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Lemey C, Larsen ME, Devylder J, Courtet P, Billot R, Lenca P, Walter M, Baca-García E, Berrouiguet S. Clinicians' Concerns About Mobile Ecological Momentary Assessment Tools Designed for Emerging Psychiatric Problems: Prospective Acceptability Assessment of the MEmind App. J Med Internet Res 2019; 21:e10111. [PMID: 31021327 PMCID: PMC6658238 DOI: 10.2196/10111] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 08/27/2018] [Accepted: 10/11/2018] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Many mental disorders are preceded by a prodromal phase consisting of various attenuated and unspecific symptoms and functional impairment. Electronic health records are generally used to capture these symptoms during medical consultation. Internet and mobile technologies provide the opportunity to monitor symptoms emerging in patients' environments using ecological momentary assessment techniques to support preventive therapeutic decision making. OBJECTIVE The objective of this study was to assess the acceptability of a Web-based app designed to collect medical data during appointments and provide ecological momentary assessment features. METHODS We recruited clinicians at 4 community psychiatry departments in France to participate. They used the app to assess patients and to collect data after viewing a video of a young patient's emerging psychiatric consultation. We then asked them to answer a short anonymous self-administered questionnaire that evaluated their experience, the acceptability of the app, and their habit of using new technologies. RESULTS Of 24 practitioners invited, 21 (88%) agreed to participate. Most of them were between 25 and 45 years old, and greater age was not associated with poorer acceptability. Most of the practitioners regularly used new technologies, and 95% (20/21) connected daily to the internet, with 70% (15/21) connecting 3 times a day or more. However, only 57% (12/21) reported feeling comfortable with computers. Of the clinicians, 86% (18/21) would recommend the tool to their colleagues and 67% (14/21) stated that they would be interested in daily use of the app. Most of the clinicians (16/21, 76%) found the interface easy to use and useful. However, several clinicians noted the lack of readability (8/21, 38%) and the need to improve ergonometric features (4/21, 19%), in particular to facilitate browsing through various subsections. Some participants (5/21, 24%) were concerned about the storage of medical data and most of them (11/21, 52%) seemed to be uncomfortable with this. CONCLUSIONS We describe the first step of the development of a Web app combining an electronic health record and ecological momentary assessment features. This online tool offers the possibility to assess patients and to integrate medical data easily into face-to-face conditions. The acceptability of this app supports the feasibility of its broader implementation. This app could help to standardize assessment and to build up a strong database. Used in conjunction with robust data mining analytic techniques, such a database would allow exploration of risk factors, patterns of symptom evolution, and identification of distinct risk subgroups.
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Affiliation(s)
- Christophe Lemey
- EA 7479 SPURBO, Université de Bretagne Occidentale, Brest, France.,URCI Mental Health Department, Brest Medical University Hospital, Brest, France.,IMT Atlantique, Lab-STICC, F-29238 Brest, Brest, France
| | - Mark Erik Larsen
- Black Dog Institute, University of New South Wales, Sydney, Australia
| | - Jordan Devylder
- Graduate School of Social Service, Fordham University, New York, NY, United States
| | - Philippe Courtet
- Inserm U1061, La colombière Hospital, University of Montpellier, Montpellier, France.,Department of Emergency Psychiatry and Acute Care, CHU Montpellier, University of Montpellier, Montpellier, France.,Fondamental Foundation, Créteil, France
| | - Romain Billot
- IMT Atlantique, Lab-STICC, F-29238 Brest, Brest, France
| | | | - Michel Walter
- EA 7479 SPURBO, Université de Bretagne Occidentale, Brest, France.,URCI Mental Health Department, Brest Medical University Hospital, Brest, France
| | - Enrique Baca-García
- Carlos III Institute Of Health, CIBERSAM (Centro de Investigation en Salud Mental), Madrid, Spain.,Department of Psychiatry, Universitad Catolica Del Maule, Talca, Chile.,Department of Psychiatry, General Hospital of Villalba, Madrid, Spain.,Department of Psychiatry, University Hospital Rey Juan Carlos, Mostoles, Spain.,Deparment of Psychiatry, University Hospital Infanta Elena, Valdemoro, Spain.,Psychiatry Department, Autonoma University, Madrid, Spain.,Department of Psychiatry, IIS-Jimenez Diaz Fondation, Madrid, Spain
| | - Sofian Berrouiguet
- EA 7479 SPURBO, Université de Bretagne Occidentale, Brest, France.,IMT Atlantique, Lab-STICC, F-29238 Brest, Brest, France
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Bouayad L, Ialynytchev A, Padmanabhan B. Patient Health Record Systems Scope and Functionalities: Literature Review and Future Directions. J Med Internet Res 2017; 19:e388. [PMID: 29141839 PMCID: PMC5707430 DOI: 10.2196/jmir.8073] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 09/01/2017] [Accepted: 10/03/2017] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND A new generation of user-centric information systems is emerging in health care as patient health record (PHR) systems. These systems create a platform supporting the new vision of health services that empowers patients and enables patient-provider communication, with the goal of improving health outcomes and reducing costs. This evolution has generated new sets of data and capabilities, providing opportunities and challenges at the user, system, and industry levels. OBJECTIVE The objective of our study was to assess PHR data types and functionalities through a review of the literature to inform the health care informatics community, and to provide recommendations for PHR design, research, and practice. METHODS We conducted a review of the literature to assess PHR data types and functionalities. We searched PubMed, Embase, and MEDLINE databases from 1966 to 2015 for studies of PHRs, resulting in 1822 articles, from which we selected a total of 106 articles for a detailed review of PHR data content. RESULTS We present several key findings related to the scope and functionalities in PHR systems. We also present a functional taxonomy and chronological analysis of PHR data types and functionalities, to improve understanding and provide insights for future directions. Functional taxonomy analysis of the extracted data revealed the presence of new PHR data sources such as tracking devices and data types such as time-series data. Chronological data analysis showed an evolution of PHR system functionalities over time, from simple data access to data modification and, more recently, automated assessment, prediction, and recommendation. CONCLUSIONS Efforts are needed to improve (1) PHR data quality through patient-centered user interface design and standardized patient-generated data guidelines, (2) data integrity through consolidation of various types and sources, (3) PHR functionality through application of new data analytics methods, and (4) metrics to evaluate clinical outcomes associated with automated PHR system use, and costs associated with PHR data storage and analytics.
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Affiliation(s)
- Lina Bouayad
- Department of Information Systems and Business Analytics, Florida International University, Miami, FL, United States.,Health Services Research and Development Service, Center of Innovation on Disability and Rehabilitation Research, Tampa, FL, United States
| | - Anna Ialynytchev
- Health Services Research and Development Service, Center of Innovation on Disability and Rehabilitation Research, Tampa, FL, United States
| | - Balaji Padmanabhan
- Department of Information Systems and Decision Sciences, University of South Florida, Tampa, FL, United States
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Gal TS, Tucker TC, Gangopadhyay A, Chen Z. A data recipient centered de-identification method to retain statistical attributes. J Biomed Inform 2014; 50:32-45. [PMID: 24412834 DOI: 10.1016/j.jbi.2014.01.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2013] [Revised: 11/17/2013] [Accepted: 01/03/2014] [Indexed: 11/30/2022]
Abstract
Privacy has always been a great concern of patients and medical service providers. As a result of the recent advances in information technology and the government's push for the use of Electronic Health Record (EHR) systems, a large amount of medical data is collected and stored electronically. This data needs to be made available for analysis but at the same time patient privacy has to be protected through de-identification. Although biomedical researchers often describe their research plans when they request anonymized data, most existing anonymization methods do not use this information when de-identifying the data. As a result, the anonymized data may not be useful for the planned research project. This paper proposes a data recipient centered approach to tailor the de-identification method based on input from the recipient of the data. We demonstrate our approach through an anonymization project for biomedical researchers with specific goals to improve the utility of the anonymized data for statistical models used for their research project. The selected algorithm improves a privacy protection method called Condensation by Aggarwal et al. Our methods were tested and validated on real cancer surveillance data provided by the Kentucky Cancer Registry.
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Affiliation(s)
- Tamas S Gal
- University of Kentucky, 2365 Harrodsburg Rd., Suite A230, Lexington, KY 40504, USA.
| | - Thomas C Tucker
- University of Kentucky, 2365 Harrodsburg Rd., Suite A230, Lexington, KY 40504, USA.
| | - Aryya Gangopadhyay
- University of Maryland at Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.
| | - Zhiyuan Chen
- University of Maryland at Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.
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Jiang X, Tse K, Wang S, Doan S, Kim H, Ohno-Machado L. Recent trends in biomedical informatics: a study based on JAMIA articles. J Am Med Inform Assoc 2013; 20:e198-205. [PMID: 24214018 PMCID: PMC3861936 DOI: 10.1136/amiajnl-2013-002429] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
In a growing interdisciplinary field like biomedical informatics, information dissemination and citation trends are changing rapidly due to many factors. To understand these factors better, we analyzed the evolution of the number of articles per major biomedical informatics topic, download/online view frequencies, and citation patterns (using Web of Science) for articles published from 2009 to 2012 in JAMIA. The number of articles published in JAMIA increased significantly from 2009 to 2012, and there were some topic differences in the last 4 years. Medical Record Systems, Algorithms, and Methods are topic categories that are growing fast in several publications. We observed a significant correlation between download frequencies and the number of citations per month since publication for a given article. Earlier free availability of articles to non-subscribers was associated with a higher number of downloads and showed a trend towards a higher number of citations. This trend will need to be verified as more data accumulate in coming years.
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Affiliation(s)
- Xiaoqian Jiang
- Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California, USA
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Sokolova M, El Emam K, Arbuckle L, Neri E, Rose S, Jonker E. P2P watch: personal health information detection in peer-to-peer file-sharing networks. J Med Internet Res 2012; 14:e95. [PMID: 22776692 PMCID: PMC3415260 DOI: 10.2196/jmir.1898] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2011] [Revised: 03/05/2012] [Accepted: 04/23/2012] [Indexed: 11/24/2022] Open
Abstract
Background Users of peer-to-peer (P2P) file-sharing networks risk the inadvertent disclosure of personal health information (PHI). In addition to potentially causing harm to the affected individuals, this can heighten the risk of data breaches for health information custodians. Automated PHI detection tools that crawl the P2P networks can identify PHI and alert custodians. While there has been previous work on the detection of personal information in electronic health records, there has been a dearth of research on the automated detection of PHI in heterogeneous user files. Objective To build a system that accurately detects PHI in files sent through P2P file-sharing networks. The system, which we call P2P Watch, uses a pipeline of text processing techniques to automatically detect PHI in files exchanged through P2P networks. P2P Watch processes unstructured texts regardless of the file format, document type, and content. Methods We developed P2P Watch to extract and analyze PHI in text files exchanged on P2P networks. We labeled texts as PHI if they contained identifiable information about a person (eg, name and date of birth) and specifics of the person’s health (eg, diagnosis, prescriptions, and medical procedures). We evaluated the system’s performance through its efficiency and effectiveness on 3924 files gathered from three P2P networks. Results P2P Watch successfully processed 3924 P2P files of unknown content. A manual examination of 1578 randomly selected files marked by the system as non-PHI confirmed that these files indeed did not contain PHI, making the false-negative detection rate equal to zero. Of 57 files marked by the system as PHI, all contained both personally identifiable information and health information: 11 files were PHI disclosures, and 46 files contained organizational materials such as unfilled insurance forms, job applications by medical professionals, and essays. Conclusions PHI can be successfully detected in free-form textual files exchanged through P2P networks. Once the files with PHI are detected, affected individuals or data custodians can be alerted to take remedial action.
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Affiliation(s)
- Marina Sokolova
- Electronic Health Information Laboratory, CHEO Research Institute, Ottawa, ON, Canada.
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Abstract
Clinical research informatics is the rapidly evolving sub-discipline within biomedical informatics that focuses on developing new informatics theories, tools, and solutions to accelerate the full translational continuum: basic research to clinical trials (T1), clinical trials to academic health center practice (T2), diffusion and implementation to community practice (T3), and ‘real world’ outcomes (T4). We present a conceptual model based on an informatics-enabled clinical research workflow, integration across heterogeneous data sources, and core informatics tools and platforms. We use this conceptual model to highlight 18 new articles in the JAMIA special issue on clinical research informatics.
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Affiliation(s)
- Michael G Kahn
- Department of Pediatrics, University of Colorado, Aurora, Colorado 80045, USA.
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