Kambiz Bahaadinbeigy

The Effectiveness of Mobile Phone Text Messaging in Improving Medication Adherence for Patients with Chronic Diseases: A Systematic Review

Context Medication non-adherence is a commonly observed problem in the self-administration of treatment, regardless of the disease type. Text messaging reminders, as electronic reminders, provide an opportunity to improve medication adherence. In this study, we aimed to provide evidence addressing the question of whether text message reminders were effective in improving patients’ adherence to medication. Evidence Acquisition We carried out a systematic literature search, using the five electronic bibliographic databases: PubMed, Embase, PsycINFO, CINAHL, and the Cochrane central register of controlled trials. Studies were included on the basis of whether they examined the benefits and effects of short-message service (SMS) interventions on medication adherence. Results The results of this systematic review indicated that text messaging interventions have improved patients’ medication adherence rate (85%, 29.34). Included in the review, those who had problems with adherence, or those whom text messaging was most helpful had HIV, asthma, diabetes, schizophrenia and heart disease (73.5%). The period of intervention varied from 1 week to 14 months. The most common study design was randomized controlled trials (RCTs) (66%) carried out in the developed countries. Conclusions This study demonstrated the potential of mobile phone text messaging for medication non-adherence problem solving.

The 60 most highly cited articles published in the Journal of Telemedicine and Telecare and Telemedicine Journal and E-health

Summary We analysed the most highly cited articles in two specialist telemedicine journals, the Journal of Telemedicine and Telecare (JTT) and Telemedicine Journal and E-health (TJEH). Articles were extracted from the Science Citation Index Expanded in September 2012. A total of 1810 articles were listed for the JTT and 1550 for TJEH. In the JTT, the mean number of citations was 43 (SD 13); in TJEH the mean number of citations was 30 (SD 11). The average number of citations for the JTT was significantly higher than for TJEH (P < 0.001). In each journal, the 60 articles which had the most citations were identified as highly cited publications (HCPs). The 60 HCPs in the JTT originated from 16 countries; the 60 HCPs in TJEH originated from 10 countries. Considering both journals together, the majority of HCPs came from the US, UK, Australia and Canada. In the JTT, the mean number of authors for each HCP was 4.6 (SD = 3.1); in TJEH, the mean number of authors for each HCP was 4.5 (SD = 2.3). There was no difference between the two journals (P = 0.84) and the characteristics of the HCPs published in the JTT and TJEH were broadly similar. Although HCPs are not a direct method of measuring quality, they are an indicator of the scientific impact of the articles.

Real Time Recognition of Heart Attack in a Smart Phone.

Background: In many countries, including our own, cardiovascular disease is the most common cause of mortality and morbidity. Myocardial infarction (heart attack) is of particular importance in heart disease as well as time and type of reaction to acute myocardial infarction and these can be a determining factor in patients’ outcome. Methods: In order to reduce physician attendance time and keep patients informed about their condition, the smart phone as a common communication device has been used to process data and determine patients’ ECG signals. For ECG signal analysis, we used time domain methods for extracting the ST-segment as the most important feature of the signal to detect myocardial infarction and the thresholding methods and linear classifiers by LabVIEW Mobile Module were used to determine signal risk. Results: The sensitivity and specificity as criteria to evaluate the algorithm were 98% and 93.3% respectively in real time. Conclusions: This algorithm, because of the low computational load and high speed, makes it possible to run in a smart phone. Using Bluetooth to send the data from a portable monitoring system to a smart phone facilitates the real time applications. By using this program on the patient’s mobile, timely detection of infarction so to inform patients is possible and mobile services such as SMS and calling for a physician’s consultation can be done.

Real Time Processing and Transferring ECG Signal by a Mobile Phone

The real-time ECG signal processing system based on mobile phones is very effective in identifying continuous ambulatory patients. It could monitor cardiovascular patients in their daily life and warns them in case of cardiac arrhythmia. An ECG signal of a patient is processed by a mobile phone with this proposed algorithm. An IIR low-pass filter is used to remove the noise and it has the 55 Hz cutoff frequency and order 3. The obtained SNR showed a desirable noise removal and it helps physicians in their diagnosis. In this paper, Hilbert transform was used and the R peaks are important component to differ normal beats from abnormal ones. The results of sensitivity and positive predictivity of algorithm are 96.97% and 95.63% respectively. If an arrhythmia occurred, 4 seconds of this signal is displayed on the mobile phone then it will be sent to a remote medical center by TCP/IP protocol.

The Prediction of the Risk Level of Pulmonary Embolism and Deep Vein Thrombosis through Artificial Neural Network

Background: Venous thromboembolism is a common cause of mortality among hospitalized patients and yet it is preventable through detecting the precipitating factors and a prompt diagnosis by specialists. The present study has been carried out in order to assist specialists in the diagnosis and prediction of the risk level of pulmonary embolism in patients, by means of artificial neural network. Method: A number of 31 risk factors have been used in this study in order to evaluate the conditions of 294 patients hospitalized in 3 educational hospitals affiliated with Kerman University of Medical Sciences. Two types of artificial neural networks, namely Feed-Forward Back Propagation and Elman Back Propagation, were compared in this study. Results: Through an optimized artificial neural network model, an accuracy and risk level index of 93.23 percent was achieved and, subsequently, the results have been compared with those obtained from the perfusion scan of the patients. 86.61 percent of high risk patients diagnosed through perfusion scan diagnostic method were also diagnosed correctly through the method proposed in the present study. Conclusions: The results of this study can be a good resource for physicians, medical assistants, and healthcare staff to diagnose high risk patients more precisely and prevent the mortalities. Additionally, expenses and other unnecessary diagnostic methods such as perfusion scans can be efficiently reduced.

“Evaluation of a Very Low-Cost and Simple Teleradiology Technique”

This paper describes and analyzes a proposed solution of fundamental limitative factor of teleradiology to overcome the teleradiology usages problems in underdeveloped and developing countries. The goal is to achieve a very simple and cost-efficient way to take advantage of teleradiology in anywhere even in remote and rural areas. To meet the goal of this study, the following methodology which is consists of two main procedures was done: (1) Using a digital camera in order to provide a digital image from radiographs. (2) Using an image compression tool in order to compress digital images. The results showed that there is no significant difference between digital images (non-compress and compress images) and radiographic films. Also, there was a logic relationship between the diagnostic quality and diagnostic accuracy. Since the maximum percent of diagnostic accuracy can be seen among “Good” quality images and the minimum to was related “Poor”. The results of our study indicate that a digital camera could be utilized to capture digital images from radiographic films of chest x-ray. To reduce the size of digital images, a lossy compression technique could be applied at compression percent of 50 or less without any significant differences. The compressed images can be sent easily by email to other places for consultation and also they can be stored with a smaller size.

Design and Implementation of a Software for Teaching Health Related Topics to Deaf Students: the First Experience in Iran

Introduction: Deaf are not able to communicate with other community members due to hearing impaired. Providing health care for deaf is more complex because of their communication problems. Multimedia tools can provide multiple tangible concepts (movie, subtitles, and sign language) for the deaf and hard of hearing. In this study, identify the priority health needs of deaf students in primary schools and health education software has been created. Method: Priority health needs and software requirements were identified through interviews with teachers in primary schools in Tehran. After training videos recorded, videos edited and the required software has been created in stages. Results: As a result, health care needs, including: health, dental, ear, nails, and hair care aids, washing hands and face, the corners of the bathroom. Expected Features of the software was including the use of sign language, lip reading, pictures, animations and simple and short subtitles. Discussion: Based on the results of interviews and interest of educators and students to using of educational software for deaf health problems, we can use this software to help Teachers and student’s families to education and promotion the health of deaf students for learn effectively.

Information Retrieval in Telemedicine: a Comparative Study on Bibliographic Databases.

Background and Aims: The first step in each systematic review is selection of the most valid database that can provide the highest number of relevant references. This study was carried out to determine the most suitable database for information retrieval in telemedicine field. Methods: Cinhal, PubMed, Web of Science and Scopus databases were searched for telemedicine matched with Education, cost benefit and patient satisfaction. After analysis of the obtained results, the accuracy coefficient, sensitivity, uniqueness and overlap of databases were calculated. Results: The studied databases differed in the number of retrieved articles. PubMed was identified as the most suitable database for retrieving information on the selected topics with the accuracy and sensitivity ratios of 50.7% and 61.4% respectively. The uniqueness percent of retrieved articles ranged from 38% for Pubmed to 3.0% for Cinhal. The highest overlap rate (18.6%) was found between PubMed and Web of Science. Less than 1% of articles have been indexed in all searched databases. Conclusion: PubMed is suggested as the most suitable database for starting search in telemedicine and after PubMed, Scopus and Web of Science can retrieve about 90% of the relevant articles.