University of California, Irvine

We are pleased to introduce the collection Frontiers in Digital Health – Highlights in Human Factors and Digital Health 2021/22. This collection will welcome and showcase a selection of high impact articles authored by leaders in the field. The work presented here highlights the broad diversity of research performed across the Human Factors and Digital Health section, and aims to put a spotlight on the main areas of interest. This collection aims to further support Frontiers’ strong community by shining a spotlight on our authors' highly impactful research. Dr. Raj Ratwani serves as the vice president of scientific affairs for MedStar Health Research Institute and the director of the MedStar Health National Center for Human Factors in Healthcare. Dr. Kapil Chalil Madathil is Director of the Center for Workforce Development.

MedStar Health Research Institute (MHRI)

Clemson University

Frontiers in Digital Health

Human Factors and Digital Health

Highlights in Human Factors and Digital Health 2021/22

Background and ObjectivesChildren with congenital heart disease (CHD), have fragile hemodynamics and can deteriorate due to common childhood illnesses and the natural progression of their disease. During these acute periods of deterioration, these children often present to their local emergency departments (ED) where expertise in CHD is limited, and appropriate intervention is crucial to their survival. Previous studies identified that determining the appropriate intervention for CHD patients can be difficult for ED physicians, particularly since key components of effective decision making are not being met. Although key components of effective decision making for ED physicians have been identified, they have yet to be transformed into actionable guidance. We used decision centered design (DCD) to translate key components of decision making into decision requirements and associated design concepts, that we subsequently incorporated into a prototype clinical decision support system (CDSS).</sec>MethodsUsing framework analysis, transcripts from Critical Decision Method interviews of CHD experts and ED physicians were inductively coded to identify key decision requirements for ED physicians that are currently not well supported, and their associated design concepts. A design workshop was held to refine the identified key decision requirements and design concepts as well as to sketch information that would satisfy the identified requirements. These were iteratively incorporated into a prototype CDSS.</sec>ResultsThree decision requirements: (1) distinguish the patient's unique physiology based on their unique cardiac anatomy, (2) explicitly consider CHD specific differential diagnoses to allow a more structured reflection of diagnosis, and (3) select CHD appropriate interventions for each patient, were identified. These requirements along with design concepts and information needs identified through the design workshop were incorporated into the CDSS prototype.</sec>ConclusionWe identified key decision requirements and associated design concepts, that informed the design of a CDSS to provide actionable guidance for ED physicians when managing CHD patients. Meeting ED physicians' decision components with a CDSS requires the translation of their key decision requirements in its design. If not, we risk creating designs that interfere with clinician performance.</sec>

Background and Objectives: Children with congenital heart disease (CHD), have fragile hemodynamics and can deteriorate due to common childhood illnesses and the natural progression of their disease. During these acute periods of deterioration, these children often present to their local emergency departments (ED) where expertise in CHD is limited, and appropriate intervention is crucial to their survival. Previous studies identified that determining the appropriate intervention for CHD patients can be difficult for ED physicians, particularly since key components of effective decision making are not being met. Although key components of effective decision making for ED physicians have been identified, they have yet to be transformed into actionable guidance. We used decision centered design (DCD) to translate key components of decision making into decision requirements and associated design concepts, that we subsequently incorporated into a prototype clinical decision support system (CDSS).Methods: Using framework analysis, transcripts from Critical Decision Method interviews of CHD experts and ED physicians were inductively coded to identify key decision requirements for ED physicians that are currently not well supported, and their associated design concepts. A design workshop was held to refine the identified key decision requirements and design concepts as well as to sketch information that would satisfy the identified requirements. These were iteratively incorporated into a prototype CDSS.Results: Three decision requirements: (1) distinguish the patient's unique physiology based on their unique cardiac anatomy, (2) explicitly consider CHD specific differential diagnoses to allow a more structured reflection of diagnosis, and (3) select CHD appropriate interventions for each patient, were identified. These requirements along with design concepts and information needs identified through the design workshop were incorporated into the CDSS prototype.Conclusion: We identified key decision requirements and associated design concepts, that informed the design of a CDSS to provide actionable guidance for ED physicians when managing CHD patients. Meeting ED physicians' decision components with a CDSS requires the translation of their key decision requirements in its design. If not, we risk creating designs that interfere with clinician performance.

Decision-centered design of a clinical decision support system for acute management of pediatric congenital heart disease

Advance directives allow people to declare their treatment preferences for a potential future state of incompetency. Covid-19, with its high numbers of quickly deteriorating patients requiring intensive care, has acutely demonstrated how helpful it would be for clinicians to have reliable, readily available, up-to-date information at hand to be able to act in accordance with what the individual patient would have wanted. Yet for the past few decades advance directives have fallen short of their potential, for various reasons. At worst, advance directives are perceived as unwieldy legal documents that put excessive demands on patients without providing useful guidance for better care. Recent efforts such as advance care planning have tried to remedy some of these shortcomings but have so far met with limited success. We suggest a new concept—the Advance Care Compass—that harnesses the potential of digitalization in healthcare to overcome many of difficulties encountered so far.

Advance directives allow people to declare their treatment preferences for a potential future state of incompetency. Covid-19, with its high numbers of quickly deteriorating patients requiring intensive care, has acutely demonstrated how helpful it would be for clinicians to have reliable, readily available, up-to-date information at hand to be able to act in accordance with what the individual patient would have wanted. Yet for the past few decades advance directives have fallen short of their potential, for various reasons. At worst, advance directives are perceived as unwieldy legal documents that put excessive demands on patients without providing useful guidance for better care. Recent efforts such as advance care planning have tried to remedy some of these shortcomings but have so far met with limited success. We suggest a new concept&#x2014;the Advance Care Compass&#x2014;that harnesses the potential of digitalization in healthcare to overcome many of difficulties encountered so far.

The Advance Care Compass– A New Mechanics for Digitally Transforming Advance Directives

Objective: The purpose of this study was to evaluate the variations in electronic health record (EHR) activity among General and Specialty pediatricians by investigating the time spent and documentation length, normalized for workload.Materials and Methods: We conducted a cross-sectional study of pediatric physicians using Epic EHR at a major Southeastern academic healthcare system. We collected user-level EHR activity data of 104 pediatric physicians over 91 days from April 1 to June 30, 2020.Results: Of the 104 pediatrics physicians, 56 (54%) were General pediatricians and 48 (46%) were Specialists pediatricians. General pediatricians spent an average of 17.6 min [interquartile range (IQR): 12.9–37] using the EHR per appointment, while Specialists spent 35.7 min (IQR: 28–48.4) per appointment.Significant negative associations were found between proficiency scores and the amount of time spent in the system for Generalists (p < 0.001). On the contrary, significant positive associations were found between proficiency scores and the amount of time spent in the system for Specialists (p < 0.01).Conclusions: We report an association between EHR proficiency and efficiency levels among pediatricians within the same healthcare system, receiving the same EHR training, and using the same EHR system. The profound differences in EHR activity suggest that higher priority should be given to redesigning EHR training methods to accommodate the learning needs of physicians.

Objective: The purpose of this study was to evaluate the variations in electronic health record (EHR) activity among General and Specialty pediatricians by investigating the time spent and documentation length, normalized for workload.Materials and Methods: We conducted a cross-sectional study of pediatric physicians using Epic EHR at a major Southeastern academic healthcare system. We collected user-level EHR activity data of 104 pediatric physicians over 91 days from April 1 to June 30, 2020.Results: Of the 104 pediatrics physicians, 56 (54%) were General pediatricians and 48 (46%) were Specialists pediatricians. General pediatricians spent an average of 17.6 min [interquartile range (IQR): 12.9–37] using the EHR per appointment, while Specialists spent 35.7 min (IQR: 28–48.4) per appointment.Significant negative associations were found between proficiency scores and the amount of time spent in the system for Generalists (p &lt; 0.001). On the contrary, significant positive associations were found between proficiency scores and the amount of time spent in the system for Specialists (p &lt; 0.01).Conclusions: We report an association between EHR proficiency and efficiency levels among pediatricians within the same healthcare system, receiving the same EHR training, and using the same EHR system. The profound differences in EHR activity suggest that higher priority should be given to redesigning EHR training methods to accommodate the learning needs of physicians.

Association Between Proficiency and Efficiency in Electronic Health Records Among Pediatricians at a Major Academic Health System

Objective: We investigated use and clinical outcomes in a digital musculoskeletal (MSK) program, by generation.Method: This longitudinal study uses retrospective data collected online or by app. The study included adults with 12 or more weeks of pain who took part in a digital MSK program. We compared Gen Z and Millennials, Gen X, working age Baby Boomers, and retiree age Baby Boomer and Silent Generation. Program use outcomes were program start, program completion, and number of exercises, educational articles, and messages to coaches. Clinical outcomes were changes in pain, depression, and anxiety from baseline to 12 weeks. We calculated descriptive statistics and conducted adjusted regression models.Results: Odds of starting the program were significantly higher for Gen Xers (OR: 1.12) and working age Baby Boomers (OR: 1.37) vs. Gen Zers and Millennials. Compared to Gen Zers and Millennials, we observed significantly higher odds of program completion among Gen Xers (OR: 1.62), working age Baby Boomers (OR: 2.24), and retirees (OR: 2.36). Compared to Gen Zers and Millennials, retirees had 19 more exercise sessions (IRR: 1.69), accessed 11 more articles (IRR: 1.84), and sent 4 more messages to coaches (IRR: 1.26). Compared to Gen Z and Millennials, we observed no significant differences in change in pain for Gen Xers, working age Baby Boomers, or retirees.Conclusions: Adults from multiple generations took part in a digital MSK program. Findings suggest that older generations used a digital MSK program more than younger generations, but had similar pain outcomes.

Objective: We investigated use and clinical outcomes in a digital musculoskeletal (MSK) program, by generation.Method: This longitudinal study uses retrospective data collected online or by app. The study included adults with 12 or more weeks of pain who took part in a digital MSK program. We compared Gen Z and Millennials, Gen X, working age Baby Boomers, and retiree age Baby Boomer and Silent Generation. Program use outcomes were program start, program completion, and number of exercises, educational articles, and messages to coaches. Clinical outcomes were changes in pain, depression, and anxiety from baseline to 12 weeks. We calculated descriptive statistics and conducted adjusted regression models.Results: Odds of starting the program were significantly higher for Gen Xers (OR: 1.12) and working age Baby Boomers (OR: 1.37) vs. Gen Zers and Millennials. Compared to Gen Zers and Millennials, we observed significantly higher odds of program completion among Gen Xers (OR: 1.62), working age Baby Boomers (OR: 2.24), and retirees (OR: 2.36). Compared to Gen Zers and Millennials, retirees had 19 more exercise sessions (IRR: 1.69), accessed 11 more articles (IRR: 1.84), and sent 4 more messages to coaches (IRR: 1.26). Compared to Gen Z and Millennials, we observed no significant differences in change in pain for Gen Xers, working age Baby Boomers, or retirees.Conclusions: Adults from multiple generations took part in a digital MSK program. Findings suggest that older generations used a digital MSK program more than younger generations, but had similar pain outcomes.

Older Adult Use and Outcomes in a Digital Musculoskeletal (MSK) Program, by Generation

People with suicidal ideation and non-suicidal self-injury (NSSI) behavior face numerous barriers to help-seeking, which worsened during the COVID-19 pandemic. Mobile health applications (MHA) are discussed as one solution to improve healthcare. However, the commercial app markets are growing unregulated and rapidly, leading to an inscrutable market. This study evaluates the quality, features, functions, and prevention strategies of MHA for people with suicidal ideation and NSSI. An automatic search engine identified MHA for suicidal behavior and NSSI in the European commercial app stores. MHA quality and general characteristics were assessed using the Mobile Application Rating Scale (MARS). MHA of high quality (top 25%) were examined in detail and checked for consistency with established suicide prevention strategies. Of 10,274 identified apps, 179 MHA met the predefined inclusion criteria. Average MHA quality was moderate (M = 3.56, SD = 0.40). Most MHA provided emergency contact, but lacked security features. High-quality MHA were broadly consistent with the best-practice guidelines. The search revealed apps containing potentially harmful and triggering content, and no randomized controlled trial of any included MHA was found. Despite a large heterogeneity in the quality of MHA, high-quality MHA for suicidal behavior and NSSI are available in European commercial app stores. However, a lack of a scientific evidence base poses potential threats to users.

People with suicidal ideation and non-suicidal self-injury (NSSI) behavior face numerous barriers to help-seeking, which worsened during the COVID-19 pandemic. Mobile health applications (MHA) are discussed as one solution to improve healthcare. However, the commercial app markets are growing unregulated and rapidly, leading to an inscrutable market. This study evaluates the quality, features, functions, and prevention strategies of MHA for people with suicidal ideation and NSSI. An automatic search engine identified MHA for suicidal behavior and NSSI in the European commercial app stores. MHA quality and general characteristics were assessed using the Mobile Application Rating Scale (MARS). MHA of high quality (top 25%) were examined in detail and checked for consistency with established suicide prevention strategies. Of 10,274 identified apps, 179 MHA met the predefined inclusion criteria. Average MHA quality was moderate (M = 3.56, SD = 0.40). Most MHA provided emergency contact, but lacked security features. High-quality MHA were broadly consistent with the best-practice guidelines. The search revealed apps containing potentially harmful and triggering content, and no randomized controlled trial of any included MHA was found. Despite a large heterogeneity in the quality of MHA, high-quality MHA for suicidal behavior and NSSI are available in European commercial app stores. However, a lack of a scientific evidence base poses potential threats to users.