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Open Access Publications from the University of California

Scholarly Works (15 results)

  • Thesis
  • Peer Reviewed
UC Irvine Electronic Theses and Dissertations (2021)

Health interface technologies enable digital data, information, and knowledge sharing to support the independent and collaborative health work of different entities (e.g., patients, healthcare providers, public health professionals). As healthcare has shifted towards a patient-centered approach, this class of technologies, which includes patient portals, is increasingly being used to facilitate patient participation in their care and patient-provider collaboration. Research suggests that using these technologies may have many positive effects such as increased patient engagement and improved health outcomes.

Unfortunately, despite the potential benefits, adoption and use of these technologies are often lower than expected. One of the primary barriers is that while the typical designs support certain aspects of patients’ and providers’ individual and collaborative work, it often does not support other important facets. This is especially true for patient-facing technologies such as patient portals and Apple Health Records. In addition, the lack of a clear definition of health interface technologies has resulted in a disconnected evidence base across numerous disciplines, including health informatics and human-computer interaction.

Given the significant investments made in these technologies, and their tremendous but underachieved potential, there is an imperative need for multi-disciplinary study of health interface technologies using human-centered approaches. My multi-method dissertation research addresses these needs by deriving insights from four studies focused on empowering patients through electronic access to their medical records. Study 1 is a systematic review of patient and caregiver suggestions for improving patient portals, which provide patients with electronic access to portions of their medical record. Study 2 investigates the extent to which recent U.S. Policy is currently benefiting patients through a review of the smartphone health application (app) landscape, with a particular focus on apps capable of automatically downloading medical records via a standards-based application programming interface. Studies 3 and 4 explore patient’s interaction with their medical records, specifically laboratory test results, through a unique perspective – patient questions containing these data posted to an online health community – to understand how the design of technologies can be improved to better support patients as they view their medical records. Based on the results of these studies, I discuss implications for the design of health interface technologies to support patient work.

    Cover page: Designing Health Interface Technologies to Support Patient WorkCreative Commons 'BY-NC-ND' version 4.0 license
    • Article
    • Peer Reviewed
    UC Irvine Previously Published Works (2022)
    The objective of this study was to investigate the state of the interoperable mobile health application (app) ecosystem at the start of the 21st Century Cures Act to understand the opportunities currently available to patients for accessing and using their computable clinical data. Thus, we sought to identify third-party apps in the Apple App and Google Play Stores that seem to be capable of automatically downloading clinical data via a FHIR-based application programming interface through a targeted review of health apps. We found that few of the apps in this review have this capability (1.4% of 1,272 iOS apps and 0.6% of 1,449 Android apps). Ultimately, our results suggest that this is a nascent marketspace. If barriers to app development are not identified and addressed, and efforts are not made to educate patients and improve discoverability of apps, it could mean that patients will not benefit from these interoperability measures.
      Cover page: Investigating the Interoperable Health App Ecosystem at the Start of the 21st Century Cures Act.
      • Article
      • Peer Reviewed
      UC Irvine Previously Published Works (2019)
        Cover page: Medication safety alert fatigue may be reduced via interaction design and clinical role tailoring: a systematic review
        • Article
        • Peer Reviewed
        UC Irvine Previously Published Works (2017)
        Computerized clinical decision-support systems are members of larger sociotechnical systems, composed of human and automated actors, who send, receive, and manipulate artifacts. Sociotechnical consideration is rare in the literature. This makes it difficult to comparatively evaluate the success of CDS implementations, and it may also indicate that sociotechnical context receives inadequate consideration in practice. To facilitate sociotechnical consideration, we developed the Thinking Together model, a flexible diagrammatical means of representing CDS systems as sociotechnical systems. To develop this model, we examined the literature with the lens of Distributed Cognition (DCog) theory. We then present two case studies of vastly different CDSSs, one almost fully automated and the other with minimal automation, to illustrate the flexibility of the Thinking Together model. We show that this model, informed by DCog and the CDS literature, are capable of supporting both research, by enabling comparative evaluation, and practice, by facilitating explicit sociotechnical planning and communication.
          Cover page: Thinking Together: Modeling Clinical Decision-Support as a Sociotechnical System.
          • Article
          • Peer Reviewed
          UC Irvine Previously Published Works (2019)
          OBJECTIVE:Alert fatigue limits the effectiveness of medication safety alerts, a type of computerized clinical decision support (CDS). Researchers have suggested alternative interactive designs, as well as tailoring alerts to clinical roles. As examples, alerts may be tiered to convey risk, and certain alerts may be sent to pharmacists. We aimed to evaluate which variants elicit less alert fatigue. MATERIALS AND METHODS:We searched for articles published between 2007 and 2017 using the PubMed, Embase, CINAHL, and Cochrane databases. We included articles documenting peer-reviewed empirical research that described the interactive design of a CDS system, to which clinical role it was presented, and how often prescribers accepted the resultant advice. Next, we compared the acceptance rates of conventional CDS-presenting prescribers with interruptive modal dialogs (ie, "pop-ups")-with alternative designs, such as role-tailored alerts. RESULTS:Of 1011 articles returned by the search, we included 39. We found different methods for measuring acceptance rates; these produced incomparable results. The most common type of CDS-in which modals interrupted prescribers-was accepted the least often. Tiering by risk, providing shortcuts for common corrections, requiring a reason to override, and tailoring CDS to match the roles of pharmacists and prescribers were the most common alternatives. Only 1 alternative appeared to increase prescriber acceptance: role tailoring. Possible reasons include the importance of etiquette in delivering advice, the cognitive benefits of delegation, and the difficulties of computing "relevance." CONCLUSIONS:Alert fatigue may be mitigated by redesigning the interactive behavior of CDS and tailoring CDS to clinical roles. Further research is needed to develop alternative designs, and to standardize measurement methods to enable meta-analyses.
            Cover page: Medication safety alert fatigue may be reduced via interaction design and clinical role tailoring: a systematic review.
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2021)
              Cover page: Comparing Perspectives Around Human and Technology Support for Contact TracingCreative Commons 'BY' version 4.0 license
              • Article
              • Peer Reviewed
              UC Irvine Previously Published Works (2017)
              Social media are important platforms for risk communication during public health crises. Effective dissemination of accurate, relevant, and up-to-date health information is important for the public to raise awareness and develop risk management strategies. This study investigates Zika virus-related information circulated on Twitter, identifying the patterns of dissemination of popular tweets and tweets from public health authorities such as the CDC. We leveraged a large corpus of Twitter data covering the entire year of 2016. We analyzed the data using quantitative and qualitative content analyses, followed by machine learning to scale the manual content analyses to the corpus. The results revealed possible discrepancies between what the general public was most interested in, or concerned about, and what public health authorities provided during the Zika outbreak. We provide implications for public health authorities to improve risk communication through better alignment with the general publics information needs during public health crises.
                Cover page: Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak.
                • Article
                • Peer Reviewed
                UC Irvine Previously Published Works (2020)

                Objective

                Physician champions are "boots on the ground" physician leaders who facilitate the implementation of, and transition to, new health information technology (HIT) systems within an organization. They are commonly cited as key personnel in HIT implementations, yet little research has focused on their practices and perspectives.

                Materials and methods

                We addressed this research gap through a qualitative study of physician champions that aimed to capture their challenges and strategies during a large-scale HIT implementation. Email interviews were conducted with 45 physician champions from diverse clinical areas 5 months after a new electronic health record (EHR) system went live in a large academic medical center. We adopted a grounded theory approach to analyze the data.

                Results

                Our physician champion participants reported multiple challenges, including insufficient training, limited at-the-elbow support, unreliable communication with leadership and the EHR vendor, as well as flawed system design. To overcome these challenges, physician champions developed their own personalized training programs in a simulated context or in the live environment, sought and obtained more at-the-elbow support both internally and externally, and adapted their departmental sociotechnical context to make the system work better.

                Discussion and conclusions

                This study identified the challenges physician champions faced and the strategies they developed to overcome these challenges. Our findings suggest factors that are crucial to the successful involvement of physician champions in HIT implementations, including the availability of instrumental (eg, reward for efforts), emotional (eg, mechanisms for expressing frustrations), and peer support; ongoing engagement with the champions; and appropriate training and customization planning.
                  Cover page: Physician champions' perspectives and practices on electronic health records implementation: challenges and strategies.
                  • Article
                  • Peer Reviewed
                  UC Irvine Previously Published Works (2023)
                  OBJECTIVES: Ambient clinical documentation technology uses automatic speech recognition (ASR) and natural language processing (NLP) to turn patient-clinician conversations into clinical documentation. It is a promising approach to reducing clinician burden and improving documentation quality. However, the performance of current-generation ASR remains inadequately validated. In this study, we investigated the impact of non-lexical conversational sounds (NLCS) on ASR performance. NLCS, such as Mm-hm and Uh-uh, are commonly used to convey important information in clinical conversations, for example, Mm-hm as a yes response from the patient to the clinician question are you allergic to antibiotics? MATERIALS AND METHODS: In this study, we evaluated 2 contemporary ASR engines, Google Speech-to-Text Clinical Conversation (Google ASR), and Amazon Transcribe Medical (Amazon ASR), both of which have their language models specifically tailored to clinical conversations. The empirical data used were from 36 primary care encounters. We conducted a series of quantitative and qualitative analyses to examine the word error rate (WER) and the potential impact of misrecognized NLCS on the quality of clinical documentation. RESULTS: Out of a total of 135 647 spoken words contained in the evaluation data, 3284 (2.4%) were NLCS. Among these NLCS, 76 (0.06% of total words, 2.3% of all NLCS) were used to convey clinically relevant information. The overall WER, of all spoken words, was 11.8% for Google ASR and 12.8% for Amazon ASR. However, both ASR engines demonstrated poor performance in recognizing NLCS: the WERs across frequently used NLCS were 40.8% (Google) and 57.2% (Amazon), respectively; and among the NLCS that conveyed clinically relevant information, 94.7% and 98.7%, respectively. DISCUSSION AND CONCLUSION: Current ASR solutions are not capable of properly recognizing NLCS, particularly those that convey clinically relevant information. Although the volume of NLCS in our evaluation data was very small (2.4% of the total corpus; and for NLCS that conveyed clinically relevant information: 0.06%), incorrect recognition of them could result in inaccuracies in clinical documentation and introduce new patient safety risks.
                    Cover page: Mm-hm, Uh-uh: are non-lexical conversational sounds deal breakers for the ambient clinical documentation technology?
                    • Article
                    • Peer Reviewed
                    UC Irvine Previously Published Works (2017)
                    Computerized clinical decision-support systems are members of larger sociotechnical systems, composed of human and automated actors, who send, receive, and manipulate artifacts. Sociotechnical consideration is rare in the literature. This makes it difficult to comparatively evaluate the success of CDS implementations, and it may also indicate that sociotechnical context receives inadequate consideration in practice. To facilitate sociotechnical consideration, we developed the Thinking Together model, a flexible diagrammatical means of representing CDS systems as sociotechnical systems. To develop this model, we examined the literature with the lens of Distributed Cognition (DCog) theory. We then present two case studies of vastly different CDSSs, one almost fully automated and the other with minimal automation, to illustrate the flexibility of the Thinking Together model. We show that this model, informed by DCog and the CDS literature, are capable of supporting both research, by enabling comparative evaluation, and practice, by facilitating explicit sociotechnical planning and communication.
                      Cover page: Thinking Together: Modeling Clinical Decision-Support as a Sociotechnical System.Creative Commons 'BY' version 4.0 license
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