scholarly journals Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 961
Author(s):  
Matthias Klumpp ◽  
Marcus Hintze ◽  
Milla Immonen ◽  
Francisco Ródenas-Rigla ◽  
Francesco Pilati ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Health Care Professionals ◽  
Real Life ◽  
Use Cases ◽  
Comparative Approach ◽  
Successful Implementation ◽  
Diverse Range ◽  
Efficiency And Effectiveness ◽  
Health Care Application

The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved efficiency and effectiveness by the introduction of novel AI applications are huge. However, experiences with real-life AI use cases are still scarce. As a first step towards structuring and comparing such experiences, this paper is presenting a comparative approach from nine European hospitals and eleven different use cases with possible application areas and benefits of hospital AI technologies. This is structured as a current review and opinion article from a diverse range of researchers and health care professionals. This contributes to important improvement options also for pandemic crises challenges, e.g., the current COVID-19 situation. The expected advantages as well as challenges regarding data protection, privacy, or human acceptance are reported. Altogether, the diversity of application cases is a core characteristic of AI applications in hospitals, and this requires a specific approach for successful implementation in the health care sector. This can include specialized solutions for hospitals regarding human–computer interaction, data management, and communication in AI implementation projects.

Emerging Pharmacotherapy and Health Care Needs of Patients in the Age of Artificial Intelligence and Digitalization

2020 ◽  
Vol 54 (10) ◽  
pp. 1038-1046
Author(s):  
Barbara J. Zarowitz
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Ethnic Diversity ◽  
Health Care Professionals ◽  
Large Data ◽  
The United States ◽  
Wearable Devices ◽  
Data Sets ◽  
Care Needs ◽  
Clinician Training

Advances in the application of artificial intelligence, digitization, technology, iCloud computing, and wearable devices in health care predict an exciting future for health care professionals and our patients. Projections suggest an older, generally healthier, better-informed but financially less secure patient population of wider cultural and ethnic diversity that live throughout the United States. A pragmatic yet structured approach is recommended to prepare health care professionals and patients for emerging pharmacotherapy needs. Clinician training should include genomics, cloud computing, use of large data sets, implementation science, and cultural competence. Patients will need support for wearable devices and reassurance regarding digital medicine.

Health-Care Professionals Perceived Barriers to Effective Cancer Pain Management in the Home Hospice Setting: Is Dying at Home Really Best?

2019 ◽  
pp. 003022281985787
Author(s):  
Lee A. Johnson ◽  
Cynthia J. Bell ◽  
Sheila Ridner ◽  
Barbara Murphy
Keyword(s):  
Health Care ◽  
Pain Management ◽  
Cancer Pain ◽  
Health Care Professionals ◽  
Cultural Beliefs ◽  
Comparative Approach ◽  
Unexpected Finding ◽  
Convenience Sample ◽  
Alternative Placement ◽  
Patients At Risk

Hospice health-care professionals (HCP) evaluate and manage cancer pain in patient homes. This study explores HCP’s perceptions of barriers that affect pain management for home hospice cancer patients. A convenience sample of 20 experienced hospice HCP were recruited from a regional hospice agency. Data were collected through two focus groups using semistructured interviews and analyzed using a constant comparative approach to generate themes. An unexpected finding revealed patient’s religious and cultural beliefs about suffering and family caregiver’s beliefs that patients deserve to suffer due to past actions are barriers to pain management in home hospice. Hospice HCP can identify patients at risk for suffering at the end of life. Interventions targeting spiritual suffering and needs are needed. Home hospice HCP have an ethical obligation to address undue suffering through family’s withholding of necessary pain medications and should consider alternative placement when home is not suitable for a peaceful death.

Barriers in the Decision Making About and Performance of Continuous Sedation Until Death in Nursing Homes

2019 ◽  
Vol 60 (5) ◽  
pp. 916-925
Author(s):  
Lenzo Robijn ◽  
Luc Deliens ◽  
Judith Rietjens ◽  
Peter Pype ◽  
Kenneth Chambaere
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Nursing Homes ◽  
Health Care Professionals ◽  
Comparative Approach ◽  
Organizational Barriers ◽  
Organization Of Care ◽  
Continuous Sedation ◽  
And Performance ◽  
Design And Methods

Abstract Background and Objectives While decision making about and performance of continuous sedation involve many challenges, they appear to be particularly pervasive in nursing homes. This study aims to identify barriers to the decision making and performance of continuous sedation until death in Flemish nursing homes as experienced by the health care professionals involved. Research Design and Methods Ten focus groups were held with 71 health care professionals including 16 palliative care physicians, 42 general practitioners, and 13 nursing home staff. Discussions were transcribed verbatim and analyzed using a constant comparative approach. Results Perceived barriers concerned factors prior to and during sedation and were classified according to three types: (a) personal barriers related to knowledge and skills including the lack of clarity on what continuous sedation should be used for (linguistic ambiguity) and when and how it should be used (practical ambiguity); (b) relational barriers concerning communication and collaboration both between health care professionals and with family; (c) organizational barriers related to the organization of care in nursing homes where, for example, there is no on-site physician, or where the recommended medication is not always available. Discussion and Implications The findings suggest there are considerable challenges for sound decision making about and performance of continuous sedation until death in nursing homes. There is a need for multicomponent initiatives that provide guidance in the context of the complexity of a resident’s medical situation, the family, and the specific organization of care, which would have the potential to facilitate and improve the decision-making process and performance of continuous sedation in nursing homes.

May We Support Your Decision?

1996 ◽  
Vol 1 (3) ◽  
pp. 175-178 ◽  
Author(s):  
Colin Gordon
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Decision Making ◽  
Clinical Practice ◽  
Decision Support ◽  
Health Care Professionals ◽  
Medical Decision Making ◽  
Electronic Patient Record ◽  
Medical Decision ◽  
Technical Developments

Expert systems to support medical decision-making have so far achieved few successes. Current technical developments, however, may overcome some of the limitations. Although there are several theoretical currents in medical artificial intelligence, there are signs of them converging. Meanwhile, decision support systems, which set themselves more modest goals than replicating or improving on clinicians' expertise, have come into routine use in places where an adequate electronic patient record exists. They may also be finding a wider role, assisting in the implementation of clinical practice guidelines. There is, however, still much uncertainty about the kinds of decision support that doctors and other health care professionals are likely to want or accept.

scholarly journals Covid, AI, and Robotics—A Neurologist's Perspective

2021 ◽  
Vol 8 ◽  
Author(s):  
Syed Nizamuddin Ahmed
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Literature Review ◽  
Current System ◽  
Personal Perspective ◽  
Ideal Situation ◽  
Efficiency And Effectiveness ◽  
Rapid Pace ◽  
And Robotics ◽  
The Ideal

Two of the major revolutions of this century are the Artificial Intelligence and Robotics. These technologies are penetrating through all disciplines and faculties at a very rapid pace. The application of these technologies in medicine, specifically in the context of Covid 19 is paramount. This article briefly reviews the commonly applied protocols in the Health Care System and provides a perspective in improving the efficiency and effectiveness of the current system. This article is not meant to provide a literature review of the current technology but rather provides a personal perspective of the author regarding what could happen in the ideal situation.

scholarly journals Real-Time Detection of Behavioural Anomalies for Older People, the 3-PEGASE Study: Methods of an Artificial Intelligence Real-life Prospective Trial. (Preprint)

2019 ◽  
Author(s):  
Antoine Piau ◽  
Benoit Lepage ◽  
Carole Bernon ◽  
Marie-Pierre Gleyzes ◽  
Fati Nourhashemi
Keyword(s):  
Artificial Intelligence ◽  
Older Adults ◽  
Health Care Professionals ◽  
Primary Outcome ◽  
Prospective Trial ◽  
Real Life ◽  
Second Phase ◽  
Care Partners ◽  
Over Time

BACKGROUND Most frail older persons are living at home and we face difficulties in achieving seamless monitoring to detect adverse health changes. Even more important, this lack of follow-up could have a negative impact on the living choices made by older individuals and their care partners. People could give up their homes for the more reassuring environment of a medicalized living facility. We have developed a low-cost non-obtrusive sensor-based solution to trigger automatic alerts in case of an acute event or subtle changes over time. It could facilitate the follow-up of older adults in their own homes, and thus support independent living. OBJECTIVE The primary objective of our prospective open-label study is to evaluate the relevance of the automatic alerts generated by our artificial intelligence-driven monitoring solution as judged by the recipients: older adult, caregiver, and professional support worker. The secondary objective is to evaluate its ability to detect subtle functional and cognitive decline and major medical events. METHODS The primary outcome assessment will be performed for each successive 2-month follow-up period to estimate the progression of our learning algorithm performances over time. Twenty-five frail or disabled participants aged 75 and above and living alone in their own homes, will be enrolled for a 6-month follow-up period. RESULTS The first phase with five participants for a 4-month feasibility period has been completed and the expected completion date for the second phase of the study (20 participants for 6 months) is July 2020. CONCLUSIONS The originality of our 6-month real-life project lies in the choice of the primary outcome and in our user-centered design. We will evaluate the relevance of the alerts and the algorithm performances over time according to the end users. The first-line recipients of the information are the older adults and care partners rather than health-care professionals. Despite the fast pace of e-Health device development, no study addressed the specific everyday needs of older adults and their families using such a participatory design and ‘bottom-up’ approach. CLINICALTRIAL ClinicalTrials.gov NCT03484156

scholarly journals Hydroxychloroquine as prophylaxis when treating patients with coronavirus disease 2019 – Perception of frontline health care workers in South India

2021 ◽  
Vol 0 ◽  
pp. 1-6
Author(s):  
Karthik Mani ◽  
Minu Velan
Keyword(s):  
Health Care ◽  
Health Care Workers ◽  
Health Care Professionals ◽  
South India ◽  
Research Question ◽  
Physician Assistants ◽  
Successful Implementation ◽  
Snowball Sampling ◽  
Health Care Practitioners ◽  
Care Workers

Objectives: In March 2020, the Indian Council of Medical Research (ICMR) recommended the use of hydroxychloroquine (HCQ) for prophylaxis in asymptomatic health care workers who care for suspected or confirmed patients and household contacts of confirmed patients with coronavirus disease 2019 (COVID-19). This recommendation was received by health-care practitioners with mixed opinions. The objectives of the study were to explore the views of frontline health-care practitioners (physicians, nurses, and physician assistants) in South India related to the ICMR recommendation of HCQ prophylaxis. Material and Methods: The survey research design was used to conduct this study. A ten-item electronic survey was developed based on the research question. The survey link was shared with frontline health-care practitioners in South India through email and WhatsApp messages identified through convenience sampling. Furthermore, the recipients were requested to forward the link to other frontline health-care professionals in their network (snowball sampling). Data were collected from April 16, 2020, to May 7, 2020. Results: The number of responses received was 132. Of 80 respondents who treated or anticipate treating patients with COVID-19, only 29 respondents reported that they complied with the ICMR’s HCQ chemoprophylaxis recommendation. Participants expressed concerns about the side effects and lack of conclusive evidence. Conclusion: Frontline health care workers in South India have mixed opinions with regard to the safety of HCQ prophylaxis. To promote the acceptance of and successful implementation of prophylaxis recommendations, it is essential that health authorities consider research evidence and seek stakeholder input before finalizing recommendations.

scholarly journals 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

10.2196/18590 ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. e18590
Author(s):  
Subash Thapa ◽  
Jesper Bo Nielsen ◽  
Abdullah M Aldahmash ◽  
Fatima R Qadri ◽  
Anja Leppin
Keyword(s):  
Health Care ◽  
Saudi Arabia ◽  
Patient Care ◽  
Health Care Professionals ◽  
Digital Health ◽  
University Hospital ◽  
Digital Tools ◽  
Successful Implementation ◽  
Cross Sectional Survey ◽  
Willingness To Use

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.

scholarly journals Personalising screening of sight-threatening diabetic retinopathy - qualitative evidence to inform effective implementation

2020 ◽  
Author(s):  
Paula Byrne ◽  
Clare Thetford ◽  
Mark Gabbay ◽  
Pam Clarke ◽  
Emily Doncaster ◽  
...  
Keyword(s):  
Health Care ◽  
Diabetic Retinopathy ◽  
Health Care Professionals ◽  
Controlled Trial ◽  
Comparative Method ◽  
Variable Interval ◽  
Incidence Rates ◽  
Successful Implementation ◽  
Eye Screening ◽  
Screening Intervals

Abstract Background Internationally, systematic screening for sight-threatening diabetic retinopathy (STDR) usually includes annual recall. Researchers and policy-makers support extending screening intervals, citing evidence from observational studies with low incidence rates. However, there is little research around the acceptability to people with diabetes (PWD) and health care professionals (HCP) about changing eye screening intervals. Methods We conducted a qualitative study to explore issues surrounding acceptability and the barriers and enablers for changing from annual screening, using in-depth, semi-structured interviews analysed using the constant comparative method. PWD were recruited from general practices and HCPs from eye screening networks and related specialties in North West England using purposive sampling. Interviews were conducted prior to the commencement of and during a randomised controlled trial (RCT) comparing fixed annual with variable (6, 12 or 24 month) interval risk-based screening. Results Thirty PWD and 21 HCP participants were interviewed prior to and 30 PWD during the parallel RCT. The data suggests that a move to variable screening intervals was generally acceptable in principle, though highlighted significant concerns and challenges to successful implementation. The current annual interval was recognised as unsustainable against a backdrop of increasing diabetes prevalence. There were important caveats attached to acceptability and a need for clear safeguards around: the safety and reliability of calculating screening intervals, capturing all PWDs, referral into screening of PWDs with diabetic changes regardless of planned interval. For PWDs the 6-month interval was perceived positively as medical reassurance, and the 12-month seen as usual treatment. Concerns were expressed by many HCPs and PWDs that a 2-year interval was too lengthy and was risky for detecting STDR. There were also concerns about a negative effect upon PWD care and increasing non-attendance rates. Amongst PWDs, there was considerable conflation and misunderstanding about different eye-related appointments within the health care system. Conclusions Implementing variable-interval screening into clinical practice is generally acceptable to PWD and HCP with important caveats, and misconceptions must be addressed. Clear safeguards against increasing non-attendance, loss of diabetes control and alternative referral pathways are required. For risk calculation systems to be safe, reliable monitoring and clear communication is required.

scholarly journals Introducing Artificial Intelligence Training in Medical Education

10.2196/16048 ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. e16048 ◽  
Author(s):  
Ketan Paranjape ◽  
Michiel Schinkel ◽  
Rishi Nannan Panday ◽  
Josip Car ◽  
Prabath Nanayakkara
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Medical Education ◽  
Health Care Professionals ◽  
Access To Health Care ◽  
Clinical Decision Making ◽  
New Technology ◽  
Medical Knowledge ◽  
Clinical Decision ◽  
Use Of Data

Health care is evolving and with it the need to reform medical education. As the practice of medicine enters the age of artificial intelligence (AI), the use of data to improve clinical decision making will grow, pushing the need for skillful medicine-machine interaction. As the rate of medical knowledge grows, technologies such as AI are needed to enable health care professionals to effectively use this knowledge to practice medicine. Medical professionals need to be adequately trained in this new technology, its advantages to improve cost, quality, and access to health care, and its shortfalls such as transparency and liability. AI needs to be seamlessly integrated across different aspects of the curriculum. In this paper, we have addressed the state of medical education at present and have recommended a framework on how to evolve the medical education curriculum to include AI.

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