A comparative evaluation of mobile medical APPS (MMAS) for reading and interpreting malaria rapid diagnostic tests

Background The World Health Organization recommends confirmatory diagnosis by microscopy or malaria rapid diagnostic test (RDT) in patients with suspected malaria. In recent years, mobile medical applications (MMAs), which can interpret RDT test results have entered the market. To evaluate the performance of commercially available MMAs, an evaluation was conducted by comparing RDT results read by MMAs to RDT results read by the human eye. Methods Five different MMAs were evaluated on six different RDT products using cultured Plasmodium falciparum blood samples at five dilutions ranging from 20 to 1000 parasites (p)/microlitre (µl) and malaria negative blood samples. The RDTs were performed in a controlled, laboratory setting by a trained operator who visually read the RDT results. A second trained operator then used the MMAs to read the RDT results. Sensitivity (Sn) and specificity (Sp) for the RDTs were calculated in a Bayesian framework using mixed models. Results The RDT Sn of the P. falciparum (Pf) test line, when read by the trained human eye was significantly higher compared to when read by MMAs (74% vs. average 47%) at samples of 20 p/µl. In higher density samples, the Sn was comparable to the human eye (97%) for three MMAs. The RDT Sn of test lines that detect all Plasmodium species (Pan line), when read by the trained human eye was significantly higher compared to when read by MMAs (79% vs. average 56%) across all densities. The RDT Sp, when read by the human eye or MMAs was 99% for both the Pf and Pan test lines across all densities. Conclusions The study results show that in a laboratory setting, most MMAs produced similar results interpreting the Pf test line of RDTs at parasite densities typically found in patients that experience malaria symptoms (> 100 p/µl) compared to the human eye. At low parasite densities for the Pf line and across all parasite densities for the Pan line, MMAs were less accurate than the human eye. Future efforts should focus on improving the band/line detection at lower band intensities and evaluating additional MMA functionalities like the ability to identify and classify RDT errors or anomalies.

Modern Medical Innovation on the Preferred Information about the Medicine using AI Technique

The number of mobile Medicare applications has grown exponentially over the past few years, and it is expected to continue to grow soon. The use of health apps promises to be a good way to improve patient care and make work easier for professional. However, some cases of malfunction or misdiagnosis and treatment recommendations have been reported. Regulation is essential to protect users and support product development. So, to suppress the malfunctions we present a pharmacopeia Medicare app in which the customer can see the original profile and the specification of any stimulant with its useful information. This inculcates a clean process which procures a less chance of misapplication of the drugs. These mobile medical app companies have improved access to clinical references and point of care tools. However, it is difficult to identify mobile medical apps that are suitable for the practice of pharmacy. This app is entirely based on our experience in accrediting websites with health-related content and journal.

Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study

Background The increasing health service demand driven by the aging of the global population calls for the development of modes of health service delivery that are less human resource–intensive. Electronic health (eHealth) and medical apps are expected to play an important role in this development. Although evidence shows mobile medical apps might be effective in improving the care, self-management, self-efficacy, health-related behavior, and medication adherence of older adults, little is known about older adults’ intention to use these technologies when needed, or the factors influencing this intention. Objective The objective of this study was to investigate the relationship of technology acceptance factors and intention to use mobile medical apps among community-dwelling older adults. Methods Data was collected using questionnaires. The factors selected from the literature have been validated using Cronbach α and tested for significance using logistic regressions. Results Almost half (49.7%) of the included older adults reported no intention to use medical apps. Adjusted logistic regression analysis per factor showed that the factors Attitude toward use (odds ratio [OR] 8.50), Perceived usefulness (OR 5.25), Perceived ease of use (OR 4.22), Service availability (OR 3.46), Sense of control (OR 3.40), Self-perceived effectiveness (OR 2.69), Facilities (OR 2.45), Personal innovativeness (OR 2.08), Social relationships (OR 1.79), Subjective norm (OR 1.48), and Feelings of anxiety (OR 0.62) significantly influenced the intention to use mobile medical apps among older adults, whereas the factor Finance (OR 0.98) did not. When considered together, a controlled multivariate logistic regression yielded high explained variances of 0.542 (Cox-Snell R2) and 0.728 (Nagelkerke R2). Conclusions The high odds ratios and explained variance indicate that the factors associated with the intention to use medical apps are largely understood and the most important factors have been identified. To advance the evidence base, experimental controlled research should investigate the causality between the factors, intention to use, and actual use. For this purpose, our evidence suggests that policies designed to improve Attitude toward use appear most effective, followed by policies addressing Perceived usefulness, Perceived ease of use, Service availability, and Sense of control.

What are the implications of standards to ensure safe use of dermatological health apps? (Preprint)

BACKGROUND Dermatological health applications can address a range of pathologies from melanoma to eczema and have the potential to significantly impact the health of the user. This paper details a systematic review of standards addressing dermatological health apps and their implication on the safe use of such apps. OBJECTIVE To survey the literature to ascertain the state of evidence to address this review’s primary research question: “What are the implications of standards to ensure safe use of dermatological health apps?” METHODS Six databases were systematically searched for records relevant to the questions using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The Reporting Items for Practice Guidelines in Healthcare (RIGHT) checklist was used to analyse records when applicable, and when not a standardised checklist was used. Database searches identified 2193 records, of which 67 records were ultimately included for analysis. RESULTS A total of 67 records were identified, and these could be organised into 6 themes. These 6 themes included studies investigating the accuracy of apps, general standards, articles, reviews of current dermatological apps, recommendations and reviews of mobile medical apps and standards. CONCLUSIONS This systematic review showed that there is a large variance in the quality of dermatological apps available to the public and the standards and guidelines currently in place are insufficient in eliminating all inaccuracies. Standards and guidelines surrounding the algorithms often used in dermatological apps as well as guidance on effective use of existing apps could potentially allow for more effective dermatological health apps. INTERNATIONAL REGISTERED REPORT RR2-10.1136/bmjopen-2018-022969

Uncertain Multiplicative Language Decision Method Based on Group Compromise Framework for Evaluation of Mobile Medical APPs in China

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel multiple attribute group decision making algorithm based on group compromise framework, which need not determine the weight of decision-maker. The algorithm utilized an uncertain multiplicative linguistic variable to measure the individual original preference to express the real evaluation information as much as possible. The attribute weight was calculated by maximizing the differences among alternatives. It determined the individual alternatives ranking according to the net flow of each alternative. By solved the 0–1 optimal model with the objective of minimizing the differences between individual ranking, the ultimate group compromise ranking was obtained. Then we took 10 well-known M-medical APPs in Chinese as an example, we summarized service categories provided for users and constructed the assessment system consisting of 8 indexes considering the service quality users are concerned with. Finally, the effectiveness and superiority of the proposed method and the consistency of ranking results were verified, through comparing the group ranking results of 3 similar algorithms. The experiments show that group compromise ranking is sensitive to attribute weight.

Examining mobile medical app usage intentions (Preprint)

BACKGROUND The successful operation of medical mobile applications primarily depends on the extent to which users are fully motivated to adopt it. OBJECTIVE Therefore, the primary purpose of this study is to investigate the factors influencing mobile medical application usage intentions. METHODS This study applied the Unified Theory of Acceptance and Use of Technology (UTAUT2) to build a comprehensive model that explains the usage intentions of mobile medical apps. RESULTS Research findings confirm the validity of the UTAUT2 in explaining the intention of using mobile medical apps in the context of mobile medical services. Also, the results focus on the enhancement in the role of the other, rather contextual attributes of the IT/IS environment (i.e., personal involvement and personal innovativeness). CONCLUSIONS By conducting surveys, mobile medical app designers can know that personal involvement and personal innovativeness leads to influences on the effectiveness of corporate marketing efforts about using mobile medical apps.

Intention to use Medical Apps Among Older Adults in the Netherlands: Cross-Sectional Study (Preprint)

BACKGROUND The increasing health service demand driven by the aging of the global population calls for the development of modes of health service delivery that are less human resource–intensive. Electronic health (eHealth) and medical apps are expected to play an important role in this development. Although evidence shows mobile medical apps might be effective in improving the care, self-management, self-efficacy, health-related behavior, and medication adherence of older adults, little is known about older adults’ intention to use these technologies when needed, or the factors influencing this intention. OBJECTIVE The objective of this study was to investigate the relationship of technology acceptance factors and intention to use mobile medical apps among community-dwelling older adults. METHODS Data was collected using questionnaires. The factors selected from the literature have been validated using Cronbach α and tested for significance using logistic regressions. RESULTS Almost half (49.7%) of the included older adults reported no intention to use medical apps. Adjusted logistic regression analysis per factor showed that the factors Attitude toward use (odds ratio [OR] 8.50), Perceived usefulness (OR 5.25), Perceived ease of use (OR 4.22), Service availability (OR 3.46), Sense of control (OR 3.40), Self-perceived effectiveness (OR 2.69), Facilities (OR 2.45), Personal innovativeness (OR 2.08), Social relationships (OR 1.79), Subjective norm (OR 1.48), and Feelings of anxiety (OR 0.62) significantly influenced the intention to use mobile medical apps among older adults, whereas the factor Finance (OR 0.98) did not. When considered together, a controlled multivariate logistic regression yielded high explained variances of 0.542 (Cox-Snell R²) and 0.728 (Nagelkerke R²). CONCLUSIONS The high odds ratios and explained variance indicate that the factors associated with the intention to use medical apps are largely understood and the most important factors have been identified. To advance the evidence base, experimental controlled research should investigate the causality between the factors, intention to use, and actual use. For this purpose, our evidence suggests that policies designed to improve Attitude toward use appear most effective, followed by policies addressing Perceived usefulness, Perceived ease of use, Service availability, and Sense of control.