security, patient confidentiality, and unknown future government regulations. Future technologies for electronic health records include bar coding, radio-frequency identification, and speech recognition.

EHR Quality Documentation Research Thesis

This research proposal contains and introduction to my proposed research, background of the issue at hand, purpose of the research, significance of the research, research questions that I will be asking, definition of terms, limitations that I may be facing, literature review, SWOT Analysis, and Work Flow diagram on literature review. Also discussed are my proposed research methodology, research design, population sample, data collection procedures, as well as a table of survey variables that I propose to include. This proposal will go over why documentation quality and quantity is so important and the history behind why we are facing a documentation crisis. I am proposing to be able to conduct my research to see how the documentation quality and quantity has improved, or declined since the implementation of EHRs and voice recognition systems across the North Eastern Pennsylvania Region

A systematic review of speech recognition technology in health care

BACKGROUND To undertake a systematic review of existing literature relating to speech recognition technology and its application within health care. METHODS A systematic review of existing literature from 2000 was undertaken. Inclusion criteria were: all papers that referred to speech recognition (SR) in health care settings, used by health professionals (allied health, medicine, nursing, technical or support staff), with an evaluation or patient or staff outcomes. Experimental and non-experimental designs were considered. Six databases (Ebscohost including CINAHL, EMBASE, MEDLINE including the Cochrane Database of Systematic Reviews, OVID Technologies, PreMED-LINE, PsycINFO) were searched by a qualified health librarian trained in systematic review searches initially capturing 1,730 references. Fourteen studies met the inclusion criteria and were retained. RESULTS The heterogeneity of the studies made comparative analysis and synthesis of the data challenging resulting in a narrative presentation of the results. SR, although not as accurate as human transcription, does deliver reduced turnaround times for reporting and cost-effective reporting, although equivocal evidence of improved workflow processes. CONCLUSIONS SR systems have substantial benefits and should be considered in light of the cost and selection of the SR system, training requirements, length of the transcription task, potential use of macros and templates, the presence of accented voices or experienced and in-experienced typists, and workflow patterns.Funding for this study was provided by the University of Western Sydney. NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program. NICTA is also funded and supported by the Australian Capital Territory, the New South Wales, Queensland and Victorian Governments, the Australian National University, the University of New South Wales, the University of Melbourne, the University of Queensland, the University of Sydney, Griffith University, Queensland University of Technology, Monash University and other university partners

Space Station Freedom automation and robotics: An assessment of the potential for increased productivity

This report presents the results of a study performed in support of the Space Station Freedom Advanced Development Program, under the sponsorship of the Space Station Engineering (Code MT), Office of Space Flight. The study consisted of the collection, compilation, and analysis of lessons learned, crew time requirements, and other factors influencing the application of advanced automation and robotics, with emphasis on potential improvements in productivity. The lessons learned data collected were based primarily on Skylab, Spacelab, and other Space Shuttle experiences, consisting principally of interviews with current and former crew members and other NASA personnel with relevant experience. The objectives of this report are to present a summary of this data and its analysis, and to present conclusions regarding promising areas for the application of advanced automation and robotics technology to the Space Station Freedom and the potential benefits in terms of increased productivity. In this study, primary emphasis was placed on advanced automation technology because of its fairly extensive utilization within private industry including the aerospace sector. In contrast, other than the Remote Manipulator System (RMS), there has been relatively limited experience with advanced robotics technology applicable to the Space Station. This report should be used as a guide and is not intended to be used as a substitute for official Astronaut Office crew positions on specific issues