1
|
Ramgopal S, Heffernan ME, Bendelow A, Davis MM, Carroll MS, Florin TA, Alpern ER, Macy ML. Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care. Acad Pediatr 2023; 23:140-147. [PMID: 35577283 DOI: 10.1016/j.acap.2022.05.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 04/26/2022] [Accepted: 05/07/2022] [Indexed: 02/09/2023]
Abstract
BACKGROUND Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play an increasing role in health care in the future. We sought to understand parental perceptions of computer-assisted health care of children in the emergency department (ED). METHODS We conducted a population-weighted household panel survey of parents with minor children in their home in a large US city to evaluate perceptions of the use of computer programs for the care of children with respiratory illness. We identified demographics associated with discomfort with AI using survey-weighted logistic regression. RESULTS Surveys were completed by 1620 parents (panel response rate = 49.7%). Most respondents were comfortable with the use of computer programs to determine the need for antibiotics (77.6%) or bloodwork (76.5%), and to interpret radiographs (77.5%). In multivariable analysis, Black non-Hispanic parents reported greater discomfort with AI relative to White non-Hispanic parents (odds ratio [OR] 1.67, 95% confidence interval [CI] 1.03-2.70) as did younger parents (18-25 years) relative to parents ≥46 years (OR 2.48, 95% CI 1.31-4.67). The greatest perceived benefits of computer programs were finding something a human would miss (64.2%, 95% CI 60.9%-67.4%) and obtaining a more rapid diagnosis (59.6%; 56.2%-62.9%). Areas of greatest concern were diagnostic errors (63.0%, 95% CI 59.6%-66.4%), and recommending incorrect treatment (58.9%, 95% CI 55.5%-62.3%). CONCLUSIONS Parents were generally receptive to computer-assisted management of children with respiratory illnesses in the ED, though reservations emerged. Black non-Hispanic and younger parents were more likely to express discomfort about AI.
Collapse
Affiliation(s)
- Sriram Ramgopal
- Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (S Ramgopal, TA Florin, ER Alpern, and ML Macy), Chicago, Ill.
| | - Marie E Heffernan
- Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago (ME Heffernan, MM Davis, M Carroll, and ML Macy), Chicago, Ill; Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (ME Heffernan and MM Davis), Chicago, Ill
| | - Anne Bendelow
- Data Analytics and Reporting, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (A Bendelow and M Carroll), Chicago, Ill
| | - Matthew M Davis
- Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago (ME Heffernan, MM Davis, M Carroll, and ML Macy), Chicago, Ill; Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (ME Heffernan and MM Davis), Chicago, Ill
| | - Michael S Carroll
- Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago (ME Heffernan, MM Davis, M Carroll, and ML Macy), Chicago, Ill; Data Analytics and Reporting, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (A Bendelow and M Carroll), Chicago, Ill
| | - Todd A Florin
- Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (S Ramgopal, TA Florin, ER Alpern, and ML Macy), Chicago, Ill
| | - Elizabeth R Alpern
- Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (S Ramgopal, TA Florin, ER Alpern, and ML Macy), Chicago, Ill
| | - Michelle L Macy
- Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine (S Ramgopal, TA Florin, ER Alpern, and ML Macy), Chicago, Ill; Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago (ME Heffernan, MM Davis, M Carroll, and ML Macy), Chicago, Ill
| |
Collapse
|
2
|
Rawson TM, Peiffer-Smadja N, Holmes A. Artificial Intelligence in Infectious Diseases. Artif Intell Med 2022. [DOI: 10.1007/978-3-030-64573-1_103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
3
|
Optimizing antimicrobial use: challenges, advances and opportunities. Nat Rev Microbiol 2021; 19:747-758. [PMID: 34158654 DOI: 10.1038/s41579-021-00578-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/14/2021] [Indexed: 02/06/2023]
Abstract
An optimal antimicrobial dose provides enough drug to achieve a clinical response while minimizing toxicity and development of drug resistance. There can be considerable variability in pharmacokinetics, for example, owing to comorbidities or other medications, which affects antimicrobial pharmacodynamics and, thus, treatment success. Although current approaches to antimicrobial dose optimization address fixed variability, better methods to monitor and rapidly adjust antimicrobial dosing are required to understand and react to residual variability that occurs within and between individuals. We review current challenges to the wider implementation of antimicrobial dose optimization and highlight novel solutions, including biosensor-based, real-time therapeutic drug monitoring and computer-controlled, closed-loop control systems. Precision antimicrobial dosing promises to improve patient outcome and is important for antimicrobial stewardship and the prevention of antimicrobial resistance.
Collapse
|
4
|
Young AT, Amara D, Bhattacharya A, Wei ML. Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. LANCET DIGITAL HEALTH 2021; 3:e599-e611. [PMID: 34446266 DOI: 10.1016/s2589-7500(21)00132-1] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 06/15/2021] [Accepted: 06/17/2021] [Indexed: 12/14/2022]
Abstract
Artificial intelligence (AI) promises to change health care, with some studies showing proof of concept of a provider-level performance in various medical specialties. However, there are many barriers to implementing AI, including patient acceptance and understanding of AI. Patients' attitudes toward AI are not well understood. We systematically reviewed the literature on patient and general public attitudes toward clinical AI (either hypothetical or realised), including quantitative, qualitative, and mixed methods original research articles. We searched biomedical and computational databases from Jan 1, 2000, to Sept 28, 2020, and screened 2590 articles, 23 of which met our inclusion criteria. Studies were heterogeneous regarding the study population, study design, and the field and type of AI under study. Six (26%) studies assessed currently available or soon-to-be available AI tools, whereas 17 (74%) assessed hypothetical or broadly defined AI. The quality of the methods of these studies was mixed, with a frequent issue of selection bias. Overall, patients and the general public conveyed positive attitudes toward AI but had many reservations and preferred human supervision. We summarise our findings in six themes: AI concept, AI acceptability, AI relationship with humans, AI development and implementation, AI strengths and benefits, and AI weaknesses and risks. We suggest guidance for future studies, with the goal of supporting the safe, equitable, and patient-centred implementation of clinical AI.
Collapse
Affiliation(s)
- Albert T Young
- School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Dominic Amara
- School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Maria L Wei
- Department of Dermatology, University of California, San Francisco, San Francisco, CA, USA; Dermatology Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA.
| |
Collapse
|
5
|
Charani E, McKee M, Ahmad R, Balasegaram M, Bonaconsa C, Merrett GB, Busse R, Carter V, Castro-Sanchez E, Franklin BD, Georgiou P, Hill-Cawthorne K, Hope W, Imanaka Y, Kambugu A, Leather AJM, Mbamalu O, McLeod M, Mendelson M, Mpundu M, Rawson TM, Ricciardi W, Rodriguez-Manzano J, Singh S, Tsioutis C, Uchea C, Zhu N, Holmes AH. Optimising antimicrobial use in humans - review of current evidence and an interdisciplinary consensus on key priorities for research. THE LANCET REGIONAL HEALTH. EUROPE 2021; 7:100161. [PMID: 34557847 PMCID: PMC8454847 DOI: 10.1016/j.lanepe.2021.100161] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Addressing the silent pandemic of antimicrobial resistance (AMR) is a focus of the 2021 G7 meeting. A major driver of AMR and poor clinical outcomes is suboptimal antimicrobial use. Current research in AMR is inequitably focused on new drug development. To achieve antimicrobial security we need to balance AMR research efforts between development of new agents and strategies to preserve the efficacy and maximise effectiveness of existing agents. Combining a review of current evidence and multistage engagement with diverse international stakeholders (including those in healthcare, public health, research, patient advocacy and policy) we identified research priorities for optimising antimicrobial use in humans across four broad themes: policy and strategic planning; medicines management and prescribing systems; technology to optimise prescribing; and context, culture and behaviours. Sustainable progress depends on: developing economic and contextually appropriate interventions; facilitating better use of data and prescribing systems across healthcare settings; supporting appropriate and scalable technological innovation. Implementing this strategy for AMR research on the optimisation of antimicrobial use in humans could contribute to equitable global health security.
Collapse
Affiliation(s)
- Esmita Charani
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | - Martin McKee
- London School of Hygiene and Tropical Medicine, London, UK
| | - Raheelah Ahmad
- School of Health Sciences City, University of London, UK
| | - Manica Balasegaram
- The Global Antibiotic Research and Development Partnership, Geneva, Switzerland
| | - Candice Bonaconsa
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | | | | | - Vanessa Carter
- Stanford University Medicine X e-Patient Scholars Program 2017, Health Communication and Social Media South Africa, Africa CDC Civil Society Champion for AMR
| | - Enrique Castro-Sanchez
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| | - Bryony D Franklin
- University College London School of Pharmacy, London, UK
- Imperial College Healthcare NHS Trust, Centre for Medication Safety and Service Quality, Pharmacy Department, London, UK
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Kerri Hill-Cawthorne
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| | - William Hope
- Department of Molecular and Clinical Pharmacology, University of Liverpool, UK
| | - Yuichi Imanaka
- Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Andrew Kambugu
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Andrew JM Leather
- King's Centre for Global Health and Health Partnerships, School of Population Health and Environmental Sciences, King's College London, London, UK
| | - Oluchi Mbamalu
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | - M McLeod
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
- Imperial College Healthcare NHS Trust, Centre for Medication Safety and Service Quality, Pharmacy Department, London, UK
| | - Marc Mendelson
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | | | - Timothy M Rawson
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
- Department of Bioengineering, Imperial College London, London, UK
| | | | - Jesus Rodriguez-Manzano
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
- Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London
| | - Sanjeev Singh
- Department of Infection Control and Epidemiology, Amrita Institute of Medical Science, Amrita Vishwa Vidyapeetham, Kochi (Kerala), India
| | - Constantinos Tsioutis
- Department of Internal Medicine and Infection Prevention and Control, School of Medicine, European University Cyprus, Nicosia, Cyprus
| | - Chibuzor Uchea
- Drug-Resistant Infections Priority Programme,Wellcome Trust, London, UK
| | - Nina Zhu
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| | - Alison H Holmes
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| |
Collapse
|
6
|
Artificial Intelligence in Infectious Diseases. Artif Intell Med 2021. [DOI: 10.1007/978-3-030-58080-3_103-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|
7
|
Rawson TM, Ahmad R, Toumazou C, Georgiou P, Holmes AH. Artificial intelligence can improve decision-making in infection management. Nat Hum Behav 2019; 3:543-545. [PMID: 31190023 DOI: 10.1038/s41562-019-0583-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Timothy M Rawson
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Raheelah Ahmad
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Christofer Toumazou
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Alison H Holmes
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, London, UK.
| |
Collapse
|