Purchase individual online access for 1 year to this journal.
Price: EUR 150.00
Impact Factor 2022: 1.205
Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured.
The following types of contributions and areas are considered:
1. Original articles:
Technology development in medicine: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine.
Significance of medical technology and informatics for healthcare: The appropriateness, efficacy and usefulness deriving from the application of engineering methods, devices and informatics in medicine and with respect to public health are discussed.
2. Technical notes:
Short communications on novel technical developments with relevance for clinical medicine.
3. Reviews and tutorials (upon invitation only):
Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented.
4. Minisymposia (upon invitation only):
Under the leadership of a Special Editor, controversial issues relating to healthcare are highlighted and discussed by various authors.
Abstract: BACKGROUND: Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. OBJECTIVE: To establish a novel medical information management and decision model for uncertain demand optimization. METHODS: A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new…comprehensive improved particle swarm algorithm. RESULTS: The optimal management and decision model can effectively reduce the medicine inventory cost. CONCLUSIONS: The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.
Keywords: Medical information system, fuzzy mathematics, uncertain demand, optimal procurement model
Abstract: Medical information sharing is one of the most attractive applications of cloud computing, where searchable encryption is a fascinating solution for securely and conveniently sharing medical data among different medical organizers. However, almost all previous works are designed in symmetric key encryption environment. The only works in public key encryption do not support keyword trapdoor security, have long ciphertext related to the number of receivers, do not support receiver revocation without re-encrypting, and do not preserve the membership of receivers. In this paper, we propose a searchable encryption supporting multiple receivers for medical information sharing based on bilinear maps in…public key encryption environment. In the proposed protocol, data owner stores only one copy of his encrypted file and its corresponding encrypted keywords on cloud for multiple designated receivers. The keyword ciphertext is significantly shorter and its length is constant without relation to the number of designated receivers, i.e., for n receivers the ciphertext length is only twice the element length in the group. Only the owner knows that with whom his data is shared, and the access to his data is still under control after having been put on the cloud. We formally prove the security of keyword ciphertext based on the intractability of Bilinear Diffie-Hellman problem and the keyword trapdoor based on Decisional Diffie-Hellman problem.
Keywords: Medical information sharing, searchable encryption, multiple receivers, ciphertext security, trapdoor security
Abstract: BACKGROUND: With the rapid development of cloud computing techniques, it is attractive for personal health record (PHR) service providers to deploy their PHR applications and store the personal health data in the cloud. However, there could be a serious privacy leakage if the cloud-based system is intruded by attackers, which makes it necessary for the PHR service provider to encrypt all patients' health data on cloud servers. OBJECTIVE: Existing techniques are insufficiently secure under circumstances where advanced threats are considered, or being inefficient when many recipients are involved. Therefore, the objectives of our solution are…(1) providing a secure implementation of re-encryption in white-box attack contexts and (2) assuring the efficiency of the implementation even in multi-recipient cases. METHODS: We designed the multi-recipient re-encryption functionality by randomness-reusing and protecting the implementation by obfuscation. RESULTS: The proposed solution is secure even in white-box attack contexts. Furthermore, a comparison with other related work shows that the computational cost of the proposed solution is lower. CONCLUSIONS: The proposed technique can serve as a building block for supporting secure, efficient and privacy-preserving personal health record service systems.
Keywords: Personal health record services, electronic medical records, privacy-preserving, obfuscator, multi-recipient re-encryption
Abstract: OBJECTIVE: To analyze intima-media thickness (IMT) of carotid artery and lipoprotein-associated phospholipase A2 (Lp-PLA2) in patients with coronary heart diseases of different types. METHODS: A total of 1000 patients with suspicious coronary heart diseases were selected for carotid ultrasonography, coronary CT and Lp-PLA2, and divided into normal group, coronary atherosclerosis group and coronary heart disease group. RESULTS: Statistical significance was observed in differences of IMT and Lp-PLA2 between normal group, coronary atherosclerosis group and coronary heart disease group. IMT and Lp-PLA2 were positively correlated. The worse the coronary heart disease, the higher…the IMT or Lp-PLA2 values. CONCLUSION: IMT and Lp-PLA2 ware closely correlated with coronary artery stenosis. IMT and Lp-PLA2 have certain predicting values for severity of coronary heart diseases. The combination of the two can improve noninvasive diagnosis of coronary heart diseases.
Abstract: BACKGROUND: Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could examine the nonlinearity to gain insight into the EEG signals but very limited work has been done to address the quantitative…DVV approach. Hence, the outcomes of the quantitative DVV should be evaluated to detect the epileptic seizures. OBJECTIVE: To develop a new epileptic seizure detection method based on quantitative DVV. METHODS: This new epileptic seizure detection method employed an improved delay vector variance (IDVV) to extract the nonlinearity value as a distinct feature. Then a multi-kernel functions strategy was proposed in the extreme learning machine (ELM) network to provide precise disease detection and prediction. RESULTS: The nonlinearity is more sensitive than the energy and entropy. 87.5% overall accuracy of recognition and 75.0% overall accuracy of forecasting were achieved. CONCLUSIONS: The proposed IDVV and multi-kernel ELM based method was feasible and effective for epileptic EEG detection. Hence, the newly proposed method has importance for practical applications.
Abstract: BACKGROUND: Because medical personnel share different work shifts (i.e., three work shifts) and do not have a fixed work schedule, implementing timely, flexible, and quick e-learning methods for their continued education is imperative. Hospitals are currently focusing on developing e-learning. OBJECTIVE: This study aims to explore the key factors that influence the effectiveness of e-learning in medical personnel. METHODS: This study recruited medical personnel as the study participants and collected sample data by using the questionnaire survey method. RESULTS: This study is based on the information systems success model…(IS success model), a significant model in MIS research. This study found that the factors (i.e., information quality, service quality, convenience, and learning climate) influence the e-learning satisfaction and in turn influence effectiveness in medical personnel. CONCLUSIONS: This study provided recommendations to medical institutions according to the derived findings, which can be used as a reference when establishing e-learning systems in the future.
Keywords: E-learning, IS success model, e-learning effectiveness, e-learning satisfaction
Abstract: BACKGROUND: The intrinsic mechanism of multimorbidity is difficult to recognize and prediction and diagnosis are difficult to carry out accordingly. Bayesian networks can help to diagnose multimorbidity in health care, but it is difficult to obtain the conditional probability table (CPT) because of the lack of clinically statistical data. OBJECTIVE: Today, expert knowledge and experience are increasingly used in training Bayesian networks in order to help predict or diagnose diseases, but the CPT in Bayesian networks is usually irrational or ineffective for ignoring realistic constraints especially in multimorbidity. METHODS: In order…to solve these problems, an evidence reasoning (ER) approach is employed to extract and fuse inference data from experts using a belief distribution and recursive ER algorithm, based on which evidence reasoning method for constructing conditional probability tables in Bayesian network of multimorbidity is presented step by step. RESULTS: A multimorbidity numerical example is used to demonstrate the method and prove its feasibility and application. Bayesian network can be determined as long as the inference assessment is inferred by each expert according to his/her knowledge or experience. CONCLUSIONS: Our method is more effective than existing methods for extracting expert inference data accurately and is fused effectively for constructing CPTs in a Bayesian network of multimorbidity.
Keywords: Evidence reasoning, Bayesian network, multimorbidity, health care, construction method
Abstract: At present, China has achieved an initial establishment and gradual implementation of a framework for national essential drugs policy. With the further implementation of the national essential drugs policy, it is not clear how the policy works, whether it achieves the original intention of essential drugs policy, and what impact essential drugs policy exerts on the primary health care system. In view of it, we conducted a field research on sample areas of Shandong Province to understand the conditions of the implementation of the essential drugs policy in Shandong Province. From three perspectives of medical institutions, patients and medical staff,…this thesis analyzes the impact of essential drugs policy on village-level and township-level health service system, summarizes the effectiveness of implementing essential drugs policy, discovers the problems of various aspects and conducts an in-depth analysis of the causes, and puts forward feasible suggestions to provide reference for improving the essential drugs policy. The assessment results show that the implementation of essential drugs policy in Shandong Province has played a positive role in promoting the sound development of the primary health care system, changed the situation of covering hospital expenses with medicine revenue in the past, contributed to the return of medical institutions to public welfare, and reduced the patient's economic burden of disease. But there emerge many problems as follows: impact on the doctor's diagnosis and treatment due to incompleteness of drug types, and distribution not in place, patient loss and operational difficulty of village clinic. Thus, this thesis makes recommendations of drugs catalog formulation, drug procurement, sales and use, and meanwhile points out that the supporting financial compensation policy and performance appraisal policy and other measures in place are a prerequisite for a positive role of essential drugs policy.
Keywords: Essential drugs policy, evaluation indicators, primary health care system