How Consumers and Physicians View New Medical Technology: Comparative Survey

Medical practitioner perspectives on AI in emergency triage

Introduction

A proposed Diagnostic AI System for Robot-Assisted Triage ("DAISY") is under development to support Emergency Department ("ED") triage following increasing reports of overcrowding and shortage of staff in ED care experienced within National Health Service, England ("NHS") but also globally. DAISY aims to reduce ED patient wait times and medical practitioner overload. The objective of this study was to explore NHS health practitioners' perspectives and attitudes towards the future use of AI-supported technologies in ED triage.

Methods

Between July and August 2022 a qualitative-exploratory research study was conducted to collect and capture the perceptions and attitudes of nine NHS healthcare practitioners to better understand the challenges and benefits of a DAISY deployment. The study was based on a thematic analysis of semi-structured interviews. The study involved qualitative data analysis of the interviewees' responses. Audio-recordings were transcribed verbatim, and notes included into data documents. The transcripts were coded line-by-line, and data were organised into themes and sub-themes. Both inductive and deductive approaches to thematic analysis were used to analyse such data.

Results

Based on a qualitative analysis of coded interviews with the practitioners, responses were categorised into broad main thematic-types, namely: trust; current practice; social, legal, ethical, and cultural concerns; and empathetic practice. Sub-themes were identified for each main theme. Further quantitative analyses explored the vocabulary and sentiments of the participants when talking generally about NHS ED practices compared to discussing DAISY. Limitations include a small sample size and the requirement that research participants imagine a prototype AI-supported system still under development. The expectation is that such a system would work alongside the practitioner. Findings can be generalisable to other healthcare AI-supported systems and to other domains.

Discussion

This study highlights the benefits and challenges for an AI-supported triage healthcare solution. The study shows that most NHS ED practitioners interviewed were positive about such adoption. Benefits cited were a reduction in patient wait times in the ED, assistance in the streamlining of the triage process, support in calling for appropriate diagnostics and for further patient examination, and identification of those very unwell and requiring more immediate and urgent attention. Words used to describe the system were that DAISY is a "good idea", "help", helpful, "easier", "value", and "accurate". Our study demonstrates that trust in the system is a significant driver of use and a potential barrier to adoption. Participants emphasised social, legal, ethical, and cultural considerations and barriers to DAISY adoption and the importance of empathy and non-verbal cues in patient interactions. Findings demonstrate how DAISY might support and augment human medical performance in ED care, and provide an understanding of attitudinal barriers and considerations for the development and implementation of future triage AI-supported systems.

Establishment and validation of an AI-aid method in the diagnosis of myocardial perfusion imaging

BACKGROUND

This study aimed to develop and validate an AI (artificial intelligence)-aid method in myocardial perfusion imaging (MPI) to differentiate ischemia in coronary artery disease.

METHODS

We retrospectively selected 599 patients who had received gated-MPI protocol. Images were acquired using hybrid SPECT-CT systems. A training set was used to train and develop the neural network and a validation set was used to test the predictive ability of the neural network. We used a learning technique named "YOLO" to carry out the training process. We compared the predictive accuracy of AI with that of physician interpreters (beginner, inexperienced, and experienced interpreters).

RESULTS

Training performance showed that the accuracy ranged from 66.20% to 94.64%, the recall rate ranged from 76.96% to 98.76%, and the average precision ranged from 80.17% to 98.15%. In the ROC analysis of the validation set, the sensitivity range was 88.9 ~ 93.8%, the specificity range was 93.0 ~ 97.6%, and the AUC range was 94.1 ~ 96.1%. In the comparison between AI and different interpreters, AI outperformed the other interpreters (most P-value < 0.05).

CONCLUSION

The AI system of our study showed excellent predictive accuracy in the diagnosis of MPI protocols, and therefore might be potentially helpful to aid radiologists in clinical practice and develop more sophisticated models.

Patient perspective on the use of carbon fibre plates for extremity fracture fixation

INTRODUCTION

Carbon fibre-reinforced polyetheretherketone (CFR-PEEK) plates represent an exciting development within trauma and orthopaedic surgery, offering advantages including radiolucency, material properties similar to bone, and lack of localised tissue reaction. As more call for trials examining their use, there is no data available as to the acceptability of these implants to patients. This study aimed to therefore examine the acceptability of CFR-PEEK plates to patients undergoing fracture surgery.

METHODS

This was a prospective cross-sectional survey of patients undergoing surgery for a fracture of the ankle, distal femur, distal radius, or proximal humerus. Once a decision had been made to pursue operative fixation with a plate, patients were provided with descriptions of both CFR-PEEK and stainless steel and titanium metal implants alongside the current clinical evidence. All patients undertook a questionnaire examining their views as to the advantages and disadvantages of CFR-PEEK plates, and whether they would be happy to participate in a trial comparing both.

RESULTS

Ninety-nine patients were happy to participate (64 females, mean age 50). Eighty-seven patients reported that they would want a CFR-PEEK implant for their fracture, and 76 reported that they would be willing to participate in an RCT comparing their use. Commonly reported advantages included radiolucency, low weight and biocompatibility. Disadvantages reported included cost and concerns regarding durability.

CONCLUSIONS

This study demonstrates that CFR-PEEK implants would be acceptable to patients undergoing fracture surgery, with high numbers of patients stating that they would be willing to participate in a randomised study examining their use.

Smart Wearables for the Detection of Occupational Physical Fatigue: A Literature Review

Today's world is changing dramatically due to the influence of various factors. Whether due to the rapid development of technological tools, advances in telecommunication methods, global economic and social events, or other reasons, almost everything is changing. As a result, the concepts of a "job" or work have changed as well, with new work shifts being introduced and the office no longer being the only place where work is done. In addition, our non-stop active society has increased the stress and pressure at work, causing fatigue to spread worldwide and becoming a global problem. Moreover, it is medically proven that persistent fatigue is a cause of serious diseases and health problems. Therefore, monitoring and detecting fatigue in the workplace is essential to improve worker safety in the long term. In this paper, we provide an overview of the use of smart wearable devices to monitor and detect occupational physical fatigue. In addition, we present and discuss the challenges that hinder this field and highlight what can be done to advance the use of smart wearables in workplace fatigue detection.

Medical Technologies Past and Present: How History Helps to Understand the Digital Era

This article explores the relationship between medicine's history and its digital present through the lens of the physician-patient relationship. Today the rhetoric surrounding the introduction of new technologies into medicine tends to emphasize that technologies are disturbing relationships, and that the doctor-patient bond reflects a more 'human' era of medicine that should be preserved. Using historical studies of pre-modern and modern Western European medicine, this article shows that patient-physician relationships have always been shaped by material cultures. We discuss three activities - recording, examining, and treating - in the light of their historical antecedents, and suggest that the notion of 'human medicine' is ever-changing: it consists of social attributions of skills to physicians that played out very differently over the course of history.

Telehealth, Social Media, Patient Empowerment, and Physician Burnout: Seeking Middle Ground

The digital revolution is an ongoing process that has nevertheless profoundly affected century-old medical practice. Digitalization has many facets, ranging from telehealth to social media and even new instant communication devices, each of which affect both patients' and physicians' realities. Although the benefits of developments such as telehealth and novel applications of social media to medicine are more easily perceived by all stakeholders, they still have their own hurdles and risks, such as coldness and impersonal treatment in telehealth, and misinformation on social media. The widespread digitalization of health records has greatly facilitated patient access to health information, becoming a major patient empowerment tool; however, some forms of unrestricted access, such as to test results-in particular, prior to consultations-have unclear benefits to patients with cancer and have also become a hurdle for care teams. In addition, the advent of instant messaging, which is revolutionizing personal communication in many cultures, is gradually affecting patient-physician communication and, combined with unrestricted patient access to test results, is creating new challenges for physicians. How these transformations are affecting patients themselves and physicians' well-being and mental health are matters addressed in this text. Last, to address potential biases in an article written by two oncologists, and in line with this year's ASCO presidential theme of including a diversity of voices, we decided to give voice to patients with cancer by collecting the opinions of high-profile patient advocates about the controversial topics addressed in this text.

The Emergence of Artificial Intelligence in Cardiology: Current and Future Applications

Artificial intelligence technology is emerging as a promising entity in cardiovascular medicine, potentially improving diagnosis and patient care. In this article, we review the literature on artificial intelligence and its utility in cardiology. We provide a detailed description of concepts of artificial intelligence tools like machine learning, deep learning, and cognitive computing. This review discusses the current evidence, application, prospects, and limitations of artificial intelligence in cardiology.

Exploring the COVID-19 Pandemic as a Catalyst for PHR App User Behavior Change in Taiwan: A Development and Usability Study

Background

During the COVID-19 pandemic, personal health records (PHRs) have enabled patients to monitor and manage their medical data without visiting hospitals and, consequently, minimize their infection risk. Taiwan’s National Health Insurance Administration (NHIA) launched the My Health Bank (MHB) service, a national PHR system through which insured individuals to access their cross-hospital medical data. Furthermore, in 2019, the NHIA released the MHB software development kit (SDK), which enables development of mobile apps with which insured individuals can retrieve their MHB data. However, the NHIA MHB service has its limitations, and the participation rate among insured individuals is low.

Objective

We aimed to integrate the MHB SDK with our developed blockchain-enabled PHR mobile app, which enables patients to access, store, and manage their cross-hospital PHR data. We also collected and analyzed the app’s log data to examine patients’ MHB use during the COVID-19 pandemic.

Methods

We integrated our existing blockchain-enabled mobile app with the MHB SDK to enable NHIA MHB data retrieval. The app utilizes blockchain technology to encrypt the downloaded NHIA MHB data. Existing and new indexes can be synchronized between the app and blockchain nodes, and high security can be achieved for PHR management. Finally, we analyzed the app’s access logs to compare patients’ activities during high and low COVID-19 infection periods.

Results

We successfully integrated the MHB SDK into our mobile app, thereby enabling patients to retrieve their cross-hospital medical data, particularly those related to COVID-19 rapid and polymerase chain reaction testing and vaccination information and progress. We retrospectively collected the app’s log data for the period of July 2019 to June 2021. From January 2020, the preliminary results revealed a steady increase in the number of people who applied to create a blockchain account for access to their medical data and the number of app subscribers among patients who visited the outpatient department (OPD) and emergency department (ED). Notably, for patients who visited the OPD and ED, the peak proportions with respect to the use of the app for OPD and ED notes and laboratory test results also increased year by year. The highest proportions were 52.40% for ED notes in June 2021, 88.10% for ED laboratory test reports in May 2021, 34.61% for OPD notes in June 2021, and 41.87% for OPD laboratory test reports in June 2021. These peaks coincided with Taiwan’s local COVID-19 outbreak lasting from May to June 2021.

Conclusions

This study developed a blockchain-enabled mobile app, which can periodically retrieve and integrate PHRs from the NHIA MHB's cross-hospital data and the investigated hospital's self-pay medical data. Analysis of users’ access logs revealed that the COVID-19 pandemic substantially increased individuals’ use of PHRs and their health awareness with respect to COVID-19 prevention.

Machine Learning in Clinical Psychology and Psychotherapy Education: A Mixed Methods Pilot Survey of Postgraduate Students at a Swiss University

Background: There is increasing use of psychotherapy apps in mental health care. Objective: This mixed methods pilot study aimed to explore postgraduate clinical psychology students' familiarity and formal exposure to topics related to artificial intelligence and machine learning (AI/ML) during their studies. Methods: In April-June 2020, we conducted a mixed-methods online survey using a convenience sample of 120 clinical psychology students enrolled in a two-year Masters' program at a Swiss University. Results: In total 37 students responded (response rate: 37/120, 31%). Among respondents, 73% (n = 27) intended to enter a mental health profession, and 97% reported that they had heard of the term "machine learning." Students estimated 0.52% of their program would be spent on AI/ML education. Around half (46%) reported that they intended to learn about AI/ML as it pertained to mental health care. On 5-point Likert scale, students "moderately agreed" (median = 4) that AI/M should be part of clinical psychology/psychotherapy education. Qualitative analysis of students' comments resulted in four major themes on the impact of AI/ML on mental healthcare: (1) Changes in the quality and understanding of psychotherapy care; (2) Impact on patient-therapist interactions; (3) Impact on the psychotherapy profession; (4) Data management and ethical issues. Conclusions: This pilot study found that postgraduate clinical psychology students held a wide range of opinions but had limited formal education on how AI/ML-enabled tools might impact psychotherapy. The survey raises questions about how curricula could be enhanced to educate clinical psychology/psychotherapy trainees about the scope of AI/ML in mental healthcare.

Willingness to Use Digital Health Tools in Patient Care Among Health Care Professionals and Students at a University Hospital in Saudi Arabia: Quantitative Cross-sectional Survey

BACKGROUND

The adoption rate of digital health in the health care sector is low in many countries. A facilitating factor for successful implementation and adoption of digital health is acceptance by current and future health care professionals.

OBJECTIVE

This study was conducted to identify factors associated with willingness to use digital health tools in patient care among health care professionals and students.

METHODS

This was a quantitative cross-sectional survey study conducted among health care professionals and students at a university hospital in Riyadh, Saudi Arabia. A nonprobability convenience sampling procedure was used to recruit participants. Data were collected using a self-completed e-questionnaire that was distributed by email. Chi-square tests, t tests, and logistic regression were used to analyze the data.

RESULTS

We found that 181 out of 218 health care professionals (83.0%; 75.6% [59/78] physicians; 87.1% [122/140] nurses) and 115 out of 154 students (74.7%; 80.0% [76/95] medical students and 66.1% [39/59] nursing students) were willing to use digital tools in patient care. Willingness to use digital tools was significantly associated with attitude (Adjusted Odds Ratios [AOR] 1.96; 95% CI 1.14-3.36) and self-efficacy (AOR 1.64; 95% CI 1.17-2.30) among health care professionals, and with current year of study (AOR 2.08; 95% CI 1.18-3.68) and self-efficacy (AOR 1.77; 95% CI 1.17-2.69) among students. No significant difference in willingness to use digital tools was found between physicians and nurses (P=.113), and between medical and nursing students (P=.079).

CONCLUSIONS

The findings of this study should encourage policy makers and hospital managers to implement relevant eHealth interventions within routine health care systems in Saudi Arabia. For successful implementation, digital health education programs should be implemented simultaneously, so that current and future health care professionals are able to develop required positive attitudes as well as practical skills and competencies.

US primary care in 2029: A Delphi survey on the impact of machine learning

OBJECTIVE

To solicit leading health informaticians' predictions about the impact of AI/ML on primary care in the US in 2029.

DESIGN

A three-round online modified Delphi poll.

PARTICIPANTS

Twenty-nine leading health informaticians.

METHODS

In September 2019, health informatics experts were selected by the research team, and invited to participate the Delphi poll. Participation in each round was anonymous, and panelists were given between 4-8 weeks to respond to each round. In Round 1 open-ended questions solicited forecasts on the impact of AI/ML on: (1) patient care, (2) access to care, (3) the primary care workforce, (4) technological breakthroughs, and (5) the long-future for primary care physicians. Responses were coded to produce itemized statements. In Round 2, participants were invited to rate their agreement with each item along 7-point Likert scales. Responses were analyzed for consensus which was set at a predetermined interquartile range of ≤ 1. In Round 3 items that did not reach consensus were redistributed.

RESULTS

A total of 16 experts participated in Round 1 (16/29, 55%). Of these experts 13/16 (response rate, 81%), and 13/13 (response rate, 100%), responded to Rounds 2 and 3, respectively. As a result of developments in AI/ML by 2029 experts anticipated workplace changes including incursions into the disintermediation of physician expertise, and increased AI/ML training requirements for medical students. Informaticians also forecast that by 2029 AI/ML will increase diagnostic accuracy especially among those with limited access to experts, minorities and those with rare diseases. Expert panelists also predicted that AI/ML-tools would improve access to expert doctor knowledge.

CONCLUSIONS

This study presents timely information on informaticians' consensus views about the impact of AI/ML on US primary care in 2029. Preparation for the near-future of primary care will require improved levels of digital health literacy among patients and physicians.

Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media

Background

High-quality medical resources are in high demand worldwide, and the application of artificial intelligence (AI) in medical care may help alleviate the crisis related to this shortage. The development of the medical AI industry depends to a certain extent on whether industry experts have a comprehensive understanding of the public’s views on medical AI. Currently, the opinions of the general public on this matter remain unclear.

Objective

The purpose of this study is to explore the public perception of AI in medical care through a content analysis of social media data, including specific topics that the public is concerned about; public attitudes toward AI in medical care and the reasons for them; and public opinion on whether AI can replace human doctors.

Methods

Through an application programming interface, we collected a data set from the Sina Weibo platform comprising more than 16 million users throughout China by crawling all public posts from January to December 2017. Based on this data set, we identified 2315 posts related to AI in medical care and classified them through content analysis.

Results

Among the 2315 identified posts, we found three types of AI topics discussed on the platform: (1) technology and application (n=987, 42.63%), (2) industry development (n=706, 30.50%), and (3) impact on society (n=622, 26.87%). Out of 956 posts where public attitudes were expressed, 59.4% (n=568), 34.4% (n=329), and 6.2% (n=59) of the posts expressed positive, neutral, and negative attitudes, respectively. The immaturity of AI technology (27/59, 46%) and a distrust of related companies (n=15, 25%) were the two main reasons for the negative attitudes. Across 200 posts that mentioned public attitudes toward replacing human doctors with AI, 47.5% (n=95) and 32.5% (n=65) of the posts expressed that AI would completely or partially replace human doctors, respectively. In comparison, 20.0% (n=40) of the posts expressed that AI would not replace human doctors.

Conclusions

Our findings indicate that people are most concerned about AI technology and applications. Generally, the majority of people held positive attitudes and believed that AI doctors would completely or partially replace human ones. Compared with previous studies on medical doctors, the general public has a more positive attitude toward medical AI. Lack of trust in AI and the absence of the humanistic care factor are essential reasons why some people still have a negative attitude toward medical AI. We suggest that practitioners may need to pay more attention to promoting the credibility of technology companies and meeting patients’ emotional needs instead of focusing merely on technical issues.

Real-Time Access to Electronic Health Record via a Patient Portal: Is it Harmful? A Retrospective Observational Study

BACKGROUND

The rapid implementation of patient portals, through which patients can view their electronic health record, creates possibilities for information exchange and communication between patients and health care professionals. However, real-time disclosure of test results and clinical reports poses a source of concern.

OBJECTIVE

This study aimed to examine negative experiences resulting from real-time disclosure of medical information through a patient portal.

METHODS

Data were collected over a 2-year period in 4 datasets consisting of incidents reported by health care professionals, complaints of patients, patient issues at a portal helpdesk, and a survey among health care professionals. Incidents, complaints, issues, and answers on the survey were counted and analyzed through an iterative process of coding.

RESULTS

Within the chosen time frame of 2 years, on average, 7978 patients per month logged into the portal at least once. The amount of negative incidents and complaints was limited. A total of 6 incidents, 4 complaints, and 2506 issues at the helpdesk concerning the patient portal were reported, of which only 2, 1, and 3 cases of these respective databases concerned real-time disclosure of medical information through the patient portal. Moreover, 32 out of 216 health care professionals reported patients that had negative experiences with real-time disclosure. Most negative consequences concerned confused and anxious patients when confronted with unexpected or incomprehensible results.

CONCLUSIONS

Real-time access through a patient portal did not substantially result in negative consequences. The negative consequences that did occur can be mitigated by adequate preparation and instruction of patients concerning the various functionalities of the patient portal, real-time disclosure of test results in particular, and can also be managed through educating health care professionals about the patient portal and making adjustments in the daily practice of health care professionals.

Can mobile health apps replace GPs? A scoping review of comparisons between mobile apps and GP tasks

Background

Mobile health applications (mHealth apps) are increasingly being used to perform tasks that are conventionally performed by general practitioners (GPs), such as those involved in promoting health, preventing disease, diagnosis, treatment, monitoring, and support for health services. This raises an important question: can mobile apps replace GPs? This study aimed to systematically search for and identify mobile apps that can perform GP tasks.

Methods

A scoping review was carried out. The Google Play Store and Apple App Store were searched for mobile apps, using search terms derived from the UK Royal College of General Practitioners (RCGP) guideline on GPs’ core capabilities and competencies. A manual search was also performed to identify additional apps.

Results

The final analysis included 17 apps from the Google Play Store and Apple App Store, and 21 apps identified by the manual search. mHealth apps were found to have the potential to replace GPs for tasks such as recording medical history and making diagnoses; performing some physical examinations; supporting clinical decision making and management; assisting in urgent, long-term, and disease-specific care; and health promotion. In contrast, mHealth apps were unable to perform medical procedures, appropriately utilise other professionals, and coordinate a team-based approach.

Conclusions

This scoping review highlights the functions of mHealth apps that can potentially replace GP tasks. Future research should focus on assessing the performance and quality of mHealth apps in comparison with that of real doctors.

Artificial intelligence and the future of psychiatry: Qualitative findings from a global physician survey

BACKGROUND

The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics.

OBJECTIVE

This study aimed to explore psychiatrists' opinions about the potential impact innovations in artificial intelligence and machine learning on psychiatric practice.

METHODS

In Spring 2019, we conducted a web-based survey of 791 psychiatrists from 22 countries worldwide. The survey measured opinions about the likelihood future technology would fully replace physicians in performing ten key psychiatric tasks. This study involved qualitative descriptive analysis of written responses ("comments") to three open-ended questions in the survey.

RESULTS

Comments were classified into four major categories in relation to the impact of future technology on: (1) patient-psychiatrist interactions; (2) the quality of patient medical care; (3) the profession of psychiatry; and (4) health systems. Overwhelmingly, psychiatrists were skeptical that technology could replace human empathy. Many predicted that 'man and machine' would increasingly collaborate in undertaking clinical decisions, with mixed opinions about the benefits and harms of such an arrangement. Participants were optimistic that technology might improve efficiencies and access to care, and reduce costs. Ethical and regulatory considerations received limited attention.

CONCLUSIONS

This study presents timely information on psychiatrists' views about the scope of artificial intelligence and machine learning on psychiatric practice. Psychiatrists expressed divergent views about the value and impact of future technology with worrying omissions about practice guidelines, and ethical and regulatory issues.

Identifying How Patient Portals Impact Communication in Oncology

Patient portals are becoming widespread throughout health-care systems. Initial research has demonstrated that they positively impact patient-provider communication and patients' health knowledge, but little is known about the impact of patient portals in the cancer setting, where highly complex and uncertain medical data are available for patients to view. To better understand communicative behaviors and perceptions of the patient portal and how it is utilized in oncology, in-depth, semi-structured interviews were conducted with 48 participants: 35 patients and 13 oncologists. Thematic analysis identified that portals help to enhance participation during in-person consultations, increase patients' self-advocacy, and build rapport with providers. However, patients' comfort level with reviewing information via the portal depended upon the severity of the test. Oncologists worried about patient anxiety and widening health disparities, but acknowledged that the portal can motivate them to expedite communication about laboratory and scan results. As patient portals become more widely used in all medical settings, oncologists should become more engaged with how patients are viewing their medical information and consider the portal within the framework of patient-centered care by valuing patients' communication preferences.

Approach to the use of technologies in health systems: eHealth and mHealth

Introduction: Given the demands of society in the twenty-first century, information and communication technologies should be incorporated into future models of the public health system.Objective: To investigate about the use of eHealth and mHealth through a quantitative study.Materials and methods: A quantitative study was carried out using a 16-item questionnaire that inquires about 9 dimensions: self-diagnostic technologies, complementation genetic test, use of smartphones, data privacy, electronic medical records, costs of medical services, annual physical examinations, concern about radiation exposure, and management of internet and technologies.Results: The exploratory sample (n=250) was made up of health professionals (55 doctors and 77 medical students) and health service users (122 patients) from Spain. One of the similarities was the promotion of the use of smartphones, but there were differences regarding the value given to diagnosis made by using technologies as opposed to that made by professionals.Conclusion: The most relevant difference in terms of expectations among health service users and health care professionals was related to the ownership of the medical history.

Artificial Intelligence in Cardiology

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes.

Artificial Intelligence and the Future of Primary Care: Exploratory Qualitative Study of UK General Practitioners' Views

Background

The potential for machine learning to disrupt the medical profession is the subject of ongoing debate within biomedical informatics and related fields.

Objective

This study aimed to explore general practitioners’ (GPs’) opinions about the potential impact of future technology on key tasks in primary care.

Methods

In June 2018, we conducted a Web-based survey of 720 UK GPs’ opinions about the likelihood of future technology to fully replace GPs in performing 6 key primary care tasks, and, if respondents considered replacement for a particular task likely, to estimate how soon the technological capacity might emerge. This study involved qualitative descriptive analysis of written responses (“comments”) to an open-ended question in the survey.

Results

Comments were classified into 3 major categories in relation to primary care: (1) limitations of future technology, (2) potential benefits of future technology, and (3) social and ethical concerns. Perceived limitations included the beliefs that communication and empathy are exclusively human competencies; many GPs also considered clinical reasoning and the ability to provide value-based care as necessitating physicians’ judgments. Perceived benefits of technology included expectations about improved efficiencies, in particular with respect to the reduction of administrative burdens on physicians. Social and ethical concerns encompassed multiple, divergent themes including the need to train more doctors to overcome workforce shortfalls and misgivings about the acceptability of future technology to patients. However, some GPs believed that the failure to adopt technological innovations could incur harms to both patients and physicians.

Conclusions

This study presents timely information on physicians’ views about the scope of artificial intelligence (AI) in primary care. Overwhelmingly, GPs considered the potential of AI to be limited. These views differ from the predictions of biomedical informaticians. More extensive, stand-alone qualitative work would provide a more in-depth understanding of GPs’ views.

Perceptions and use of technology in older people with ophthalmic conditions

Background: Technologies such as mobile applications are increasingly being developed for patients to help manage their clinical conditions. However there is a paucity of information confirming the capacity or willingness of older patients with ophthalmic complaints to engage with such computer applications. The aim of this paper is to assess the perception and use of a range of common computing technologies by older ophthalmic patients, in order to guide future ophthalmology-specific development and clinical use.

Methods: Patients attending Manchester Royal Eye Hospital were surveyed with questions designed to measure their perceptions, attitudes and experiences of using technology.  Inclusion criteria included any patient aged 40 or over who attended the ophthalmology outpatients department.

Results: A total of 300 patients completed the questionnaire. The male-to-female ratio was 128:169. The majority of patients owned predominantly mobile forms of technology such as tablets and smart phones. The most common uses of technology were for communicating with friends, watching television and gathering information. Patients aged over 80 had particular difficulty using technology and used it less regularly. Less than 10% overall stated eyesight as a reason for stopping using technology.

Conclusions: Technology is used regularly by a large proportion of older ophthalmic patients, with numbers reducing significantly only in those aged 80 years or over. There appears to be potential for further medical use, though developers and clinicians should consider the perceptions and challenges highlighted through this survey.

A Prospective Evaluation of Three-Dimensional Image Simulation: Patient-Reported Outcomes and Mammometrics in Primary Breast Augmentation

BACKGROUND

Outcomes in primary breast augmentation depend on careful preoperative planning and clear communication between patient and surgeon. Three-dimensional imaging with computer simulation is an evolving technology with the potential to enhance the preoperative consultation for patients considering primary breast augmentation. The purpose of this study was to prospectively evaluate the impact of three-dimensional imaging with computer simulation on patient-reported and objective, mammometric outcomes in women undergoing primary breast augmentation.

METHODS

One hundred patients were enrolled in a prospective trial with randomized and nonrandomized arms. The randomized arm was composed of a control group consisting of patients who underwent tissue-based planning without simulation (n = 13) and an intervention group consisting of patients who were simulated (n = 10). The remainder constituted the nonrandomized group who specifically sought preoperative simulation. Patient-reported outcomes (BREAST-Q) and mammometric data were recorded and compared preoperatively and 6 months postoperatively.

RESULTS

Over time, significantly more patients refused randomization and chose simulation (p = 0.03). Breast augmentation led to substantial improvements in satisfaction with breasts, sexual well-being, and outcome. Simulation, however, did not significantly impact patient-reported outcomes or mammometric parameters. No strong correlations were identified between patient-reported outcomes and mammometrics.

CONCLUSIONS

Patients are likely to use novel technology such as three-dimensional photography with computer simulation if they perceive it to enhance their understanding of their final outcome. These patients may seek out practices specifically offering such technology. Incorporation of simulation into the preoperative consultation, however, did not lead to clinically meaningful changes in patient-reported outcomes.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Therapeutic, II.

Computerization and the future of primary care: A survey of general practitioners in the UK

OBJECTIVE

To describe the opinions of British general practitioners regarding the potential of future technology to replace key tasks carried out in primary care.

DESIGN

Cross sectional online survey.

PARTICIPANTS

1,474 registered GPs in the United Kingdom.

MAIN OUTCOME MEASURES

Investigators measured GPs' opinions about the likelihood that future technology will be able to fully replace-not merely aid-the average GP in performing six primary care tasks; in addition, if GPs considered replacement for a particular task likely, the survey measured opinions about how many years from now this technological capacity might emerge.

RESULTS

A total of 720 (49%) responded to the survey. Most GPs believed it unlikely that technology will ever be able to fully replace physicians when it comes to diagnosing patients (489, 68%), referring patients to other specialists (444, 61%), formulating personalized treatment plans (441, 61%), and delivering empathic care (680, 94%). GPs were not in agreement about prognostics: one in two participants (380, 53%) considered it likely that technology will be fully capable of replacing physicians in performing this task, nearly half (187, 49%) of whom believed that the technological capacity will arise in the next ten years. Against these findings, the majority of GPs (578, 80%) believed it likely that future technology will be able to fully replace humans to undertake documentation; among them 261 (79%) estimated that the technological wherewithal would emerge during the next ten years. In general, age and gender were not correlated with opinions; nor was reported burnout and job satisfaction or whether GPs worked full time or part time.

CONCLUSIONS

The majority of UK GPs in this survey were skeptical about the potential for future technology to perform most primary care tasks as well as or better than humans. However, respondents were optimistic that in the near future technology would have the capacity to fully replace GPs' in undertaking administrative duties related to patient documentation.

End user and implementer experiences of mHealth technologies for noncommunicable chronic disease management in young adults: a qualitative systematic review protocol

REVIEW OBJECTIVE

The objective of this review is to systematically identify, review and synthesize relevant qualitative research on end user and implementer experiences of mobile health (mHealth) technologies developed for noncommunicable chronic disease management in young adults. "End users" are defined as young people aged 15-24 years, and "implementers" are defined as health service providers, clinicians, policy makers and administrators.The two key questions we wish to systematically explore from identified relevant qualitative studies or studies with qualitative components are.

Implications of Patient Portal Transparency in Oncology: Qualitative Interview Study on the Experiences of Patients, Oncologists, and Medical Informaticists

Background

Providing patients with unrestricted access to their electronic medical records through patient portals has impacted patient-provider communication and patients’ personal health knowledge. However, little is known about how patient portals are used in oncology.

Objective

The aim of this study was to understand attitudes of the portal’s adoption for oncology and to identify the advantages and disadvantages of using the portal to communicate and view medical information.

Methods

In-depth semistructured interviews were conducted with 60 participants: 35 patients, 13 oncologists, and 12 medical informaticists. Interviews were recorded, transcribed, and thematically analyzed to identify critical incidents and general attitudes encountered by participants.

Results

Two primary themes were discovered: (1) implementation practices influence attitudes, in which the decision-making and execution process of introducing portals throughout the hospital did not include the input of oncologists. Lack of oncologists’ involvement led to a lack of knowledge about portal functionality, such as not knowing the time period when test results would be disclosed to patients; (2) perceptions of portals as communication tools varies by user type, meaning that each participant group (patients, oncologists, and medical informaticists) had varied opinions about how the portal should be used to transmit and receive information. Oncologists and medical informaticists had difficulty understanding one another’s culture and communication processes in their fields, while patients had preferences for how they would like to receive communication, but it largely depended upon the type of test being disclosed.

Conclusions

The majority of patients (54%, 19/35) who participated in this study viewed lab results or scan reports via the portal before being contacted by a clinician. Most were relatively comfortable with this manner of disclosure but still preferred face-to-face or telephone communication. Findings from this study indicate that portal education is needed for both patients and oncologists, especially when portals are implemented across entire health systems since highly specialized areas of medicine may have unique needs and uses. Patient portals in oncology can potentially alter the way diagnoses are delivered and how patients and oncologists communicate. Therefore, communication about the portal should be established during initial consultations so patients can decide whether they want to be informed in such a manner.

A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors

Background. Mobile health and digital medicine technologies are becoming increasingly used by individuals with common, chronic diseases to monitor their health. Numerous devices, sensors, and apps are available to patients and consumers-some of which have been shown to lead to improved health management and health outcomes. However, no randomized controlled trials have been conducted which examine health care costs, and most have failed to provide study participants with a truly comprehensive monitoring system. Methods. We conducted a prospective randomized controlled trial of adults who had submitted a 2012 health insurance claim associated with hypertension, diabetes, and/or cardiac arrhythmia. The intervention involved receipt of one or more mobile devices that corresponded to their condition(s) (hypertension: Withings Blood Pressure Monitor; diabetes: Sanofi iBGStar Blood Glucose Meter; arrhythmia: AliveCor Mobile ECG) and an iPhone with linked tracking applications for a period of 6 months; the control group received a standard disease management program. Moreover, intervention study participants received access to an online health management system which provided participants detailed device tracking information over the course of the study. This was a monitoring system designed by leveraging collaborations with device manufacturers, a connected health leader, health care provider, and employee wellness program-making it both unique and inclusive. We hypothesized that health resource utilization with respect to health insurance claims may be influenced by the monitoring intervention. We also examined health-self management. Results & Conclusions. There was little evidence of differences in health care costs or utilization as a result of the intervention. Furthermore, we found evidence that the control and intervention groups were equivalent with respect to most health care utilization outcomes. This result suggests there are not large short-term increases or decreases in health care costs or utilization associated with monitoring chronic health conditions using mobile health or digital medicine technologies. Among secondary outcomes there was some evidence of improvement in health self-management which was characterized by a decrease in the propensity to view health status as due to chance factors in the intervention group.

Bringing Health and Fitness Data Together for Connected Health Care: Mobile Apps as Enablers of Interoperability

Background

A transformation is underway regarding how we deal with our health. Mobile devices make it possible to have continuous access to personal health information. Wearable devices, such as Fitbit and Apple’s smartwatch, can collect data continuously and provide insights into our health and fitness. However, lack of interoperability and the presence of data silos prevent users and health professionals from getting an integrated view of health and fitness data. To provide better health outcomes, a complete picture is needed which combines informal health and fitness data collected by the user together with official health records collected by health professionals. Mobile apps are well positioned to play an important role in the aggregation since they can tap into these official and informal health and data silos.

Objective

The objective of this paper is to demonstrate that a mobile app can be used to aggregate health and fitness data and can enable interoperability. It discusses various technical interoperability challenges encountered while integrating data into one place.

Methods

For 8 years, we have worked with third-party partners, including wearable device manufacturers, electronic health record providers, and app developers, to connect an Android app to their (wearable) devices, back-end servers, and systems.

Results

The result of this research is a health and fitness app called myFitnessCompanion, which enables users to aggregate their data in one place. Over 6000 users use the app worldwide to aggregate their health and fitness data. It demonstrates that mobile apps can be used to enable interoperability. Challenges encountered in the research process included the different wireless protocols and standards used to communicate with wireless devices, the diversity of security and authorization protocols used to be able to exchange data with servers, and lack of standards usage, such as Health Level Seven, for medical information exchange.

Conclusions

By limiting the negative effects of health data silos, mobile apps can offer a better holistic view of health and fitness data. Data can then be analyzed to offer better and more personalized advice and care.