Iterative Communication Research Articles

Advance care planning in patients with respiratory failure.

Advance care planning (ACP) is a complex and iterative communication process between patients, surrogates and clinicians that defines goals of care that may include, but is not limited to, documentation of advance directives. The aim of ACP is to promote patient-centred care tailored to the patient's clinical situation through informed preparation for the future and improved communication between patient, clinicians and surrogates, if the latter need to make decisions on patient's behalf.The aim of this article is to review research related to ACP in acute and chronic respiratory failure, regarding the process, communication, shared decision-making, implementation and outcomes.Research has produced controversial results on ACP interventions due to the heterogeneity of measures and outcomes, but positive outcomes have been described regarding the quality of patient-physician communication, preference for comfort care, decisional conflict and patient-caregiver congruence of preferences and improved documentation of ACP or advance directives.The main barriers to ACP in chronic respiratory failure are the uncertainty of prognosis (particularly in the organ failure trajectory), the choice of the best timing for initiation and the lack of training of healthcare workers. In acute respiratory failure, the ACP process can be very short, should include the patient whenever possible, and is based on a discussion of treatments appropriate to the patient's functional status prior to the event (e.g. assessment of frailty) and clear communication of the likely consequences of possible options.All healthcare worker dealing with patients with serious illnesses should have training in communication skills to promote engagement in ACP discussions.

Clinician Perspectives on Virtual Specialty Palliative Care for Patients With Advanced Illnesses.

Background: Patients with serious illnesses have unmet symptom and psychosocial needs. Specialty palliative care could address many of these needs; however, access varies by geography and health system. Virtual visits and automated referrals could increase access and lead to improved quality of life, health outcomes, and patient-centered care for patients with serious illness. Objectives: We sought to understand referring clinician perspectives on barriers and facilitators to utilizing virtual tools to increase upstream access to palliative care. Design: Participants in this multisite qualitative study included practicing clinicians who commonly place palliative care referrals across multiple specialties, including hematology/oncology, family medicine, cardiology, and geriatrics. All interviews were transcribed and subsequently coded and analyzed by trained research coordinators using Atlas.ti software. Settings/Subjects: This study included 23 clinicians (21 physicians, 2 nonphysicians) across 5 specialties, 4 practice settings, and 7 states in the United States. Results: Respondents felt that community-based specialty palliative services including symptom management, advance care planning, physical therapy, and mental health counseling would benefit their patients. However, they had mixed feelings about automated referrals, with some clinicians feeling hesitant about not being alerted to such referrals. Many respondents were supportive of virtual palliative care, particularly for those who may have difficulty accessing physician offices, but most respondents felt that such care should only be provided after an initial in-person consultation where clinicians can meet face-to-face with patients. Conclusion: Clinicians believe that automated referrals and virtual palliative care could increase access to the benefits of specialty palliative care. However, virtual palliative care models should give attention to iterative communication with primary clinicians and the perceived need for an initial in-person visit.

Integrated impact assessment for land and water management

Impact assessment considers the future consequences of current or proposed actions, but multiple impact assessment types and silos of expertise make integration difficult. When faced with the development of policy and planning for the complex bio-physical and social-economic systems found in river catchments, integrated impact assessment (IIA) becomes imperative. IIA has well-recognised potential when considering multiple, intersecting impact domains in one impact assessment verses siloed technical workstreams, often not linked until the decision-making stage, and with little transparency around how integration transpires. A “collective” and systemic view of all impacts is essential for understanding the causal relationships between system components and their full consequences including cumulative impacts. In land and water management, the development and integrated assessment of scenarios of change requires integration of disciplinary expertise, and local and indigenous knowledge systems. The challenge here is to turn practice towards less technocratic, more collaborative, and better integrated approaches. This paper therefore advances a participatory approach to IIA that uses participation and co-production of knowledge throughout. Here IIA is facilitated by broad leadership and iterative communication of concepts, ideas, methods, and accessible data between all participants through purposeful management of the process.

Harnessing federated generative learning for green and sustainable Internet of Things

The rapid proliferation of devices in the Internet of Things (IoT) has ushered in a transformative era of data-driven connectivity across various domains. However, this exponential growth has raised pressing concerns about environmental sustainability and data privacy. In response to these challenges, this paper introduces One-shot Federated Learning (OSFL), an innovative paradigm that harmonizes sustainability and machine learning within IoT ecosystems. OSFL revolutionizes the traditional Federated Learning (FL) workflow by condensing multiple iterative communication rounds into a single operation, thus significantly reducing energy consumption, communication overhead, and latency. This breakthrough is coupled with the strategic integration of generative learning techniques, ensuring robust data privacy while promoting efficient knowledge sharing among IoT devices. By curtailing resource utilization, OSFL aligns seamlessly with the vision of green and sustainable IoT, effectively extending device lifespans and mitigating their environmental footprint. Our research underscores the transformative potential of OSFL, poised to reshape the landscape of IoT applications across domains such as energy-efficient smart cities and groundbreaking healthcare solutions. This contribution marks a pivotal step towards a more responsible, sustainable, and technologically advanced future.

A new era for science-industry research collaboration – a view towards the future

Direct engagement of the fishing industry in the provision and co-creation of knowledge and data for research and management is increasingly prevalent. In both the North Atlantic and North Pacific, enhanced and targeted engagement is evident. More is needed. Science-Industry collaborative approaches to developing questions, collecting data, interpreting data, and sharing knowledge create opportunities for information transfer and improved understanding of ecosystem interactions, stock dynamics, economic incentives, and response to management. These collaborations require clear communication and awareness of objectives and outcomes. These initiatives also require careful attention to conditions and interactions that foster respect, trust, and communication. Respect is critical and entails acknowledging the respective skills and expertise of both scientists and fishers. Trust is needed to build confidence in the information developed and its use. Communication is essential to maintain relationships and leverage shared insights. To assess current trends and future opportunities related to this type of engagement, we convened a networking session of research scientists, industry scientists, industry leaders, and fishers at the Annual Science Meeting of the International Council for the Exploration of the Sea (ICES) to address the following questions: (1) What are scientific needs that could be addressed with industry-collected data or knowledge? And (2) How can science-industry collaboration be made sustainable? Here we identify opportunities and acknowledge challenges, outline necessary conditions for respectful and sustainable collaborative research, and highlight ways to promote stakeholder involvement in developing science. We address industry concerns and solicit industry advice. We also address challenges to scientists in ensuring standards for scientific data, conflict of interest, and applying information to advise management. The discussions in this session and subsequent correspondence have led to a set of guidelines and best practices that provide a framework to advance further collaboration between industry and research science. We identify opportunities for directed engagement. We also detail potential approaches to clarify expectations and develop avenues for iterative communication and engagement to sustain collaborative efforts over time. The intent is to improve and expand data streams and contextual understanding of ecosystem processes, stock assessment, and socio-economic dynamics to the benefits of science and industry alike.

CCOMPARISON OF PHOTOCEPHALOMETRY METHODS IN RHINOPLASTY

Cephalometric measurements are widely used and essential when planning rhinoplasty and other surgical and non-surgical facial interventions. They provide measurements and simulations, which are extremely useful both for more iterative communication with the patient, as well as for more accurate planning of surgical techniques and maneuvers to be used during surgery. Despite its importance in facial aesthetic evaluation, the different forms of implementation often generate misunderstanding by professionals when planning and simulating images because they suffer from slight distortions in relation to the real measurement. The main objective of the present study was to compare three measuring instruments used in the facial surgeon’s clinical practice: rigid ruler (RR), millimeter glasses (MG), and millimeter adhesive tape (MAT), evaluating whether there would be a difference between the measurements obtained by each of them in the analysis of digital photographic images. It was observed that in the profile view all the instruments used presented significantly different measurements from each other, and something similar was verified in the frontal view when comparing MG and MAT with RR. It was evident that the use of these widely disseminated objects, despite initially appearing useful, can bring different values to each other, eventually leading to inaccurate measurements, planning, and simulations. New studies are necessary to elucidate which of the methodologies would be the most appropriate for estimating real measurements.

Testing EEG functional connectivity between sensorimotor and face processing visual regions in individuals with congenital facial palsy.

Moebius syndrome (MBS) is characterized by the congenital absence or underdevelopment of cranial nerves VII and VI, leading to facial palsy and impaired lateral eye movements. As a result, MBS individuals cannot produce facial expressions and did not develop motor programs for facial expressions. In the latest model of sensorimotor simulation, an iterative communication between somatosensory, motor/premotor cortices, and visual regions has been proposed, which should allow more efficient discriminations among subtle facial expressions. Accordingly, individuals with congenital facial motor disability, specifically with MBS, should exhibit atypical communication within this network. Here, we aimed to test this facet of the sensorimotor simulation models. We estimated the functional connectivity between the visual cortices for face processing and the sensorimotor cortices in healthy and MBS individuals. To this aim, we studied the strength of beta band functional connectivity between these two systems using high-density EEG, combined with a change detection task with facial expressions (and a control condition involving non-face stimuli). The results supported our hypothesis such that when discriminating subtle facial expressions, participants affected by congenital facial palsy (compared to healthy controls) showed reduced connectivity strength between sensorimotor regions and visual regions for face processing. This effect was absent for the condition with non-face stimuli. These findings support sensorimotor simulation models and the communication between sensorimotor and visual areas during subtle facial expression processing.

Efficient Federated Learning with Self-Regulating Clients

Motivation. Since its inception [6], Federated Learning (FL) has been enjoying a strong interest from the privacypreserving AI research community. FL also has been commercially implemented in popular applications such as Google's Gboard and Apple Siri. In FL, Machine Learning (ML) models are trained cooperatively by many clients (e.g., mobile phones) without explicitly sharing their identity and private data. The training is done through iterative communication rounds between a central parameter/model server and clients. In each communication round, the global model is supplied to a subset of clients who use their private data to do local training on their respective devices. The updated models from each participating client are anonymously sent back to the central server and aggregated to get the global model for the next communication round.

Developing Indicators to Measure the Implementation of the Western Cape Alcohol Harms Reduction Strategy in South Africa

This manuscript describes a process to develop a set of indicators to monitor and evaluate the implementation of the Western Cape Alcohol-Related Harms Reduction (AHR) White Paper in South Africa and provide a final set of indicators. Drawing on the framework in Andréasson et al. (2009), a logic model with categories and types of indicators (i.e. prevention, determinants, consumption, and alcohol-related harms) was used to develop an initial set of 255 indicators. The methodological process followed involved a) scoping of a large electronic database maintained by the South African Medical Research Council, b) a comprehensive literature review and, c) reaching out to18 international key informants. Iterative communications with stakeholders from diverse government entities via email, telephone calls and individual and multi-person face-to-face meetings, together with a consensus process involving the study team was used to refine the indicators. The final set included 176 indicators; 108, (61.4%) of these were “core” indicators, and 68 (38.6%) were “expanded” indicators, meaning they added to the core indicators in given areas which would be useful to have but are of a lower priority or are likely to be less easy to obtain. Of the core indicators, 45 (42.4%) were deemed by policy makers/researchers in the Premier’s office as “high-level indicators,” denoting that they were the most essential. This manuscript demonstrates that it is possible to develop evidence-based, location-specific indicators to evaluate policy implementation.

Knowledge Sharing for Pulmonary Nodule Detection in Medical Cyber-Physical Systems.

With the rapid development of edge intelligence (EI) and machine learning (ML), the applications of Cyber-Physical Systems (CPS) have been discovered in all aspects of the life world. As one of its most essential branches, Medical CPS (MCPS) determines human health and medical treatment in the Internet of Everything (IOE) era. Knowledge sharing is the critical point of MCPS and has also been humanity's best dream through the ages. This paper explores a novel knowledge-sharing model in MCPS and takes a pulmonary nodule detection task as a significant case for building an Unet-based mask generator. A Classification-guided Module (CGM)-based discriminator with knowledge from EMRs is set against a generator to offer a promising result for each mask from the inexperienced participant of federated ML. After an iterative communication between the federated server and its clients for knowledge sharing, the segmented sub-image owns a coincident attribute distribution with that of the EMRs from the experts. Besides, the adversarial network augment the data to normalize the data distribution for all the clients as a remission for none independent identically distributed (non-IID) data problem. We implement a detection framework on the simulated EI environment following an existing adaptive synchronization strategy based on data sharing and median loss function. On 1304 scans of the merged dataset, our proposed framework can help boost the detection performance for most of the existing methods of pulmonary nodule detection.

Acceptability of Phone-Based Communication Intervention by Healthcare Workers as an Adjunct to Routine Referral Form: A Qualitative Study in South Western Uganda

Introduction: A functional maternal referral system should encompass a feasible communication system between health facilities. In Uganda, the current paper-based patient referral form is associated with inadequate patient-information and low feedback rates. A recent quasi-experimental study demonstrated that a phone-based communication intervention is feasible for iterative communication between health facilities, and there were improved maternal-fetal outcomes and high rates of feedback. However, the acceptability of the intervention was not assessed. Objective: The study assessed the acceptability of a phone-based communication intervention by the health care workers (HCWs) for iterative communication between the referring and receiving health facilities. Methods: This was a qualitative study conducted in South Western Uganda, in April 2021. The study employed a theoretical framework of acceptability of medical interventions. We conducted in-depth interviews with HCWs and used deductive-inductive analysis. Results: We enrolled a total of 23 HCWs, of whom 69.6% (n = 16) were females while 30.4% (n = 7) were males. Majority (65.2%, n = 15), were midwives and the rest were: doctors (30.4%, n = 7) and a nurse (4.3%). The HCWs were positive towards the intervention: they believed that the intervention reduced delays, promoted professional escort, encouraged sharing of supplies, enabled exchange of relatively more patient details, feedback and improved case management. They believed it was culturally acceptable and had enough skills and experience of operating phones. All participants recommended scale out of the intervention, but advised on the need for dedicated human-resource to coordinate phone calls, ensure availability of airtime and charged battery. Conclusion: This study demonstrates that the phone-based communication intervention was highly accepted by the healthcare workers, and that hospitals can successfully give feedback to lower health centres through iterative phone calls. This provides a possible solution to the long-standing challenge of poor feedback rates and a vicious cycle of poor maternal-fetal outcomes in resource limited settings.

Manufacturing Populism: Digitally Amplified Vernacular Authority

This article shows that digital technologies can play an outsized role in populist discourse because the imagined “voice of the people” gains its authority through the appearance of continuities and consistencies across many iterative communication events. Those iterations create an observable aggregate volition which is the basis of vernacular authority. Digital technologies give institutions the ability to generate those iterative communications quickly. Through example analyses, I show three different ways that institutional actors deployed digital technologies to promote their populist political agendas by manufacturing “the will of the people.” Each of these examples suggests that digital technologies hybridize communication in ways that suggest the elite are always already part of “the people.”

COMMUTE: Communication-efficient transfer learning for multi-site risk prediction

Objectives:We propose a communication-efficient transfer learning approach (COMMUTE) that effectively incorporates multi-site healthcare data for training a risk prediction model in a target population of interest, accounting for challenges including population heterogeneity and data sharing constraints across sites. Methods:We first train population-specific source models locally within each site. Using data from a given target population, COMMUTE learns a calibration term for each source model, which adjusts for potential data heterogeneity through flexible distance-based regularizations. In a centralized setting where multi-site data can be directly pooled, all data are combined to train the target model after calibration. When individual-level data are not shareable in some sites, COMMUTE requests only the locally trained models from these sites, with which, COMMUTE generates heterogeneity-adjusted synthetic data for training the target model. We evaluate COMMUTE via extensive simulation studies and an application to multi-site data from the electronic Medical Records and Genomics (eMERGE) Network to predict extreme obesity. Results:Simulation studies show that COMMUTE outperforms methods without adjusting for population heterogeneity and methods trained in a single population over a broad spectrum of settings. Using eMERGE data, COMMUTE achieves an area under the receiver operating characteristic curve (AUC) around 0.80, which outperforms other benchmark methods with AUC ranging from 0.51 to 0.70. Conclusion:COMMUTE improves the risk prediction in a target population with limited samples and safeguards against negative transfer when some source populations are highly different from the target. In a federated setting, it is highly communication efficient as it only requires each site to share model parameter estimates once, and no iterative communication or higher-order terms are needed.

Information on advance care planning on websites of dementia associations in Europe: A content analysis

Objective To gain insight into the advance care planning (ACP) content provided on dementia associations’ websites in Europe. Methods We conducted a content analysis of dementia associations’ websites in Europe regarding ACP information, using deductive and inductive approaches and a reference framework derived from two ACP definitions. Results We included 26 dementia associations’ websites from 20 countries and one European association, covering 12 languages. Ten websites did not mention ACP. The information on the remaining 16 varied in terms of themes addressed and amount of information. Four explicitly define ACP. Several websites made multiple references to legal frameworks (n = 10, 705 excerpts), choosing legal representatives (n = 12, 274 excerpts), and care and treatment preferences (n = 14, 89 excerpts); while themes such as communication with family (n = 9, 67 excerpts) and professionals (n = 9, 49 excerpts) or identifying personal values (n = 9, 73 excerpts) were mentioned on fewer websites or addressed in fewer excerpts. Conclusion ACP content is non-existent in 10 out of 26 dementia associations’ websites. On those that have ACP content, legal and medical themes were prominent. It would be beneficial to include more comprehensive ACP information stressing the importance of communication with families and professionals, in line with current ACP conceptualisations framing ACP as an iterative communication process, rather than a documentation-focused exercise.

Mandated Caregiver Training in the Veterans Health Administration: Caregiver Inquiry Informs National Dissemination.

A minority of family caregivers receive training, with implications for their own and their recipient's outcomes. Federal policy has supported the implementation and expansion of caregiver training and support. The Department of Veterans Affairs (VA) has developed a national Caregiver Support Program and collaborated with VA health services researchers to explore caregivers' acceptance of an evidence-based training program in preparation for system-wide dissemination. This approach entailed a convergent mixed-methods design, which involved separate analyses of quantitative and qualitative data. Survey questions based on the Kirkpatrick model for training evaluation measured caregivers' reaction and learning, and interview questions elicited caregivers' reports about the value of the program for them. Most caregivers reported satisfaction with the training when responding to survey questions, although qualitative interviews revealed caveats suggesting need to hone the best timing and specific group of caregivers for maximal benefit. Our findings indicate that understanding program-user fit may be particularly critical when implementing training for caregivers as they come to the program at different points along their caregiving journey, needing differing types and intensities of support. While a general program may appeal to policymakers aiming to scale caregiver training within a large, heterogeneous system, there may be shortcomings in terms of end-user acceptance and subsequent downstream outcomes such as reach and ultimately program effectiveness. Good, iterative communication flow between program developers and policymakers facilitates this understanding and, in turn, decisions about scaling.

Challenges and Opportunities for Companies to Build HTA/Payer Perspectives Into Drug Development Through the Use of a Dynamic Target Product Profile.

Background: The target product profile (TPP) outlines the desired profile of a target product aimed at a particular disease and is used by companies to plan clinical development. Considering the increasing importance of health technology assessment (HTA) in informing reimbursement decisions, a robust TPP needs to be built to address HTA needs, to guide an integrated evidence generation plan that will support HTA submissions. This study assessed current practices and experiences of companies in building HTA considerations into TPP development. Methods: An opinion survey was designed and conducted in 2019, as a cross-sectional questionnaire consisting of multiple-choice questions. The questionnaire provided a qualitative assessment of companies’ strategies and experiences in building HTA considerations into the TPP. Eligible survey participants were the senior management of Global HTA/Market Access Departments at 18 top international pharmaceutical companies. Results: 11 companies responded to the survey. All companies included HTA requirements in TPP development, but the timing and process varied. The key focus of HTA input related to health problems and treatment pathways, clinical efficacy/effectiveness, and safety. Variance of HTA methods and different value frameworks were identified as a challenge for development plans. Stakeholder engagement, such as HTA scientific advice, was used to pressure test the TPP. Conclusion: This research provides insight into current practice and potential opportunities for value-based drug development. It demonstrates the evolution of the TPP to encompass HTA requirements and suggests that the TPP could have a role as an iterative communication tool for use with HTA agencies to enhance an integrated evidence generation plan.

Factors That Determine the Experience of Transition to an Inpatient Palliative Care Unit for Patients and Caregivers: A Qualitative Study.

Objective: Transitions in care settings near the end of life can present challenges to patients and families, especially when there are also adjustments in level of care and illness trajectory. In this study, we explored what factors influenced how patients and family caregivers experienced a transition to an inpatient Palliative Care Unit (PCU). Methods: This qualitative study was conducted at a PCU in Toronto, Canada. Semi-structured interviews were held with 29 participants (14 patients and 15 family caregivers) during their time on the PCU. Data was analyzed through an iterative process of constant comparison to generate themes. The recruitment process continued to the point of thematic saturation. Results: Five themes were identified that represented the participants’ experiences in transitioning to the PCU: Being prepared, Feeling supported, Coming to terms with end of life issues, Dealing with uncertainty, and Continuity of care. Conclusions: Our findings highlight the need for clear and iterative communication with patients and family caregivers during the transition to a PCU. Identification and consideration of the common themes involved in the experience of transfer to PCU can help guide future practice and improve the experience of patients and families during transitions at the end of life.

One step forward towards the full integration of BEM and CAD software: An effective adaptive approach

The advent of Isogeometric analysis enabled advances towards the straightforward connection between geometric design and mechanical modelling phases. 3D approaches of the Isogeometric Boundary Element Method (IGABEM) stand out in this context, because it requires information only from the boundary as well as the Computer-Aided Design (CAD) models. Thus, the 3D IGABEM best fulfils the isogeometric paradigm, since the geometric representation provided by CAD packages can be interpreted directly by BEM as mesh. However, there is a lack of information regarding convergence and accurate mesh refinement for the proper mechanical fields representation in the 3D IGABEM. Although the IGA models from CAD are geometrically exact in various problems, they usually are not refined enough for the accurate mechanical fields representation. This study proposes mesh adaptivity strategies for the 3D IGABEM formulation in elastostatics, which provide accurate geometric representation and mechanical fields description and contribute towards the full coupling of BEM and CAD schemes. The proposed strategy utilises the error based upon the hypersingular residuals, which provides point-wise error estimates at the boundary. Then, errors based on displacements/tractions or strains can be assessed. The adaptive scheme utilises mesh optimality criteria for both local and global conditions. The refinement strategy applies the knot insertion process, which makes the adaptivity procedure robust and accessible since it does not require iterative communication with the CAD system. The proposed adaptive strategy based on strains error provides good convergence rates in comparison to globally uniform refinement for homogeneous and nonhomogeneous bodies. Additionally, the mesh adaptivity strategy can be applied for fibre-reinforced IGABEM formulations, for which a different error estimator is proposed accounting for the coupling 1DBEM/BEM and FEM/BEM. The strain-based error estimator identifies the required mesh refinement for minimising the oscillating adherence forces surrounding the fibre discontinuity regions. Five applications demonstrate the accuracy of the proposed adaptive schemes, in which the globally homogeneous refinement is a reference.

Accuracy of curability expectations in patients with gastrointestinal cancers.

Assessment of illness and treatment understanding among cancer patients has largely focused on those with advanced disease. Less is known about patient expectations at earlier stages of cancer and potential modifiers of accurate understanding. We assessed accuracy of cure expectations in patients across all stages with gastrointestinal (GI) cancers. Accuracy was determined by independent reviews of patient health records by oncologists on the investigative team. Impact on cure accuracy of selected clinical variables and health-information preferences was analyzed. Hundred and thirty five patients were included for analysis, with 100% interrater agreement for accuracy between oncologist reviewers. Sixety five patients (48%) had accurate cure expectations from their cancer treatment. Accuracy was lower in Stage IV versus Stage I-III disease (35% vs. 63%, p < 0.01), lower in unresectable versus resectable disease (35% vs. 67%, p < 0.01), and higher in patients with early-stage disease who received adjuvant chemotherapy versus those who did not (78% vs. 53%, p=0.04). Accuracy did not differ by health-information preferences and remained stable over time. Of 63 patients who died, baseline accuracy differed by location of death (p=0.03), with greater accuracy in those who died with home hospice (56%). Accuracy was lower in those who were hospitalized in the last 30 days of life versus those who were not (25% vs. 59%, p=0.01). Inaccurate cure expectations are prevalent across all stages of GI cancers, but particularly among those with metastatic or unresectable disease. High-quality, iterative communication strategies may facilitate patient illness and treatment understanding throughout the disease course.

Physicians' perspectives of prognosis and goals of care discussions after hip fracture.

Hip fracture often represents a major transition in patients' health, with a 1-year mortality rate between 25% and 30% and a challenging recovery course. Caring for hip fracture patients presents opportunities for goals of care discussions that include prognostic information and guidance about functional dependence. We conducted qualitative, semi-structured interviews with 23 attending physicians involved with the care of hip fracture patients, including orthopedic surgeons, anesthesiologists, internists, and geriatricians, across 13 health systems in the United States and Canada. Questions addressed knowledge and interpretation of prognosis, discussing prognosis and goals of care, and timing and prioritization of surgery. Interviews were analyzed using a constructivist grounded theory approach to identify themes and develop a coding taxonomy. Physicians agreed that hip fracture had a considerable 1-year mortality, felt that it was important to discuss prognostic outcomes and the recovery process, wanted to elucidate patients' priorities, and often promoted timely surgery. Physicians perceived challenges when discussing mortality data with new patients in an acute setting. They more easily discussed outcomes related to functional dependence and quality of life. Some physicians used iterative communication as a strategy to have in-depth conversations in a busy perioperative setting. Providing timely, compassionate care for hip fracture patients is challenging. There are opportunities to study iterative communication to encourage dialogue at key points of patient care to better discuss prognosis and recovery and bolster coordinated multidisciplinary care that focuses on patients' goals and values.