Developing a mobile health application for wound telemonitoring: a pilot study on abdominal surgeries post-discharge care.

BACKGROUND: Many early signs of Surgical Site Infection (SSI) developed during the first thirty days after discharge remain inadequately recognized by patients. Hence, it is important to use interactive technologies for patient support in these times. It helps to diminish unnecessary exposure and in-person outpatient visits. Therefore, this study aims to develop a follow-up system for remote monitoring of SSIs in abdominal surgeries. MATERIAL AND METHODS: This pilot study was carried out in two phases including development and pilot test of the system. First, the main requirements of the system were extracted through a literature review and exploration of the specific needs of abdominal surgery patients in the post-discharge period. Next extracted data was validated according to the agreement level of 30 clinical experts by the Delphi method. After confirming the conceptual model and the primary prototype, the system was designed. In the pilot test phase, the usability of the system was qualitatively and quantitatively evaluated by the participation of patients and clinicians. RESULTS: The general architecture of the system consists of a mobile application as a patient portal and a web-based platform for patient remote monitoring and 30-day follow-up by the healthcare provider. Application has a wide range of functionalities including collecting surgery-related documents, and regular assessment of self-reported symptoms via systematic tele-visits based on predetermined indexes and wound images. The risk-based models embedded in the database included a minimum set with 13 rules derived from the incidence, frequency, and severity of SSI-related symptoms. Accordingly, alerts were generated and displayed via notifications and flagged items on clinicians' dashboards. In the pilot test phase, out of five scheduled tele-visits, 11 (of 13) patients (85%), completed at least two visits. The nurse-centered support was very helpful in the recovery stage. Finally, the result of a pilot usability evaluation showed users' satisfaction and willingness to use the system. CONCLUSION: Implementing a telemonitoring system is potentially feasible and acceptable. Applying this system as part of routine postoperative care management can provide positive effects and outcomes, especially in the era of coronavirus disease when more willingness to telecare service is considered.

Prevalence of self-medication among the elderly: A systematic review and meta-analysis.

BACKGROUND: Self-medication is the use of unprescribed drugs to treat a disease. Elderly self-medication can be more dangerous compared to other age groups because of changes in organ functions that occur due to senescence. This study aimed to estimate the prevalence of self-medication in the elderly, its related factors, and common drugs used in this regard. MATERIALS AND METHODS: Electronic databases such as PubMed, Scopus, and Web of Science were searched between January 2016 and June 2021. The search strategy was built on two core concepts: "self-medication" and "aged". The search was limited to original articles in the English language. A random effect model was used to estimate the pooled prevalence of self-medication. Heterogeneity among studies was assessed using both the I2 statistic and the χ 2 test. Also, a meta-regression model was used to investigate the potential sources of heterogeneity of the studies. RESULTS: Out of 520 non-duplicate studies, 38 were included in the meta-analysis. Self-medication in the elderly ranged from 0.3% to 82%. The pooled proportion of self-medication was 36% (95% CI: 27%-45%). The result of the χ 2 test and the I2 index (P < 0.001, I2= 99.90%) revealed notable heterogeneity among the included studies in the meta-analysis. The meta-regression showed a significant association between the sample size (adjusted ß = -0.01; P = 0.043) and the pooled proportion of self-medication. CONCLUSION: The prevalence of self-medication in the elderly is high. Education through mass media to raise awareness about the dangers of self-medication can help solve this problem.

Remote Monitoring of Colorectal Cancer Survivors Using a Smartphone App and Internet of Things-Based Device: Development and Usability Study.

BACKGROUND: Patients with colorectal cancer who undergo surgery face many postoperative problems. These problems include the risk of relapse, side effects, and long-term complications. OBJECTIVE: This study sought to design and develop a remote monitoring system as a technological solution for the postdischarge care of these patients. METHODS: This research was conducted in 3 main steps: system feature extraction, system design, and evaluation. After feature extraction from a systematic review, the necessary features were defined by 18 clinical experts in Iran. In the next step, the architecture of the system was designed based on the requirements; the software and hardware parts of the system were embedded in the architecture, then the software system components were drawn using the unified modeling language diagrams, and the details of software system implementation were identified. Regarding the hardware design, different accessible hardware modules were evaluated, and suitable ones were selected. Finally, the usability of the system was evaluated by demonstrating it over a Skype virtual meeting session and using Nilsen's usability principles. RESULTS: A total of 21 mandatory features in 5 main categories, including patient information registration, periodic monitoring of health parameters, education, reminders, and assessments, were defined and validated for the system. The software was developed using an ASP.Net core backend, a Microsoft SQL Server database, and an Ionic frontend alongside the Angular framework, to build an Android app. The user roles of the system included 3 roles: physicians, patients, and the system administrator. The hardware was designed to contain an Esp8266 as the Internet of Things module, an MLX90614 infrared temperature sensor, and the Maxim Integrated MAX30101 sensor for sensing the heartbeat. The hardware was designed in the shape of a wristband device using SolidWorks 2020 and printed using a 3D printer. The firmware of the hardware was developed in Arduino with the capability of firmware over the air. In evaluating the software system from the perspective of usability, the system received an average score of 3.8 out of 5 from 4 evaluators. CONCLUSIONS: Sensor-based telemonitoring systems for patients with colorectal cancer after surgery are possible solutions that can make the process automatic for patients and caregivers. The apps for remote colorectal patient monitoring could be designed to be useful; however, more research regarding the developed system's implementation in clinic settings and hospitals is required to understand the probable barriers and limitations.

Prognosis of COVID-19 patients using lab tests: A data mining approach.

Background: The rapid prevalence of coronavirus disease 2019 (COVID-19) has caused a pandemic worldwide and affected the lives of millions. The potential fatality of the disease has led to global public health concerns. Apart from clinical practice, artificial intelligence (AI) has provided a new model for the early diagnosis and prediction of disease based on machine learning (ML) algorithms. In this study, we aimed to make a prediction model for the prognosis of COVID-19 patients using data mining techniques. Methods: In this study, a data set was obtained from the intelligent management system repository of 19 hospitals at Shahid Beheshti University of Medical Sciences in Iran. All patients admitted had shown positive polymerase chain reaction (PCR) test results. They were hospitalized between February 19 and May 12 in 2020, which were investigated in this study. The extracted data set has 8621 data instances. The data include demographic information and results of 16 laboratory tests. In the first stage, preprocessing was performed on the data. Then, among 15 laboratory tests, four of them were selected. The models were created based on seven data mining algorithms, and finally, the performances of the models were compared with each other. Results: Based on our results, the Random Forest (RF) and Gradient Boosted Trees models were known as the most efficient methods, with the highest accuracy percentage of 86.45% and 84.80%, respectively. In contrast, the Decision Tree exhibited the least accuracy (75.43%) among the seven models. Conclusion: Data mining methods have the potential to be used for predicting outcomes of COVID-19 patients with the use of lab tests and demographic features. After validating these methods, they could be implemented in clinical decision support systems for better management and providing care to severe COVID-19 patients.

Risk Factors Associated with Falls in Older Adults with Dementia and Alzheimer's Diseases among Older Adults in the United States.

Objective: This study aimed to examine the risk of fall, fall injury, and fall numbers among older adults with dementia and Alzheimer diseases. Additionally, this study explored the relationship of falls by medication use of neurodegenerative diseases. Methods: The survey data from the years 2020 of Health and Retirement Study Consumption and Activities Mail Survey (HRS CAMS) was used. The HRS CAMS includes information of demographic characteristics, fall information, and medical background including dementia and Alzheimer diseases, and medication record. A regression model was used to test whether neurodegenerative diseases and medications was associated with fall risk factors. Results: The sample (n = 8782) was predominately female (54.7%) and white (60.7%) with a mean age of 70.4 years. When controlled for covariates, the findings show 10 percent higher risk of fall for elderly people with dementia and Alzheimer. People with dementia were 9% more likely to have higher risk of injury by fall and those with dementia and Alzheimer's had more than 7 times of higher chance of a higher number of falls. Using Alzheimer's prescription was associated with lower 90% lower risk of fall than controls. Conclusions: Dementia and Alzheimer diseases are significant risk factor for falls in older adults. This study suggests that older adults with neurodegenerative diseases have higher risk, and needs more regular medical checkups to decrease the risk of fall.

Simulated practice effects on the transfer and retention of gait sequences from the upper to the lower extremity.

This study investigated transfer of training from upper extremity limbs (the index fingers) to the lower extremity limbs (the legs) for performance of three gait sequences of different difficulty. Fifteen subjects participated in the study. Subjects in an iPad training group practiced by sequentially moving their left-and right-hand index fingers across tiles to each of three targets displayed on an iPad for 20 trials. Subjects in a gait training group practiced by sequentially walking across tiles to each of the 3 targets displayed on a screen for 20 trials. A no practice group did not receive practice trials. Immediately following practice of each level of difficulty, a transfer test (20 trials) was given for which subjects walked to the target just practiced. A retention test of 36 trials (12 trials at each difficulty level) was administered 20 min following performance of the last transfer test trial. The retention test showed that reaction times were shorter for the iPad training than gait training and no training groups; anticipatory postural adjustment times were equivalent for the iPad and gait training groups, but shorter than for the no training group; and movement times were shorter for the iPad training group than for the gait training and no training groups. These results suggest that iPad training (upper extremity) followed by performance of gait training (lower extremity) had greater benefits for learning (as measured by the delayed retention test) the gait sequences than practicing the actual gait sequences themselves.

Mobile Health Technology and Healthcare Providers: Systemic Barriers to Adoption.

OBJECTIVES: Despite the growing use of mobile health (mHealth), certain barriers seem to be hindering the use of mHealth applications in healthcare. This article presents a systematic review of the literature on barriers associated with mHealth reported by healthcare professionals. METHODS: This systematic review was carried out to identify studies published from January 2015 to December 2019 by searching four electronic databases (PubMed/MEDLINE, Web of Science, Embase, and Google Scholar). Studies were included if they reported perceived barriers to the adoption of mHealth from healthcare providers' perspectives. Content analysis and categorization of barriers were performed based on a focus group discussion that explored researchers' knowledge and experiences. RESULTS: Among the 273 papers retrieved through the search strategy, 18 works were selected and 18 barriers were identified. The relevant barriers were categorized into three main groups: technical, individual, and healthcare system. Security and privacy concerns from the category of technical barriers, knowledge and limited literacy from the category of individual barriers, and economic and financial factors from the category of healthcare system barriers were chosen as three of the most important challenges related to the adoption of mHealth described in the included publications. CONCLUSIONS: mHealth adoption is a complex and multi-dimensional process that is widely implemented to increase access to healthcare services. However, it is influenced by various factors and barriers. Understanding the barriers to adoption of mHealth applications among providers, and engaging them in the adoption process will be important for the successful deployment of these applications.

Target position and avoidance margin effects on path planning in obstacle avoidance.

This study examined how people choose their path to a target, and the visual information they use for path planning. Participants avoided stepping outside an avoidance margin between a stationary obstacle and the edge of a walkway as they walked to a bookcase and picked up a target from different locations on a shelf. We provided an integrated explanation for path selection by combining avoidance margin, deviation angle, and distance to the obstacle. We found that the combination of right and left avoidance margins accounted for 26%, deviation angle accounted for 39%, and distance to the obstacle accounted for 35% of the variability in decisions about the direction taken to circumvent an obstacle on the way to a target. Gaze analysis findings showed that participants directed their gaze to minimize the uncertainty involved in successful task performance and that gaze sequence changed with obstacle location. In some cases, participants chose to circumvent the obstacle on a side for which the gaze time was shorter, and the path was longer than for the opposite side. Our results of a path selection judgment test showed that the threshold for participants abandoning their preferred side for circumventing the obstacle was a target location of 15 cm to the left of the bookcase shelf center.

Hierarchical goal effects on center of mass velocity and eye fixations during gait.

The purpose of this study was to determine the effect of hierarchical goal structure of a yet-to-be performed task on gait and eye fixation behavior while walking to the location of where the task was to be performed. Subjects performed different goal-directed tasks representing three hierarchical levels of planning. The first level of planning consisted of having the subject walk to a bookcase on which an object (a cup) was located in the middle of a shelf. The second level of planning consisted of walking to the bookcase and picking up the cup which was in the middle, on the right side, or on the left side of the bookcase shelf. The third level of planning consisted of walking to the bookcase, picking up the cup which was located in the middle of the bookcase shelf, and moving it to a higher shelf. Findings showed that hierarchal goals do affect center of mass velocity and eye fixation behavior. Center of mass velocity to the bookcase increased with an increase in the number of goals. Subjects decreased gait velocity as they approached the bookcase and adjusted their last steps to accommodate picking up the cup. The findings also demonstrated the important role of vision in controlling gait velocity in goal-directed tasks. Eye fixation duration was more important than the number of eye fixations in controlling gait velocity. Thus, the amount of information gained through object fixation duration is of greater importance than the number of fixations on the object for effective goal achievement.

Challenges and Practical Considerations in Applying Virtual Reality in Medical Education and Treatment.

Despite the benefits of using virtual reality (VR) in medical education and treatment, some challenges and limitations result in the uselessness or misuse of this technology. Therefore, recognizing potential challenges related to VR might be helpful in the strategic decision-making process to implement and develop this technology in the healthcare field. Accordingly, our review aimed to determine the challenges associated with the application of VR in the field of medical education and treatment. We searched Science Direct, Google Scholar, and PubMed databases for relevant papers using a defined search query. We restricted the search to articles in English or Persian language published by the end of 2018. The main challenges of developing and using VR with educational and therapeutic objectives are categorized as general and specific. General challenges include reduced face-to-face communications, education, cost challenges, users' attitudes, and specific challenges such as designing, safety considerations, VR side effects, evaluation, and validation of VR applications. Challenges related to VR will have different effects, thus identifying each of them helps to determine the solutions for each challenge. Also, it is suggested to develop and update laws, standards, and protocols, which play an important role in increasing the effective application of VR at the national level.

Optimized Patients' Length of Hospital Stay with Interventions Based on Health Information Technology: A Review Study.

BACKGROUND: Information and communications technologies (ICTs) may facilitate shorting length of stay (LOS) of patients through the optimization of processes and delivery services. OBJECTIVES: This study aims to provide technology-based solutions and interventions based on health information technology (HIT) that have optimization potentials of patients' LOS. METHODS: This review study searched papers in PubMed, Scopus as well as Google Scholar without presuming time limits by the end of 2019. English and Persian Papers were included, which addressed an association between the ICT and LOS as well as its positive effect in shortening LOS. RESULTS: Identified technologies were finally classified into eleven groups. Based on the findings, common health technologies such as health information systems, telemedicine especially tele-consultation, electronic discharge planning tools, and visual analytical dashboards in order to expedite the process and help to optimize LOS seem appropriate. CONCLUSIONS: HIT-based interventions have potential that may support better management of processes related to patients' admission, hospitalization, and discharge. However consistently evaluation along with using any new technology is necessary.

Surgical Patients Follow-Up by Smartphone-Based Applications: A Systematic Literature Review.

BACKGROUND: Telemedicine technology with the development of mobile applications (apps) has provided a new approach for the follow-up of patients. OBJECTIVES: This study aims to carry out an overview of the studies related to the use of mobile apps in the follow-up of surgical patients. METHODS: In this study, an electronic search of four databases included PubMed, Scopus, Embase, and web of science was carried out. It included studies in the English language from the beginning of 2009 to June 2019. RESULTS: Twenty-three articles were selected for the final analysis, that all of them were published from 2015 onwards. In most studies, fourteen to thirty-days follow-up period for different outpatient and inpatient surgeries was planned. Apps' components in the studies mostly include indexes for evaluation of recovery quality, pain level, and the surgical site infection. The most important achievement of studies included feasibility, early detection of complications, reducing unscheduled in-person visits, patients' self-efficiency, and satisfaction. CONCLUSIONS: Our review showed that mHealth-based interventions have potential that may support better management of post-discharge systematic follow-up of surgery patients.

A study of factors related to patients' length of stay using data mining techniques in a general hospital in southern Iran.

PURPOSE: The length of stay (LOS) in hospitals is a widely used indicator for goals such as health care management, quality control, utilizing hospital services and resources, and determining the degree of efficiency. Various methods have been used to identify the factors influencing the LOS. This study adopts a comparative approach of data mining techniques for investigating effective factors and predict the length of stay in Shahid-Mohammadi Hospital, Bandar Abbas, Iran. METHODS: Using a dataset consists of 526 patient records of the Shahid-Mohammadi Hospital from March 2016 to March 2017, factors affecting the LOS were ranked using information gain and correlation indices. In addition, classification models for LOS prediction were created based on nine data mining classifiers applied with and without feature selection technique. Finally, the models were compared. RESULTS: The most important factors affecting LOS are the number of para-clinical services, counseling frequency, clinical ward, the specialty and the degree of the doctor, and the cause of hospitalization. In addition, regarding to the classifiers created based on the dataset, the best accuracy (83.91%) and sensitivity (80.36%) belongs to the Logistic Regression and Naïve Bayes respectively. In addition, the best AUC (0.896) belongs to the Random Forest and Generalized Linear classifiers. CONCLUSION: The results showed that most of the proposed models are suitable for classification of the length of stay, although the Logistic Regression might have a slightly better performance than others in term of accuracy, and this model can be used to determine the patients' Length of Stay. In general, continuous monitoring of the factors influencing each of the performance indicators based on proper and accurate models in hospitals is important for helping management decisions.

Factors affecting length of stay in Children Hospital in Southern Iran.

BACKGROUND: One of the effective indicators for determining the efficiency and optimal use of hospital resources is the length of stay (LOS). This study aimed to determine the patients' length of stay and the factors affecting the LOS in the Children's hospital. METHOD: A cross-sectional study was performed on Children Hospital medical record database including 350 records (April 2015 to Dec 2015). Records were selected by stratified random sampling with proportional allocation. Then the predetermined demographic and hospital variables were extracted through the study of patients' medical records. All statistical analysis were performed using SPSS software. RESULTS: The overall median of the LOS in the studied hospital was 3 days (IQR =3). The results showed that in this hospital the LOS has a significant relationship with the variables of time of admission, the place of residence, type of admission, and the degree of attending physician. Also, with the increasing number of visits, ultrasonography, counseling and laboratory test, LOS was increased. CONCLUSION: Improving processes related to diagnostic procedures, providing adequate staffing for specialized services in all hours of the day, preventing unnecessary and non-emergency admissions in the evening and night, will be effective in optimizing patient LOS.

Study of challenges to utilise mobile-based health care monitoring systems: A descriptive literature review.

Mobile health encompasses remote and wireless applications to provide health services. Despite the advantages of applying mobile-based monitoring systems, there are challenges and limitations; understanding the challenges may assist in identifying available solutions and optimising decision-making to apply mHealth technologies more practically. This study aimed to investigate the main challenges related to mHealth-based systems for health monitoring purposes. This review was carried out through investigation of English evidence from four databases, including Scopus, PubMed, Embase, and Web of Science, using a defined search strategy from 2013 to 2017. Two independent researchers reviewed the results based on PRISMA guidelines, and data was categorised using a bottom-up approach to reach a framework for the most general challenges. Among the 105 papers obtained, eight works were selected. The revealed challenges were categorised into six main branches across a tree (with 55 nodes, four levels) including user-related, infrastructure, process, management, resource and training challenges. Identifying the resolvable and preventable challenges, such as those related to training, design might play a crucial role in preventing loss of resources and in growing the success rate of a project, particularly if considered in national level projects.