Assessing Health Care Professionals' Mindset in Adopting Telemedicine Post COVID-19: Pilot Questionnaire Study.

BACKGROUND: Amidst the COVID-19 pandemic, the traditional health care model has evolved toward a more patient-centric model. In relation to this trend, digital health services have seen an acceleration, which may have significant implications for the health care model. Due to the impact of COVID-19 on health care facilities, it is important to explore health professionals' willingness to adopt a patient-centric digital health delivery model for medicine and health care. OBJECTIVE: The aim of this study was to pilot a survey that assesses the impact and implementation of telehealth in view of health care providers prior to and post COVID-19. METHODS: A total of 26 volunteer health care professionals participated in the pilot study, of which 19/26 (73%) completed the general demographics portion. Among these respondents, 9/26 (35%) completed the entirety of the survey. The questionnaire included questions relating to general demographics, accessibility and benefits, usability, and engagements with telemedicine. Participants were randomly assigned to 1 of the 4 questionnaire designs (A-D) based on their expertise in telehealth. Of the 9 total participants who completed their randomly assigned questionnaire, 1 (11%) was randomly assigned to A, 3 (33%) were randomly assigned to B, 2 (22%) were randomly assigned to C, and 3 (33%) were randomly assigned to D. RESULTS: Responses and data from the study questionnaire were collected from Qualtrics. Microsoft Excel was used for data organization. Due to limited responses and data, no advanced statistical software was implemented. From the 9 participants who completed the entirety of the survey, responses from those with telehealth experience (n=4) showed that telehealth was preferred for follow-ups, lab results, and consultations, and that with telehealth, there was greater flexibility with appointment times and a decrease in the number of patients seen. Among the 4 health care providers with telehealth experience, all of them believed it improved accessibility and reduced physical barriers; health care professionals believed telehealth reduced translational barriers with patients. Among health care professionals without telehealth experience (n=5), 60% (3/5) reported a decrease in appointments for in-office visits post COVID-19 and strongly agreed or agreed that telehealth could influence the quality of care for patients. All 5 participants also reported no general concerns about telehealth prior to the pandemic and agreed that it would provide accessibility for patients. CONCLUSIONS: Preliminary findings of our pilot study showed initial support of a dynamical shift within the health care model due to the rise in the use of telehealth services between health care providers and patients but no statistically significant results. Further research and investigation with a larger sample size is warranted to better understand the mindset of health care professionals in adopting telemedicine post COVID-19.

Framework to enable pharmacist access to health care data using Blockchain technology and artificial intelligence.

BACKGROUND: Decentralization and authentication are embedded in blockchain technology, which utilizes artificial intelligence (AI) to ensure seamless sharing of data among different health care providers while safeguarding data privacy. Although community pharmacists are highly accessible to patients and possess robust clinical knowledge, they are limited in the clinical services they can provide owing to their lack of access to patient health records. We proposed a blockchain- and AI-based conceptual framework by performing a scoping review of successful blockchain integration in health systems. OBJECTIVE: To formulate a conceptual framework based on a scoping review to improve access to health care data in the community pharmacy setting through the adoption of blockchain technology and AI. METHODS: We performed a scoping review of literature based on Preferred Reporting Items for Systematic reviews and Meta-Analyses review criteria to identify the specific areas where blockchain can be implemented in health systems. We utilized the Pharmacists' Patient Care Process (PPCP) to identify 2 critical areas for blockchain integration that can support community pharmacists to access patient electronic health records and implement patient-specific information in clinical decision-making. RESULTS: We included 7 articles out of 70 articles in our final review. The 2 areas in the PPCP identified for the use of blockchain on the basis of the literature review were "Assess" and "Implement." Our proposed model involves pharmacists using AI and blockchain technology to comprehensively assess any concerns with the prescribed medication through access to laboratory results for patients and then implement a plan based on a comprehensive assessment of the patient's health record. CONCLUSIONS: Utilizing blockchain to securely share health data with community pharmacies has the potential to improve patient outcomes, optimize medication safety, and amplify pharmacists' roles in patient care. Future research should focus on implementing the model in the real-world settings.

PGxKnow: a pharmacogenomics educational HoloLens application of augmented reality and artificial intelligence.

Aim: To develop and assess an augmented reality tool for pharmacogenomics (PGx) education based on artificial intelligence. Materials & methods: A HoloLens application was developed using feedback from three clinical PGx-trained pharmacists. 15 Participants independently reviewed the application and assessed usability using the system usability scale (SUS). Results & conclusion: Eighteen different frames were developed. Each video module was 2-3 min for the education. The application included textual information and 3D structures of PGx concepts. The mean SUS score for 15 participants (11 pharmacy students and four pharmacists) was 83, with a standard deviation of 6.6. Results suggest that PGxKnow has the potential to bridge the gap in PGx education, further widespread utilization of PGx and boost its impact on precision medicine.

Artificial Intelligence-Powered Smartphone App to Facilitate Medication Adherence: Protocol for a Human Factors Design Study.

BACKGROUND: Medication Guides consisting of crucial interactions and side effects are extensive and complex. Due to the exhaustive information, patients do not retain the necessary medication information, which can result in hospitalizations and medication nonadherence. A gap exists in understanding patients' cognition of managing complex medication information. However, advancements in technology and artificial intelligence (AI) allow us to understand patient cognitive processes to design an app to better provide important medication information to patients. OBJECTIVE: Our objective is to improve the design of an innovative AI- and human factor-based interface that supports patients' medication information comprehension that could potentially improve medication adherence. METHODS: This study has three aims. Aim 1 has three phases: (1) an observational study to understand patient perception of fear and biases regarding medication information, (2) an eye-tracking study to understand the attention locus for medication information, and (3) a psychological refractory period (PRP) paradigm study to understand functionalities. Observational data will be collected, such as audio and video recordings, gaze mapping, and time from PRP. A total of 50 patients, aged 18-65 years, who started at least one new medication, for which we developed visualization information, and who have a cognitive status of 34 during cognitive screening using the TICS-M test and health literacy level will be included in this aim of the study. In Aim 2, we will iteratively design and evaluate an AI-powered medication information visualization interface as a smartphone app with the knowledge gained from each component of Aim 1. The interface will be assessed through two usability surveys. A total of 300 patients, aged 18-65 years, with diabetes, cardiovascular diseases, or mental health disorders, will be recruited for the surveys. Data from the surveys will be analyzed through exploratory factor analysis. In Aim 3, in order to test the prototype, there will be a two-arm study design. This aim will include 900 patients, aged 18-65 years, with internet access, without any cognitive impairment, and with at least two medications. Patients will be sequentially randomized. Three surveys will be used to assess the primary outcome of medication information comprehension and the secondary outcome of medication adherence at 12 weeks. RESULTS: Preliminary data collection will be conducted in 2021, and results are expected to be published in 2022. CONCLUSIONS: This study will lead the future of AI-based, innovative, digital interface design and aid in improving medication comprehension, which may improve medication adherence. The results from this study will also open up future research opportunities in understanding how patients manage complex medication information and will inform the format and design for innovative, AI-powered digital interfaces for Medication Guides. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/21659.

The inclusion of health data standards in the implementation of pharmacogenomics systems: a scoping review.

Background: Despite potential benefits, the practice of incorporating pharmacogenomics (PGx) results in clinical decisions has yet to diffuse widely. In this study, we conducted a review of recent discussions on data standards and interoperability with a focus on sharing PGx test results among health systems. Materials & methods: We conducted a literature search for PGx clinical decision support systems between 1 January 2012 and 31 January 2020. Thirty-two out of 727 articles were included for the final review. Results: Nine of the 32 articles mentioned data standards and only four of the 32 articles provided solutions for the lack of interoperability. Discussions: Although PGx interoperability is essential for widespread implementation, a lack of focus on standardized data creates a formidable challenge for health information exchange. Conclusion: Standardization of PGx data is essential to improve health information exchange and the sharing of PGx results between disparate systems. However, PGx data standards and interoperability are often not addressed in the system-level implementation.

Improving Medication Information Presentation Through Interactive Visualization in Mobile Apps: Human Factors Design.

BACKGROUND: Despite the detailed patient package inserts (PPIs) with prescription drugs that communicate crucial information about safety, there is a critical gap between patient understanding and the knowledge presented. As a result, patients may suffer from adverse events. We propose using human factors design methodologies such as hierarchical task analysis (HTA) and interactive visualization to bridge this gap. We hypothesize that an innovative mobile app employing human factors design with an interactive visualization can deliver PPI information aligned with patients' information processing heuristics. Such an app may help patients gain an improved overall knowledge of medications. OBJECTIVE: The objective of this study was to explore the feasibility of designing an interactive visualization-based mobile app using an HTA approach through a mobile prototype. METHODS: Two pharmacists constructed the HTA for the drug risperidone. Later, the specific requirements of the design were translated using infographics. We transferred the wireframes of the prototype into an interactive user interface. Finally, a usability evaluation of the mobile health app was conducted. RESULTS: A mobile app prototype using HTA and infographics was successfully created. We reiterated the design based on the specific recommendations from the usability evaluations. CONCLUSIONS: Using HTA methodology, we successfully created a mobile prototype for delivering PPI on the drug risperidone to patients. The hierarchical goals and subgoals were translated into a mobile prototype.

Do executives' backgrounds matter to IPO investors? Evidence from the life science industry.

In this study, we focus on the impact of senior executives' industry backgrounds on the amount of capital raised in the stock market. The primary contribution of the study entails applying the upper echelon theory to the initial public offering (IPO) phenomenon. Specifically, we hypothesize that the industry backgrounds of corporate executives affect the amount of capital that the firm raised in the primary stock market. We argue that the firm's future investment strategies are unobserved by the investors ex-ante and investors expect firms' investment strategies to be based on the executives' industry backgrounds. As a result, the executives' industry backgrounds influence the investors' expectations about what investment strategies the firm is likely to deploy. Furthermore, the above logic also suggests that executives of different industry backgrounds should prefer different investment strategies corresponding with demand for different amount of capital. As a result, we expect the industry backgrounds to covary with the capital raised from both the supply and demand perspectives. To test the hypotheses, we ran a reduced econometric model wherein the executives' background predicts the amount of capital raised. Regression analyses suggest that the capital raised is negatively associated with the number of senior executives with prior career experience in the healthcare and genomic sectors but positively associated with the number of senior executives with prior career experience in regulatory affairs. The results provide tentative support for the notion that investors infer corporate strategies from senior executives' industry backgrounds.

Comparable stocks, boundedly rational stock markets and IPO entry rates.

In this study, we examine how initial public offerings (IPO) entry rates are affected when stock markets are boundedly rational and IPO firms infer information from their counterparts in the market. We hypothesize a curvilinear relationship between the number of comparable stocks and initial public offerings (IPO) entry rates into the NASDAQ Stock Exchange. Furthermore, we argue that trading volume and changes in stock returns partially mediates the relationship between the number of comparable stocks and IPO entry rates. The statistical evidence provides strong support for the hypotheses.