Journal of Medical Systems (J Med Syst )

Publisher: Springer Verlag

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.

  • Impact factor
    1.78
  • 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
    • Authors own final version only can be archived
    • Publisher's version/PDF cannot be used
    • On author's website or institutional repository
    • On funders designated website/repository after 12 months at the funders request or as a result of legal obligation
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (The original publication is available at www.springerlink.com)
    • 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: Cardiac events could be taken into account as the leading causes of death throughout the globe. Such events also trigger an undesirable increase in what treatment procedures cost. Despite the giant leaps in technological development in heart surgery, coronary surgery still carries the high risk of the mortality. Besides, there is still a long way ahead to accurately predict and assess the mortality risk. This study is an attempt to develop an expert system for the risk assessment of mortality following the cardiac surgery. The developed system involves three main steps. In the first step, a filtering feature selection method is applied to select the best features. In the second step, an ad hoc data-driven method is utilized to generate the preliminary fuzzy inference system. Finally, a hybrid optimization method is presented to select the optimum subset of the rules. The study relies on 1,811 samples to evaluate the diagnosis performance of the proposed system. The obtained classification accuracy is very promising with regard to other benchmark classification methods including binary logistic regression (LR) and multilayer perceptron neural network (MLP) with the same attributes. The developed system leads to 100 % sensitivity and 84.7 % specificity, while LR and MLP methods statistically come up with lower figures (65, 78.6 and 65 %, 75.8 %), respectively. Now, a fuzzy supportive tool can be potentially taken as an alternative for the current mortality risk assessment system that are applied in coronary surgeries, and are chiefly based on crisp database.
    Journal of Medical Systems 10/2014; 38(10):102.
  • Maximilian Sandholzer, Imre Rurik, Tobias Deutsch, Thomas Frese
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    ABSTRACT: Undergraduate and postgraduate medical education in general practice is complex as a wide medical spectrum needs to be covered. Modern guidelines demand students to be able to recall immense amounts of information relating to the diagnosis and management of clinical problems. With the intent of making a medical textbook digitally available on student mobile devices, preferences of students and potential of the idea was aimed to be researched. A total estimation among fourth year medical students at the Leipzig Medical School was conducted in June 2013. Students were asked to answer a semi-structured self-designed questionnaire regarding their detailed smartphone and app usage as well as their attitude and expectations towards education and practice supporting apps. The response rate was 93.2 % (n = 290/311). The majority (69.3 %) were female students. The mean age was 24.5 years. Of the respondents, 64.2 % owned a smartphone and 22.5 % a tablet computer. A total of 32.4 % were already using medical apps for the smartphone - mostly drug reference or disease diagnosis and management apps. Regarding their wishes, 68.7 % would like or very like to see an app on general practice. The respective means of the most important desired features on a Likert scale reaching from 1 (not important) to 5 (very important) were 4.3 for drug reference information, 4.2 for guidelines for differential diagnosis, 3.9. for medical pictures libraries and 3.9 for physical examination videos. The willingness to pay for a profound app averages at 14.35 Euros (SD = 16.21). Concluding, students clearly demand for an app on general practice. Such an app should ideally be smartphone optimized. Aside of what is usually available in traditional textbooks, multimedia features such as videos on examining methods or a medical picture library are very important to students and may help to bridge the gap between text-based knowledge and practical application. Therefore, authors of medical textbooks need to be aware that the development of an app is no trivial technical translation as raised students expectations demand for multimedia and interactive features as well as comprehensive drug information. Further research should focus on developing concepts to bring together developers and university professionals as well as experienced medical specialists to enable the development of apps that satisfy the demands of undergraduate and postgraduate educational needs.
    Journal of Medical Systems 10/2014; 38(10):125.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Wireless Body Area Networks (WBANs) are amongst the best options for remote health monitoring. However, as standalone systems WBANs have many limitations due to the large amount of processed data, mobility of monitored users, and the network coverage area. Integrating WBANs with cloud computing provides effective solutions to these problems and promotes the performance of WBANs based systems. Accordingly, in this paper we propose a cloud-based real-time remote health monitoring system for tracking the health status of non-hospitalized patients while practicing their daily activities. Compared with existing cloud-based WBAN frameworks, we divide the cloud into local one, that includes the monitored users and local medical staff, and a global one that includes the outer world. The performance of the proposed framework is optimized by reducing congestion, interference, and data delivery delay while supporting users' mobility. Several novel techniques and algorithms are proposed to accomplish our objective. First, the concept of data classification and aggregation is utilized to avoid clogging the network with unnecessary data traffic. Second, a dynamic channel assignment policy is developed to distribute the WBANs associated with the users on the available frequency channels to manage interference. Third, a delay-aware routing metric is proposed to be used by the local cloud in its multi-hop communication to speed up the reporting process of the health-related data. Fourth, the delay-aware metric is further utilized by the association protocols used by the WBANs to connect with the local cloud. Finally, the system with all the proposed techniques and algorithms is evaluated using extensive ns-2 simulations. The simulation results show superior performance of the proposed architecture in optimizing the end-to-end delay, handling the increased interference levels, maximizing the network capacity, and tracking user's mobility.
    Journal of Medical Systems 10/2014; 38(10):121.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Compliance checking for clinical pathways (CPs) is getting increasing attention in health-care organizations due to stricter requirements for cost control and treatment excellence. Many compliance measures have been proposed for treatment behavior inspection in CPs. However, most of them look at aggregated data seen from an external perspective, e.g. length of stay, cost, infection rate, etc., which may provide only a posterior impression of the overall conformance with the established CPs such that in-depth and in near real time checking on the compliance of the essential/critical treatment behaviors of CPs is limited. To provide clinicians real time insights into violations of the established CP specification and support online compliance checking, this article presents a semantic rule-based CP compliance checking system. In detail, we construct a CP ontology (CPO) model to provide a formal grounding of CP compliance checking. Using the proposed CPO, domain treatment constraints are modeled into Semantic Web Rule Language (SWRL) rules to specify the underlying treatment behaviors and their quantified temporal structure in a CP. The established SWRL rules are integrated with the CP workflow such that a series of applicable compliance checking and evaluation can be reminded and recommended during the pathway execution. The proposed approach can, therefore, provides a comprehensive compliance checking service as a paralleling activity to the patient treatment journey of a CP rather than an afterthought. The proposed approach is illustrated with a case study on the unstable angina clinical pathway implemented in the Cardiology Department of a Chinese hospital. The results demonstrate that the approach, as a feasible solution to provide near real time conformance checking of CPs, not only enables clinicians to uncover non-compliant treatment behaviors, but also empowers clinicians with the capability to make informed decisions when dealing with treatment compliance violations in the pathway execution.
    Journal of Medical Systems 10/2014; 38(10):123.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Advancement in network technology provides new ways to utilize telecare medicine information systems (TMIS) for patient care. Although TMIS usually faces various attacks as the services are provided over the public network. Recently, Jiang et al. proposed a chaotic map-based remote user authentication scheme for TMIS. Their scheme has the merits of low cost and session key agreement using Chaos theory. It enhances the security of the system by resisting various attacks. In this paper, we analyze the security of Jiang et al.'s scheme and demonstrate that their scheme is vulnerable to denial of service attack. Moreover, we demonstrate flaws in password change phase of their scheme. Further, our aim is to propose a new chaos map-based anonymous user authentication scheme for TMIS to overcome the weaknesses of Jiang et al.'s scheme, while also retaining the original merits of their scheme. We also show that our scheme is secure against various known attacks including the attacks found in Jiang et al.'s scheme. The proposed scheme is comparable in terms of the communication and computational overheads with Jiang et al.'s scheme and other related existing schemes. Moreover, we demonstrate the validity of the proposed scheme through the BAN (Burrows, Abadi, and Needham) logic.
    Journal of Medical Systems 10/2014; 38(10):120.
  • [Show abstract] [Hide abstract]
    ABSTRACT: We developed a content validated computerized epilepsy treatment clinical decision support system to assist clinicians with selecting the best antiepilepsy treatments. Before disseminating our computerized epilepsy treatment clinical decision support system, further rigorous validation testing was necessary. As reliability is a precondition of validity, we verified proof of reliability first. We evaluated the consistency of the epilepsy treatment clinical decision support system in three areas including the preferred antiepilepsy drug choice, the top three recommended choices, and the rank order of the three choices. We demonstrated 100 % reliability on 15,000 executions involving a three-step process on five different common pediatric epilepsy syndromes. Evidence for the reliability of the epilepsy treatment clinical decision support system was essential for the long-term viability of the system, and served as a crucial component for the next phase of system validation.
    Journal of Medical Systems 10/2014; 38(10):119.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The radio frequency identification (RFID) technology has been widely adopted and being deployed as a dominant identification technology in a health care domain such as medical information authentication, patient tracking, blood transfusion medicine, etc. With more and more stringent security and privacy requirements to RFID based authentication schemes, elliptic curve cryptography (ECC) based RFID authentication schemes have been proposed to meet the requirements. However, many recently published ECC based RFID authentication schemes have serious security weaknesses. In this paper, we propose a new ECC based RFID authentication integrated with an ID verifier transfer protocol that overcomes the weaknesses of the existing schemes. A comprehensive security analysis has been conducted to show strong security properties that are provided from the proposed authentication scheme. Moreover, the performance of the proposed authentication scheme is analyzed in terms of computational cost, communicational cost, and storage requirement.
    Journal of Medical Systems 10/2014; 38(10):116.
  • [Show abstract] [Hide abstract]
    ABSTRACT: In a mobile health management system, mobile devices act as the application hosting devices for personal health records (PHRs) and the healthcare servers construct to exchange and analyze PHRs. One of the most popular PHR standards is continuity of care record (CCR). The CCR is expressed in XML formats. However, parsing is an expensive operation that can degrade XML processing performance. Hence, the objective of this study was to identify different operational and performance characteristics for those CCR parsing models including the XML DOM parser, the SAX parser, the PULL parser, and the JSON parser with regard to JSON data converted from XML-based CCR. Thus, developers can make sensible choices for their target PHR applications to parse CCRs when using mobile devices or servers with different system resources. Furthermore, the simulation experiments of four case studies are conducted to compare the parsing performance on Android mobile devices and the server with large quantities of CCR data.
    Journal of Medical Systems 10/2014; 38(10):117.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The aim of the paper is to use data mining technology to establish a classification of breast cancer survival patterns, and offers a treatment decision-making reference for the survival ability of women diagnosed with breast cancer in Taiwan. We studied patients with breast cancer in a specific hospital in Central Taiwan to obtain 1,340 data sets. We employed a support vector machine, logistic regression, and a C5.0 decision tree to construct a classification model of breast cancer patients' survival rates, and used a 10-fold cross-validation approach to identify the model. The results show that the establishment of classification tools for the classification of the models yielded an average accuracy rate of more than 90 % for both; the SVM provided the best method for constructing the three categories of the classification system for the survival mode. The results of the experiment show that the three methods used to create the classification system, established a high accuracy rate, predicted a more accurate survival ability of women diagnosed with breast cancer, and could be used as a reference when creating a medical decision-making frame.
    Journal of Medical Systems 10/2014; 38(10):106.
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper we analyse the efficiency of primary care centres (PCCs) adopting Information and Communication Technology (ICT) devices, using a new database on primary care centres in the Basque Region in Spain. Using a four-stage Data Envelopment Analysis methodology, we are able to explicitly take into account the role of ICT in affecting the efficiency of primary care centres. We understand that this is the first time that ICT enters into the determination of efficiency of the health sector. The role of exogenous factors is explicitly considered in this analysis and shows that including these variables is not neutral to the efficiency evaluation, but leads to an efficiency indicator that only encompasses the effect of managerial skills. The paper provides some useful policy implications regarding the role of ICT in improving the efficiency of primary care units.
    Journal of Medical Systems 10/2014; 38(10):122.
  • Brahim Hadji, Rodolphe Meyer, Samir Melikeche, Sylvie Escalon, Patrice Degoulet
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    ABSTRACT: Face the challenge of minimizing their resource utilization without reducing the quality of healthcare. Achieving this aim requires precise analysis and optimization of various inputs and outputs. This paper presents a systematic review of the relationships between hospital resources (considered productivity inputs) and financial and activity outcomes (considered productivity outputs). Several electronic bibliographic databases and the Internet were searched for articles published between January 1990 and December 2013 that examined the relationships between hospital resources and financial and activity outcomes. We assessed the quality of the study design, the nature of the sample, input and output indicators, and the statistical methods used for each selected study. Thirty-eight original papers were selected. Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) were the most statistical methods used. Based on our analysis, we retained 18 input and 19 output indicators that could constitute the basis for hospital productivity benchmarking. Selecting a small set of shared economic and activity indicators is relevant for assessing the productivity of a hospital, measuring trends and performing national or international benchmarking. Such indicators should be combined with quality measures for a comprehensive evaluation approach.
    Journal of Medical Systems 10/2014; 38(10):127.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Measuring and providing performance feedback to physicians has gained momentum not only as a way to comply with regulatory requirements, but also as a way to improve patient care. Measurement of structural, process, and outcome metrics in a reliable, evidence-based, specialty-specific manner maximizes the probability of improving physician performance. The manner in which feedback is provided influences whether the measurement tool will be successful in changing behavior. We created an innovative reporting tool template for anesthesiology practitioners designed to provide detailed, continuous feedback covering many aspects of clinical practice.
    Journal of Medical Systems 09/2014; 38(9):105.
  • [Show abstract] [Hide abstract]
    ABSTRACT: In these days, there are many various diseases, whose diagnosis is very hardly. Breast cancer is one of these type diseases. In this paper, accuracy diagnosis of normal, benign, and malign breast cancer cell were found by combining mean success rates Jensen Shannon, Hellinger, and Triangle measure which connected with each other. In this article, an diagnostic method based on feature extraction Discrete Wavelet Entropy Energy (DWEE) and Jensen Shannon, Hellinger, Triangle Measure (JHT) Classifier for diagnosis of breast cancer. This diagnosis method is called as DWEE-JHT this paper. With this diagnosis method have found optimal feature subset using discrete wavelet transform feature extraction. Then these convenient features are given to Jensen Shannon, Hellinger, Triangle Measure (JHT) classifier. Then, between classifiers which are Jensen Shannon, Hellinger, and triangle distance have been validated the measures via relationships. Afterwards, breast cancer cells are classified using Jensen Shannon, Hellinger, and Triangle distance. Mean success rate of 16 feature vector with Jensen Shannon classifier is found % 97.81. Mean success rate of 16 feature vector with Hellinger classifier is found % 97.75. Mean success rate of 16 feature vector with Triangle classifier is found % 97.87. By averaging of results obtained from these 3 classifiers are found as 97.81 % average of accuracy diagnosis.
    Journal of Medical Systems 09/2014; 38(9):92.
  • [Show abstract] [Hide abstract]
    ABSTRACT: RFID technology is increasingly used in applications that require tracking, identification, and authentication. It attaches RFID-readable tags to objects for identification and execution of specific RFID-enabled applications. Recently, research has focused on the use of grouping-proofs for preserving privacy in RFID applications, wherein a proof of two or more tags must be simultaneously scanned. In 2010, a privacy-preserving grouping proof protocol for RFID based on ECC in public-key cryptosystem was proposed but was shown to be vulnerable to tracking attacks. A proposed enhancement protocol was also shown to have defects which prevented proper execution. In 2012, Lin et al. proposed a more efficient RFID ECC-based grouping proof protocol to promote inpatient medication safety. However, we found this protocol is also vulnerable to tracking and impersonation attacks. We then propose a secure privacy-preserving RFID grouping proof protocol for inpatient medication safety and demonstrate its resistance to such attacks.
    Journal of Medical Systems 09/2014; 38(9):66.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Grassroots healthcare institutions (GHIs) are the smallest administrative levels of medical institutions, where most patients access health services. The latest report from the National Bureau of Statistics of China showed that 96.04 % of 950,297 medical institutions in China were at the grassroots level in 2012, including county-level hospitals, township central hospitals, community health service centers, and rural clinics. In developing countries, these institutions are facing challenges involving a shortage of funds and talent, inconsistent medical standards, inefficient information sharing, and difficulties in management during the adoption of health information technologies (HIT). Because of the necessity and gravity for GHIs, our aim is to provide hospital information services for GHIs using Cloud computing technologies and service modes. In this medical scenario, the computing resources are pooled by means of a Cloud-based Virtual Desktop Infrastructure (VDI) to serve multiple GHIs, with different hospital information systems dynamically assigned and reassigned according to demand. This paper is concerned with establishing a Cloud-based Hospital Information Service Center to provide hospital information software as a service (HI-SaaS) with the aim of providing GHIs with an attractive and high-performance medical information service. Compared with individually establishing all hospital information systems, this approach is more cost-effective and affordable for GHIs and does not compromise HIT performance.
    Journal of Medical Systems 09/2014; 38(9):104.
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    ABSTRACT: When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledge is often an important contribution to their ability to make more informed decisions. In this paper we describe a method by which an external, formal representation of clinical and molecular genetic knowledge can be integrated into an EHR such that customized knowledge can be delivered to clinicians in a context-appropriate manner.Web Ontology Language-Description Logic (OWL-DL) is a formal knowledge representation language that is widely used for creating, organizing and managing biomedical knowledge through the use of explicit definitions, consistent structure and a computer-processable format, particularly in biomedical fields. In this paper we describe: 1) integration of an OWL-DL knowledge base with a standards-based EHR prototype, 2) presentation of customized information from the knowledge base via the EHR interface, and 3) lessons learned via the process. The integration was achieved through a combination of manual and automatic methods. Our method has advantages for scaling up to and maintaining knowledge bases of any size, with the goal of assisting clinicians and other EHR users in making better informed health care decisions.
    Journal of Medical Systems 09/2014; 38(9):75.
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    ABSTRACT: Efficient management of patient flow (demand) in emergency departments (EDs) has become an urgent issue for many hospital administrations. Today, more and more attention is being paid to hospital management systems to optimally manage patient flow and to improve management strategies, efficiency and safety in such establishments. To this end, EDs require significant human and material resources, but unfortunately these are limited. Within such a framework, the ability to accurately forecast demand in emergency departments has considerable implications for hospitals to improve resource allocation and strategic planning. The aim of this study was to develop models for forecasting daily attendances at the hospital emergency department in Lille, France. The study demonstrates how time-series analysis can be used to forecast, at least in the short term, demand for emergency services in a hospital emergency department. The forecasts were based on daily patient attendances at the paediatric emergency department in Lille regional hospital centre, France, from January 2012 to December 2012. An autoregressive integrated moving average (ARIMA) method was applied separately to each of the two GEMSA categories and total patient attendances. Time-series analysis was shown to provide a useful, readily available tool for forecasting emergency department demand.
    Journal of Medical Systems 09/2014; 38(9):107.

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