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: 2.21

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 2.213
2013 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 1.96
Cited half-life 2.90
Immediacy index 0.89
Eigenfactor 0.00
Article influence 0.34
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

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    • Author can archive a pre-print version
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    • 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

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents a robust device for automated screening of pediatric heart diseases based on our unique processing method in murmur characterization; the Arash-Band method. The present study modifies the Arash-Band method and employs output of the modified method in conjunction with the two other original techniques to extract indicative feature vectors for the screening. The extracted feature vectors are classified by using the support vector machine method. Results show that the proposed modifications significantly enhances performance of the Arash-Band in terms of the both accuracy and sensitivity as the corresponding effect sizes are sufficiently large. The proposed algorithm has been incorporated into an Android-based tablet to constitute an intelligent phonocardiogram with the automatic screening capability. In order to obtain confidence interval of the accuracy and sensitivity, an inferable statistical test is applied on our database containing the phonocardiogram signals recorded from 263 of the referrals to a hospital. The expected value of the accuracy/sensitivity is estimated to be 87.45 % / 87.29 % with a 95 % confidence interval of (80.19 % - 92.47 %) / (76.01 % - 95.78 %) exhibiting superior performance than a pediatric cardiologist who relies on conventional or even computer-assisted auscultation.
    Journal of Medical Systems 11/2015; 40(1):16. DOI:10.1007/s10916-015-0359-3
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    ABSTRACT: Accurately and efficiently identifying the location of patients during the course of rehabilitation is an important issue. Wireless transmission technology can reach this goal. Tracking technologies such as RFID (Radio frequency identification) can support process improvement and improve efficiencies of rehabilitation. There are few published models or methods to solve the problem of positioning and apply this technology in the rehabilitation center. We propose a mechanism to enhance the accuracy of positioning technology and provide information about turns and obstacles on the path; and user-centered services based on location-aware to enhanced quality care in rehabilitation environment. This paper outlines the requirements and the role of RFID in assisting rehabilitation environment. A prototype RFID hospital support tool is established. It is designed to provide assistance for monitoring rehabilitation patients. It can simultaneously calculate the rehabilitant's location and the duration of treatment, and automatically record the rehabilitation course of the rehabilitant, so as to improve the management efficiency of the rehabilitation program.
    Journal of Medical Systems 11/2015; 40(1):4. DOI:10.1007/s10916-015-0370-8
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    ABSTRACT: The continued availability of products at any store is the major issue in order to provide good customer service. If the store is a drugstore this matter reaches a greater importance, as out of stock of a drug when there is high demand causes problems and tensions in the healthcare system. There are numerous studies of the impact this issue has on patients. The lack of any drug in a pharmacy in certain seasons is very common, especially when some external factors proliferate favoring the occurrence of certain diseases. This study focuses on a particular drug consumed in the city of Jaen, southern Andalucia, Spain. Our goal is to determine in advance the Salbutamol demand. Advanced data mining techniques have been used with spatial variables. These last have a key role to generate an effective model. In this research we have used the attributes that are associated with Salbutamol demand and it has been generated a very accurate prediction model of 5.78% of mean absolute error. This is a very encouraging data considering that the consumption of this drug in Jaen varies 500% from one period to another.
    Journal of Medical Systems 11/2015; 40(Smart Living in Healthcare and Innovations):6. DOI:10.1007/s10916-015-0379-z
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    ABSTRACT: Despite of various benefits such as a convenience and efficiency, home healthcare systems have some inherent security risks that may cause a serious leak on personal health information. This work presents a Secure User Profiling Structure which has the patient information including their health information. A patient and a hospital keep it at that same time, they share the updated data. While they share the data and communicate, the data can be leaked. To solve the security problems, a secure communication channel with a hash function and an One-Time Password between a client and a hospital should be established and to generate an input value to an OTP, it uses a dual hash-function. This work presents a dual hash function-based approach to generate the One-Time Password ensuring a secure communication channel with the secured key. In result, attackers are unable to decrypt the leaked information because of the secured key; in addition, the proposed method outperforms the existing methods in terms of computation cost.
    Journal of Medical Systems 11/2015; 40(1):1. DOI:10.1007/s10916-015-0365-5
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    ABSTRACT: Patient medication safety is an important issue in patient medication systems. In order to prevent medication errors, integrating Radio Frequency Identification (RFID) technology into automated patient medication systems is required in hospitals. Based on RFID technology, such systems can provide medical evidence for patients' prescriptions and medicine doses, etc. Due to the mutual authentication between the medication server and the tag, RFID authentication scheme is the best choice for automated patient medication systems. In this paper, we present a RFID mutual authentication scheme based on elliptic curve cryptography (ECC) to enhance patient medication safety. Our scheme can achieve security requirements and overcome various attacks existing in other schemes. In addition, our scheme has better performance in terms of computational cost and communication overhead. Therefore, the proposed scheme is well suitable for patient medication systems.
    Journal of Medical Systems 11/2015; 40(1):12. DOI:10.1007/s10916-015-0362-8
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    ABSTRACT: The accuracy of optical tracking systems is important to scientists. With the improvements reported in this regard, such systems have been applied to an increasing number of operations. To enhance the accuracy of these systems further and to reduce the effect of synchronization and visual field errors, this study introduces a field-programmable gate array (FPGA)-based synchronization control method, a method for measuring synchronous errors, and an error distribution map in field of view. Synchronization control maximizes the parallel processing capability of FPGA, and synchronous error measurement can effectively detect the errors caused by synchronization in an optical tracking system. The distribution of positioning errors can be detected in field of view through the aforementioned error distribution map. Therefore, doctors can perform surgeries in areas with few positioning errors, and the accuracy of optical tracking systems is considerably improved. The system is analyzed and validated in this study through experiments that involve the proposed methods, which can eliminate positioning errors attributed to asynchronous cameras and different fields of view.
    Journal of Medical Systems 11/2015; 40(1):7. DOI:10.1007/s10916-015-0368-2
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    ABSTRACT: Computer growth charting is increasingly available for clinical and research applications. The LMS method is used to define the growth curves on the charts most commonly used in practice today. The data points for any given chart are at discrete points, and computer programs may simply round to the closest LMS data point when calculating growth centiles. We sought to determine whether applying an interpolation algorithm to the LMS data for commonly used growth charts may reduce the inherent errors which occur with rounding to the nearest data point. We developed a simple, easily implemented interpolation algorithm to use with LMS data. Using published growth charts, we compared predicted growth centiles using our interpolation algorithm versus a standard rounding approach. Using a test scenario of a patient at the 50th centile in weight, compared to using our interpolation algorithm, the method of simply rounding to the nearest data point resulted in maximal z-score errors in weight of the following: 2.02 standard deviations for the World Health Organization 0-to-23 month growth chart, 1.07 standard deviations for the Fenton preterm growth chart, 0.71 standard deviations for the Olsen preterm growth chart, and 0.11 standard deviations for the CDC 2-to-18 year growth chart. Failure to include an interpolation algorithm when designing computerizing growth charts can lead to large errors in centile and z-score calculations.
    Journal of Medical Systems 11/2015; 40(1):15. DOI:10.1007/s10916-015-0389-x
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    ABSTRACT: This research analyzes the impact of mobile phone screen size on user comprehension of health information and application structure. Applying experimental approach, we asked randomly selected users to read content and conduct tasks on a commonly used diabetes mobile application using three different mobile phone screen sizes. We timed and tracked a number of parameters, including correctness, effectiveness of completing tasks, content ease of reading, clarity of information organization, and comprehension. The impact of screen size on user comprehension/retention, clarity of information organization, and reading time were mixed. It is assumed on first glance that mobile screen size would affect all qualities of information reading and comprehension, including clarity of displayed information organization, reading time and user comprehension/retention of displayed information, but actually the screen size, in this experimental research, did not have significant impact on user comprehension/retention of the content or on understanding the application structure. However, it did have significant impact on clarity of information organization and reading time. Participants with larger screen size took shorter time reading the content with a significant difference in the ease of reading. While there was no significant difference in the comprehension of information or the application structures, there were a higher task completion rate and a lower number of errors with the bigger screen size. Screen size does not directly affect user comprehension of health information. However, it does affect clarity of information organization, reading time and user's ability to recall information.
    Journal of Medical Systems 11/2015; 40(1):11. DOI:10.1007/s10916-015-0381-5
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    ABSTRACT: Alzheimer's disease (AD) is the most common dementia in developed countries. Between the identified risk factors, one of the most important is the age. Its prevalence reaches 24 % in men and 33 % in women over 85 years. Increase in life expectancy, making it a serious public health problem. Prevention of Alzheimer's disease represents a major challenge to health. Given that Alzheimer's disease is largely dependent on the genetics of each person and uninterrupted progress of the age, which is try to make people aware that there are other factors that can alter your chance of developing the Alzheimer disease and although currently not reduce, help is not increased in the near or distant future.The aim of this paper is to develop and evaluate a Web-Mobile application (Alzhe Alert) used to calculate the risk of Alzheimer's from a short questionnaire using a computer or mobile device, so that any user, without requiring computer skills, can access the website to estimate their risk of developing the disease in the coming years depending on their habits and daily basis activities. The users who have realized the questionnaire can to observe in a graph the result, and they will know which is at risk for Alzheimer's at present and over the next 50 years if they continue with the same habits and lifestyle. The objective is that the users can be aware of the risk they have different habits of life about their health. Currently, 243 users (84 women and 159 men) of white race have completed the questionnaire. 76 % of the users have got a risk below the average.
    Journal of Medical Systems 11/2015; 40(1):3. DOI:10.1007/s10916-015-0369-1
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    ABSTRACT: Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or patient physical factors, to estimate clinical outcomes at early stages of CTPs (e.g., admission). They lack the ability to deal with temporal evolution of CTPs. In addition, most of the existing studies employ data mining or machine learning methods to generate a prediction model for a specific type of clinical outcome, however, a mathematical model that predicts multiple clinical outcomes simultaneously, has not yet been established. In this study, a hybrid approach is proposed to provide a continuous predictive monitoring service on multiple clinical outcomes. More specifically, a probabilistic topic model is applied to discover underlying treatment patterns of CTPs from electronic medical records. Then, the learned treatment patterns, as low-dimensional features of CTPs, are exploited for clinical outcome prediction across various stages of CTPs based on multi-label classification. The proposal is evaluated to predict three typical classes of clinical outcomes, i.e., length of stay, readmission time, and the type of discharge, using 3492 pieces of patients' medical records of the unstable angina CTP, extracted from a Chinese hospital. The stable model was characterized by 84.9% accuracy and 6.4% hamming-loss with 3 latent treatment patterns discovered from data, which outperforms the benchmark multi-label classification algorithms for clinical outcome prediction. Our study indicates the proposed approach can potentially improve the quality of clinical outcome prediction, and assist physicians to understand the patient conditions, treatment inventions, and clinical outcomes in an integrated view.
    Journal of Medical Systems 11/2015; 40(1):8. DOI:10.1007/s10916-015-0380-6
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    ABSTRACT: We present in this paper a novel approach based on multi-agent technology for Web information foraging. We proposed for this purpose an architecture in which we distinguish two important phases. The first one is a learning process for localizing the most relevant pages that might interest the user. This is performed on a fixed instance of the Web. The second takes into account the openness and dynamicity of the Web. It consists on an incremental learning starting from the result of the first phase and reshaping the outcomes taking into account the changes that undergoes the Web. The system was implemented using a colony of artificial ants hybridized with tabu search in order to achieve more effectiveness and efficiency. To validate our proposal, experiments were conducted on MedlinePlus, a real website dedicated for research in the domain of Health in contrast to other previous works where experiments were performed on web logs datasets. The main results are promising either for those related to strong Web regularities and for the response time, which is very short and hence complies the real time constraint.
    Journal of Medical Systems 11/2015; 40(1):5. DOI:10.1007/s10916-015-0350-z
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    ABSTRACT: Physicians increasingly use handheld electronic devices (HED) to assist in daily work activities. The objectives of our study were to describe the practice patterns of pediatric hospitalists in the use of HED during daily work activities and Family Centered Rounds (FCR). We also examined perceptions of pediatric hospitalists on benefits and barriers of these devices on trainee education and family/patient interactions. An anonymous cross-sectional survey was sent to the American Academy of Pediatrics' Section on Hospital Medicine Listserv between October-November 2012, to determine pediatric hospitalists usage and attitudes of HED on FCR. A total of 140 Listserv members responded. Seventy six percent reported using a HED in daily work activities. One-third claimed their institution has a policy on device use. Eighty one percent of respondents practice FCR at their institution. Only 34 % of those who practice FCR use a HED on FCR. Those who have used a HED on FCR responded "always" or "often" to the following questions: 48 % feel the use of these devices improves educational experiences for learners on FCR, and 49 % feel these devices improve patient/family educational opportunities on FCR. Over 75 % of pediatric hospitalists used a HED in their daily work activities. A majority is unaware or claims their institution has no policy on handheld device use. While most respondents practice FCR, only one-third used these devices on FCR despite the belief that these devices improve trainee and patient/family educational opportunities on FCR.
    Journal of Medical Systems 11/2015; 40(1):9. DOI:10.1007/s10916-015-0366-4
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    ABSTRACT: The revolution of internet and specifically mobile internet has occurred at a blinding pace over the last decade. With the advent of smart phones, the hand held device has become much more than a medium of voice calling. Healthcare has been catching up with the digital revolution in the form of Hospital Information System and Laboratory Information System. However, the advent of instant messaging services, which are abundantly used by the youth, can be used to improve communication and coordination among the various stake holders in the healthcare sector. We have tried to look at the impact of using the WhatsApp messenger service in the laboratory management system, by forming multiple groups of the various subsections of the laboratory. A total of 35 members used this service for a period of 3 months and their response was taken on a scale of 1 to 10. There was significant improvement in the communication in the form of sharing photographic evidence, information about accidents, critical alerts, duty rosters, academic activities and getting directives from seniors. There was also some increase in the load of adding information to the application and disturbance in the routine activities; but the benefits far outweighed the minor hassles. We thereby suggest and foresee another communication revolution which will change the way information is shared in a healthcare sector, with hospital specific dedicated apps.
    Journal of Medical Systems 11/2015; 40(1):14. DOI:10.1007/s10916-015-0384-2
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    ABSTRACT: The objective of this analysis is to describe the utilization metrics of a pharmacy clinical surveillance system (PCSS) at a tertiary, academic medical center.We performed a retrospective database analysis assessing rule-based alerts (RBA), interventions and pharmacist communication notes documented in the PCSS from January 1, 2014 to December 31, 2014. Reports were generated on 92 unique RBAs sent to clinicians for evaluation. Metrics assessed included the number of RBAs that were triggered, clinically evaluated, intervened on by pharmacists, and therapeutic category of interventions. Pharmacy communication notes were also evaluated.A total of 399,979 RBAs were triggered through the PCSS. During that time, pharmacists documented a total of 17,733 interventions. The most common RBAs were related to lab abnormalities (132,487; 33 %) and anticoagulation/antiplatelet therapy (126,425; 32.1 %). Interventions were most frequently related to RBAs regarding anticoagulation/antiplatelet therapy (6412; 36 %) and antimicrobial therapy (3320; 19 %). Pharmacist communication was most commonly related to clarification of medication and lab orders, and therapeutic drug monitoring.Based on utilization metrics presented, the implementation of a PCSS has successfully generated RBAs to aid pharmacists in clinical practice and improved departmental documentation and communication. Further analysis is warranted to assess the impact of the RBAs, interventions, and communication notes on outcomes such as hospital cost and adverse drug events.
    Journal of Medical Systems 11/2015; 40(1):24. DOI:10.1007/s10916-015-0398-9
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    ABSTRACT: Analysis of neuromuscular fatigue finds various applications ranging from clinical studies to biomechanics. Surface electromyography (sEMG) signals are widely used for these studies due to its non-invasiveness. During cyclic dynamic contractions, these signals are nonstationary and cyclostationary. In recent years, several nonstationary methods have been employed for the muscle fatigue analysis. However, cyclostationary based approach is not well established for the assessment of muscle fatigue. In this work, cyclostationarity associated with the biceps brachii muscle fatigue progression is analyzed using sEMG signals and Spectral Correlation Density (SCD) functions. Signals are recorded from fifty healthy adult volunteers during dynamic contractions under a prescribed protocol. These signals are preprocessed and are divided into three segments, namely, non-fatigue, first muscle discomfort and fatigue zones. Then SCD is estimated using fast Fourier transform accumulation method. Further, Cyclic Frequency Spectral Density (CFSD) is calculated from the SCD spectrum. Two features, namely, cyclic frequency spectral area (CFSA) and cyclic frequency spectral entropy (CFSE) are proposed to study the progression of muscle fatigue. Additionally, degree of cyclostationarity (DCS) is computed to quantify the amount of cyclostationarity present in the signals. Results show that there is a progressive increase in cyclostationary during the progression of muscle fatigue. CFSA shows an increasing trend in muscle fatiguing contraction. However, CFSE shows a decreasing trend. It is observed that when the muscle progresses from non-fatigue to fatigue condition, the mean DCS of fifty subjects increases from 0.016 to 0.99. All the extracted features found to be distinct and statistically significant in the three zones of muscle contraction (p < 0.05). It appears that these SCD features could be useful in the automated analysis of sEMG signals for different neuromuscular conditions.
    Journal of Medical Systems 11/2015; 40(1):28. DOI:10.1007/s10916-015-0394-0