Journal of Medical Systems (J Med Syst)

Publisher: Springer Verlag

Journal description

Journal of Medical Systems provides a forum for the presentation and discussion of the increasingly extensive applications of new systems techniques and methods in hospital clinic and physician's office administration; pathology radiology and pharmaceutical delivery systems; medical records storage and retrieval; and ancillary patient-support systems. The journal publishes informative articles essays and studies across the entire scale of medical systems from large hospital programs to novel small-scale medical services. Education is an integral part of this amalgamation of sciences and selected articles are published in this area. Since existing medical systems are constantly being modified to fit particular circumstances and to solve specific problems the journal includes a special section devoted to status reports on current installations.

Current impact factor: 1.37

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 1.372
2012 Impact Factor 1.783
2011 Impact Factor 1.132
2010 Impact Factor 1.064
2009 Impact Factor 0.654
2008 Impact Factor 0.674
2007 Impact Factor 0.45
2006 Impact Factor 0.581

Impact factor over time

Impact factor

Additional details

5-year impact 1.86
Cited half-life 4.00
Immediacy index 0.14
Eigenfactor 0.00
Article influence 0.33
Website Journal of Medical Systems website
Other titles Journal of medical systems (Online)
ISSN 1573-689X
OCLC 44169645
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Springer Verlag

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on pre-print servers such as
    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: As the core of health information technology (HIT), electronic medical record (EMR) systems have been changing to meet health care demands. To construct a new-generation EMR system framework with the capability of self-learning and real-time feedback, thus adding intelligence to the EMR system itself, this paper proposed a novel EMR system framework by constructing a direct pathway between the EMR workflow and EMR data. A prototype of this framework was implemented based on patient similarity learning. Patient diagnoses, demographic data, vital signs and structured lab test results were considered for similarity calculations. Real hospitalization data from 12,818 patients were substituted, and Precision @ Position measurements were used to validate self-learning performance. Our EMR system changed the way in which orders are placed by establishing recommendation order menu and shortcut applications. Two learning modes (EASY MODE and COMPLEX MODE) were provided, and the precision values @ position 5 of both modes were 0.7458 and 0.8792, respectively. The precision performance of COMPLEX MODE was better than that of EASY MODE (tested using a paired Wilcoxon-Mann-Whitney test, p < 0.001). Applying the proposed framework, the EMR data value was directly demonstrated in the clinical workflow, and intelligence was added to the EMR system, which could improve system usability, reliability and the physician's work efficiency. This self-learning mechanism is based on dynamic learning models and is not limited to a specific disease or clinical scenario, thus decreasing maintenance costs in real world applications and increasing its adaptability.
    Journal of Medical Systems 05/2015; 39(5):237. DOI:10.1007/s10916-015-0237-z
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    ABSTRACT: The increasingly large databases available to researchers necessitate high-quality metadata that is not always available. We describe a method for generating this metadata independently. Cluster analysis and expectation-maximization were used to separate days into holidays/weekends and regular workdays using anesthesia data from Vanderbilt University Medical Center from 2004 to 2014. This classification was then used to describe differences between the two sets of days over time. We evaluated 3802 days and correctly categorized 3797 based on anesthesia case time (representing an error rate of 0.13 %). Use of other metrics for categorization, such as billed anesthesia hours and number of anesthesia cases per day, led to similar results. Analysis of the two categories showed that surgical volume increased more quickly with time for non-holidays than holidays (p < 0.001). We were able to successfully generate metadata from data by distinguishing holidays based on anesthesia data. This data can then be used for economic analysis and scheduling purposes. It is possible that the method can be expanded to similar bimodal and multimodal variables.
    Journal of Medical Systems 05/2015; 39(5):232. DOI:10.1007/s10916-015-0232-4
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    ABSTRACT: To protect the transmission of the sensitive medical data, a secure and efficient authenticated key agreement scheme should be deployed when the healthcare delivery session is established via Telecare Medicine Information Systems (TMIS) over the unsecure public network. Recently, Islam and Khan proposed an authenticated key agreement scheme using elliptic curve cryptography for TMIS. They claimed that their proposed scheme is provably secure against various attacks in random oracle model and enjoys some good properties such as user anonymity. In this paper, however, we point out that any legal but malicious patient can reveal other user's identity. Consequently, their scheme suffers from server spoofing attack and off-line password guessing attack. Moreover, if the malicious patient performs the same time of the registration as other users, she can further launch the impersonation attack, man-in-the-middle attack, modification attack, replay attack, and strong replay attack successfully. To eliminate these weaknesses, we propose an improved ECC-based authenticated key agreement scheme. Security analysis demonstrates that the proposed scheme can resist various attacks and enables the patient to enjoy the remote healthcare services with privacy protection. Through the performance evaluation, we show that the proposed scheme achieves a desired balance between security and performance in comparisons with other related schemes.
    Journal of Medical Systems 05/2015; 39(5):233. DOI:10.1007/s10916-015-0233-3
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    ABSTRACT: The Telecare medical information system (TMIS) presents effective healthcare delivery services by employing information and communication technologies. The emerging privacy and security are always a matter of great concern in TMIS. Recently, Chen at al. presented a password based authentication schemes to address the privacy and security. Later on, it is proved insecure against various active and passive attacks. To erase the drawbacks of Chen et al.'s anonymous authentication scheme, several password based authentication schemes have been proposed using public key cryptosystem. However, most of them do not present pre-smart card authentication which leads to inefficient login and password change phases. To present an authentication scheme with pre-smart card authentication, we present an improved anonymous smart card based authentication scheme for TMIS. The proposed scheme protects user anonymity and satisfies all the desirable security attributes. Moreover, the proposed scheme presents efficient login and password change phases where incorrect input can be quickly detected and a user can freely change his password without server assistance. Moreover, we demonstrate the validity of the proposed scheme by utilizing the widely-accepted BAN (Burrows, Abadi, and Needham) logic. The proposed scheme is also comparable in terms of computational overheads with relevant schemes.
    Journal of Medical Systems 05/2015; 39(5):215. DOI:10.1007/s10916-015-0215-5
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    ABSTRACT: This study focuses on the situation of health information exchange (HIE) in the context of a nationwide network. It aims to create a security framework that can be implemented to ensure the safe transmission of health information across the boundaries of care providers in Malaysia and other countries. First, a critique of the major elements of nationwide health information networks is presented from the perspective of security, along with such topics as the importance of HIE, issues, and main approaches. Second, a systematic evaluation is conducted on the security solutions that can be utilized in the proposed nationwide network. Finally, a secure framework for health information transmission is proposed within a central cloud-based model, which is compatible with the Malaysian telehealth strategy. The outcome of this analysis indicates that a complete security framework for a global structure of HIE is yet to be defined and implemented. Our proposed framework represents such an endeavor and suggests specific techniques to achieve this goal.
    Journal of Medical Systems 05/2015; 39(5):235. DOI:10.1007/s10916-015-0235-1
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    ABSTRACT: There is a growing emphasis on both cost containment and better quality health care. The creation of better methods for alerting providers and their departments to the costs associated with patient care is one tool for improving efficiency. Since anesthetic medications used in the OR setting are one easily monitored factor contributing to OR costs, anesthetic cost report cards can be used to assess the cost and, potentially the quality of care provided by each practitioner. An ongoing challenge is the identification of the most effective strategies to control costs, promote cost awareness and at the same time maximize quality. To test the scorecard concept, we utilized existing informatics systems to gather and analyze drug costs for anesthesia providers in the OR. Drug costs were analyzed by medication class for each provider. Individual anesthesiologist's anesthetic costs were collected and compared to the average costs of the overall group and individual trends over time were noted. We presented drug usage data in an electronic report card format. Real-time individual reports can be provided to anesthesiologists to allow for anesthetic cost feedback. Data provided can include number of cases, average case time, total anesthetic medication costs, and average anesthetic cost per case. Also included can be subcategories of pre-medication, antibiotics, hypnotics, local anesthetics, neuromuscular blocking drugs, analgesics, vasopressors, beta-blockers, anti-emetics, volatile anesthetics, and reversal agents. The concept of anesthetic cost report card should be further developed for individual feedback, and could include many other dimensions. Such a report card can be utilized to encourage lower anesthetic costs, quality improvement among anesthesia providers, and for cost containment in the operating room.
    Journal of Medical Systems 05/2015; 39(5):226. DOI:10.1007/s10916-015-0226-2
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    ABSTRACT: Thoraco-abdominal aneurysms (TAAA) represents a particularly lethal vascular disease that without surgical repair carries a dismal prognosis. However, there is an inherent risk from surgical repair of spinal cord ischaemia that can result in paraplegia. One method of reducing this risk is cerebrospinal fluid (CSF) drainage. We believe that the CSF contains clinically significant biomarkers that can indicate impending spinal cord ischaemia. This work therefore presents a novel measurement method for proteins, namely albumin, as a precursor to further work in this area. The work uses an interdigitated electrode (IDE) sensor and shows that it is capable of detecting various concentrations of albumin (from 0 to 100 g/L) with a high degree of repeatability at 200 MHz (R(2) = 0.991) and 4 GHz (R(2) = 0.975).
    Journal of Medical Systems 04/2015; 39(4):208. DOI:10.1007/s10916-015-0208-4
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    ABSTRACT: In this article, a smart wireless sensing non-invasive system for estimating the amount of fluid loss, a person experiences while physical activity is presented. The system measures three external body parameters, Heart Rate, Galvanic Skin Response (GSR, or skin conductance), and Skin Temperature. These three parameters are entered into an empirically derived formula along with the user's body mass index, and estimation for the amount of fluid lost is determined. The core benefit of the developed system is the affluence usage in combining with smart home monitoring systems to care elderly people in ambient assisted living environments as well in automobiles to monitor the body parameters of a motorist.
    Journal of Medical Systems 04/2015; 39(4):206. DOI:10.1007/s10916-015-0206-6
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    ABSTRACT: Blood tests allow doctors to check for certain diseases and conditions. However, using a syringe to extract the blood can be deemed invasive, slightly painful, and its analysis time consuming. In this paper, we propose a new non-invasive system to detect the health status (Healthy or Diseased) of an individual based on facial block texture features extracted using the Gabor filter. Our system first uses a non-invasive capture device to collect facial images. Next, four facial blocks are located on these images to represent them. Afterwards, each facial block is convolved with a Gabor filter bank to calculate its texture value. Classification is finally performed using K-Nearest Neighbor and Support Vector Machines via a Library for Support Vector Machines (with four kernel functions). The system was tested on a dataset consisting of 100 Healthy and 100 Diseased (with 13 forms of illnesses) samples. Experimental results show that the proposed system can detect the health status with an accuracy of 93 %, a sensitivity of 94 %, a specificity of 92 %, using a combination of the Gabor filters and facial blocks.
    Journal of Medical Systems 04/2015; 39(4):227. DOI:10.1007/s10916-015-0227-1
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    ABSTRACT: Body temperature is a health or disease marker that has been in clinical use for centuries. The threshold currently applied to define fever, with small variations, is 38 °C. However, current approaches do not provide a full picture of the thermoregulation process and its correlation with disease. This paper describes a new non-invasive body temperature device that improves the understanding of the pathophysiology of diseases by integrating a variety of temperature data from different body locations. This device enables to gain a deeper insight into fever, endogenous rhythms, subject activity and ambient temperature to provide anticipatory and more efficient treatments. Its clinical use would be a big step in the overcoming of the anachronistic febrile/afebrile dichotomy and walking towards a system medicine approach to certain diseases. This device has already been used in some clinical applications successfully. Other possible applications based on the device features and clinical requirements are also described in this paper.
    Journal of Medical Systems 04/2015; 39(4):209. DOI:10.1007/s10916-015-0209-3
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    ABSTRACT: Breast cancer is one of the most common cause of cancer mortality. Early detection through mammography screening could significantly reduce mortality from breast cancer. However, most of screening methods may consume large amount of resources. We propose a computational model, which is solely based on personal health information, for breast cancer risk assessment. Our model can be served as a pre-screening program in the low-cost setting. In our study, the data set, consisting of 3976 records, is collected from Taipei City Hospital starting from 2008.1.1 to 2008.12.31. Based on the dataset, we first apply the sampling techniques and dimension reduction method to preprocess the testing data. Then, we construct various kinds of classifiers (including basic classifiers, ensemble methods, and cost-sensitive methods) to predict the risk. The cost-sensitive method with random forest classifier is able to achieve recall (or sensitivity) as 100 %. At the recall of 100 %, the precision (positive predictive value, PPV), and specificity of cost-sensitive method with random forest classifier was 2.9 % and 14.87 %, respectively. In our study, we build a breast cancer risk assessment model by using the data mining techniques. Our model has the potential to be served as an assisting tool in the breast cancer screening.
    Journal of Medical Systems 04/2015; 39(4):210. DOI:10.1007/s10916-015-0210-x
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    ABSTRACT: It was with great interest when I read Youm & Weichmann’s recent article about the Med AppJam hosted at UC Irvine School of Medicine, in light of my own recent experience at a similar event [1]. The concept of gathering individuals into teams to create a new product has become of interest across the country. These so called ‘Hackathons’ often at times find a home for the weekend on the campus of a University where participants form teams seeking to create a product centered around a theme or problem proposed by the organizers. While these hackathons tend to be heavily geared towards those in the tech field, they are slowly finding a niche in the medical community.Recently I had the privilege to attend the MedStart Innovation Challenge, which is a weekend hackathon hosted by the Tufts School of Medicine in conjunction with their MD/MBA program [2]. MedStart has been around since 2013, when it was developed with the mindset of bringing together multiple disciplines across the span of hea ...
    Journal of Medical Systems 03/2015; 39(60). DOI:10.1007/s10916-015-0247-x