Effect of standardized EHR-integrated handoff report on intraoperative communication outcomes.

OBJECTIVES: We evaluated the effectiveness and implementability of a standardized EHR-integrated handoff report to support intraoperative handoffs. MATERIALS AND METHODS: A pre-post intervention study was used to compare the quality of intraoperative handoffs supported by unstructured notes (pre) to structured, standardized EHR-integrated handoff reports (post). Participants included anesthesia clinicians involved in intraoperative handoffs. A mixed-method approach was followed, supported by general observations, shadowing, surveys, and interviews. RESULTS: One hundred and fifty-one intraoperative permanent handoffs (78 pre, 73 post) were included. One hundred percent of participants in the post-intervention cohort utilized the report. Compared to unstructured, structured handoffs using the EHR-integrated handoff report led to: (1) significant increase in the transfer of information about airway management (55%-78%, P < .001), intraoperative course (63%-86%, P < .001), and potential concerns (64%-88%, P < .001); (2) significant improvement in clinician satisfaction scores, with regards to information clarity and succinctness (4.5-4.7, P = .002), information transfer (3.8-4.2, P = .011), and opportunities for fewer errors reported by senders (3.3-2.5, P < .001) and receivers (3.2-2.4, P < .001); and (3) significant decrease in handoff duration (326.2-262.3 s, P = .016). Clinicians found the report implementation highly acceptable, appropriate, and feasible but noted a few areas for improvement to enhance its usability and integration within the intraoperative workflow. DISCUSSION AND CONCLUSION: A standardized EHR-integrated handoff report ensures the effectiveness and efficiency of intraoperative handoffs with its structured, consistent format that-promotes up-to-date and pertinent intraoperative information transfer; reduces opportunities for errors; and streamlines verbal communication. Handoff standardization can promote safe and high-quality intraoperative care.

Determining if COPD Self-Management Televisit-Based Interventions are evaluated among and equitably effective across diverse patient populations to Reduce Acute Care Utilization: A Scoping Review.

TOPIC IMPORTANCE: With telemedicine's expansion during the COVID-19 pandemic, it became critical to evaluate whether patients have equitable access and capabilities to optimally use televisits for improved COPD outcomes such as reduced hospitalizations. This scoping review evaluated whether televisit-based interventions are evaluated and equitably effective in improving healthcare utilization outcomes among diverse patient populations with COPD. REVIEW FINDINGS: Using a systematic search for televisit-based COPD self-management interventions we found 20 studies for inclusion, all but one of which was published prior to the COVID-19 pandemic. Most (11/20) were 'good' quality. The majority (19/20) of studies reported age and gender; few provided race (3/20) or income (1/20) data. The most frequently used televisit-based modalities were in-person plus phone (6/20), video-only (6/20), and phone-only (4/20). Most (12/20) showed a significant reduction in at least one healthcare utilization metric; nine found hospitalization-related reductions. Effective interventions typically used two modalities (e.g., in-person plus televisits) and/or video modality. SUMMARY: Most studies failed to report on participants' race or income leading to a lack of data on equity of interventions' effectiveness across diverse patient populations. Multi-modality televisit-based interventions, particularly with an in-person component, were most commonly effective; no associations were seen with study quality or size. With the increasing reliance on telemedicine to provide chronic disease care, the lack of data among diverse populations since the COVID-19 pandemic began limits generalizability of these findings for real-world clinical settings. More comprehensive evaluations of televisit-based interventions are needed in the post-pandemic era within and across diverse patient populations.

A Culturally Adapted Perioperative Mental Health Intervention for Older Black Surgical Patients.

OBJECTIVES: Perioperative mental health of older Black surgical patients is associated with poor surgical outcomes; however, evidence-based perioperative interventions are lacking. Our two study objectives included: first, examine factors affecting perioperative care experiences of older Black surgical patients with mental health problems, and second, ascertain design and implementation requirements for a culturally-adapted perioperative mental health intervention. DESIGN SETTING AND PARTICIPANTS: We conducted six focus groups with older Black patients (n = 15; ≥50 years; surgery within the past 5 years and/or interest in mental health research; history of distress, anxiety, or depression coping with surgery/hospitalization/) from a large academic medical center. We engaged study partners, including interventionists and community members, to gather insights on intervention and implementation needs. We followed a hybrid inductive-deductive thematic approach using open coding and the National Institute on Minority Health and Health Disparities Research Framework. RESULTS: Patients reported that their psychological well-being and long-term mental health outcomes were not appropriately considered during perioperative care. Perceived stressors included interpersonal and structural barriers to using mental healthcare services, clinician treatment biases and ageism in care, and lack of healthcare professional connections/resources. Patients utilized various coping strategies, including talk therapy, faith/spirituality, and family and friends. CONCLUSION: This study offers valuable insights into the experiences of older Black surgical patients and the critical elements for developing a personalized perioperative mental health intervention to support their well-being before, during, and after surgery. Our findings demonstrated a need for a patient-centered and culturally adapted intervention targeting the individual/behavioral and interpersonal levels. Informed by the cultural adaptation framework, we propose a multi-component intervention that integrates psychological and pharmacological components.

Effect of Machine Learning on Anaesthesiology Clinician Prediction of Postoperative Complications: The Perioperative ORACLE Randomised Clinical Trial.

Background: Anaesthesiology clinicians can implement risk mitigation strategies if they know which patients are at greatest risk for postoperative complications. Although machine learning models predicting complications exist, their impact on clinician risk assessment is unknown. Methods: This single-centre randomised clinical trial enrolled patients age ≥18 undergoing surgery with anaesthesiology services. Anaesthesiology clinicians providing remote intraoperative telemedicine support reviewed electronic health records with (assisted group) or without (unassisted group) also reviewing machine learning predictions. Clinicians predicted the likelihood of postoperative 30-day all-cause mortality and postoperative acute kidney injury within 7 days. Area under the receiver operating characteristic curve (AUROC) for the clinician predictions was determined. Results: Among 5,071 patient cases reviewed by 89 clinicians, the observed incidence was 2% for postoperative death and 11% for acute kidney injury. Clinician predictions agreed with the models more strongly in the assisted versus unassisted group (weighted kappa 0.75 versus 0.62 for death [difference 0.13, 95%CI 0.10-0.17] and 0.79 versus 0.54 for kidney injury [difference 0.25, 95%CI 0.21-0.29]). Clinicians predicted death with AUROC of 0.793 in the assisted group and 0.780 in the unassisted group (difference 0.013, 95%CI -0.070 to 0.097). Clinicians predicted kidney injury with AUROC of 0.734 in the assisted group and 0.688 in the unassisted group (difference 0.046, 95%CI -0.003 to 0.091). Conclusions: Although there was evidence that the models influenced clinician predictions, clinician performance was not statistically significantly different with and without machine learning assistance. Further work is needed to clarify the role of machine learning in real-time perioperative risk stratification. Trial Registration: ClinicalTrials.gov NCT05042804.

Effect of Telemedicine Support for Intraoperative Anaesthesia Care on Postoperative Outcomes: The TECTONICS Randomised Clinical Trial.

Background: Novel applications of telemedicine can improve care quality and patient outcomes. Telemedicine for intraoperative decision support has not been rigorously studied. Methods: This single centre randomised clinical trial ( clinicaltrials.gov NCT03923699 ) of unselected adult surgical patients was conducted between July 1, 2019 and January 31, 2023. Patients received usual care or decision support from a telemedicine service, the Anesthesiology Control Tower (ACT). The ACT provided real-time recommendations to intraoperative anaesthesia clinicians based on case reviews, machine-learning forecasting, and physiologic alerts. ORs were randomised 1:1. Co-primary outcomes of 30-day all-cause mortality, respiratory failure, acute kidney injury (AKI), and delirium were analysed as intention-to-treat. Results: The trial completed planned enrolment with 71927 surgeries (35956 ACT; 35971 usual care). After multiple testing correction, there was no significant effect of the ACT vs. usual care on 30-day mortality [641/35956 (1.8%) vs 638/35971 (1.8%), risk difference 0.0% (95% CI -0.2% to 0.3%), p=0.96], respiratory failure [1089/34613 (3.1%) vs 1112/34619 (3.2%), risk difference -0.1% (95% CI -0.4% to 0.3%), p=0.96], AKI [2357/33897 (7%) vs 2391/33795 (7.1%), risk difference -0.1% (-0.6% to 0.4%), p=0.96], or delirium [1283/3928 (32.7%) vs 1279/3989 (32.1%), risk difference 0.6% (-2.0% to 3.2%), p=0.96]. There were no significant differences in secondary outcomes or in sensitivity analyses. Conclusions: In this large RCT of a novel application of telemedicine-based remote monitoring and decision support using real-time alerts and case reviews, we found no significant differences in postoperative outcomes. Large-scale intraoperative telemedicine is feasible, and we suggest future avenues where it may be impactful.

Perioperative mental health intervention for depression and anxiety symptoms in older adults study protocol: design and methods for three linked randomised controlled trials.

INTRODUCTION: Preoperative anxiety and depression symptoms among older surgical patients are associated with poor postoperative outcomes, yet evidence-based interventions for anxiety and depression have not been applied within this setting. We present a protocol for randomised controlled trials (RCTs) in three surgical cohorts: cardiac, oncological and orthopaedic, investigating whether a perioperative mental health intervention, with psychological and pharmacological components, reduces perioperative symptoms of depression and anxiety in older surgical patients. METHODS AND ANALYSIS: Adults ≥60 years undergoing cardiac, orthopaedic or oncological surgery will be enrolled in one of three-linked type 1 hybrid effectiveness/implementation RCTs that will be conducted in tandem with similar methods. In each trial, 100 participants will be randomised to a remotely delivered perioperative behavioural treatment incorporating principles of behavioural activation, compassion and care coordination, and medication optimisation, or enhanced usual care with mental health-related resources for this population. The primary outcome is change in depression and anxiety symptoms assessed with the Patient Health Questionnaire-Anxiety Depression Scale from baseline to 3 months post surgery. Other outcomes include quality of life, delirium, length of stay, falls, rehospitalisation, pain and implementation outcomes, including study and intervention reach, acceptability, feasibility and appropriateness, and patient experience with the intervention. ETHICS AND DISSEMINATION: The trials have received ethics approval from the Washington University School of Medicine Institutional Review Board. Informed consent is required for participation in the trials. The results will be submitted for publication in peer-reviewed journals, presented at clinical research conferences and disseminated via the Center for Perioperative Mental Health website. TRIAL REGISTRATION NUMBERS: NCT05575128, NCT05685511, NCT05697835, pre-results.

Expanding Critical Care Delivery beyond the Intensive Care Unit: Determining the Design and Implementation Needs for a Tele-Critical Care Consultation Service.

BACKGROUND: Unplanned intensive care unit (ICU) admissions from medical/surgical floors and increased boarding times of ICU patients in the emergency department (ED) are common; approximately half of these are associated with adverse events. We explore the potential role of a tele-critical care consult service (TC3) in managing critically ill patients outside of the ICU and potentially preventing low-acuity unplanned admissions and also investigate its design and implementation needs. METHODS: We conducted a qualitative study involving general observations of the units, shadowing of clinicians during patient transfers, and interviews with clinicians from the ED, medical/surgical floor units and their ICU counterparts, tele-ICU, and the rapid response team at a large academic medical center in St. Louis, Missouri, United States. We used a hybrid thematic analysis approach supported by open and structured coding using the Consolidated Framework for Implementation Research (CFIR). RESULTS: Over 165 hours of observations/shadowing and 26 clinician interviews were conducted. Our findings suggest that a tele-critical care consult (TC3) service can prevent avoidable, lower acuity ICU admissions by offering a second set of eyes via remote monitoring and providing guidance to bedside and rapid response teams in the care delivery of these patients on the floor/ED. CFIR-informed enablers impacting the successful implementation of the TC3 service included the optional and on-demand features of the TC3 service, around-the-clock availability, and continuous access to trained critical care clinicians for avoidable lower acuity (ALA) patients outside of the ICU, familiarity with tele-ICU staff, and a willingness to try alternative patient risk mitigation strategies for ALA patients (suggested by TC3), before transferring all unplanned admissions to ICUs. Conversely, the CFIR-informed barriers to implementation included a desire to uphold physician autonomy by floor/ED clinicians, potential role conflicts with rapid response teams, additional workload for floor/ED nurses, concerns about obstructing unavoidable, higher acuity admissions, and discomfort with audio-visual tools. To amplify these potential enablers and mitigate potential barriers to TC3 implementation, informed by this study, we propose two key characteristics-essential for extending the delivery of critical care services beyond the ICU-underlying a telemedicine critical care consultation model including its virtual footprint and on-demand and optional service features. CONCLUSION: Tele-critical care represents an innovative strategy for delivering safe and high-quality critical care services to lower acuity borderline patients outside the ICU setting.

A Perioperative Mental Health Intervention for Depressed and Anxious Older Surgical Patients: Results From a Feasibility Study.

OBJECTIVES: The perioperative period is challenging and stressful for older adults. Those with depression and/or anxiety have an increased risk of adverse surgical outcomes. We assessed the feasibility of a perioperative mental health intervention composed of medication optimization and a wellness program following principles of behavioral activation and care coordination for older surgical patients. METHODS: We included orthopedic, oncologic, and cardiac surgical patients aged 60 and older. Feasibility outcomes included study reach, the number of patients who agreed to participate out of the total eligible; and intervention reach, the number of patients who completed the intervention out of patients who agreed to participate. Intervention efficacy was assessed using the Patient Health Questionnaire for Anxiety and Depression (PHQ-ADS). Implementation potential and experiences were collected using patient surveys and qualitative interviews. Complementary caregiver feedback was also collected. RESULTS: Twenty-three out of 28 eligible older adults participated in this study (mean age 68.0 years, 65% women), achieving study reach of 82% and intervention reach of 83%. In qualitative interviews, patients (n = 15) and caregivers (complementary data, n = 5) described overwhelmingly positive experiences with both the intervention components and the interventionist, and reported improvement in managing depression and/or anxiety. Preliminary efficacy analysis indicated improvement in PHQ-ADS scores (F = 12.13, p <0.001). CONCLUSIONS: The study procedures were reported by participants as feasible and the perioperative mental health intervention to reduce anxiety and depression in older surgical patients showed strong implementation potential. Preliminary data suggest its efficacy for improving depression and/or anxiety symptoms. A randomized controlled trial assessing the intervention and implementation effectiveness is currently ongoing.

User-Centered Design of a Machine Learning Dashboard for Prediction of Postoperative Complications.

BACKGROUND: Machine learning models can help anesthesiology clinicians assess patients and make clinical and operational decisions, but well-designed human-computer interfaces are necessary for machine learning model predictions to result in clinician actions that help patients. Therefore, the goal of this study was to apply a user-centered design framework to create a user interface for displaying machine learning model predictions of postoperative complications to anesthesiology clinicians. METHODS: Twenty-five anesthesiology clinicians (attending anesthesiologists, resident physicians, and certified registered nurse anesthetists) participated in a 3-phase study that included (phase 1) semistructured focus group interviews and a card sorting activity to characterize user workflows and needs; (phase 2) simulated patient evaluation incorporating a low-fidelity static prototype display interface followed by a semistructured interview; and (phase 3) simulated patient evaluation with concurrent think-aloud incorporating a high-fidelity prototype display interface in the electronic health record. In each phase, data analysis included open coding of session transcripts and thematic analysis. RESULTS: During the needs assessment phase (phase 1), participants voiced that (a) identifying preventable risk related to modifiable risk factors is more important than nonpreventable risk, (b) comprehensive patient evaluation follows a systematic approach that relies heavily on the electronic health record, and (c) an easy-to-use display interface should have a simple layout that uses color and graphs to minimize time and energy spent reading it. When performing simulations using the low-fidelity prototype (phase 2), participants reported that (a) the machine learning predictions helped them to evaluate patient risk, (b) additional information about how to act on the risk estimate would be useful, and (c) correctable problems related to textual content existed. When performing simulations using the high-fidelity prototype (phase 3), usability problems predominantly related to the presentation of information and functionality. Despite the usability problems, participants rated the system highly on the System Usability Scale (mean score, 82.5; standard deviation, 10.5). CONCLUSIONS: Incorporating user needs and preferences into the design of a machine learning dashboard results in a display interface that clinicians rate as highly usable. Because the system demonstrates usability, evaluation of the effects of implementation on both process and clinical outcomes is warranted.

Behavioral Mechanisms That Mediate Mental and Physical Health Improvements in People With Chronic Pain Who Receive a Digital Health Intervention: Prospective Cohort Pilot Study.

BACKGROUND: Preliminary evidence suggests that digital mental health intervention (Wysa for Chronic Pain) can improve mental and physical health in people with chronic musculoskeletal pain and coexisting symptoms of depression or anxiety. However, the behavioral mechanisms through which this intervention acts are not fully understood. OBJECTIVE: The purpose of this study was to identify behavioral mechanisms that may mediate changes in mental and physical health associated with use of Wysa for Chronic Pain during orthopedic management of chronic musculoskeletal pain. We hypothesized that improved behavioral activation, pain acceptance, and sleep quality mediate improvements in self-reported mental and physical health. METHODS: In this prospective cohort, pilot mediation analysis, adults with chronic (≥3 months) neck or back pain received the Wysa for Chronic Pain digital intervention, which uses a conversational agent and text-based access to human counselors to deliver cognitive behavioral therapy and related therapeutic content. Patient-reported outcomes and proposed mediators were collected at baseline and 1 month. The exposure of interest was participants' engagement (ie, total interactions) with the digital intervention. Proposed mediators were assessed using the Behavioral Activation for Depression Scale-Short Form, Chronic Pain Acceptance Questionnaire, and Athens Insomnia Scale. Outcomes included Patient-Reported Outcomes Measurement Information System Anxiety, Depression, Pain Interference, and Physical Function scores. A mediation analysis was conducted using the Baron and Kenny method, adjusting for age, sex, and baseline mediators and outcome values. P<.20 was considered significant for this pilot study. RESULTS: Among 30 patients (mean age 59, SD 14, years; 21 [70%] female), the mediation effect of behavioral activation on the relationship between increased intervention engagement and improved anxiety symptoms met predefined statistical significance thresholds (indirect effect -0.4, 80% CI -0.7 to -0.1; P=.13, 45% of the total effect). The direction of mediation effect was generally consistent with our hypothesis for all other proposed mediator or outcome relationships, as well. CONCLUSIONS: In a full-sized randomized controlled trial of patients with chronic musculoskeletal pain, behavioral activation, pain acceptance, and sleep quality may play an important role in mediating the relationship between use of a digital mental health intervention (Wysa for Chronic Pain) and improved mental and physical health. TRIAL REGISTRATION: ClinicalTrials.gov NCT05194722; https://clinicaltrials.gov/ct2/show/NCT05194722.

A multi- and mixed-method adaptation study of a patient-centered perioperative mental health intervention bundle.

BACKGROUND: Anxiety and depression are common among older adults and can intensify during perioperative periods, but few mental health interventions are designed for older surgical patients' unique needs. As part of the feasibility trial, we developed and adapted a perioperative mental health (PMH) bundle for older patients comprised of behavioral activation (BA) and medication optimization (MO) to ameliorate anxiety and depressive symptoms before, during, and after cardiac, orthopedic, and oncologic surgery. METHODS: We used mixed-methods including workshop studios with patients, caregivers, clinicians, researchers, and interventionists; intervention refinement and reflection meetings; patient case review meetings; intervention session audio-recordings and documentation forms; and patient and caregiver semi-structured interviews. We used the results to refine our PMH bundle. We used multiple analytical approaches to report the nature of adaptations, including hybrid thematic analysis and content analysis informed by the Framework for Reporting Adaptations and Modifications - Expanded. RESULTS: Adaptations were categorized by content (intervention components), context (how the intervention is delivered, based on the study, target population, intervention format, intervention delivery mode, study setting, study personnel), training, and evaluation. Of 51 adaptations, 43.1% involved content, 41.2% involved context, and 15.7% involved training and evaluation. Several key adaptations were noted: (1) Intervention content was tailored to patient preferences and needs (e.g., rewording elements to prevent stigmatization of mental health needs; adjusting BA techniques and documentation forms to improve patient buy-in and motivation). (2) Cohort-specific adaptations were recommended based on differing patient needs. (3) Compassion was identified by patients as the most important element. CONCLUSIONS: We identified evidence-based mental health intervention components from other settings and adapted them to the perioperative setting for older adults. Informed by mixed-methods, we created an innovative and pragmatic patient-centered intervention bundle that is acceptable, feasible, and responsive to the needs of older surgical populations. This approach allowed us to identify implementation strategies to improve the reach, scalability, and sustainability of our bundle, and can guide future patient-centered intervention adaptations. CLINICAL TRIALS REGISTRATION: NCT05110690 (11/08/2021).

An Intraoperative Telemedicine Program to Improve Perioperative Quality Measures: The ACTFAST-3 Randomized Clinical Trial.

Importance: Telemedicine for clinical decision support has been adopted in many health care settings, but its utility in improving intraoperative care has not been assessed. Objective: To pilot the implementation of a real-time intraoperative telemedicine decision support program and evaluate whether it reduces postoperative hypothermia and hyperglycemia as well as other quality of care measures. Design, Setting, and Participants: This single-center pilot randomized clinical trial (Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments [ACTFAST-3]) was conducted from April 3, 2017, to June 30, 2019, at a large academic medical center in the US. A total of 26 254 adult surgical patients were randomized to receive either usual intraoperative care (control group; n = 12 980) or usual care augmented by telemedicine decision support (intervention group; n = 13 274). Data were initially analyzed from April 22 to May 19, 2021, with updates in November 2022 and February 2023. Intervention: Patients received either usual care (medical direction from the anesthesia care team) or intraoperative anesthesia care monitored and augmented by decision support from the Anesthesiology Control Tower (ACT), a real-time, live telemedicine intervention. The ACT incorporated remote monitoring of operating rooms by a team of anesthesia clinicians with customized analysis software. The ACT reviewed alerts and electronic health record data to inform recommendations to operating room clinicians. Main Outcomes and Measures: The primary outcomes were avoidance of postoperative hypothermia (defined as the proportion of patients with a final recorded intraoperative core temperature >36 °C) and hyperglycemia (defined as the proportion of patients with diabetes who had a blood glucose level ≤180 mg/dL on arrival to the postanesthesia recovery area). Secondary outcomes included intraoperative hypotension, temperature monitoring, timely antibiotic redosing, intraoperative glucose evaluation and management, neuromuscular blockade documentation, ventilator management, and volatile anesthetic overuse. Results: Among 26 254 participants, 13 393 (51.0%) were female and 20 169 (76.8%) were White, with a median (IQR) age of 60 (47-69) years. There was no treatment effect on avoidance of hyperglycemia (7445 of 8676 patients [85.8%] in the intervention group vs 7559 of 8815 [85.8%] in the control group; rate ratio [RR], 1.00; 95% CI, 0.99-1.01) or hypothermia (7602 of 11 447 patients [66.4%] in the intervention group vs 7783 of 11 672 [66.7.%] in the control group; RR, 1.00; 95% CI, 0.97-1.02). Intraoperative glucose measurement was more common among patients with diabetes in the intervention group (RR, 1.07; 95% CI, 1.01-1.15), but other secondary outcomes were not significantly different. Conclusions and Relevance: In this randomized clinical trial, anesthesia care quality measures did not differ between groups, with high confidence in the findings. These results suggest that the intervention did not affect the targeted care practices. Further streamlining of clinical decision support and workflows may help the intraoperative telemedicine program achieve improvement in targeted clinical measures. Trial Registration: ClinicalTrials.gov Identifier: NCT02830126.

Perioperative Anxiety and Depression in Older Adults: Epidemiology and Treatment.

The intervals before and after major surgery is a high-risk period for older adults; in this setting, anxiety and depression are common and serious problems. We comprehensively reviewed current evidence on perioperative anxiety and depression in older adults, focusing on epidemiology, impact, correlates, medication risks, and treatment. Principles of perioperative mental healthcare are proposed based on the findings. Prevalence estimates of clinically significant anxiety and depression range from 5% to 45% for anxiety and 6% to 52% for depression, depending on surgical populations and measurement tools. Anxiety and depression may increase risk for surgical complications and reduce patient participation during rehabilitation. Medical comorbidities, pain, insomnia, cognitive impairment, and delirium are common co-occurring problems. Concomitant uses of central nervous system acting medications (benzodiazepines, anticholinergics, and opioids) amplify the risks of delirium and falls. Based on these findings, we propose that anxiety and depression care should be part of perioperative management in older adults; components include education, psychological support, opioid-sparing pain management, sleep management, deprescribing central nervous system active medications, and continuation and optimization of existing antidepressants. More research is needed to test and improve these care strategies.

Multi-stakeholder perspectives regarding preferred modalities for mental health intervention delivered in the orthopedic clinic: a qualitative analysis.

BACKGROUND: Although depressive and anxious symptoms negatively impact musculoskeletal health and orthopedic outcomes, a gap remains in identifying modalities through which mental health intervention can realistically be delivered during orthopedic care. The purpose of this study was to understand orthopedic stakeholders' perceptions regarding the feasibility, acceptability, and usability of digital, printed, and in-person intervention modalities to address mental health as part of orthopedic care. METHODS: This single-center, qualitative study was conducted within a tertiary care orthopedic department. Semi-structured interviews were conducted between January and May 2022. Two stakeholder groups were interviewed using a purposive sampling approach until thematic saturation was reached. The first group included adult orthopedic patients who presented for management of ≥ 3 months of neck or back pain. The second group included early, mid, and late career orthopedic clinicians and support staff members. Stakeholders' interview responses were analyzed using deductive and inductive coding approaches followed by thematic analysis. Patients also performed usability testing of one digital and one printed mental health intervention. RESULTS: Patients included 30 adults out of 85 approached (mean (SD) age 59 [14] years, 21 (70%) women, 12 (40%) non-White). Clinical team stakeholders included 22 orthopedic clinicians and support staff members out of 25 approached (11 (50%) women, 6 (27%) non-White). Clinical team members perceived a digital mental health intervention to be feasible and scalable to implement, and many patients appreciated that the digital modality offered privacy, immediate access to resources, and the ability to engage during non-business hours. However, stakeholders also expressed that a printed mental health resource is still necessary to meet the needs of patients who prefer and/or can only engage with tangible, rather than digital, mental health resources. Many clinical team members expressed skepticism regarding the current feasibility of scalably incorporating in-person support from a mental health specialist into orthopedic care. CONCLUSIONS: Although digital intervention offers implementation-related advantages over printed and in-person mental health interventions, a subset of often underserved patients will not currently be reached using exclusively digital intervention. Future research should work to identify combinations of effective mental health interventions that provide equitable access for orthopedic patients. TRIAL REGISTRATION: Not applicable.

Perioperative Handoff Enhancement Opportunities Through Technology and Artificial Intelligence: A Narrative Review.

BACKGROUND: Perioperative handoffs occur as patients progress through preoperative, intraoperative, and postoperative phases of care. These may occur between clinicians from the same or different role groups, between different care units, for brief breaks during the course of a surgery, or at shift or service changes. Perioperative handoffs occur during a period of increased vulnerability, as teams must convey critical information at a time of high cognitive load, with many potential distractions. METHODS: A search of MEDLINE was conducted for biomedical literature pertaining to perioperative handoffs and technology, electronic tools, and artificial intelligence. The reference lists of identified articles were reviewed, and additional citations were included if relevant. These articles were abstracted to summarize the current literature, and to frame the opportunity for enhanced opportunities to improve perioperative handoffs through technology and artificial intelligence. RESULTS: Several efforts to date have incorporated electronic tools to improve perioperative handoffs but have been limited by imprecision in selecting handoff elements, increased task burden for clinicians, interrupted workflows, physical barriers, and lack of institutional support for their implementation. At the same time, artificial intelligence (AI) and machine learning (ML) are being applied across healthcare, but their use in and integration into handoff workflows have not yet been studied. Use of existing technology including mobile applications, barcode scanners, and radio-frequency identification (RFID) tags to advance perioperative safety has only begun and similarly has not been applied to handoffs. CONCLUSION: In this narrative review, we synthesize prior research on electronic tools for perioperative handoffs, limitations of current tools and barriers to their implementation, and the use of AI and ML in perioperative care. We then discuss potential opportunities to further integrate healthcare technologies and apply AI-derived solutions in the concept of a "smart handoff" with the aim of reducing harm from handoffs and improving patient safety.

Potential uses of AI for perioperative nursing handoffs: a qualitative study.

Objective: Situational awareness and anticipatory guidance for nurses receiving a patient after surgery are keys to patient safety. Little work has defined the role of artificial intelligence (AI) to support these functions during nursing handoff communication or patient assessment. We used interviews to better understand how AI could work in this context. Materials and Methods: Eleven nurses participated in semistructured interviews. Mixed inductive-deductive thematic analysis was used to extract major themes and subthemes around roles for AI supporting postoperative nursing. Results: Five themes were generated from the interviews: (1) nurse understanding of patient condition guides care decisions, (2) handoffs are important to nurse situational awareness, but multiple barriers reduce their effectiveness, (3) AI may address barriers to handoff effectiveness, (4) AI may augment nurse care decision making and team communication outside of handoff, and (5) user experience in the electronic health record and information overload are likely barriers to using AI. Important subthemes included that AI-identified problems would be discussed at handoff and team communications, that AI-estimated elevated risks would trigger patient re-evaluation, and that AI-identified important data may be a valuable addition to nursing assessment. Discussion and Conclusion: Most research on postoperative handoff communication relies on structured checklists. Our results suggest that properly designed AI tools might facilitate postoperative handoff communication for nurses by identifying specific elevated risks faced by a patient, triggering discussion on those topics. Limitations include a single center, many participants lacking of applied experience with AI, and limited participation rate.

An evidence synthesis on perioperative Handoffs: A call for balanced sociotechnical solutions.

SIGNIFICANCE: Perioperative handoffs interconnect the preoperative, intraoperative, and postoperative phases underlying surgical care to maintain care continuity -yet are prone to coordination and communication failures. OBJECTIVE: To synthesize evidence on factors affecting the safety and quality of perioperative handoff conduct and process. MATERIALS AND METHODS: A search of PubMed, EMBASE, and CINAHL was conducted to include observational, descriptive studies of preoperative, intraoperative, and postoperative handoffs published in English language, peer-reviewed journals. Data analysis was informed by the Systems Engineering Initiative for Patient Safety (SEIPS) framework describing the relationship between the work-system, work processes, and outcomes. Study quality was assessed using the Quality Scoring System. RESULTS: Twenty-three studies were included. Eighteen studies focused on postoperative handoffs, with one on preoperative, three on intraoperative and only one that looked at preoperative/postoperative handoffs combined. The SEIPS framework elucidated the complex inter-related factors (enablers and barriers) related to perioperative handoff safety. While some studies found that the use of standardized handoff tools and protocols and interdisciplinary teamwork were frequently-reported enablers, other studies identified the lack of structured handoff tools and protocols, poor teamwork and communication, and improper use of documentation tools were top-cited barriers affecting handoff quality. Suggestions to ensure handoff safety and quality included implementing structured handoff checklists and protocols and building interprofessional teamwork competencies for effective communication. DISCUSSION AND CONCLUSION: Our review highlights an urgency to develop more holistic sociotechnical solutions that can create and sustain a balance between technical innovations in tools and technologies and the non-technical interventions/training needed to improve interpersonal relations and teamwork competencies - taken together, can improve the quality and safety of perioperative handoff practice.

Multi-stakeholder perspectives regarding preferred modalities for mental health intervention delivered in the orthopedic clinic: A qualitative analysis.

BACKGROUND: Although depressive and anxious symptoms negatively impact musculoskeletal health and orthopedic outcomes, a gap remains in identifying modalities through which mental health intervention can realistically be delivered during orthopedic care. The purpose of this study was to understand orthopedic stakeholders' perspectives regarding the feasibility, acceptability, and usability of digital, printed, and in-person intervention modalities to address mental health as part of orthopedic care. METHODS: This single-center, qualitative study was conducted within the orthopedic department of a tertiary care center. Semi-structured interviews were conducted between January and May 2022. Two stakeholder groups were interviewed using a purposive sampling approach until thematic saturation was reached. The first group included adult orthopedic patients who presented for management of ≥ 3 months of neck or back pain. The second group included early, mid, and late career orthopedic clinicians and support staff members. Stakeholders' interview responses were analyzed using deductive and inductive coding approaches followed by thematic analysis. Patients also performed usability testing of one digital and one printed mental health intervention. RESULTS: Patients included 30 adults out of 85 approached (mean (SD) age 59 (14) years, 21 (70%) women, 12 (40%) non-White). Clinical team stakeholders included 22 orthopedic clinicians and support staff members out of 25 approached (11 (50%) women, 6 (27%) non-White). Clinical team members perceived a digital mental health intervention to be feasible and scalable to implement, and many patients appreciated that the digital modality offered privacy, immediate access to resources, and the ability to engage during non-business hours. However, stakeholders also expressed that a printed mental health resource is still necessary to meet the needs of patients who prefer and/or can only engage with tangible, rather than digital, mental health resources. Many clinical team members expressed skepticism regarding the current feasibility of scalably incorporating in-person mental health support into orthopedic care. CONCLUSIONS: Although digital intervention offers implementation-related advantages over printed and in-person mental health interventions, a subset of often underserved patients will not currently be reached using exclusively digital intervention. Future research should work to identify combinations of effective mental health interventions that provide equitable access for orthopedic patients. TRIAL REGISTRATION: Not applicable.