Health Care Delivery Research Articles

CommSense: A Wearable Sensing Computational Framework for Evaluating Patient-Clinician Interactions

Quality patient-provider communication is critical to improve clinical care and patient outcomes. While progress has been made with communication skills training for clinicians, significant gaps exist in how to best monitor, measure, and evaluate the implementation of communication skills in the actual clinical setting. Advancements in ubiquitous technology and natural language processing make it possible to realize more objective, real-time assessment of clinical interactions and in turn provide more timely feedback to clinicians about their communication effectiveness. In this paper, we propose CommSense, a computational sensing framework that combines smartwatch audio and transcripts with natural language processing methods to measure selected "best-practice'' communication metrics captured by wearable devices in the context of palliative care interactions, including understanding, empathy, presence, emotion, and clarity. We conducted a pilot study involving N=40 clinician participants, to test the technical feasibility and acceptability of CommSense in a simulated clinical setting. Our findings demonstrate that CommSense effectively captures most communication metrics and is well-received by both practicing clinicians and student trainees. Our study also highlights the potential for digital technology to enhance communication skills training for healthcare providers and students, ultimately resulting in more equitable delivery of healthcare and accessible, lower cost tools for training with the potential to improve patient outcomes.

Exploring challenges and enablers for community pharmacists using electronic prescriptions (Wasfaty) in Makkah region, Saudi Arabia: a qualitative study using the theoretical domains framework

BackgroundTransition to electronic prescribing (e-prescribing) systems, such as Wasfaty, represents a significant advancement in healthcare. Introduced by the Saudi Arabian Ministry of Health in 2019, Wasfaty aims to enhance medication availability and streamline healthcare delivery. This study explores the challenges and enablers community pharmacists face when using the Wasfaty system in Saudi Arabia. This study uses the Theoretical Domains Framework (TDF) to analyse behavioural and contextual factors influencing pharmacists’ adoption of electronic prescriptions. TDF identifies key challenges and enablers across multiple behavioural domains, making it well-suited for understanding complex healthcare implementation processes.MethodsA qualitative study design was employed using the Theoretical Domains Framework (TDF) to understand factors affecting Wasfaty use. Participants were purposively sampled, focusing on community pharmacists experienced with Wasfaty prescriptions. Recruitment and interviews occurred from June to August 2024. Data saturation was achieved at 18 interviews. Transcripts were coded and mapped into TDF domains to identify barriers and enablers.ResultsFive key TDF domains influenced Wasfaty use: environmental context and resources; social influences; beliefs about capabilities; social/professional role and identity; and knowledge. Challenges included high prescription volumes, medication shortages, technical difficulties, resistance from elderly patients, and inconsistent training. Some pharmacists reported inadequate training as a barrier, while others highlighted effective programs as enablers.ConclusionSignificant barriers, such as insufficient training and high prescription volumes, impede effective Wasfaty use. However, continuous training, prior experience with electronic systems, and organisational support were crucial enablers. Addressing these challenges through targeted interventions can enhance e-prescription efficiency, improving patient care and outcomes. Findings underscore the importance of ongoing professional development and supportive work environments in fostering pharmacists’ competence in electronic systems.

Claim Pricing in Claim Adjudication Process

The claim adjudication process is a critical function within healthcare organizations, determining the legitimacy and value of claims submitted for payment. This paper explores the pricing logic applied during claim adjudication, focusing on the algorithms and methodologies used to evaluate claims effectively. By analyzing the impact of pricing logic on the overall efficiency and accuracy of claim processing, this study aims to provide insights that can enhance healthcare reimbursement practices and improve operational efficiency. Keywords – Claim Adjudication, Claim Pricing, Healthcare Organization, Reimbursement, Algorithms.

Support Experiences and Wishes of Bereaved Parents After the Loss of Their Child to Cancer.

The death of a child has a tremendous impact on parents' lives. The experience of parents who have lost a child to cancer may differ from other bereavement experiences, including other childhood and adulthood causes of death, because of the uncertainty of the prognosis, the aggressive treatment, and the potential for regret about treatment decisions. Bereavement care remains scarce, and effective interventions to meet the diverse needs of parents have not been defined. To provide insights on bereaved parents' experiences, their needs, and wishes of support following the loss of their child to cancer. We conducted 18 qualitative, in-depth, semi-structured interviews with 23 bereaved parents (seven fathers, 16 mothers), and used reflexive thematic analysis to analyze the data. Parents received both informal and professional support. Regarding informal support, parents expressed a high level of ambivalence rooted in grief illiteracy. Parents also recognized their own struggles to express what forms of informal support they would have liked to receive. Support provided by healthcare professionals, institutions, and organizations involved in the children's care or in bereavement was inconsistent due to personnel time constraints, interpersonal relationships, or disruptions due to the COVID-19 pandemic. These factors could result in parents not having access to certain forms of support or not receiving long-term support. Improving grief literacy may strengthen informal support and make discussions of grief and death less taboo. Institutional policies, training, and networking may help to ensure that support provided by healthcare professionals, institutions, and organizations is less vulnerable to inconsistencies.

Medical students‘ leadership competence in health care: development of a self-assessment scale

BackgroundMedical leadership plays an increasing role already in early career stages. Undergraduate medical students in the transition to postgraduate education feel not well prepared for their leadership roles. While leadership curricula have been developed, instruments for students’ self-assessment of leadership competences as part of their professional development are still missing. The aim of our study was to develop a self-assessment scale for undergraduate medical students’ leadership competences.MethodsThe medical leadership competence scale (MeLeCoS) for undergraduate medical students was developed in twelve steps. For item generation, we employed the Medical Leadership Competence Framework (MLCF), which is also used as a framework for many leadership curricula and includes five leadership domains for three fields of education: undergraduate education, postgraduate education, and continuing practice. In a pretest, 67 items were tested with n = 88 undergraduate medical students. For content validation we performed group discussions with a total of 17 students. After item reduction a test-version with 45 items and a 5-point Likert scale (1: ‘never’, 2: ‘rarely’, 3: ‘sometimes’, 4: ‘often’, 5: ‘always’) was used in a test-sample of final-year students (n = 129). Descriptive statistics and factor analyses were performed.ResultsThe final version of the MeLeCoS includes 37 items and the scale’s Cronbach’s alpha was 0.87. Six factors could be identified and two of them, respectively, represent leadership aspects from the following three areas: (1) the medical students themselves, (2) the interrelation of the medical students with a healthcare organisation regarding general management and improvement, and (3) general leadership aspects of medical students within undergraduate medical studies and the healthcare system. The overall mean of the MeLeCoS was 3.50 ± 0.39. Factor 2 (‘Demonstrating responsible behaviour and shaping relations’) reached the highest mean (4,36 ± 0.37) and factor 5 (‘Promoting improvement and innovation in undergraduate medical education’ the lowest (1.91 ± 0.87).ConclusionsThe medical leadership competence self-assessment scale (MeLeCoS) is a reliable instrument for undergraduate medical students’ self-assessment of leadership competence with good content validity. It could be used for students’ self-reflection on leadership competences in addition to rater-based assessments in leadership curricula and for longitudinal development of students’ professional identity.

Hybrid managers in an evolving healthcare: Does gender matter?

Hybrid managers have the potential to respond to the need for more integrated, responsive and accountable healthcare. Scholars have studied the antecedents of hybridization, but the role of gender has been neglected. Therefore, we study whether and how gender impacts on the way in which medical professionals exercise their managerial role. We adopted a qualitative approach in order to gain an in-depth understanding of the specificities of women hybrids. Data was collected through semi-structured interviews, focusing on hybrids in Italy in the field of neurology. We found that women hybrids show specific abilities and motivations, but they also encounter a specific lack of opportunities. Women hybrid managers appear well positioned to foster the evolution of professionalism, but healthcare organizations should implement policies and practices to effectively support them. While existing research has treated hybrid managers as a homogenous group, we underline the specificities of women hybrids. They can support the evolution of healthcare organizations towards logics of service integration, user centricity, and staff engagement. Therefore, our findings have important theoretical and practical implications for health policy and management.

Effects of COVID-19 pandemic on psychiatric and psychological consultation-liaison contacts in a general hospital in North-East of Italy: a retrospective study

BackgroundThe COVID-19 pandemic has prompted significant changes in healthcare, particularly affecting psychiatric and psychological Consultation-Liaison (CL) services in general hospital settings.AimTo assess the effects of COVID-19-related restrictions on utilization of psychiatric and psychological CL services in Northeast Italy during 2020, and to compare it to the use of services in the previous year (2019).MethodsThe study collected data on psychiatric and psychological consultations in 2019 and 2020 from a hospital database. It categorizes consultations by type of patient (inpatient or outpatient) and referral source (hospital wards, general practitioners, other specialists). Pandemic-related restrictions were classified as “lockdown,” “intermediate restrictions,” and “no or reduced restrictions” based on the Covid Stringency Index (CSI). Poisson regression models were employed to analyze the data.ResultsThe findings reveal a significant 28% increase in the number of psychiatric and psychological consultations in 2020. Consultations for outpatients increased by 51%, while those for inpatients decreased by 11%. However, the lockdown and intermediate restriction phases were deemed responsible of a decrease of 42.9% and 19.5% in consultations respectively.DiscussionThis study highlights the persistent psychological burden during the COVID-19 pandemic, alongside reduced CL services due to lockdown measures. Integrating telemedicine into these types of services becomes imperative for meeting patient needs during restrictions. These findings can inform policies and practices to improve effective mental health care delivery during and beyond pandemics. Future research should explore the impact of pandemic-related restrictions on mental healthcare across settings and clinical factors affecting service accessibility.

Reasons for 90-day emergency department visits after primary knee arthroplasty.

Postoperative visits to the emergency department (ED) generate additional costs on health care systems and consume already limited resources. We sought to determine the rate and reasons why patients who underwent primary knee arthroplasty returned to the ED within 90 days of postoperative discharge, which could guide the development of preventative measures. We identified patients who underwent primary knee arthroplasty at 2 hospitals in Nova Scotia, Canada, between April 2021 and March 2022 and who had an ED visit within 90 days of postoperative discharge. We reviewed data for timing and reason for ED visits. Of 687 patients who had primary knee arthroplasty surgeries, 145 (21.1%) patients visited the ED within 90 days of postoperative discharge. Most visits occurred in the early postoperative period, predominantly for surgical reasons (94.7% within 7 days) and shifting toward medical reasons over time. Pain was the most common surgical reason for ED visits (15.9%), followed by swelling (9.7%), and hematoma drainage (9.7%). Understanding the reasons for postoperative ED visits after knee arthroplasty is important in developing strategies to reduce ED overcrowding and improve patient outcomes. Implementing targeted interventions, such as enhanced pain management and patient education, may help alleviate the burden on EDs, reduce costs, and improve overall health care delivery for patients undergoing knee arthroplasty.

Patient Health Record Protection Beyond the Health Insurance Portability and Accountability Act: Mixed Methods Study

Background The security and privacy of health care information are crucial for maintaining the societal value of health care as a public good. However, governance over electronic health care data has proven inefficient, despite robust enforcement efforts. Both federal (HIPAA [Health Insurance Portability and Accountability Act]) and state regulations, along with the ombudsman rule, have not effectively reduced the frequency or impact of data breaches in the US health care system. While legal frameworks have bolstered data security, recent years have seen a concerning increase in breach incidents. This paper investigates common breach types and proposes best practices derived from the data as potential solutions. Objective The primary aim of this study is to analyze health care and hospital breach data, comparing it against HIPAA compliance levels across states (spatial analysis) and the impact of the Omnibus Rule over time (temporal analysis). The goal is to establish guidelines for best practices in handling sensitive information within hospitals and clinical environments. Methods The study used data from the Department of Health and Human Services on reported breaches, assessing the severity and impact of each breach type. We then analyzed secondary data to examine whether HIPAA’s storage and retention rule amendments have influenced security and privacy incidents across all 50 states. Finally, we conducted a qualitative analysis of textual data from vulnerability and breach reports to identify actionable best practices for health care settings. Results Our findings indicate that hacking or IT incidents have the most significant impact on the number of individuals affected, highlighting this as a primary breach category. The overall difference-in-differences trend reveals no significant reduction in breach rates (P=.50), despite state-level regulations exceeding HIPAA requirements and the introduction of the ombudsman rule. This persistence in breach trends implies that even strengthened protections and additional guidelines have not effectively curbed the rising number of affected individuals. Through qualitative analysis, we identified 15 unique values and associated best practices from industry standards. Conclusions Combining quantitative and qualitative insights, we propose the “SecureSphere framework” to enhance data security in health care institutions. This framework presents key security values structured in concentric circles: core values at the center and peripheral values around them. The core values include employee management, policy, procedures, and IT management. Peripheral values encompass the remaining security attributes that support these core elements. This structured approach provides a comprehensive security strategy for protecting patient health information and is designed to help health care organizations develop sustainable practices for data security.

Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions

The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and policymakers about the potential and challenges of integrating AI into audiological practice. The PubMed, Cochrane, and Google Scholar databases were searched for articles published in English from 1990 to 2024 with the following query: “(audiology) AND (“artificial intelligence” OR “machine learning” OR “deep learning”)”. The PRISMA extension for scoping reviews (PRISMA-ScR) was followed. The database research yielded 1359 results, and the selection process led to the inclusion of 104 manuscripts. The integration of AI in audiology has evolved significantly over the succeeding decades, with 87.5% of manuscripts published in the last 4 years. Most types of AI were consistently used for specific purposes, such as logistic regression and other statistical machine learning tools (e.g., support vector machine, multilayer perceptron, random forest, deep belief network, decision tree, k-nearest neighbor, or LASSO) for automated audiometry and clinical predictions; convolutional neural networks for radiological image analysis; and large language models for automatic generation of diagnostic reports. Despite the advances in AI technologies, different ethical and professional challenges are still present, underscoring the need for larger, more diverse data collection and bioethics studies in the field of audiology.

Networks for healthcare delivery: asystematic literature review.

Network configurations have been proposed as an efficient form of organisation and a promising area of research; however, a lack of conceptual clarity can be noted. The purpose of this review is to allow for a broad appreciation of network configurations and provide guidance for future studies of the concept. A systematic literature review was conducted based on the PRISMA method; Scopus, Web of Science, PubMed and the Cochrane Library were searched for conference proceedings and journal articles describing organisational networks to integrate resources aimed at care delivery. Around 80 articles were included in the final review and analysed thematically and by use of bibliographic coupling. The last decades have seen an increase in the frequency of articles describing networks for healthcare delivery. The most common contexts are care for multiple and/or long-term conditions. Three clusters of articles were found, corresponding to different conceptualisations of networks in healthcare: efficiency-enhancing cooperation, efficiency-enhancing integration and involvement for cocreation. To increase conceptual clarity and allow the research on network configurations in healthcare to produce meta-learnings and guidance to practice, scholars are advised to provide ample descriptions of studied networks and relate them to established network classifications. The current review has only included articles including networks as a key concept, which provides a focused overview of the use of network configurations but limits the insights into similar approaches not described explicitly as networks.

Measuring Hospital Inpatient Procedure Access Inequality in the United States

Abstract Geographic disparities in access to inpatient procedures are a significant issue within the U.S. healthcare system. This study introduces the Procedure Access Inequality (PAI) index, a standardized metric to quantify these disparities while adjusting for disease prevalence. Using data from the Healthcare Cost and Utilization Project State Inpatient Databases, we analyzed inpatient procedure data from 18 states between 2016 and 2019. The PAI index reveals notable variability in access inequality across different procedures, with minimally invasive and newer procedures exhibiting higher inequality. Key findings indicate that procedures such as skin grafts and minimally invasive gastrectomy have the highest PAI scores, while cesarean sections and percutaneous coronary interventions have the lowest. The study highlights that higher inequality is associated with greater market concentration and in particular, fewer hospitals offering these procedures. These findings emphasize the need for targeted policy interventions to address procedural access disparities to promote more equitable healthcare delivery across the United States.

Research on healthcare data sharing in the context of digital platforms considering the risks of data breaches

BackgroundWithin China's healthcare landscape, the sharing of medical data has emerged as a pivotal force propelling advancements in the insurance sector and enhancing patient engagement with healthcare services. However, medical institutions often exhibit reluctance toward data sharing due to apprehensions regarding data security and privacy safeguards. To navigate this conundrum, our research introduces and empirically validates a model grounded in evolutionary game theory, offering a robust theoretical framework and actionable strategies for facilitating healthcare data sharing while harmonizing the dual imperatives of data utility and privacy preservation.MethodsIn this paper, we construct an evolutionary game model involving medical institutions, big data innovation platforms, and insurance companies within the context of digital platforms. The model integrates exogenous causes of data breaches, endogenous causes of data breaches, compensation payments, government penalties, subsidies, unreasonable fees, claims efficiency, and insurance fraud.ResultsThe stability analysis of the evolutionary game identifies eight equilibrium points among medical institutions, platforms, and insurance companies. Numerical simulations demonstrate convergence toward strategy E7 = (0, 0, 1), suggesting a trend for medical institutions to adopt a fully anonymous information-sharing strategy, platforms to implement strict regulation, and insurance companies to opt for an auditing approach. Sensitivity analysis reveals that the parameters selected in this study significantly influence the players' behavioral choices and the game's equilibria.ConclusionsWhen breaches occur, medical institutions tend to seek co-sharing between platforms and insurance companies. This promotes enhanced regulation by platforms and incentivizes insurance companies to perform audits. If the responsibility for the breach is attributed to the platform or the insurance company, the liability sharing system will push healthcare organizations to choose a fully anonymous information sharing strategy. Otherwise, medical institutions will choose partially anonymous information sharing for more benefits. In case of widespread data leakage, the amount of compensation shall augment, and the role of compensation shall replace the role of government supervision. Then, the government shall penalize them, which shall reduce the motivation of each subject.

Ensuring Safe Practice by Late Career Physicians: Institutional Policies and Implementation Experiences.

Late career physicians (LCPs; physicians working beyond age 65 to 75 years) may be at higher risk for delivering unsafe care. To oversee LCPs, some health care organizations (HCOs) have adopted LCP policies requiring cognitive, physical, and practice performance screening assessments. Despite recent controversies, little is known about the content and implementation of such policies. To characterize key features of LCP policies and the perspectives of medical leaders responsible for policy development and implementation. Mixed-methods study using content analysis and key informant interviews. 29 U.S. HCOs with LCP policies active in 2020. 21 purposively sampled interviewees in physician leadership roles at 18 HCOs. Descriptive statistics of policy features and content analysis of interviews. Although policies had many commonalities-mandatory universal screening at a trigger age around 70 years, a strategy of screening followed by in-depth assessment of positive results, and commitment to patient safety as the key motive-they varied substantially in the testing required, funding, processes after a positive screening result, and decision making around concerning results. Policies prioritized institutional discretion in interpreting and responding to test results; many lacked clear language about appeals or other procedural protections for physicians. Leaders were generally satisfied with policies but reported preemptive retirements as physicians approached the screening age and cautioned that substantial investment in cultivating physicians' buy-in was required for successful rollout. Sampled policies and interviews may not be representative of all HCOs. The analysis excluded the experiences of HCOs that tried and failed to implement LCP screening. Policies about LCPs are considered successful by institutional leaders. Policy variations and early adopters' implementation experiences highlight opportunities to improve physician acceptance and program rigor. The Greenwall Foundation.

RECOMMENDATIONS ON THE ORGANIZATION OF CARE IN PRIMARY HEALTH CARE IN PRISONS

The research aims to develop recommendations for the organization of care in primary health care in prisons. An integrative review was used, which covered 267 articles in databases such as SciELO, PubMed and LILACS, resulting in the final selection of 12 studies. The research included articles published between 2019 and 2024, with some texts from previous years due to their methodological relevance. The main findings highlight the importance of intersectorality, continuous training of professionals and gender-sensitive health policies. Challenges include the precariousness of working conditions and the need to adapt the PNAISP to better serve different groups, especially women. The conclusion stated that the organization of health care in primary care in prisons requires an integrated and intersectoral approach, based on evidence and solid public policies. The work emphasizes the importance of humanized practices and collaboration between health and justice to ensure equity in access to health for the population deprived of liberty (PDL).

AI’s pivotal impact on redefining stakeholder roles and their interactions in medical education and health care

Artificial Intelligence (AI) has the potential to revolutionize medical training, diagnostics, treatment planning, and healthcare delivery while also bringing challenges such as data privacy, the risk of technological overreliance, and the preservation of critical thinking. This manuscript explores the impact of AI and Machine Learning (ML) on healthcare interactions, focusing on faculty, students, clinicians, and patients. AI and ML's early inclusion in the medical curriculum will support student-centered learning; however, all stakeholders will require specialized training to bridge the gap between medical practice and technological innovation. This underscores the importance of education in the ethical and responsible use of AI and emphasizing collaboration to maximize its benefits. This manuscript calls for a re-evaluation of interpersonal relationships within healthcare to improve the overall quality of care and safeguard the welfare of all stakeholders by leveraging AI's strengths and managing its risks.

Linking theory and practice to advance sustainable healthcare: the development of maturity model version 1.0.

Climate change and increased awareness of planetary health have made reducing ecological footprints a priority for healthcare organizations. However, improving healthcare's environmental impact remains difficult. Numerous researchers argue these difficulties are caused by healthcare's environmental impact being multidimensional, influenced throughout the healthcare chain, and often has downstream consequences that are hard to identify or to measure. Even though existing research describes many successful approaches to reduce healthcare's environmental impact, a robust multidimensional framework to assess this impact is lacking. This research aims at developing a maturity model for sustainable healthcare that could be used for self-assessment by healthcare professionals to identify improvement actions and for sharing best practices in environmental sustainability. A design-oriented approach for maturity model development was combined with an expert panel and six case studies to develop, refine and expand the maturity model for environmentally sustainable healthcare. A maturity model was developed containing four domains: 'Governance', 'Organization Structures', 'Processes', and 'Outcomes and Control'. Applying the model in real-world environments demonstrated the model's understandability, ease of use, usefulness, practicality and ability to identify improvement actions for environmental sustainability in healthcare organizations. This study found that healthcare practitioners could apply the maturity model developed and tested in this study in several hours without training to help them gain valuable insights into the environment footprint of the healthcare setting they worked in. Systematically implementing the model developed in this study could help address the urgent need to mitigate the substantial environmental impact of healthcare. These implementations can help evaluate and improve the maturity model.

Predicting dropout and non-response to psychotherapy for personality disorders: A study protocol focusing on therapist, patient, and the therapeutic relationship

BackgroundThe abandonment of psychotherapeutic treatments is influenced by various factors, including patient characteristics, therapist traits, and the therapeutic relationship. Despite the well-documented importance of these factors, limited empirical research has focused on the role of the therapeutic relationship and the characteristics of therapist-patient dyads in predicting treatment dropout. This study protocol outlines a longitudinal research project aimed at predicting dropout and non-response in psychotherapy for individuals with personality disorders. The research seeks to identify predictive factors related to psychotherapy outcomes, focusing on patient, therapist, and dyadic elements. Specifically, the study will examine the influence of therapist characteristics (e.g., personality traits, countertransference, responsiveness) on treatment outcomes, explore the impact of relational factors (e.g., treatment expectations, epistemic trust, therapeutic alliance) on therapy effectiveness, and assess how the therapeutic alliance within therapist-patient dyads affects the likelihood of dropout and non-response.MethodsThe longitudinal study will include 100 therapist-patient dyads (200 participants) recruited from various Mental Health Services in Milan, Italy. Validated instruments will be administered to both patients and therapists at four-time points: T0 (baseline), T1 (3 months), T2 (6 months), and T3 (1 year). Data will be collected at baseline and at the one-year mark to evaluate the relationships between therapist, patient, and dyadic factors and treatment outcomes.DiscussionIdentifying predictive variables associated with high dropout rates can help preempt treatment discontinuation, reducing the financial and operational burdens on mental health services. Understanding these factors will enable the development of targeted interventions to improve treatment engagement and reduce attrition. This approach could enhance outcomes for individuals with personality disorders and lead to more efficient resource allocation and sustainable delivery of mental health care.

The Application of Trauma-Informed Care to Health Care for Military-Connected Individuals.

Military families face unique stressors beyond civilian life, such as deployments, frequent relocations, and the potential for combat, all of which can significantly impact well-being. A trauma-informed care (TIC) approach to military medicine is paramount; however, a critical gap exists, with no published curricula to guide practitioners in employing TIC in the care of military-connected individuals. We delivered a 50-minute interactive and virtual session to second-year medical students at the Uniformed Services University (USU) that reviewed the neurobiology of adversity and the relevance of TIC in caring for military-connected populations. Participants completed a 14-question pre- and posttest on perceived knowledge, attitudes, practice, and confidence, as well as posttest questions evaluating session quality. The USU Institutional Review Board approved this evaluation. One hundred sixty medical students participated in the session, with 78 matched pre- and posttest responses. We observed a statistically significant pre-post improvement (p ≤ .05) in all category scores, with the largest changes in knowledge (1.33) and confidence (1.33). On a 5-point Likert scale, with 5 being best, mean scores for overall quality of the session and relevance of the material to participants' learning and future practice were 3.95 and 4.20, respectively. By equipping health care providers with knowledge and confidence to apply TIC in military medicine, we can improve the well-being of service members and their families across both military and civilian health care settings. Broader implementation of this program has potential to improve patient outcomes and overall health care delivery for this population.

Clinic-Level Predictors of Psychotherapy Dosage in the Military Health System.

This study aimed to describe the demand for, supply of, and clinic processes associated with behavioral health care delivery in the Military Health System and to examine the clinic-level factors associated with receipt of a minimally adequate dosage of psychotherapy. This retrospective study used administrative behavioral health data from eight military treatment facilities (N=25,433 patients; N=241,028 encounters) that were participating in a larger implementation study of evidence-based psychotherapy for posttraumatic stress disorder. Minimally adequate dosage of psychotherapy was defined in two ways: at least three sessions within a 90-day period and at least six sessions within a 90-day period. The authors then used a path model to examine clinic-level factors hypothesized to predict psychotherapy dosage, including care demand, supply, and processes. Patients had an average of 2.5 psychotherapy appointments per quarter. Wait times for intake, between intake and the first psychotherapy session, and between follow-up sessions all averaged 17 days or longer. Path modeling showed that a higher patient-to-encounter ratio was associated with a longer wait time between follow-up psychotherapy appointments. In turn, a longer wait time between appointments was associated with a lower probability of receiving an adequate dosage of psychotherapy. However, a greater proportion of care delivered in groups was associated with a greater probability of receiving at least six sessions of psychotherapy. Receipt of a minimally adequate dosage of psychotherapy in the Military Health System is hindered by clinic staffing and workflows that increase wait times between follow-up psychotherapy appointments.