Validating the Effectiveness of the Patient-Centered Cancer Care Framework by Assessing the Impact of Work System Factors on Patient-Centered Care and Quality of Care: Interview Study With Newly Diagnosed Cancer Patients

BACKGROUND

Patients with cancer who have recently been diagnosed have distinct requirements compared to cancer survivors. It is crucial to take into account their unique needs to ensure that they make informed decisions and are receptive to the care provided.

OBJECTIVE

This study suggested a framework titled Effectiveness of Patient-Centered Cancer Care that considers the needs of newly diagnosed patients with cancer and related work system factors. This study investigated how work system factors influence the perceptions of patient-centered care, quality of care, and associated outcomes among newly diagnosed patients with cancer. Patient-centered care is defined in terms of workload and communication considerations, whereas the quality of care is assessed through indicators such as trust in physicians, satisfaction with care, and perceptions of technology.

METHODS

This study used qualitative data collected through interviews with newly diagnosed patients with cancer (N=20) right after their first visits with their physicians. Thematic analysis was conducted to validate the 5 hypotheses of the framework, mapping the interactions among quality of care, patient-centered care, and work system factors.

RESULTS

We found that workload and patient-centered communication impact the quality of care and that the work system elements impact the patient-centeredness (workload and communication) and the quality of care (trust in physicians, satisfaction with care, and perception of technology use).

CONCLUSIONS

Qualitatively validating the proposed Effectiveness of Patient-Centered Cancer Care framework, this study demonstrated its efficacy in elucidating the interplay of various factors. The framework holds promise for informing interventions geared toward enhancing patients' experiences during their initial visits after diagnosis. There is a pressing need for heightened attention to the organizational design, patient processes, and collaborative efforts among diverse stakeholders and providers to optimize the overall patient experience.

Shaping the future of chronic disease management: Insights into patient needs for AI-based homecare systems

BACKGROUND

The rising demand for healthcare resources, especially in chronic disease management, has elevated the importance of Artificial Intelligence (AI) in healthcare. While AI-based homecare systems are being developed, the perspectives of chronic patients, who are one of the primary beneficiaries and risk bearers of these technologies, remain largely under-researched. While recent research has highlighted the importance of AI-based homecare systems, the current understanding of patients' desired designs and features is still limited.

OBJECTIVE

This paper explores chronic patients' perspectives regarding AI-based homecare systems, an area currently underrepresented in research. We aim to identify the factors influencing their decision to use such systems, elucidate the potential roles of government and other concerned authorities, and provide feedback to AI developers to enhance adoption, system design, and usability and improve the overall healthcare experiences of chronic patients.

METHOD

A web-based open-ended questionnaire was designed to gather the perspectives of chronic patients about AI-based homecare systems. In total, responses from 181 participants were collected. Using Krippendorff's clustering technique, an inductive thematic analysis was performed to identify the main themes and their respective subthemes.

RESULT

Through rigorous coding and thematic analysis of the collected responses, we identified four major themes further segmented into thirteen subthemes. These four primary themes were: 1) "Personalized Design", emphasizing the need for patients to manage their health condition better through personalized and educational resources and user-friendly interfaces; 2) "Emotional & Social Support", underscoring the desire for AI systems to facilitate social connectivity and provide emotional support to improve the well-being of chronic patients at home; 3) "System Integration & Proactive Care", addressing the importance of seamless communication, proactive patient monitoring and integration with existing healthcare platforms; and 4) "Ethics & Regulation", prioritizing ethical guidelines, regulatory compliance, and affordability in the design.

CONCLUSION

This study has offered significant insights into the needs and expectations of chronic patients regarding AI-based home care systems. 'The findings highlight the importance of personalized and accessible care, emotional and social support, seamless system integration, proactive care, and ethical considerations in designing and implementing such systems. By aligning the design and operation of these systems with the lived experiences and expectations of patients, we can better ensure their acceptance and effectiveness.

The health information technology preferences and perceptions of newly diagnosed patients with cancer

BACKGROUND & GOALS

Patients with new cancer diagnoses have unique needs. In this study, we explored the technological needs and preferences of new cancer patients and the challenges to technology use among these patients.

METHODS

We used qualitative data from semi-structured interviews to identify the new cancer patients' technology preferences. Interviews were recorded and then transcribed verbatim. A thematic analysis was conducted to identify the technology perceptions of new cancer patients, their technology needs, and the challenges of technology.

RESULTS

Most of the patients preferred mhealth technologies over other types of technologies to be used in their care management. The primary needs related to potential features in these technologies include access to information just in time, convenience, access to home care, self-management, privacy, interaction, and personalization. Patients also reported challenges of current technologies they utilized, including usability, impersonality, interoperability, and cost-effectiveness.

CONCLUSION

Addressing patients' needs to increase uptake and efficient use of technologies in cancer care is critical. Growing clinical and consumer informatics technologies can potentially help cancer management if designed by employing user-centered approaches.

Perspectives of Patients With Chronic Diseases on Future Acceptance of AI-Based Home Care Systems: Cross-Sectional Web-Based Survey Study

BACKGROUND

Artificial intelligence (AI)-based home care systems and devices are being gradually integrated into health care delivery to benefit patients with chronic diseases. However, existing research mainly focuses on the technical and clinical aspects of AI application, with an insufficient investigation of patients' motivation and intention to adopt such systems.

OBJECTIVE

This study aimed to examine the factors that affect the motivation of patients with chronic diseases to adopt AI-based home care systems and provide empirical evidence for the proposed research hypotheses.

METHODS

We conducted a cross-sectional web-based survey with 222 patients with chronic diseases based on a hypothetical scenario.

RESULTS

The results indicated that patients have an overall positive perception of AI-based home care systems. Their attitudes toward the technology, perceived usefulness, and comfortability were found to be significant factors encouraging adoption, with a clear understanding of accountability being a particularly influential factor in shaping patients' attitudes toward their motivation to use these systems. However, privacy concerns persist as an indirect factor, affecting the perceived usefulness and comfortability, hence influencing patients' attitudes.

CONCLUSIONS

This study is one of the first to examine the motivation of patients with chronic diseases to adopt AI-based home care systems, offering practical insights for policy makers, care or technology providers, and patients. This understanding can facilitate effective policy formulation, product design, and informed patient decision-making, potentially improving the overall health status of patients with chronic diseases.

Artificial Intelligence-Based Consumer Health Informatics Application: Scoping Review

BACKGROUND

There is no doubt that the recent surge in artificial intelligence (AI) research will change the trajectory of next-generation health care, making it more approachable and accessible to patients. Therefore, it is critical to research patient perceptions and outcomes because this trend will allow patients to be the primary consumers of health technology and decision makers for their own health.

OBJECTIVE

This study aimed to review and analyze papers on AI-based consumer health informatics (CHI) for successful future patient-centered care.

METHODS

We searched for all peer-reviewed papers in PubMed published in English before July 2022. Research on an AI-based CHI tool or system that reports patient outcomes or perceptions was identified for the scoping review.

RESULTS

We identified 20 papers that met our inclusion criteria. The eligible studies were summarized and discussed with respect to the role of the AI-based CHI system, patient outcomes, and patient perceptions. The AI-based CHI systems identified included systems in mobile health (13/20, 65%), robotics (5/20, 25%), and telemedicine (2/20, 10%). All the systems aimed to provide patients with personalized health care. Patient outcomes and perceptions across various clinical disciplines were discussed, demonstrating the potential of an AI-based CHI system to benefit patients.

CONCLUSIONS

This scoping review showed the trend in AI-based CHI systems and their impact on patient outcomes as well as patients' perceptions of these systems. Future studies should also explore how clinicians and health care professionals perceive these consumer-based systems and integrate them into the overall workflow.

Perceived Patient Workload and Its Impact on Outcomes During New Cancer Patient Visits: Analysis of a Convenience Sample

BACKGROUND

Studies exploring the workload in health care focus on the doctors' perspectives. The ecology of the health care environment is critical and different for doctors and patients.

OBJECTIVE

In this study, we explore the patient workload among newly diagnosed patients with cancer during their first visit and its impact on the patient's perceptions of the quality of care (their trust in their doctors, their satisfaction with the care visits, their perception of technology use).

METHODS

We collected data from the Hackensack Meridian Health, John Theurer Cancer Center between February 2021 and May 2022. The technology use considered during the visit is related to doctors' use of electronic health records. A total of 135 participants were included in the study. Most participants were 50-64 years old (n=91, 67.41%). A majority (n=81, 60%) of them were White, and only (n=16, 11.85%) went to graduate schools.

RESULTS

The findings captured the significant effect of overall workload on trust in doctors and perception of health IT use within the visits. On the other hand, the overall workload did not impact patients' satisfaction during the visit. A total of 80% (n=108) of patients experienced an overall high level of workload. Despite almost 55% (n=75) of them experiencing a high mental load, 71.1% (n=96) reported low levels of effort, 89% (n=120) experienced low time pressure, 85.2% (n=115) experienced low frustration levels, and 69.6% (n=94) experienced low physical activity. The more overall workload patients felt, the less they trusted their doctors (odds ratio [OR] 0.059, 95% CI 0.001-2.34; P=.007). Low trust was also associated with the demanding mental tasks in the visits (OR 0.055, 95% CI 0.002-2.64; P<.001), the physical load (OR 0.194, 95% CI 0.004-4.23; P<.001), the time load (OR 0.183, 95% CI 0.02-2.35; P=.046) the effort needed to cope with the environment (OR 0.163, 95% CI 0.05-1.69; P<.001), and the frustration levels (OR 0.323, 95% CI 0.04-2.55; P=.03). The patients' perceptions of electronic health record use during the visit were negatively impacted by the overall workload experienced by the patients (OR 0.315, 95% CI 0.08-6.35; P=.01) and the high frustration level experienced (OR 0.111, 95% CI 0.015-3.75; P<.001).

CONCLUSIONS

The study's findings established pathways for future research and have implications for cancer patients' workload. Better technology design and use can minimize perceived workload, which might contribute to the trust relationship between doctors and patients in this critical environment. Future human factors work needs to explore the workload and driving factors in longitudinal studies and assess whether these workloads might contribute to unintended patient outcomes and medical errors.

Lung Cancer Screening Decision Aid Designed for a Primary Care Setting: A Randomized Clinical Trial

Importance

Guidelines recommend shared decision-making prior to initiating lung cancer screening (LCS). However, evidence is lacking on how to best implement shared decision-making in clinical practice.

Objective

To evaluate the impact of an LCS Decision Tool (LCSDecTool) on the quality of decision-making and LCS uptake.

Design, Setting, and Participants

This randomized clinical trial enrolled participants at Veteran Affairs Medical Centers in Philadelphia, Pennsylvania; Milwaukee, Wisconsin; and West Haven, Connecticut, from March 18, 2019, to September 29, 2021, with follow-up through July 18, 2022. Individuals aged 55 to 80 years with a smoking history of at least 30 pack-years who were current smokers or had quit within the past 15 years were eligible to participate. Individuals with LCS within 15 months were excluded. Of 1047 individuals who were sent a recruitment letter or had referred themselves, 140 were enrolled.

Intervention

A web-based patient- and clinician-facing LCS decision support tool vs an attention control intervention.

Main Outcome and Measures

The primary outcome was decisional conflict at 1 month. Secondary outcomes included decisional conflict immediately after intervention and 3 months after intervention, knowledge, decisional regret, and anxiety immediately after intervention and 1 and 3 months after intervention and LCS by 6 months.

Results

Of 140 enrolled participants (median age, 64.0 [IQR, 61.0-69.0] years), 129 (92.1%) were men and 11 (7.9%) were women. Of 137 participants with data available, 75 (53.6%) were African American or Black and 62 (44.3%) were White; 4 participants (2.9%) also reported Hispanic or Latino ethnicity. Mean decisional conflict score at 1 month did not differ between the LCSDecTool and control groups (25.7 [95% CI, 21.4-30.1] vs 29.9 [95% CI, 25.6-34.2], respectively; P = .18). Mean LCS knowledge score was greater in the LCSDecTool group immediately after intervention (7.0 [95% CI, 6.3-7.7] vs 4.9 [95% CI, 4.3-5.5]; P < .001) and remained higher at 1 month (6.3 [95% CI, 5.7-6.8] vs 5.2 [95% CI, 4.5-5.8]; P = .03) and 3 months (6.2 [95% CI, 5.6-6.8] vs 5.1 [95% CI, 4.4-5.8]; P = .01). Uptake of LCS was greater in the LCSDecTool group at 6 months (26 of 69 [37.7%] vs 15 of 71 [21.1%]; P = .04).

Conclusions and Relevance

In this randomized clinical trial of an LCSDecTool compared with attention control, no effect on decisional conflict occurred at 1 month. The LCSDecTool used in the primary care setting did not yield a significant difference in decisional conflict. The intervention led to greater knowledge and LCS uptake. These findings can inform future implementation strategies and research in LCS shared decision-making.

Trial Registration

ClinicalTrials.gov Identifier: NCT02899754.

Multimedia tablet or paper handout to supplement counseling during preterm birth hospitalization

BACKGROUND

Parents of premature infants engage in shared decision-making regarding the care of their infant. The process of prenatal counseling typically involves a verbal conversation with a neonatal provider during hospitalization. Support people may not be available, and the pregnant person's memory is impaired by medications, pain, and stress. The American Academy of Pediatrics, American College of Obstetricians and Gynecologists, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development have called for improvements to this process, including the development of educational aids.

OBJECTIVE

This study aimed to investigate whether a multimedia tablet would be more effective than a paper handout in supplementing verbal clinician counseling during preterm birth hospitalization.

STUDY DESIGN

This was a randomized controlled trial including English-speaking pregnant people aged ≥18 years and hospitalized at 22 to 33 weeks' gestation for preterm birth. Exclusion criteria were known fetal or chromosomal anomaly and delivery before study completion. Pregnant people received either a multimedia tablet or a paper handout before verbal clinician counseling. Preintervention assessment included demographics and State-Trait Anxiety Inventory, and postintervention assessment included the Parent Knowledge of Premature Birth Questionnaire and State-Trait Anxiety Inventory. Continuous variables were analyzed by t-test and categorical variables by Fisher exact test.

RESULTS

A total of 122 pregnant people referred for counseling were screened; 76 were randomized, and 59 completed the study. Demographics were similar between groups, except that pregnant people in the handout group were older (mean 32 vs 29 years; P=.03). The multimedia tablet group (n=32) was less likely to report reviewing all the educational material than the paper handout group (n=27) (41% vs 72%; P=.037). Both groups correctly answered a similar number of knowledge items (P=.088). Postintervention state anxiety decreased in both groups (P<.0001), with no difference between groups. Computerized tracking showed that the multimedia group spent a median of 37 minutes reviewing the tablet.

CONCLUSION

Contrary to our hypothesis, a paper handout and multimedia tablet were equally effective in the labor unit for supplementing verbal preterm birth counseling, and both decreased parental anxiety.

The Impact of Patient-Centered Care on Cancer Patients' QOC, Self-Efficacy, and Trust Towards Doctors: Analysis of a National Survey

Patient-centered approaches impact cancer patients' perceptions and outcomes in different ways. This study explores the impact of patient-centered care practices on cancer patients' quality-of-care (QOC), self-efficacy, and trust in their doctors. We utilized cross-sectional national survey data from the National Cancer Institute collected between 2017 and 2020. All estimates were weighted using the jackknife method. We used multivariable logistic regression to test our hypotheses adjusted for the demographics of the 1932 cancer patients that responded to the survey. Findings indicate that patient-centered communication resulted in better QOC, self-efficacy, and trust in doctors. In addition, engagement in their care improved patients' trust in cancer-related information received from doctors. QOC and patients' trust in doctors were significantly improved with the patients' understanding of the next steps, addressing feelings, clear explanation of the problems, spending enough time with the clinicians, addressing uncertainty, and involvement in decisions. Patients who were given a chance to ask questions were significantly more likely to trust their doctors. Technology use did not impact any of these interactions. Patient-centered strategies should consider the needs of the patients in the cancer settings to improve overall outcomes. Organizations should also build strategies that are goal-oriented and centered around the patients' needs, as standard strategies cannot induce the wanted results.

Using health information technology to support the needs of Children with Medical Complexity: Mapping review of consumer informatics applications

Background

Children with medical complexity (CMC) are fragile populations that require continuous care and supervision. CMC family caregivers experience many challenges trying to address CMC patients' needs which puts these caregivers in a stressful situation that may negatively impact the care of CMC patients. Consumer informatics might help these caregivers in coordinating care. However, few consumer informatics applications explicitly focus on supporting CMC caregivers' needs.

Objective

This systematic mapping literature review aims to provide an overview and a structured understanding of the consumer informatics designed for CMC and their caregivers.

Methods

We followed a systematic mapping literature review process to provide an overview of the existing Consumer Informatics literature for CMC, which is the scope of our study. We screened IEEE Xplore, Web of Science, and PubMed databases using a preset list of mesh terms that cover the use of medical informatics by children with medical complexities and their caregivers. The selected articles are peer-reviewed English publications that were empirically validated from January 2002 to January 2022. After selecting and filtering the articles, we analyzed them based on the preset mapping questions using the following criteria: publication year, publication source, research type, contribution type, empirical type, the need addressed, target audience, technology users, and consumer informatics' type.

Results

The initial search resulted in a number of (N = 2,275) articles, and 17 selected publications were included. The results showed an increasing interest in CMC consumer informatics publications over time. Most of the studies were published in 2021, and feasibility research is the dominant research type. The most used technology was telehealth and telemedicine, followed by mobile health. The technologies addressed various needs, including; coordination & follow-up, medical safety, education & social support, daily living activities, shared decision making, information seeking, and emotional support. Most of the efforts were focused on ensuring good coordination and follow-up.

Conclusions

CMC consumer informatics is a promising research field to present novel initiatives and approaches to manage the caregivers' workload. Future research should be shifted toward providing more evidence-based studies to examine the effectiveness of CMC consumer informatics solutions and identify the related challenges and limitations.

Successful application of the innovation process to a case of Floyd Type I tracheal agenesis

Background

Innovation is broadly defined as the act of introducing a new product, idea, or process. The field of surgery is built upon innovation, revolutionizing technology, science, and tools to improve patient care. While most innovative solutions are aimed at problems with a significant patient population, the process can also be used on orphan pathologies without obvious solutions. We present a case of tracheal agenesis, a rare congenital anomaly with an overwhelming mortality and few good treatment options, that benefited from the innovation process and achieved survival with no ventilator dependence at three years of age.

Methods

Utilizing the framework of the innovation process akin to the Stanford Biodesign Program, 1) the parameters of the clinical problem were identified, 2) previous solutions and existing technologies were analyzed, newly invented solutions were brainstormed, and value analysis of the possible solutions were carried out using crowd wisdom, and 3) the selected solution was prototyped and tested using 3D modeling, iterative testing on 3D prints of actual-sized patient parts, and eventual implementation in the patient after regulatory clearance.

Results

A 3D-printed external bioresorbable splint was chosen as the solution. Our patient underwent airway reconstruction with "trachealization of the esophagus": esophageotracheal fistula resection, esophagotracheoplasty, and placement of a 3D-printed polycaprolactone (PCL) stent for external esophageal airway support at five months of age.

Conclusions

The innovation process provided our team with the guidance and imperative steps necessary to develop an innovative device for the successful management of an infant survivor with Floyd Type I tracheal agenesis.

Article summary

We present a case of tracheal agenesis, a rare congenital anomaly with an overwhelming mortality and few good treatment options, that benefited from the innovation process and achieved survival with no ventilator dependence at three years of age.The importance of this report is to reveal how the innovation process, which is typically used for problems with significant patient population, can also be used on orphan pathologies without obvious solutions.

Managing Critical Patient-Reported Outcome Measures in Oncology Settings: System Development and Retrospective Study

BACKGROUND

Remote monitoring programs based on the collection of patient-reported outcome (PRO) data are being increasingly adopted in oncology practices. Although PROs are a great source of patient data, the management of critical PRO data is not discussed in detail in the literature.

OBJECTIVE

This first-of-its-kind study aimed to design, describe, and evaluate a closed-loop alerting and communication system focused on managing PRO-related alerts in cancer care.

METHODS

We designed and developed a novel solution using an agile software development methodology by incrementally building new capabilities. We evaluated these new features using participatory design and the Fit between Individuals, Task, and Technology framework.

RESULTS

A total of 8 questionnaires were implemented using alerting features, resulting in an alert rate of 7.82% (36,838/470,841) with 13.28% (10,965/82,544) of the patients triggering at least one alert. Alerts were reviewed by 501 staff members spanning across 191 care teams. All the alerts were reviewed with a median response time of 1 hour (SD 185 hours) during standard business hours. The most severe (red) alerts were documented 56.83% (2592/4561) of the time, whereas unlabeled alerts were documented 27.68% (1298/4689) of the time, signaling clinician concordance with the alert thresholds.

CONCLUSIONS

A PRO-based alert and communication system has some initial benefits in reviewing clinically meaningful PRO data in a reasonable amount of time. We have discussed key system design considerations, workflow integration, and the mitigation of potential impact on the burden of care teams. The introduction of a PRO-based alert and communication system provides a reliable mechanism for care teams to review and respond to patient symptoms quickly. The system was standardized across many different oncology settings, demonstrating system flexibility. Future studies should focus on formally evaluating system usability through qualitative methods.

Clinicians' Perceptions of an Artificial Intelligence-Based Blood Utilization Calculator: Qualitative Exploratory Study

BACKGROUND

According to the US Food and Drug Administration Center for Biologics Evaluation and Research, health care systems have been experiencing blood transfusion overuse. To minimize the overuse of blood product transfusions, a proprietary artificial intelligence (AI)-based blood utilization calculator (BUC) was developed and integrated into a US hospital's electronic health record. Despite the promising performance of the BUC, this technology remains underused in the clinical setting.

OBJECTIVE

This study aims to explore how clinicians perceived this AI-based decision support system and, consequently, understand the factors hindering BUC use.

METHODS

We interviewed 10 clinicians (BUC users) until the data saturation point was reached. The interviews were conducted over a web-based platform and were recorded. The audiovisual recordings were then anonymously transcribed verbatim. We used an inductive-deductive thematic analysis to analyze the transcripts, which involved applying predetermined themes to the data (deductive) and consecutively identifying new themes as they emerged in the data (inductive).

RESULTS

We identified the following two themes: (1) workload and usability and (2) clinical decision-making. Clinicians acknowledged the ease of use and usefulness of the BUC for the general inpatient population. The clinicians also found the BUC to be useful in making decisions related to blood transfusion. However, some clinicians found the technology to be confusing due to inconsistent automation across different blood work processes.

CONCLUSIONS

This study highlights that analytical efficacy alone does not ensure technology use or acceptance. The overall system's design, user perception, and users' knowledge of the technology are equally important and necessary (limitations, functionality, purpose, and scope). Therefore, the effective integration of AI-based decision support systems, such as the BUC, mandates multidisciplinary engagement, ensuring the adequate initial and recurrent training of AI users while maintaining high analytical efficacy and validity. As a final takeaway, the design of AI systems that are made to perform specific tasks must be self-explanatory, so that the users can easily understand how and when to use the technology. Using any technology on a population for whom it was not initially designed will hinder user perception and the technology's use.

Digital Twins for Managing Health Care Systems: Rapid Literature Review

BACKGROUND

Although most digital twin (DT) applications for health care have emerged in precision medicine, DTs can potentially support the overall health care process. DTs (twinned systems, processes, and products) can be used to optimize flows, improve performance, improve health outcomes, and improve the experiences of patients, doctors, and other stakeholders with minimal risk.

OBJECTIVE

This paper aims to review applications of DT systems, products, and processes as well as analyze the potential of these applications for improving health care management and the challenges associated with this emerging technology.

METHODS

We performed a rapid review of the literature and reported available studies on DTs and their applications in health care management. We searched 5 databases for studies published between January 2002 and January 2022 and included peer-reviewed studies written in English. We excluded studies reporting DT usage to support health care practice (organ transplant, precision medicine, etc). Studies were analyzed based on their contribution toward DT technology to improve user experience in health care from human factors and systems engineering perspectives, accounting for the type of impact (product, process, or performance/system level). Challenges related to the adoption of DTs were also summarized.

RESULTS

The DT-related studies aimed at managing health care systems have been growing over time from 0 studies in 2002 to 17 in 2022, with 7 published in 2021 (N=17 studies). The findings reported on applications categorized by DT type (system: n=8; process: n=5; product: n=4) and their contributions or functions. We identified 4 main functions of DTs in health care management including safety management (n=3), information management (n=2), health management and well-being promotion (n=3), and operational control (n=9). DTs used in health care systems management have the potential to avoid unintended or unexpected harm to people during the provision of health care processes. They also can help identify crisis-related threats to a system and control the impacts. In addition, DTs ensure privacy, security, and real-time information access to all stakeholders. Furthermore, they are beneficial in empowering self-care abilities by enabling health management practices and providing high system efficiency levels by ensuring that health care facilities run smoothly and offer high-quality care to every patient.

CONCLUSIONS

The use of DTs for health care systems management is an emerging topic. This can be seen in the limited literature supporting this technology. However, DTs are increasingly being used to ensure patient safety and well-being in an organized system. Thus, further studies aiming to address the challenges of health care systems challenges and improve their performance should investigate the potential of DT technology. In addition, such technologies should embed human factors and ergonomics principles to ensure better design and more successful impact on patient and doctor experiences.

Real-world implementation evaluation of an electronic health record-integrated consumer informatics tool that collects patient-generated contextual data

OBJECTIVE

Use the RE-AIM framework to examine the implementation of a patient contextual data (PCD) Tool designed to share patients' needs, values, and preferences with care teams ahead of clinical encounters.

MATERIALS & METHODS

Observational study that follows initial PCD Tool scaling across primary care at a Midwestern academic health network. Program invitations, enrollment, patient submissions, and clinician views were tracked over a 1-year study period. Logistic regression modeled the likelihood of using the PCD Tool, accounting for patient covariates.

RESULTS

Of 58,874 patients who could be contacted by email, 9,183 (15.6%) became PCD Tool users. Overall, 76% of primary care providers had patients who used the PCD Tool. Older age, female gender, non-minority race, patient portal activation, and Medicare coverage were significantly associated with increased likelihood of use. Number of office visits, medical issues, and behavioral health conditions also associated with use. Primary care staff viewed 18.7% of available PCD Tool summaries, 1.1% to 57.6% per clinic.

DISCUSSION

The intervention mainly reached non-minority patients and patients who used more health services. Given the requirement for an email address on file, some patients may have been underrepresented. Overall, patient reach and adoption and clinician adoption, implementation, and maintenance of this Tool were modest but stable, consistent with a non-directive approach to fostering adoption by introducing the Tool in the absence of clear expectations for use.

CONCLUSION

Healthcare organizations must implement effective methods to increase the reach, adoption, implementation, and maintenance of PCD tools across all patient populations. Assisting people, particularly racial minorities, with PCD Tool registration and actively supporting clinician use are critical steps in implementing technology that facilitates care.

Effect of risk, expectancy, and trust on clinicians' intent to use an artificial intelligence system -- Blood Utilization Calculator

A gap exists between the capabilities of artificial intelligence (AI) technologies in healthcare and the extent to which clinicians are willing to adopt these systems. Our study addressed this gap by leveraging 'expectancy-value theory' and 'modified extended unified theory of acceptance and use of technology' to understand why clinicians may be willing or unwilling to adopt AI systems. The study looked at the 'expectancy,' 'trust,' and 'perceptions' of clinicians related to their intention of using an AI-based decision support system known as the Blood Utilization Calculator (BUC). The study used purposive sampling to recruit BUC users and administered a validated online survey from a large hospital system in the Midwest in 2021. The findings captured the significant effect of 'perceived risk' (negatively) and 'expectancy' (positively) on clinicians' 'trust' in BUC. 'Trust' was also found to mediate the relationship of 'perceived risk' and 'expectancy' with the 'intent to use BUC.' The study's findings established pathways for future research and have implications on factors influencing BUC use.

Predictors of Healthcare Professionals' Work Difficulty Perception during the COVID-19 Pandemic: Study of Work Environment in a Pandemic Hospital

COVID-19 has dramatically changed the work environment in healthcare, which is creating an additional burden for healthcare professionals. In this study, we investigate the factors that trigger professionals to have negative perceptions of their jobs during the pandemic. A cross-sectional survey is used for this study. The respondents are selected based on convenience random sampling. We use 345 questionaries for the analysis. Respondents are health care professionals (nurses, doctors, midwives, technicians, etc.) working in a pandemic hospital in Turkey. We run a multivariable logistic regression model to analyze the predictors of work difficulty perception. The model is adjusted for the respondents’ demographical characteristics and emotional wellbeing. We found that depression and burnout are significantly correlated with the perception of job difficulty (OR Severe PHQ-9 = 10.8, p = 0.004; OR Severe Burnout = 7.83, p < 0.001). The professionals who are changed from one department to another are also more likely to perceive the job as difficult (OR Department Change = 1.60, p = 0.045). However, the professionals that received sufficient applause from society are more likely to think that they did not face any difficulties doing their job during the pandemic (OR Applause = 0.56, p < 0.016). Anxiety, monetary motivation, religious beliefs, and information availability did not contribute to the perceived difficulty in their jobs. Thus, efforts need to be made to give them more social support and smooth their changes in departments and functions to facilitate their jobs.

A Veteran-Centric Web-Based Decision Aid for Lung Cancer Screening: Usability Analysis

BACKGROUND

Web-based tools developed to facilitate a shared decision-making (SDM) process may facilitate the implementation of lung cancer screening (LCS), an evidence-based intervention to improve cancer outcomes. Veterans have specific risk factors and shared experiences that affect the benefits and potential harms of LCS and thus may value a veteran-centric LCS decision tool (LCSDecTool).

OBJECTIVE

This study aims to conduct usability testing of an LCSDecTool designed for veterans receiving care at a Veteran Affairs medical center.

METHODS

Usability testing of the LCSDecTool was conducted in a prototype version (phase 1) and a high-fidelity version (phase 2). A total of 18 veterans and 8 clinicians participated in phase 1, and 43 veterans participated in phase 2. Quantitative outcomes from the users included the System Usability Scale (SUS) and the End User Computing Satisfaction (EUCS) in phase 1 and the SUS, EUCS, and Patient Engagement scale in phase 2. Qualitative data were obtained from observations of user sessions and brief interviews. The results of phase 1 informed the modifications of the prototype for the high-fidelity version. Phase 2 usability testing took place in the context of a pilot hybrid type 1 effectiveness-implementation trial.

RESULTS

In the phase 1 prototype usability testing, the mean SUS score (potential range: 0-100) was 81.90 (SD 9.80), corresponding to an excellent level of usability. The mean EUCS score (potential range: 1-5) was 4.30 (SD 0.71). In the phase 2 high-fidelity usability testing, the mean SUS score was 65.76 (SD 15.23), corresponding to a good level of usability. The mean EUCS score was 3.91 (SD 0.95); and the mean Patient Engagement scale score (potential range 1 [low] to 5 [high]) was 4.62 (SD 0.67). The median time to completion in minutes was 13 (IQR 10-16). A thematic analysis of user statements documented during phase 2 high-fidelity usability testing identified the following themes: a low baseline level of awareness and knowledge about LCS increased after use of the LCSDecTool; users sought more detailed descriptions about the LCS process; the LCSDecTool was generally easy to use, but specific navigation challenges remained; some users noted difficulty understanding medical terms used in the LCSDecTool; and use of the tool evoked veterans' struggles with prior attempts at smoking cessation.

CONCLUSIONS

Our findings support the development and use of this eHealth technology in the primary care clinical setting as a way to engage veterans, inform them about a new cancer control screening test, and prepare them to participate in an SDM discussion with their provider.

Clinicians’ Social Support, Job Stress, and Intent to Leave Healthcare during COVID-19

The onset of COVID-19 has escalated healthcare workers’ psychological distress. Multiple factors, including prolonged exposure to COVID-19 patients, irregular working hours, and workload, have substantially contributed to stress and burnout among healthcare workers. To explore the impact of COVID-19 on healthcare workers, our study compares the job stress, social support, and intention to leave the job among healthcare workers working in a pandemic (H_P) and a non-pandemic hospital (H_NP) in Turkey during the pandemic. The cross-sectional, paper-based survey involved 403 healthcare workers including physicians, registered nurses, health technicians, and auxiliary staff across two hospitals from 1 September 2020 to 31 November 2020. The findings indicate a significant impact of ‘Job stress’ on ‘Intent to leave’ job among participants in the H_P. We noted that ‘intent to leave’ and ‘job stress’ were significantly higher among the H_P healthcare workers than those working in the H_NP, respectively. However, workers’ ‘social support’ was significantly lower in the H_P. Healthcare workers, during COVID-19, face several hurdles such as job stress, reduced social support, and excessive workload, all of which are potential factors influencing a care provider’s intent to leave the job.

Impact of Health Perception and Knowledge on Genetic Testing Decisions Using the Health Belief Model

PURPOSE

Early detection of cancer risk is essential as it is associated with a higher chance of survival, more successful treatment, and improved quality of life. Genetic testing helps at-risk patients estimate the likelihood of developing cancer in a lifetime. This study aims to indentify the factors (perceived susceptibility, severity, benefits, and self-efficacy) that impact one's decision to take the genetic test.

METHODS

We examined the impacts of different factors of the health belief model on the engagement of patients in genetic testing using data from the National Cancer Institute's 2020 cross-sectional nationally representative data published in 2021. Complete surveys were answered by 3,865 participants (weighted population size = 253,815,197). All estimates were weighted to be nationally representative of the US population using the jackknife weighting method for parameter estimation. We used multivariable logistic regression to test our hypotheses for patients who have taken the genetic test for cancer risk detection. We adjusted the multivariate model for age, education, income, race, sex, cancer history, familial cancer history, and education.

RESULTS

We tested five hypotheses using the health belief model. Respondents who had genetic testing were more likely to rely on their health care providers and genetic counselors to make their decisions. Respondents who had genetic tests also reported less reliability on other sources than doctors: for the internet and social media (odds ratio = 0.33; P < .001) and for journals and magazines (odds ratio = 0.48; P = .007).

CONCLUSION

The findings show that patients generally rely on suggestions from their health care providers and counselors in genetic testing decisions. These findings also indicate that health care providers play a critical role in helping patients decide whether to use genetic testing to detect cancer risk in the early stages.

Artificial Intelligence to Improve Health Outcomes in the NICU and PICU: A Systematic Review

CONTEXT

Artificial intelligence (AI) technologies are increasingly used in pediatrics and have the potential to help inpatient physicians provide high-quality care for critically ill children.

OBJECTIVE

We aimed to describe the use of AI to improve any health outcome(s) in neonatal and pediatric intensive care.

DATA SOURCE

PubMed, IEEE Xplore, Cochrane, and Web of Science databases.

STUDY SELECTION

We used peer-reviewed studies published between June 1, 2010, and May 31, 2020, in which researchers described (1) AI, (2) pediatrics, and (3) intensive care. Studies were included if researchers assessed AI use to improve at least 1 health outcome (eg, mortality).

DATA EXTRACTION

Data extraction was conducted independently by 2 researchers. Articles were categorized by direct or indirect impact of AI, defined by the European Institute of Innovation and Technology Health joint report.

RESULTS

Of the 287 publications screened, 32 met inclusion criteria. Approximately 22% (n = 7) of studies revealed a direct impact and improvement in health outcomes after AI implementation. Majority were in prototype testing, and few were deployed into an ICU setting. Among the remaining 78% (n = 25) AI models outperformed standard clinical modalities and may have indirectly influenced patient outcomes. Quantitative assessment of health outcomes using statistical measures, such as area under the receiver operating curve (56%; n = 18) and specificity (38%; n = 12), revealed marked heterogeneity in metrics and standardization.

CONCLUSIONS

Few studies have revealed that AI has directly improved health outcomes for pediatric critical care patients. Further prospective, experimental studies are needed to assess AI's impact by using established implementation frameworks, standardized metrics, and validated outcome measures.

Engaging veteran stakeholders to identify patient-centred research priorities for optimizing implementation of lung cancer screening

BACKGROUND

Patient engagement in research agenda setting is increasingly being seen as a strategy to improve the responsiveness of healthcare to patient priorities. Implementation of low-dose computed tomography (LDCT) screening for lung cancer is suboptimal, suggesting that research is needed.

OBJECTIVES

This study aimed to describe an approach by which a Veteran patient group worked with other stakeholders to develop a research agenda for LDCT screening and to describe the research questions that they prioritized.

METHODS

We worked with Veterans organizations to identify 12 Veterans or family members at risk for or having experience with lung cancer to form a Patient Advisory Council (PAC). The PAC met repeatedly from June 2018 to December 2020, both independently and jointly, with stakeholders representing clinicians, health administrators and researchers to identify relevant research topics. The PAC prioritized these topics and then identified questions within these areas where research was needed using an iterative process. Finally, they ranked the importance of obtaining answers to these questions.

RESULTS

PAC members valued the co-learning generated by interactions with stakeholders, but emphasized the importance of facilitation to avoid stakeholders dominating the discussion. The PAC prioritized three broad research areas-(1) the impact of insurance on uptake of LDCT; (2) how best to inform Veterans about LDCT; and (3) follow-up and impact of screening results. Using these areas as guides, PAC members identified 20 specific questions, ranking as most important (1) innovative outreach methods, (2) the impact of screening on psychological health, and (3) the impact of outsourcing scans from VA to non-VA providers on completion of recommended follow-up of screening results. The latter two were not identified as high priority by the stakeholder group.

CONCLUSIONS

We present an approach that facilitates co-learning between Veteran patients and providers, researchers and health system administrators to increase patient confidence in their ability to contribute important information to a research agenda. The research questions prioritized by the Veterans who participated in this project illustrate that for this new screening technology, patients are concerned about the practical details of implementation (e.g., follow-up) and the technology's impact on quality of life.

PATIENT OR PUBLIC CONTRIBUTION

Veterans and Veteran advocates contributed to our research team throughout the entire research process, including conceiving and co-authoring this manuscript.

Impact of Pre-visit Contextual Data Collection on Patient-Physician Communication and Patient Activation: a Randomized Trial

BACKGROUND

Patient contextual data (PCD) are often missing from electronic health records, limiting the opportunity to incorporate preferences and life circumstances into care. Engaging patients through tools that collect and summarize such data may improve communication and patient activation. However, differential tool adoption by race might widen health care disparities.

OBJECTIVE

Determine if a digital tool designed to collect and present PCD improves communication and patient activation; secondarily, evaluate if use impacts outcomes by race.

DESIGN, SETTING, AND PARTICIPANTS

A pragmatic, two-armed, non-blinded, randomized controlled trial conducted during 2019 in a primary care setting.

INTERVENTION

The PCD tool (PatientWisdom) invited patients to identify preferences, values, goals, and barriers to care. Patients were randomized to a standard pre-visit email or facilitated enrollment with dedicated outreach to encourage use of the tool.

MAIN OUTCOMES AND MEASURES

Outcomes of interest were post-visit patient communication and patient activation measured by the Communication Assessment Tool (CAT) and Patient Activation Measure (PAM), respectively. Outcomes were evaluated using treatment-on-the-treated (TOT) and intention-to-treat (ITT) principles.

KEY RESULTS

A total of 301 patients were enrolled. Facilitated enrollment resulted in a five-fold increase in uptake of the PCD tool. TOT analysis indicated that the PCD tool was associated with notable increases in specific CAT items rated as excellent: "treated me with respect" (+ 13 percentage points; p = 0.04), "showed interest in my ideas" (+ 14 percentage points; p = 0.03), "showed care and concern" (+ 16 percentage points; p = 0.02), and "spent about the right amount of time with me" (+ 11 percentage points; p = 0.05). There were no significant pre/post-visit differences in PAM scores between arms (- 4.41 percentage points; p = 0.58). ITT results were similar. We saw no evidence of the treatment effect varying by race in ITT or TOT analyses.

CONCLUSIONS AND RELEVANCE

The inclusion of PCD enhanced essential aspects of patient-provider communication but did not affect patient activation. Outcomes did not differ by race.

TRIAL REGISTRATION

Clincaltrials.gov identifier: NCT03766841.

Adapting the design of a Web-based decision support clinical trial during the COVID-19 pandemic

BACKGROUND

The public health crises that emerged in the COVID-19 pandemic significantly impacted the provision of medical care and placed sudden restrictions on ongoing clinical research. Patient-facing clinical research confronted unique challenges in which recruitment and study protocols were halted and then adapted to meet safety procedures during the pandemic. Our study protocol included the use of a Lung Cancer Screening Decision Tool (LCSDecTool) in the context of a primary care visit and was considerably impacted by the pandemic. We describe our experience adapting a multi-site clinical trial of the LCSDecTool within the Department of Veterans Affairs Health Care System. We conducted a randomized controlled trial (RCT) comparing the LCSDecTool to a control intervention. Outcomes included lung cancer screening (LCS) knowledge, shared decision-making, and uptake and adherence to LCS protocol. We identified three strategies that led to the successful adaptation of the study design during the pandemic: (1) multi-level coordination and communication across the organization and study sites, (2) flexibility and adaptability in research during a time of uncertainty and changes in regulation, and (3) leveraging technology to deliver the intervention and conduct study visits, which raised issues concerning equity and internal and external validity.

CONCLUSION

Our experience highlights strategies successfully employed to adapt an intervention and behavioral research study protocol during the COVID-19 pandemic. This experience will inform clinical research moving forward both during and subsequent to the constraints placed on research and clinical care during the COVID-19 pandemic.

Impact of using wearable devices on psychological Distress: Analysis of the health information national Trends survey

AIM

This study explores the possible impact of wearables on psychological distress and their implications on designs.

METHOD

The study conceptualizes and tests two exploratory models by analyzing the US-based Health Information National Trends Survey of 2019 and 2020. Six variants from the databases were used in the study as predictors. We used models 4 and 6 of the Hayes PROCESS macros to test our conceptual parallel and sequential mediation models, respectively.

RESULTS

The finding indicates significant and negative indirect effects of 'Use of wearable device' on 'Psychological distress.' In parallel mediation models, 'self-care' and 'health perception' were noted to be significant mediators. Wearable devices were associated with improved 'Health perception,' 'Self-care,' and longer 'workout duration,', which in turn helped reduce 'psychological distress' (better mental health). The sequential mediation model captured the indirect effect of 'Use of wearable device' on 'Psychological distress' when sequentially mediated by 'workout duration,' 'BMI,' 'self-care,' and 'health perception' in the given order.

CONCLUSION

As the adoption of digital wearables is increasing due to their growing potential to augment physiological and psychosocial health, it is critical that these technologies are designed to address the needs of users from diverse backgrounds (race, education level, age).

Mobile health technology to improve maternal health awareness in tribal populations: mobile for mothers

Mobile health (mHealth) applications have the potential to improve health awareness. This study reports a quasi-controlled intervention to augment maternal health awareness among tribal pregnant mothers through the mHealth application. Households from 2 independent villages with similar socio-demographics in tribal regions of India were selected as intervention (Village A) and control group (Village B). The control group received government mandated programs through traditional means (orally), whereas the intervention group received the same education through mHealth utilization. Postintervention, awareness about tetanus injections and consumption of iron tablets was significantly (P < .001) improved in the intervention group by 55% and 58%, respectively. Awareness about hygiene significantly (P < .001) increased by 57.1%. In addition, mothers in the intervention group who recognized vaginal bleeding, severe abdominal pain, severe blurring of vision, or convulsions as danger signs during pregnancy significantly (P < .001) increased by 18.30%, 23.2%, 20.0%, and 4.90%, respectively. Our study indicates that despite the low literacy of users, mHealth intervention can improve maternal health awareness among tribal communities.

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

BACKGROUND

Despite advancements in artificial intelligence (AI) to develop prediction and classification models, little research has been devoted to real-world translations with a user-centered design approach. AI development studies in the health care context have often ignored two critical factors of ecological validity and human cognition, creating challenges at the interface with clinicians and the clinical environment.

OBJECTIVE

The aim of this literature review was to investigate the contributions made by major human factors communities in health care AI applications. This review also discusses emerging research gaps, and provides future research directions to facilitate a safer and user-centered integration of AI into the clinical workflow.

METHODS

We performed an extensive mapping review to capture all relevant articles published within the last 10 years in the major human factors journals and conference proceedings listed in the "Human Factors and Ergonomics" category of the Scopus Master List. In each published volume, we searched for studies reporting qualitative or quantitative findings in the context of AI in health care. Studies are discussed based on the key principles such as evaluating workload, usability, trust in technology, perception, and user-centered design.

RESULTS

Forty-eight articles were included in the final review. Most of the studies emphasized user perception, the usability of AI-based devices or technologies, cognitive workload, and user's trust in AI. The review revealed a nascent but growing body of literature focusing on augmenting health care AI; however, little effort has been made to ensure ecological validity with user-centered design approaches. Moreover, few studies (n=5 against clinical/baseline standards, n=5 against clinicians) compared their AI models against a standard measure.

CONCLUSIONS

Human factors researchers should actively be part of efforts in AI design and implementation, as well as dynamic assessments of AI systems' effects on interaction, workflow, and patient outcomes. An AI system is part of a greater sociotechnical system. Investigators with human factors and ergonomics expertise are essential when defining the dynamic interaction of AI within each element, process, and result of the work system.

Exploring the Role of the Internet, Care Quality and Communication in Shaping Mental Health: An Analysis of the Health Information National Trends Survey

Determinants of user mental health are diverse, interrelated, and often multifaceted. This study explores how internet use, perceived care quality, patient education, and patient centered communication influence mental health, using structural equation modeling. Findings suggest that increased internet use even for health purposes negatively impacts mental health (= -0:087; = -0:065; P < 0:001). On the other hand, education level, patient centered-communication (PC-Com) and perception of care quality impact mental health positively (= 0:082; = 0:146; = 0:077; P < 0:001; respectively). Moreover, we also explored the changes across various demographics. The influence of patient education on PC-Com was only significant for Hispanic respondents (= -0:160; P < 0:001). Internet use for health purposes influenced P C-Com negatively for White American respondents (= -0:047; P = 0:015). The study reinstated that the internet use, patient centered communication, patient education, and perceived care quality might influence mental health. The society will increasingly seek health information from online sources, so our study provides recommendations to make online health information sources more user friendly and trustworthy, ultimately to minimize negative impact on mental health.

How clinician-patient communication affects trust in health information sources: Temporal trends from a national cross-sectional survey

Background

Understanding patients’ trust in health information sources is critical to designing work systems in healthcare. Patient-centered communication during the visit might be a major factor in shaping patients’ trust in information sources.

Objective

The purpose of this paper is to explore relationships between patient ratings of clinician communication during the visit and patient trust in health information sources.

Methodology

We conducted a secondary analysis of the nationally-representative Health Information National Trends Surveys; HINTS4 Cycle1 (2011), HINTS4 Cycle4 (2014), and HINTS5 Cycle1 (2017), and HINTS5 Cycle2 (2018). We created a composite score of patient-centered communication from five questions and dichotomized at the median. We created multivariable logistic regression models to see how patient-centered communication influenced trust in different information sources across cycles. Consecutively, we used hierarchical analysis for aggregated data.

Results

We analyzed data from 14,425 individuals. In the adjusted logistic models for each cycle and the hierarchical model, clinicians’ perceived patient-centered communication skills were significantly associated with increased trust in the clinicians as an information source.

Conclusion

Clinicians still represent an essential source of trustworthy information reinforced by patient-centered communication skills. Given that trust helps build healing relationships that lead to better healthcare outcomes, communication sets an essential foundation to establish necessary trust. Interpreting information from the internet sources for patients is likely to remain a vital clinician function.

Online Medical Record Nonuse Among Patients: Data Analysis Study of the 2019 Health Information National Trends Survey

BACKGROUND

Online medical records are being used to organize processes in clinical and outpatient settings and to forge doctor-patient communication techniques that build mutual understanding and trust.

OBJECTIVE

We aimed to understand the reasons why patients tend to avoid using online medical records and to compare the perceptions that patients have of online medical records based on demographics and cancer diagnosis.

METHODS

We used data from the Health Information National Trends Survey Cycle 3, a nationally representative survey, and assessed outcomes using descriptive statistics and chi-square tests. The patients (N=4328) included in the analysis had experienced an outpatient visit within the previous 12 months and had answered the online behavior question regarding their use of online medical records.

RESULTS

Patients who were nonusers of online medical records consisted of 58.36% of the sample (2526/4328). The highest nonuser rates were for patients who were Hispanic (460/683, 67.35%), patients who were non-Hispanic Black (434/653, 66.46%), and patients who were older than 65 years (968/1520, 63.6%). Patients older than 65 years were less likely to use online medical records (odds ratio [OR] 1.51, 95% CI 1.24-1.84, P<.001). Patients who were White were more likely to use online medical records than patients who were Black (OR 1.71, 95% CI 1.43-2.05, P<.001) or Hispanic (OR 1.65, 95% CI 1.37-1.98, P<.001). Patients who were diagnosed with cancer were more likely to use online medical records compared to patients with no cancer (OR 1.31, 95% CI 1.11-1.55, 95% CI 1.11-1.55, P=.001). Among nonusers, older patients (≥65 years old) preferred speaking directly to their health care providers (OR 1.76, 95% CI 1.35-2.31, P<.001), were more concerned about privacy issues caused by online medical records (OR 1.79, 95% CI 1.22-2.66, P<.001), and felt uncomfortable using the online medical record systems (OR 10.55, 95% CI 6.06-19.89, P<.001) compared to those aged 18-34 years. Patients who were Black or Hispanic were more concerned about privacy issues (OR 1.42, 1.09-1.84, P=.007).

CONCLUSIONS

Studies should consider social factors such as gender, race/ethnicity, and age when monitoring trends in eHealth use to ensure that eHealth use does not induce greater health status and health care disparities between people with different backgrounds and demographic characteristics.

How technology impacts communication between cancer patients and their health care providers: A systematic literature review

OBJECTIVE

To ensure the well-being of their patients, health care providers (HCPs) are putting more effort into the quality of the communication they provide in oncology clinics. With the emergence of Health Information Technology (HIT), the dynamics between doctors and patients in oncology settings have changed. The purpose of this literature review is to explore and demonstrate how various health information technologies impact doctor-patient communication in oncology settings.

METHOD

A systematic literature review was conducted in 4 databases (PubMed, Cochrane, Web of Science, IEEE Xplore) to select publications that are in English, published between January 2009 and September 2020. This review reports outcomes related to the impacts of using health information technologies on doctor-patient communication according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Reviews and Meta-Analysis guidelines (PRISMA).

RESULTS

We identified 31 studies which satisfied the selection and eligibility criteria. The review revealed a diverse range of HIT used to support communication between cancer patients and their HCPs in oncology settings. Outcomes related to communication were examined to demonstrate how technology can improve access to care in clinical settings and online. When technology is used effectively to support patient knowledge and shared understanding, this increases the patient's satisfaction and ability to manage emotions, make decisions, and progress in their treatment, in addition to increasing social support and building a stronger therapeutic alliance based on shared knowledge and transparency between clinicians and patients.

CONCLUSION

Technology-based solutions can help strengthen the relationship and communication between patients and their doctors. They can empower the patient's well-being, help doctors make better decisions and enhance the therapeutic alliance between them. Thus, using technology to enhance communication in healthcare settings remains beneficial if its use is structured and target oriented. Future studies should focus on comparing in-depth the difference between outpatient and inpatient settings in terms of the efforts required and the extent of the impacts from both clinicians' and cancer patients' perspectives.

When Is a Harm a Harm? Discordance between Patient and Medical Experts' Evaluation of Lung Cancer Screening Attributes

BACKGROUND

A shared decision-making (SDM) process for lung cancer screening (LCS) includes a discussion between clinicians and patients about benefits and potential harms. Expert-driven taxonomies consider mortality reduction a benefit and consider false-positives, incidental findings, overdiagnosis, overtreatment, radiation exposure, and direct and indirect costs of LCS as potential harms.

OBJECTIVE

To explore whether patients conceptualize the attributes of LCS differently from expert-driven taxonomies.

DESIGN

Cross-sectional study with semistructured interviews and a card-sort activity.

PARTICIPANTS

Twenty-three Veterans receiving primary care at a Veterans Affairs Medical Center, 55 to 73 y of age with 30 or more pack-years of smoking. Sixty-one percent were non-Hispanic African American or Black, 35% were non-Hispanic White, 4% were Hispanic, and 9% were female.

APPROACH

Semistructured interviews with thematic coding.

MAIN MEASURES

The proportion of participants categorizing each attribute as a benefit or harm and emergent themes that informed this categorization.

KEY RESULTS

In addition to categorizing reduced lung cancer deaths as a benefit (22/23), most also categorized the following as benefits: routine annual screening (8/9), significant incidental findings (20/23), follow-up in a nodule clinic (20/23), and invasive procedures (16/23). Four attributes were classified by most participants as a harm: false-positive (13/22), overdiagnosis (13/23), overtreatment (6/9), and radiation exposure (20/22). Themes regarding the evaluation of LCS outcomes were 1) the value of knowledge about body and health, 2) anticipated positive and negative emotions, 3) lack of clarity in terminology, 4) underlying beliefs about cancer, and 5) risk assessment and tolerance for uncertainty.

CONCLUSIONS

Anticipating discordance between patient- and expert-driven taxonomies of the benefits and harms of LCS can inform the development and interpretation of value elicitation and SDM discussions.

Prediction for the Risk of Multiple Chronic Conditions Among Working Population in the United States With Machine Learning Models

Objective: Chronic diseases have become the most prevalent and costly health conditions in the healthcare industry, deteriorating the quality of life, adversely affecting the work productivity, and costing astounding medical resources. However, few studies have been conducted on the predictive analysis of multiple chronic conditions (MCC) based on the working population. Results: Seven machine learning algorithms are used to support the decision making of healthcare practitioner on the risk of MCC. The models were developed and validated using checkup data from 451,425 working population collected by the healthcare providers. Our result shows that all proposed models achieved satisfactory performance, with the AUC values ranging from 0.826 to 0.850. Among the seven predictive models, the gradient boosting tree model outperformed other models, achieving an AUC of 0.850. Conclusions: Our risk prediction model shows great promise in automating real-time diagnosis, supporting healthcare practitioners to target high-risk individuals efficiently, and helping healthcare practitioners tailor proactive strategies to prevent the onset or delay the progression of the chronic diseases.

Augmenting patient safety through participation by design - An assessment of dual monitors for patients in the outpatient clinic

BACKGROUND

Patients and physicians engaging together in the electronic health record (EHR) during clinical visits may provide opportunities to both improve patient understanding and reduce medical errors.

OBJECTIVE

To assess the potential impact of a patient EHR display intervention on patient quality and safety. We hypothesized that if patients had a dedicated display with an explicit invitation to follow clinicians in the EHR that this would identify several opportunities to engage patients in their care quality and safety.

MATERIAL AND METHODS

Physician-patient outpatient encounters (24 patients and 8 physicians) were videotaped. Encounters took place in a hospital-based general internal medicine outpatient clinic where physicians and patients had their respective EHR monitors. Following the visits, each patient and physician was interviewed for 30 min to understand their perception of the mirrored-screen setting.

RESULTS

The following 7 themes were identified (a) curiosity, (b) opportunity to ask questions, (c) error identification, (d) control over medications, (e) awareness, (f) shared understanding & decision-making, (g) data privacy. These themes collectively comprised a conceptual model for how patient engagement in electronic health record use, through a dedicated second screen or an explicitly shared screen, relates to safety and quality opportunities. Therefore, the double EHR screen provides an explicit invitation for patients to join the process to influence safety.

CONCLUSION

Desired outcomes include real-time error identification and better-shared understanding and decision-making, leading to better downstream follow-through with care plans.

Use of machine learning in geriatric clinical care for chronic diseases: a systematic literature review

Objectives

Geriatric clinical care is a multidisciplinary assessment designed to evaluate older patients’ (age 65 years and above) functional ability, physical health, and cognitive well-being. The majority of these patients suffer from multiple chronic conditions and require special attention. Recently, hospitals utilize various artificial intelligence (AI) systems to improve care for elderly patients. The purpose of this systematic literature review is to understand the current use of AI systems, particularly machine learning (ML), in geriatric clinical care for chronic diseases.

Materials and Methods

We restricted our search to eight databases, namely PubMed, WorldCat, MEDLINE, ProQuest, ScienceDirect, SpringerLink, Wiley, and ERIC, to analyze research articles published in English between January 2010 and June 2019. We focused on studies that used ML algorithms in the care of geriatrics patients with chronic conditions.

Results

We identified 35 eligible studies and classified in three groups: psychological disorder (n = 22), eye diseases (n = 6), and others (n = 7). This review identified the lack of standardized ML evaluation metrics and the need for data governance specific to health care applications.

Conclusion

More studies and ML standardization tailored to health care applications are required to confirm whether ML could aid in improving geriatric clinical care.

The Impact of Previsit Contextual Data Collection on Patient-Provider Communication and Patient Activation: Study Protocol for a Randomized Controlled Trial

BACKGROUND

Patient-centered care is respectful of and responsive to individual patient preferences, needs, and values. To provide patient-centered care, clinicians need to know and incorporate patients' context into their communication and care with patients. Patient contextual data (PCD) encompass social determinants of health and patients' needs, values, goals, and preferences relevant to their care. PCD can be challenging to collect as a routine component of the time-limited primary care visit.

OBJECTIVE

This study aims to determine if patient-provider communication and patient activation are different for patient users and patient nonusers of an electronic health record (EHR)-integrated PCD tool and assess if the impact of using PCD on patient-provider communication and patient activation differs for Black and White patients.

METHODS

We describe a randomized controlled trial of a prospective cohort of non-Hispanic White and Black patients who receive primary care services at a midwestern academic health care system in the United States. We will evaluate whether providing PCD through a consumer informatics tool enhances patient-provider communication, as measured by the Communication Assessment Tool, and we will evaluate patient activation, as measured by the Patient Activation Measure for PCD tool users and nonusers. Furthermore, owing to racial disparities in care and communication, we seek to determine if the adoption and use of the tool might narrow the differences between patient groups.

RESULTS

The trial was funded in November 2017 and received local ethics review approval in February 2019. The study began recruitment in April 2019 and enrollment concluded in October 2019 with 301 participants. The analysis was completed in May 2020, and trial results are expected to be published in winter 2020.

CONCLUSIONS

Recently, there has been increased attention to the role of health information technology tools to enable patients to collaborate with providers through the sharing of PCD. The adoption of such tools may overcome the barriers of current EHRs by directly engaging patients to submit their contextual data. Effectively, these tools would support the EHR in providing a more holistic understanding of the patient. Research further supports that individuals who have robust digital engagement using consumer informatics tools have higher participation in treatment follow-up and self-care across populations. Therefore, it is critical to investigate interventions that elicit and share patients' social risks and care preferences with the health care team as a mechanism to improve individualized care and reduce the gap in health outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03766841; https://clinicaltrials.gov/ct2/show/NCT03766841.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/20309.

Role of Artificial Intelligence in Patient Safety Outcomes: Systematic Literature Review

BACKGROUND

Artificial intelligence (AI) provides opportunities to identify the health risks of patients and thus influence patient safety outcomes.

OBJECTIVE

The purpose of this systematic literature review was to identify and analyze quantitative studies utilizing or integrating AI to address and report clinical-level patient safety outcomes.

METHODS

We restricted our search to the PubMed, PubMed Central, and Web of Science databases to retrieve research articles published in English between January 2009 and August 2019. We focused on quantitative studies that reported positive, negative, or intermediate changes in patient safety outcomes using AI apps, specifically those based on machine-learning algorithms and natural language processing. Quantitative studies reporting only AI performance but not its influence on patient safety outcomes were excluded from further review.

RESULTS

We identified 53 eligible studies, which were summarized concerning their patient safety subcategories, the most frequently used AI, and reported performance metrics. Recognized safety subcategories were clinical alarms (n=9; mainly based on decision tree models), clinical reports (n=21; based on support vector machine models), and drug safety (n=23; mainly based on decision tree models). Analysis of these 53 studies also identified two essential findings: (1) the lack of a standardized benchmark and (2) heterogeneity in AI reporting.

CONCLUSIONS

This systematic review indicates that AI-enabled decision support systems, when implemented correctly, can aid in enhancing patient safety by improving error detection, patient stratification, and drug management. Future work is still needed for robust validation of these systems in prospective and real-world clinical environments to understand how well AI can predict safety outcomes in health care settings.

Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

Artificial intelligence (AI) can transform health care practices with its increasing ability to translate the uncertainty and complexity in data into actionable—though imperfect—clinical decisions or suggestions. In the evolving relationship between humans and AI, trust is the one mechanism that shapes clinicians’ use and adoption of AI. Trust is a psychological mechanism to deal with the uncertainty between what is known and unknown. Several research studies have highlighted the need for improving AI-based systems and enhancing their capabilities to help clinicians. However, assessing the magnitude and impact of human trust on AI technology demands substantial attention. Will a clinician trust an AI-based system? What are the factors that influence human trust in AI? Can trust in AI be optimized to improve decision-making processes? In this paper, we focus on clinicians as the primary users of AI systems in health care and present factors shaping trust between clinicians and AI. We highlight critical challenges related to trust that should be considered during the development of any AI system for clinical use.

Qualitative Assessment of Unmet Information Management Needs of Informal Cancer Caregivers: Four Themes to Inform Oncology Practice

PURPOSE

Family and friends often provide informal care for patients with cancer, coordinating care and supporting patients at home. Stress, depression, and burnout are increasingly recognized among these informal caregivers. Although past research has described a range of needs, including the need for information, details about unmet informational needs for caregivers have not been fully described. We sought to assess unmet information management needs for informal caregivers in the digital era.

METHODS

This was a qualitative research study with semistructured interviews and focus groups of nonprofessional caregivers for patients with cancer, facilitated using a discussion guide. Eligible caregivers supported patients in the community who were in treatment (chemotherapy or radiotherapy) or completed treatment within 3 years. Participants were recruited using informational flyers at an academic cancer center and in the local community of metropolitan Milwaukee, Wisconsin. Sessions were transcribed verbatim and analyzed inductively to identify themes.

RESULTS

Thirteen caregivers participated, the majority between 41 and 60 years of age: seven of 13, 53.8%, were predominantly women; 10 of 13 (76.9%) were educated, 10 of 13 (76.9%) had graduated from college; and of modest means, six of 13 (46.2%) had household incomes < $35,000. Four themes emerged: (1) the information overload paradox, where caregivers felt overloaded by information yet had unmet informational needs; (2) navigating volatility as a caregiver, with changing or unknown expectations; (3) caregivers as information brokers, which placed new burdens on caregivers to seek, share, and protect information; and (4) care for the caregiver, including unmet information needs related to self-care.

CONCLUSION

This study identified several informational challenges affecting caregivers. Caregivers have dynamic and evolving informational needs, and strategies that support caregivers through just-in-time information availability or dedicated caregiver check-ins may provide relief within the stress of caregiving.

Designing a tablet-based prematurity education app for parents hospitalized for preterm birth

BACKGROUND

As technology has advanced over the last decade, handheld Mobile Health (mHealth) applications have increased in popularity. Pregnancy is one area of mHealth that has rapidly expanded, however very few pregnancy apps are developed in collaboration with health professionals. This creates an environment where the pregnancy information women are accessing may be inaccurate or even dangerous. Additionally, there are relatively few medical apps devoted to prematurity or targeted to women at risk for premature birth. To address the gap in premature birth education, we assembled a multidisciplinary team, including health care professionals, and developed the Preemie Prep for Parents (P3) app.

METHODS

Our team previously conducted 5 focus group meetings to assess the information needs of our target audience. Based on this information we developed a low fidelity P3 prototype. Our software development team transferred the low fidelity prototype into a high fidelity prototype which was hosted on Test Flight (a beta testing platform). We performed heuristic evaluation as well as user testing to improve the P3 app.

RESULTS

User testing of the high fidelity P3 prototype was performed with 13 diverse participants. 6 participants were parents of currently admitted Neonatal Intensive Care Unit (NICU) babies and 7 participants were women who had been or were currently pregnant. The native language of participants included English, Spanish, and Hmong and their educational level varied between completing high school and graduate degree. Participants provided feedback on the content of the P3 app, as well as its organization and aesthetics. The feedback led to 83 iterations of the P3 app prior to its deployment. Overall, participants noted that the information was "informative" and "reliable". They also noted that the P3 app provided control over the information they could view and when they viewed it, stating "I could see info on my time". Overall, participants felt that the P3 app was a valuable tool for mothers in preterm labor and it would help them ask questions.

CONCLUSIONS

Development of a mHealth app provides unique challenges regarding content, reliability of information, organization, and aesthetics. Creation of the P3 app to address the educational needs of women at risk for premature birth required assembling a multidisciplinary team, which included target users, and implementing an iterative design process. The efficacy of this app in improving user knowledge and decreasing anxiety is currently being tested in a randomized controlled trial.

The impact of patient-generated contextual data on communication in clinical practice: A qualitative assessment of patient and clinician perspectives

BACKGROUND

Effective communication is integral to patient-centered care, yet external pressures can impede the ability to discuss important topics. One strategy to facilitate communication is pre-visit collection and sharing of patient contextual data (PCD), including life circumstances such as their beliefs, needs, and concerns.

OBJECTIVE

To understand how patients and care team members perceive the electronic collection of PCD and its impact on communication in the context of a large academic health system that implemented PatientWisdom, a new technology that elicits PCD from patients and integrates within the electronic health record (EHR).

METHODS

We conducted focus groups with patients (n = 26) and semi-structured interviews with primary care team members (n = 20). Qualitative analysis of focus group/interviews included an iterative and reflexive inductive technique to uncover emergent themes.

RESULTS

Four themes were reflected among both patient and care team: (1) the technology enhances the patient's voice; (2) the technology creates a safe space for patients to share sensitive topics; (3) PCD facilitates rapport not only between patient and provider but the entire care team; (4) PCD aligns patient and clinician goals. Two unique themes emerged among patients: (1) PCD provides opportunity for reflection; (2) PCD humanizes patients in the clinical context. One theme was evident in provider comments: collecting PCD may potentially undermine trust if not reviewed by clinical teams.

CONCLUSION

PCD collected directly from patients and available within the EHR was seen by patients and care team members as beneficial to communication. PCD collection supports a paradigm shift towards coproduction of health information and a shared responsibility for information gathering but requires investment from patients and care team to ensure the data are effectively utilized.

PRACTICE VALUE

PCD may be useful for team-based care, enabling physicians and non-physician staff to more quickly and responsively connect with patients.

Patient-Care Team Contact Patterns Impact Treatment Length of Stay in the Emergency Department

Real-time location systems (RTLS) has found extensive application in the healthcare setting, that is shown to improve safety, save cost, and increase patient satisfaction. More specifically, some studies have shown the efficacy of RTLS leading to an improved workflow in the emergency department. However, due to substantial implementation costs of such technologies, hospital administrators show reluctance in RTLS adoption. Our previous preliminary studies with RFID data in the emergency department (ED) demonstrated for the first time the quantification of `patient alone time' and its relationship to outcomes such as 30-day hospitalization. In this study, we use ED RTLS data to analyze patient-care team contact time (PCTCT) and its relationship to the total treatment length of stay (LOS) in ED. An observational cohort study was performed in the ED using RTLS data from Jan 17 - Sep 17, 2017, which included a total of 51,697 patients. PCTCT within the first hour of a patient's placement in a treatment bed was calculated and its relationship to treatment LOS was analyzed while controlling for confounding factors affecting treatment LOS. Results show that treatment LOS is highly correlated with the ED crowding captured by the patient-perprovider ratio, negatively correlated to the physician and resident visit frequency, and positively correlated to nurse visit frequency. The results can inform designing new guidelines for ideal patient-care team interactions and be used to determine optimal ED staffing levels and care team composition for effective care delivery.

Community Breast Health Education for Immigrants and Refugees: Lessons Learned in Outreach Efforts to Reduce Cancer Disparities

Community-academic partnerships are vital to address cancer disparities in geographic areas with diverse socioeconomic, language, and cultural barriers. Regarding breast health, immigrant and refugee women are a particularly vulnerable population, with considerably lower mammography rates than most communities, including racial and ethnic minorities. To promote health care equity in this high-risk population, we developed a community-academic partnership (CAP) model to promote breast health education at community faith-based centers in the city of Milwaukee, WI. In this paper, we describe the success of our partnerships, our lessons learned, and future directions.

Oncologists' Views Regarding the Role of Electronic Health Records in Care Coordination

BACKGROUND

Electronic health records (EHRs) play a significant role in complex health care processes, especially in information transfer with patients and care coordination among providers. EHRs may also generate unintended consequences, introducing new patient safety risks. To date, little investigation has been performed in oncology settings, despite the need for quality provider-patient communication and information transfer during oncology visits. In this qualitative study, we focused on oncology providers' perceptions of EHRs for supporting communication with patients and coordination of care with other providers.

METHODS

We conducted semistructured interviews with oncologists from an urban academic medical center to learn their perceptions of the use of EHRs before, during, and after clinic visits with patients. Our interview guide was developed on the basis of the work system model. We coded transcripts using inductive content analysis.

RESULTS

Data analysis yielded four main themes regarding oncologists' practices in using the EHR and perceptions about EHRs: (1) EHR use for care coordination (eg, timeliness of receiving information, SmartSet documentation); (2) EHR use in the clinic visit (eg, educating patients, using as a reinforcement tool); (3) safety hazards in care coordination associated with EHRs (eg, incomplete documentation, error propagating, no filtering mechanism to capture errors); and (4) suggestions for improvements (eg, improved SmartSet functionalities, simplification of user interface).

CONCLUSION

Current EHRs do not adequately support teamwork of oncology providers, which could lead to potential hazards in the care of patients with cancer. Redesigning EHR features that are tailored to support oncology care and addressing the concerns regarding information overload, improved organization of flagging abnormal results, and documentation-related workload are needed to minimize potential safety hazards.

Virtual Surgery for the Nasal Airway: A Preliminary Report on Decision Support and Technology Acceptance

Importance

Nasal airway obstruction (NAO) is a common problem that affects patient quality of life. Surgical success for NAO correction is variable. Virtual surgery planning via computational fluid dynamics (CFD) has the potential to improve the success rates of NAO surgery.

Objective

To elicit surgeon feedback of a virtual surgery planning tool for NAO and to determine if this tool affects surgeon decision making.

Design, Setting, and Participants

For this cross-sectional study, 60-minute face-to-face interviews with board-certified otolaryngologists were conducted at a single academic otolaryngology department from September 16, 2016, through October 7, 2016. Virtual surgery methods were introduced, and surgeons were able to interact with the virtual surgery planning tool interface. Surgeons were provided with a patient case of NAO, and open feedback of the platform was obtained, with emphasis on surgical decision making.

Main Outcomes and Measures

Likert scale responses and qualitative feedback were collected for the virtual surgery planning tool and its influence on surgeon decision making.

Results

Our 9 study participants were all male, board-certified otolaryngologists with a mean (range) 15 (4-28) number of years in practice and a mean (range) number of nasal surgeries per month at 2.2 (0.0-6.0). When examined on a scale of 1 (not at all) to 5 (completely), surgeon mean (SD) score was 3.4 (0.5) for how realistic the virtual models were compared with actual surgery. On the same scale, when asked how much the virtual surgery planning tool changed surgeon decision making, mean (SD) score was 2.6 (1.6). On a scale of 1 (strongly disagree) to 7 (strongly agree), surgeon scores for perceived usefulness of the technology and attitude toward using it were 5.1 (1.1) and 5.7 (0.9), respectively.

Conclusions and Relevance

Our study shows positive surgeon experience with a virtual surgery planning tool for NAO based on CFD simulations. Surgeons felt that future applications and areas of study of the virtual surgery planning tool include its potential role for patient counseling, selecting appropriate surgical candidates, and identifying which anatomical structures should be targeted for surgical correction.

Level of Evidence

NA.

Incorporating patient-generated contextual data into care: Clinician perspectives using the Consolidated Framework for Implementation Science

Patient contextual data (PCD), defined as patient's values, environment, or behavior influencing health, are essential to the proper care of patients, yet often are missing in the electronic health record (EHR). The current EHR structures and practice demands produce barriers to document PCD systemically. We sought to understand clinicians' perceived facilitators and barriers to use PCD using a consumer informatics technology integrated into the EHR. The PCD components include patient perceived pressures; joys; preferred approach to care; perceived health; health-goals; and visit agenda. We conducted semi-structured interviews of twenty primary care clinicians from an academic health system implementing a PCD initiative. The analysis included an inductive approach and a deductive a priori framework, the Consolidated Framework for Implementation Research (CFIR). Clinicians identified the following facilitators of adoption: reinforcement of patient engagement; a focus on enhancing team-based care; and communication around how the tool can be incorporated for individualized care. Clinicians identified barriers as: challenges incorporating PCD into the time-compressed visit and reviewing the tool involved another click in the EHR. The deductive results spanned four domains and seven constructs of CFIR, principally finding intervention source, relative advantage, organizational needs, and relative priority as facilitators with a need for ongoing leadership for the culture change. Overall, clinicians supported the adoption of a consumer informatics technology, as they reflected on the perceived value of a new data source to enhance patient-centered care and involvement in the development process. User-focused optimization efforts aided in the improved functionality and adoption of the application.

Parental Perceptions of Displayed Patient Data in a PICU: An Example of Unintentional Empowerment

OBJECTIVES

To explore the perceptions of parents of pediatric patients in a PICU regarding real-time open electronic health record data displayed in patient rooms.

DESIGN

Cross-sectional qualitative interview study.

SETTING

PICU in a large Midwestern tertiary-care children's hospital.

SUBJECTS

Parents of patients in a PICU (n = 33).

MEASUREMENTS AND MAIN RESULTS

Qualitative data were collected through in-person semi-structured, individual, and small-group interviews. Data were collected from March 2016 to July 2016, with approval from the study hospital's institutional review board. Data were analyzed using inductive thematic analysis. Results included positive effects of accessing real-time open electronic health record data on family empowerment, situation awareness, potential error detection, understanding of medical data, and facilitating discussions during rounds. Concerns were reported regarding privacy of information as well as potential misinterpretation of displayed data. We identified several ways to improve this collaborative technology to make it more family-centered.

CONCLUSIONS

This study suggests that a new health information technology system providing continuous access to open electronic health record data may be an effective way to empower and engage parents in the PICU, but potential drawbacks were also noted. The results also provide insights into the collaborative use of health information technology in the PICU setting.