Session | ||
OS-1: A digital perspective on healthcare ecosystems
Session Topics: A digital perspective on healthcare ecosystems
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Presentations | ||
1:00pm - 1:20pm
A network analysis of intermedia influence patterns in the news discourse about the Mpox epidemic Northeastern University, United States of America The Intermedia Agenda-Setting theory (IAS) posits that media outlets influence each other’s reporting on what issues are covered by co-orienting journalists towards a specific agenda. In this work, we extended the IAS theory to framing, which is often dubbed as the second level of agenda-setting (or attribute setting). The proposed Intermedia frame-building hypothesis asserts that media outlets influence each other on how an issue is covered. We studied patterns of influence in the coverage of Mpox between the national level news outlets in the United States. First, we identified the key attributes (emphasis frames) in the coverage of Mpox (agenda) and quantified their prevalence in news reporting via applied thematic analysis. Second, we derived individual time series for 16 news outlets over 6 months, signifying the proportion of published articles per day that emphasized on these attributes. Finally, we inferred networks of influence between these outlets using a methodological pipeline that combined Bayesian structure learning with Transfer entropy. In contrast to prior studies that found mainstream outlets such as the NYT as primary agenda-setters, we found that right-leaning, low-credibility outlets such as Breitbart and Blaze were central influencers. Surprisingly, such right-leaning outlets also exerted a strong cross-partisan influence on other left-leaning outlets, defying expectations of ideological silos. Thus, in addition to verifying the intermedia frame-building hypothesis, our study highlights the role of alt-right news outlets in shaping reactive patterns in public discourse during health controversies. We contribute methodological insights on inferring networks of intermedia influence to the agenda-setting scholarship. 1:20pm - 1:40pm
Characterizing EHR communication network patterns and burden 1University of California Davis; 2University of Iowa; 3University of California Los Angeles; 4University of California San Diego Cancer patients require complex care, involving 18 or more clinical disciplines. This is further exacerbated by comorbidities requiring additional specialties. The coordination and efficiency of information flow across these multi-team systems (MTSs) is essential for patient outcomes. Research has shown differences in communication flow between high- and low-performing teams, implying that patient outcomes may be improved by improving communication in cancer care MTSs. Electronic Health Records (EHRs) offer potential solutions to asynchronous intra- and inter-team communication, yet many challenges remain. First, little is known about the communication patterns of a patient’s cancer care MTS and how they vary across patients. Second, clinicians face a high EHR burden, spending nearly half their time in clinic plus time outside clinic hours in the EHR. The objective of our study was to characterize EHR communication network patterns and EHR burden in the information sharing process in roughly 10,000 lung, colorectal, and breast cancer care patients from two academic teaching hospitals. We assessed the relational nature of clinical notes in the EHR by examining the likelihood of a clinician reading a note based on author and focal patient characteristics. We also assessed the reading and writing burden by examining the number of notes written for each patient and the number of notes written by each healthcare professional per patient, and how these vary by patient characteristics. We identified certain comorbidities that significantly affected the information flow, as did cancer stage and site. Racialized groupings also significantly affected information flow, which may suggest health disparities. 1:40pm - 2:00pm
Conceptualizing and measuring “personal healthcare networks”: Reframing the structure of healthcare ecosystems through the eyes of the patient 1Columbia University School of Nursing, United States of America; 2NewYork-Presbyterian Hospital, United States of America; 3New York State Psychiatric Institute / Columbia Psychiatry, United States of America; 4Vanderbilt University, United States of America Purpose: This presentation aims to describe an approach to egocentric network data collection in which patients list and describe their network of healthcare professionals (i.e., a “personal healthcare network”) to assess patient perceptions of healthcare access, quality, and value. Preliminary findings from ongoing data collection among transgender and gender-diverse (TGD) adults will be presented. Methods: This mixed methods study surveys TGD adults (N = 130) recruited from a home nursing care program designed to support recovery immediately after gender-affirming surgery. In an online survey, name generators probe for participants’ past-year healthcare professionals in physical, mental, or gender-affirming healthcare. Next, they respond to items describing the professional and relationship (e.g., role, type(s) of care, patient-provider identity concordance, setting, modality (virtual or in-person), visit frequency, wait time, missed or cancelled appointments, knowledge of TGD healthcare, relative significance to overall care). Analysis will characterize network composition and function. We will also explore associations between measures at the ego, alter, and network levels and outcomes in self-rated physical and mental health. A subset (n = 24) will be recruited for individual interviews on the experience of creating and navigating personal healthcare networks. Contributions: Beyond building evidence on healthcare needs for TGD individuals after gender-affirming surgery, this study leverages the subjective nature of egocentric networks to resituate the patient at the center of their care teams and clinical processes. This approach may facilitate closer investigation of key variables driving the relationships between patient experiences and service outcomes across populations and health conditions. 2:00pm - 2:20pm
Mapping collaboration and service integration in mental health sector: An Australian case study 1University of Melbourne, Australia; 2University of Sydney, Australia; 3LaTrobe University, Australia; 4NEAMI National, Australia; 5Victorian Collaborative Centre for Mental Health and Wellbeing, Australia The importance of understanding regional mental health service systems as inter-organisational networks of service providers has been recognised for some time. Such networks are argued to be important in facilitating service access and coordination and hence to a more effective and client-centred model of care. However, despite a small but growing number of exemplary empirical studies of mental health and other health systems as inter-organisational networks, and an emerging theoretical conceptualisation of what makes such networks effective, recent systematic reviews have concluded that the current literature remains fragmented and inconclusive. This presentation will describe the CANVAS (Collaborative Networks of the Victorian Mental Health Service System) project, a large-scale pilot applying social network analysis (SNA) to map the organisational landscape of mental health services in an Australian state undergoing major policy-driven reform. This baseline view of the network will inform an understanding of the existing state of the service system, including referral pathways and areas of collaboration. It will also suggest opportunities for improving referral and collaborative activity. This talk will describe the progress of the project to date, and provide an initial update on the first round of data collection in two pilot regions of the state. Network data includes multilevel interorganisational data, as measured at both the organisational and team levels (e.g., information sharing, resource sharing, collaborative advocacy, similarity-based comparisons). A novel, purpose-built digital data collection platform enables real-time description of network data, allowing participating organisations and policymakers to utilise service descriptions instantly, and track evolving structures. |