Through Patients' Eyes: Regulation, Technology, Privacy, and the Future

Applied Artificial Intelligence in Healthcare: A Review of Computer Vision Technology Application in Hospital Settings

Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.

Patients' Views on AI for Risk Prediction in Shared Decision-Making for Knee Replacement Surgery: Qualitative Interview Study

BACKGROUND

The use of artificial intelligence (AI) in decision-making around knee replacement surgery is increasing, and this technology holds promise to improve the prediction of patient outcomes. Ambiguity surrounds the definition of AI, and there are mixed views on its application in clinical settings.

OBJECTIVE

In this study, we aimed to explore the understanding and attitudes of patients who underwent knee replacement surgery regarding AI in the context of risk prediction for shared clinical decision-making.

METHODS

This qualitative study involved patients who underwent knee replacement surgery at a tertiary referral center for joint replacement surgery. The participants were selected based on their age and sex. Semistructured interviews explored the participants' understanding of AI and their opinions on its use in shared clinical decision-making. Data collection and reflexive thematic analyses were conducted concurrently. Recruitment continued until thematic saturation was achieved.

RESULTS

Thematic saturation was achieved with 19 interviews and confirmed with 1 additional interview, resulting in 20 participants being interviewed (female participants: n=11, 55%; male participants: n=9, 45%; median age: 66 years). A total of 11 (55%) participants had a substantial postoperative complication. Three themes captured the participants' understanding of AI and their perceptions of its use in shared clinical decision-making. The theme Expectations captured the participants' views of themselves as individuals with the right to self-determination as they sought therapeutic solutions tailored to their circumstances, needs, and desires, including whether to use AI at all. The theme Empowerment highlighted the potential of AI to enable patients to develop realistic expectations and equip them with personalized risk information to discuss in shared decision-making conversations with the surgeon. The theme Partnership captured the importance of symbiosis between AI and clinicians because AI has varied levels of interpretability and understanding of human emotions and empathy.

CONCLUSIONS

Patients who underwent knee replacement surgery in this study had varied levels of familiarity with AI and diverse conceptualizations of its definitions and capabilities. Educating patients about AI through nontechnical explanations and illustrative scenarios could help inform their decision to use it for risk prediction in the shared decision-making process with their surgeon. These findings could be used in the process of developing a questionnaire to ascertain the views of patients undergoing knee replacement surgery on the acceptability of AI in shared clinical decision-making. Future work could investigate the accuracy of this patient group's understanding of AI, beyond their familiarity with it, and how this influences their acceptance of its use. Surgeons may play a key role in finding a place for AI in the clinical setting as the uptake of this technology in health care continues to grow.

Privatization of Medical Services and Revenue Development Project: A Cross-Sectional Survey of Staff Perceptions at the University of Jeddah Medical Center

This study aimed to assess the perceptions of staff working at the University of Jeddah (UJ) Medical Center on the possibility of finding new financing methods for the administration and privatization of the primary and specialized medical care services it provides. A questionnaire link was sent online targeting all staff at the UJ Medical Center (n = 141). The questionnaire comprised 17 items under the following sections: demographic information, staff perceptions about the current status of the services provided by the UJ Medical Center and the possibility of finding new financing methods and additional sources of revenue for the administration. Of the 101 questionnaires returned, the majority were filled by males (n = 71; 70.3%). One-third of the participants (n = 39; 38.6%) have between 5 and 9 years of working experience in Medical Administration, and most of them (n = 42; 41.6%) reported that they have a background in the concept of revenue development/privatization/self-resources/paid treatment. Most were satisfied with the current status of the services provided (average rating = 3.39/5). However, most participants (n = 72; 71.3%) reported that the UJ Medical Center is not ready for the Revenue Development Project of privatization. The survey respondents demonstrated satisfaction with the medical services provided by the UJ Medical Center and the potential application of the Revenue Development Project. However, streamlining the privatization process according to the governmental structures is crucial for it to be implemented properly at the UJ Medical Center.

Perceived technology use, attitudes, and barriers among primary care nurses

BACKGROUND

In primary healthcare, health information technology has the potential to facilitate the delivery of healthcare services by improving quality of care, efficiency and patient safety. However, little is known about the uptake and technology acceptance among primary healthcare nurses.

AIM

The aim of this study was to describe health information technology acceptance and use among primary healthcare nurses.

SETTING

Primary healthcare centres in the Western Cape.

METHODS

A quantitative descriptive survey was conducted with a sample of 160 nurses working in primary healthcare for more than 6 months, using a self-administered questionnaire based on the technology acceptance model constructs. Eighteen primary healthcare centres were randomly selected with a sample of 160 using nonprobability purposive sampling.

RESULTS

Ninety-three (58.1%) respondents completed the survey. Three-quarters of the respondents reported positive attitudes, positive perceptions of usefulness and ease of use towards the use of health information technology. Barriers of access and training were reported by 75%, with around half the respondents reporting poor computer and information accessing skills. Health information technology use was varied, with high ratings for seeking and using and low ratings of ability to use health information technology for patient administration and management. Health information technology use was predicted by perceptions of ease of use.

CONCLUSION

This research presents a mixed picture of acceptance of technology among primary healthcare nurses and highlights the lack of access to computers and Internet in these settings.

CONTRIBUTION

This study contributes to the field of technology acceptance among primary healthcare nurses.