March 2025 Dallas Medical Journal

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TRENDS IN HEALTHCARE Redefining Acute Virtual Care for Overburdened Health Systems

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March 2025

March 2025

Vol. 111 No. 03

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The Digital Health Competencies in Medical Education Framework

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“legislative advertising.” The law requires disclosure of the name and address of the person who contracts with the printer to publish legislative advertising in the DMJ: Jon R. Roth, MS, CAE, Executive Vice President & CEO, DCMS, PO Box 4680, Dallas, TX 75208-0680. Dallas Medical Journal (ISSN 0011-586X) is published monthly by Dallas County Medical Society, 140 E. 12th St., Dallas, TX 75203. (214) 948-3622. Postmaster - Send address changes to: Dallas Medical Journal | PO Box 4680 | Dallas, TX 75208-0680. Periodicals postage paid at Dallas, TX 75260 and additional post offices.

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recognition for their lifesaving work. The date was selected to commemorate Dr. Crawford W. Long’s March 30, 1842, groundbreaking use of general anesthesia in surgery. Over the years, this observance gained momentum, finally receiving national recognition when President George H.W. Bush officially designated it a national day of observance in 1990.

The Fight for Physician Autonomy This month’s DCMS Journal explores the major trends shaping healthcare today. From precision medicine and artificial intelligence (AI) to telehealth, wearable technologies, remote monitoring, regenerative medicine, and advanced genomic research, technology is transforming medical care. However, there is a growing concern that the practice of medicine is becoming more of a business transaction than a patient-centered profession. Decision-making is increasingly influenced by corporate and bureaucratic forces rather than the expertise and judgment of doctors. The heart of medicine lies in human connection, ethical decision-making, and prioritizing the wellbeing of patients above all else. However, growing interference from insurance companies, hospital administrators, private equity firms, and regulatory policies threatens the very foundation of medical autonomy.

National Doctors’ Day Standing Up for Medical Autonomy Shaina Drummond, MD MARCH 30 WAS NATIONAL DOCTORS’ DAY, a time to celebrate the dedication, resilience, and selfless commitment of physicians. Every day, doctors put their years of education, continuous learning, and relentless effort into providing quality care for their patients. I want to take a moment to recognize each of you—your passion, your sacrifices, and your unwavering dedication to medicine.

Doctors play central roles in our healthcare system, seeing over a billion patients annually in the U.S. alone, according to the Centers for Disease Control and Prevention (CDC). early half of these visits are to primary care physicians, emphasizing the vital roles they play in keeping communities healthy. The idea of National Doctors’ Day originated in 1933, thanks to Eudora Brown Almond, the wife of a Georgia physician, who believed doctors deserved more March 2025

The Impact of Insurance on Medical Decision-Making One of the biggest obstacles to physician autonomy is the interference of insurance companies in clinical decision-making.

Prior authorization requirements, inadequate network access, restrictive formularies, and reimbursement limitations dictate which treatments, medications, and procedures patients can access, often superseding the clinical judgment of physicians.

Studies show these administrative burdens delay treatment, increase patient suffering, and contribute significantly to physician burnout. Instead of focusing on medicine, doctors are buried in paperwork and fighting against red tape.

One way to combat this? Push for policy changes that simplify prior authorization, promote price transparency, and ensure that medical expertise—not financial incentives—dictates patient care.

Hospitals and the Business of Healthcare Another challenge physicians face is the increasing corporatization of healthcare. Many hospitals today prioritize efficiency, financial performance, and productivity over individualized patient care. Doctors are pressured to see more patients in less time, follow rigid protocols, and meet performance metrics that don’t always align with what’s best for their patients.

The solution? Physicians must take a stand. Getting involved in hospital leadership, medical societies, and policy advocacy ensures that patient care remains the priority. Exploring independent practice or physician-led organizations also provides more professional freedom and control over clinical decisions.

DALLAS MEDICAL JOURNAL | 3

PRESIDENT’S PAGE

The Rise of Private Equity and Corporate Medicine Private equity firms and corporate healthcare groups are rapidly acquiring physician practices, hospitals, and specialty clinics. While these acquisitions may offer financial stability, they often come at a cost: diminished clinical independence, increased administrative oversight, and a shift toward prioritizing profits over patient care. Many physicians find themselves at the mercy of business executives making key medical decisions—a shift that jeopardizes both the quality of care and the integrity of the profession.

How can physicians protect themselves? Carefully reviewing employment contracts, negotiating against restrictive non-compete clauses, and seeking legal guidance before signing agreements are essential steps.

More importantly, supporting and investing in physician-led practices can help safeguard the independence and ethics of medical decisionmaking.

Government Regulations and Bureaucracy While government policies aim to improve healthcare, many unintended consequences end up burdening physicians. Regulatory requirements— electronic health records (EHRs), prior authorizations, complex billing systems—have significantly increased the administrative workload. Instead of allowing physicians to focus on patient care, these bureaucratic mandates force doctors to spend more time navigating compliance issues, leading to dissatisfaction and burnout.

Physicians can help shape healthcare policies by engaging with policymakers, advocating for reduced administrative burdens, and pushing for EHR systems that enhance—not hinder—efficiency.

The Influence of Technology and Artificial Intelligence Artificial intelligence is rapidly making its way into medicine, with AIpowered diagnostics, automated decision-making, and algorithm-driven treatment recommendations. While these tools can enhance efficiency and accuracy, they also present a major concern: the risk of replacing human expertise with algorithmic decision-making.

When AI is controlled by non-clinical stakeholders, the physician’s role in patient care can be diminished. To prevent this, physicians must be at the forefront of AI integration, ensuring that technology serves as a tool—not a replacement—for expert medical judgment.

Reclaiming Physician Autonomy: Actionable Steps for Lasting Change To push back against these growing challenges, physicians must take proactive steps: 1. Get Involved in Advocacy: Medical societies like the Dallas County Medical Society and Texas Medical Association are fighting for policies that protect physician independence and patient-centered care.

2. Take Leadership Roles: Serving in hospital governance and professional organizations allows doctors to challenge administrative overreach.

3. Educate Patients: Patients should know how insurance restrictions affect their care, empowering them to advocate for better coverage.

4. Explore Independent Practice Models: Direct primary care (DPC), concierge medicine, locum tenens, and physician-led practices offer doctors more freedom in patient care decisions.

5. Negotiate Stronger Legal Contracts: Physicians should consult legal 4 | DALLAS MEDICAL JOURNAL

professionals to negotiate fair employment contracts, ensuring that autonomy is safeguarded, and restrictive non-compete clauses are eliminated.

6. Foster Professional Unity: Building strong physician networks and alliances enhances collective influence, enabling doctors to advocate for better working conditions, and push back against external pressures that compromise patient care 7. Push for Insurance Reform: Support initiatives that demand price transparency from insurers, so patients and physicians can make informed financial decisions. Lobby for fair reimbursement rates and reduced financial barriers.

Shaping the Future of Medicine: Empowering Physicians to Lead Physician autonomy is being undermined by insurance companies, hospital administrators, private equity groups, and shifting regulations. But doctors aren’t powerless. By staying informed, engaging in advocacy, and taking proactive steps to reclaim their roles in decision-making, physicians can preserve the integrity of medicine, and continue providing the best possible care for their patients.

Despite the increasing challenges in healthcare, a physician serves in one of the most meaningful professions. The privilege of healing, guiding, and advocating for patients in their most vulnerable moments is both an honor and a responsibility. As our healthcare system continues to evolve, our commitment to both the science and the human connection of medicine must stay strong—because, above all, our patients rely on us. DMJ

MARCH AWARENESS 2025 Women’s History Month National Nutrition Month National Multiple Sclerosis Education and Awareness Month Brain Injury Awareness Month Colorectal Cancer Awareness Month Developmental Disabilities Awareness Month Save Your Vision Month National Kidney Month Bleeding Disorders Awareness Month Myeloma Action Month National Endometriosis Awareness Month Trisomy Awareness Month

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not only improves diagnostic accuracy but also speeds up the diagnostic process, allowing for earlier intervention and better patient outcomes.

Personalized Treatment Plans AI can also analyze vast amounts of patient data, including genetic information, medical history, and lifestyle factors, to develop personalized treatment plans. This approach, known as precision medicine, tailors treatments to the individual characteristics of each patient, potentially improving the efficacy of interventions and reducing adverse effects2. For example, AI can help oncologists identify the most effective chemotherapy regimen for a specific cancer patient based on his or her unique genetic profile.

Operational Efficiency Perhaps one of the most effective non-clinical roles AI has the potential to perform is the significant enhancement of health care operational efficiency. Administrative tasks, such as scheduling appointments, managing patient records, and processing insurance claims, can be automated using AI, freeing up health care professionals to focus on patient care2. Additionally, AIpowered virtual assistants can provide patients with 24/7 access to medical information and support, reducing the burden on health care providers and improving patient satisfaction.

Artificial Intelligence in Healthcare: A DoubleEdged Sword Jon R. Roth, MS, CAE ARTIFICIAL INTELLIGENCE (AI) HAS EMERGED AS A transformative force in health care — one that promises to revolutionize medical practice by enhancing diagnostic accuracy, personalizing treatment plans, and streamlining administrative tasks. However, alongside these advantages, AI also presents significant challenges and risks that must be carefully managed and controlled.

Enhanced Diagnostic Accuracy AI algorithms, particularly those based on machine learning, have demonstrated remarkable proficiency in diagnosing diseases from medical images. For instance, AI systems can analyze radiological images to detect abnormalities such as tumors or fractures with a level of accuracy that rivals or even surpasses that of human radiologists1. This capability March 2025

Predictive Analytics AI can also leverage predictive analytics to identify patients at risk of developing certain conditions, enabling proactive interventions. For instance, AI algorithms can analyze electronic health records to predict the likelihood of hospital readmissions, allowing health care providers to implement preventive measures3. Similarly, AI can forecast disease outbreaks by analyzing patterns in public health data, aiding in the timely deployment of resources and containment strategies.

Dangers of AI in Health Care Despite its potential, AI is not infallible, and the potential dangers posed by AI in health care — whether it uses machine learning or symbolic AI/neural networks that seek to mimic human-like thinking and decision making — require that we retain the physician as absolute head of the health care team. There is a risk that AI systems may produce incorrect diagnoses, particularly if they are trained on biased or incomplete data4. Misdiagnoses can lead to inappropriate treatments, potentially causing harm to patients. It is crucial to ensure that AI systems are rigorously validated and continuously monitored to minimize the risk of errors.

Data Privacy Concerns The use of AI in health care often involves the collection and DALLAS MEDICAL JOURNAL | 7

EVP / CEO LETTER

analysis of large volumes of sensitive patient data. This raises significant privacy concerns, as unauthorized access to or breaches of this data could have serious implications for patient confidentiality4. Given the never-ending reports of health care data breaches these days, it is imperative that robust data protection measures and strict regulatory frameworks be put in place to safeguard patient information and maintain trust in AI-driven health care systems.

Ethical and Bias Issues By their design, AI systems can inadvertently perpetuate existing biases in health care if they are trained on biased data sets. For example, if an AI algorithm is trained primarily on data from a specific demographic group, it may not perform as well for patients from other groups, leading to disparities in care5. Addressing these ethical issues requires careful consideration of the data used to train AI systems and the implementation of measures to ensure fairness and equity in AI-driven health care.

Lack of Transparency Many AI algorithms operate as “black boxes,” meaning that their decisionmaking processes are not easily interpretable by, or disclosed to, humans6.

This lack of transparency can be problematic in health care, where understanding the rationale behind a diagnosis or treatment recommendation is crucial. Efforts to develop explainable AI systems that provide clear and

understandable insights into their decision-making processes are essential to address this challenge.

The integration and use of AI in health care holds immense promise, offering the potential to enhance diagnostic accuracy, personalize treatment plans, and improve operational efficiency. However, it is critical that the health care system use these tools only to augment the absolute oversight of human physicians with training, experience, and decision-making expertise not solely based on datasets. Augmented intelligence can be a game changer in health care, but exclusively artificial intelligence poses significant risks if untethered to active human review and judgment. The benefits of both human and artificial elements in health care must be continuously weighed against the risks of misdiagnosis, data privacy concerns, ethical issues, and lack of transparency, and regularly rebalanced to ensure optimal outcomes. As AI continues to evolve, it is imperative that physicians, policymakers, and technologists work collaboratively to harness this technology’s potential while mitigating its risks. By doing so, we can ensure that AI serves as a powerful tool for advancing health care and improving patient outcomes. DMJ

REFERENCES

1. How AI is being used to benefit your healthcare - Cleveland Clinic Health 2. AI healthcare benefits - IBM 3. AI in healthcare: The future of patient care and health management 4. Risks and remedies for artificial intelligence in health care - Brookings 5. The Dangers of AI in the Healthcare Industry [Report] - Thomasnet 6. AI risks in healthcare: Misdiagnosis, inequality, and ethical concerns

8 | DALLAS MEDICAL JOURNAL

Jon R. Roth, MS, CAE DCMS EVP/CEO

March 2025

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March 2025

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The Digital Health Competencies in Medical Education Framework An International Consensus Statement Based on a Delphi Study DIGITAL HEALTH IS THE USE OF INFORMATION AND communication technologies in health care to promote better health and well-being. It encompasses (among others) electronic health records, clinical decision support systems, telemedicine, mobile apps, wearable devices, data analytics, and, increasingly, artificial intelligence. The application of digital health has rapidly grown worldwide over the past 4 decades, and accelerated particularly during the COVID-19 pandemic.1-3 However, many physicians feel inadequately prepared to use digital health technologies safely and effectively in their work.4,5 According to the Stanford Medicine 2020 Health Trends Report,6 44% of physicians considered their education to be inadequate for new health care technologies. This report is consistent with findings from multiple countries showing that many medical students and junior physicians do not feel equipped to use digital health technologies and are keen to receive more training in this field.7-12 The deficiency of digital health competencies (DHCs) among health workforce hampers the opportunity to seize the full potential of these technologies to improve health outcomes.13 Effective training in digital health is vital for delivering safe, efficient, and high-quality health care.13 In the UK, the Topol Review on health care digitalization14 emphasized the improvement of health-workforce digital literacy by developing appropriate skills, attitudes, and behaviors, which are essential for better health information management and accelerated digital health care transformation.15 The World Health Organization (WHO) European Region digital health action plan (2023-2030) echoed these recommendations by highlighting the importance of digital health education, given that less than one-third of its member states reported having a digital health education strategy.16,17 Most medical schools do not include digital health education and training in their curricula.18-20 This omission can be attributed to numerous challenges, such as, among others, an already dense medical school curricula, shortage of teaching faculty with digital health expertise, lack of appropriate infrastructure and technology resources for digital health education, the dynamic and rapidly evolving nature of digital health, as well as the need for clarity as to what a March 2025

digital health curriculum should entail and how such courses should be taught.21-23 While some schools included digital health education and training, the curricula lack comprehensiveness and are often delivered in the form of elective courses.11,24-28 There is a clear and urgent need for integration of digital health education into all medical school programs.

Digital health education and training should follow a clearly defined framework of DHCs.29 Several frameworks have been developed in recent years for various health professionals, including nurses,30-33 physicians,18,34,35 allied health professionals,36 and health informatics specialists.29,37,38 Notable examples include the Health Information Competency framework,39 developed in 2014 by experts from the EU and the US, and the International Medical Informatics Association framework, published in 2004 and most recently revised in 2023.41 These frameworks outline health informatics learning objectives for all types of health care professionals at different stages of education, from bachelor to doctorate level.41,42 While useful, these frameworks focus mainly on more traditional biomedical informatics–related competencies and do not cover all aspects of digital health. Other existing digital health frameworks largely focus on nursing staff in high-income countries settings,29 limiting their adoption in preregistration medical education (which can be both undergraduate or postgraduate) and in low- and middle-income countries. There are several country-specific national medical curricula that incorporate digital health learning objectives.43-46 However, these curricula vary widely and overlook more recently introduced digital health tools such as symptoms checkers and conversational agents (eg, chat bots). Research on what constitutes the basis of digital health education is ongoing. Two recently published digital health frameworks for medical students outlined 27 artificial intelligence–specific competencies47 and 40 digital health topics,48 respectively. Nevertheless, these 2 frameworks involved experts from a single country in their development, which may limit their wider DALLAS MEDICAL JOURNAL | 11

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Article Summary IMPORTANCE: Rapid digitalization of health care and a dearth of digital health education for medical students and junior physicians worldwide means there is an imperative for more training in this dynamic and evolving field.

OBJECTIVE: To develop an evidence-informed, consensus-guided, adaptable digital health competencies framework for the design and development of digital health curricula in medical institutions globally.

EVIDENCE REVIEW: A core group was assembled to oversee the development of the Digital Health Competencies in Medical Education (DECODE) framework.

First, an initial list was created based on findings from a scoping review and expert consultations. A multidisciplinary and geographically diverse panel of 211 experts from 79 countries and territories was convened for a 2-round, modified Delphi survey conducted between December 2022 and July 2023, with an a priori consensus level of 70%. The framework structure, wordings, and learning outcomes with marginal percentage of agreement were discussed and determined in a consensus meeting organized on September 8, 2023, and subsequent postmeeting qualitative feedback. In total, 211 experts participated in round 1, 149 participated in round 2, 12 participated in the consensus meeting, and 58 participated in postmeeting feedback.

FINDINGS: The DECODE framework uses 3 main terminologies: domain, competency, and learning outcome.

Competencies were grouped into 4 domains: professionalism in digital health, patient and population digital health, health information systems, and health data science. Each competency is accompanied by a set of learning outcomes that are either mandatory or discretionary. The final framework comprises 4 domains, 19 competencies, and 33 mandatory and 145 discretionary learning outcomes, with descriptions for each domain and competency. Six highlighted areas of considerations for medical educators are the variations in nomenclature, the distinctiveness of digital health, the concept of digital health literacy, curriculum space and implementation, the inclusion of discretionary learning outcomes, and socioeconomic inequities in digital health education.

CONCLUSIONS AND RELEVANCE: This evidence-informed and consensus-guided framework will play an important role in enabling medical institutions to better prepare future physicians for the ongoing digital transformation in health care. Medical schools are encouraged to adopt and adapt this framework to align with their needs, resources, and circumstances.

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use. Given that physicians are one of the principal decision-makers in clinical care, integration of digital health solutions into health care practice would require their endorsement and active use. Improving the DHCs of medical students and physicians could help overcome barriers to more widespread adoption and use of digital health solutions.13,29 Therefore, there is a need for a comprehensive and actionable international DHC framework for medical education. To this end, we carried out an international Delphi study, with the aim of developing an evidence-informed, consensus-guided applicable set of competencies and associated learning outcomes that can be adapted for the design and development of digital health curricula in medical schools globally.

METHODS The development of the DHC in Medical Education (DECODE) framework involved 5 stages: (1) mapping exercise based on a scoping review29 to identify potential competencies; (2) iterative expert consultations and piloting of the initial list of competencies and learning outcomes; (3) a 2-round modified Delphi survey for consensus on framework structure, terminology, domains, competencies, and learning outcomes; (4) a consensus meeting to refine wordings; and (5) postmeeting activities for additional qualitative feedback and recommendations. The process is illustrated in the Figure. The modified Delphi method, used to establish consensus among a panel of experts, was chosen because it provides opportunity for experts to discuss and interact in a final meeting.49 The expert consensus process was overseen by a group of subject matter experts (J.C., Q.C.O., T.E.F., S.J.K., I.S., K.K.F.T., A.H.S., C.G.P., and R.A.) in medical education and digital health research. This study was approved by Nanyang Technological University institutional review board and followed the Accurate Consensus Reporting Document (ACCORD) reporting guideline for consensus methods in biomedicine developed via a modified Delphi.

Identification of the Initial Set of Relevant DHCs Multiple steps were used to create the list of digital health domains, competencies, and learning outcomes. The initial list of domains, competencies, and learning outcomes was based on findings from a 2020 scoping review of relevant international medical literature,29 which analyzed existing DHC frameworks used by health care professionals, considering their geographical applicability (ie, local or organizational, regional, national, and international), health care settings (eg, acute care, emergency care, and primary care), and the nomenclature used for competency areas (eg, health information technology and telemedicine). A total of 30 DHC frameworks and 28 common digital health domains were identified, and a varied focus across health professions was noted with only 1 framework developed specifically for preregistration medical education.

The core group reviewed the complete list of competencies and outcomes identified from the scoping review.29 Four digital health researchers screened competencies against predefined eligibility criteria (eTable 1 in the Supplement). During the screening process, they identified gaps in the learning outcomes. Additional literature appraisal and review of existing medical education curriculum frameworks were carried out to address these gaps by adding new domains and competencies and formulating new learning outcomes. Through iterative rounds of internal discussion, an initial framework structure was agreed upon and included terminology, domains, competencies, and associated learning outcomes. The resulting list was used to build the questionnaire for the round 1 survey of the March 2025

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Delphi study. Subsequently, 2 pilots were carried out. The survey questionnaire and the identified list of domains, competencies, and learning outcomes were distributed among the core group for an extensive review.

The survey questionnaire was revised for clarity and streamlined, while the terminologies, domains, competencies, and associated learning outcomes in the list were adjusted, modified, regrouped, and improved with the relatively newer areas of digital health.

Flow Diagram of the Expert Consensus Process Scoping review and expert consultations

Initial list of 4 domains, 18 competencies, and 189 associated learning outcomes identified

Two-Round Delphi Survey An iterative sampling method was used to create a diverse expert panel for the Delphi study. The eligibility criteria for inclusion in the panel are detailed in eAppendix 1 in the Supplement. Detailed information on the purpose of the study and the roles of each panelist were provided before written informed consent was obtained online. Only those who completed the round 1 Delphi survey were invited to round 2. Round 1 of the Delphi survey, which took place between December 2022 and April 2023, had 3 sections: (1) framework structure and terminology, (2) relevance of digital health domains, and (3) relevance of DHCs and learning outcomes for medical education. Feedback was sought from experts on the framework’s structure and terminology via free text, while the relevance of domains, competencies, and learning outcomes were determined via a Likert scale parsed as strongly agree, agree, disagree, and strongly disagree. For an item to be included in the DHC framework, a prespecified combined rating (agree and strongly agree) of at least 70% of the participants (excluding blank votes and abstentions) had to be achieved. Expert agreement percentage is commonly used as the cutoff for consensus in Delphi,50 with studies using different thresholds ranging from 67% to 80%.51-53 Qualitative analysis of the free-text suggestions was performed independently by 2 reviewers (O.C.O. and T.E.F.), and discrepancies were resolved through discussion with a third reviewer (J.C.). Suggestions were categorized into common ideas and synthesized. In round 2 of the survey (between June and July 2023), experts reviewed changes made from round 1 feedback and indicated agreement. Analysis of free-text responses from round 1 suggested for learning outcomes to be categorized to aid curriculum differentiation and definition. Experts were asked whether learning outcomes should be mandatory, elective, or supplementary for the digital health curriculum. We defined mandatory outcomes as essential for all medical students, elective outcomes as important but not universal, and supplementary outcomes as providing additional, context-specific knowledge, skills, or behaviors. In addition, experts were asked to rate the relevance of new competencies and outcomes proposed by participants in round 1. Details of the recruitment process and the 2-round Delphi survey are described in the eMethods in the Supplement.

Consensus Meeting and Postmeeting Activities A virtual consensus meeting was held in September 2023 and involved 12 participants (16 invited) who had taken part in rounds 1 and 2, and 2 members of the core group (meeting chair and notetaker). They were selected to represent a range of roles within medical education, diverse medical fields, and global geographic locations. One invited panelist who was unable to attend provided detailed written feedback, which was considered. To facilitate the discussion, the consensus meeting agenda and the revised draft of the DHC framework were sent to the invited panelists prior to the meeting. Following the presentation of the results, the consensus meeting panelists participated in focused discussions, deliberating March 2025

Round 1 Delphi survey:

221 participants rated each of the 4 domains, 18 competencies, and 189 associated learning outcomes as strongly agree, agree, disagree, or strongly disagree 4 Domains, 18 competencies, and 177 learning outcomes achieved predefined consensus levela 12 Learning outcomes did not achieve predefined consensus levela 2 New competencies and 19 new learning outcomes were suggested by round 1 participants 446 Free-text suggestions were received, from which 8 learning outcomes were merged into other learning

1 Competency and 19 learning outcomes not retained for round 2 (1 competency and 7 learning outcomes from free-text

4 Domains, 17 competencies, and 162 learning outcomes retained for round 2 21 Additional items added for round 2 2 Competencies 19 Learning outcomes

Round 2 Delphi survey:

149 participants from round 1 rated the 21 additional items (19 learning outcomes and 2 competencies) as strongly agree, agree, disagree or strongly agree, of which all achieved consensus level and were included; participants then differentiated 181 learning outcomes (162 retained and 19 added) as mandatory, elective, or supplementary 151 Learning outcomes did not achieve consensus levela 148 Learning outcomes included as discretionary 3 Learning outcomes that did not achieve consensus level were merged with other learning outcomes based on qualitative analysis of 169 free-text suggestions 30 Learning outcomes achieved predefined consensus level and included as mandatorya

Consensus meeting:

consensus on the list of mandatory and discretionary learning outcomes 33 Mandatory learning outcomes included in final DECODE framework 145 Discretionary learning outcomes included in final DECODE framework

Postmeeting activities:

Finalized wording of the 4 domains, 19 competencies, and 178(33 mandatory and 145 descretionary) learning outcomes

Flow Diagram of the Expert Consensus Process DECODE indicates the Digital Health Competencies in Medical Education framework.

Rated by 70% or more of participants.

a

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Characteristics of Participants in Each Round of Delphi Survey Participants, No. (%) Characteristics, round

Round 1 (n = 211)

Round 2 (n = 149)

Retention rate, %

NA

70.6

Survey completion Full

177 (83.9)

141 (94.6)

Partial

34 (16.1)

8 (5.4)

Country (and territory) of primary affiliation b African Region

33 (15.6)

28 (18.8)

Region of the Americas

22 (10.4)

13 (8.7)

South-East Asian Region

16 (7.6)

11 (7.4)

European Region

78 (37.0)

50 (33.6)

Eastern Mediterranean Region

23 (10.9)

13 (8 7)

Western Pacific Region

33 (18.0)

33 (22.1)

Other c

1 (0.5)

1 (0.7)

Country income classification d High-income

96 (45.5)

63 (42.6)

Upper middle-income

42 (19.9)

31 (20.9)

Lower middle-income

45 (21.8)

35 (23.6)

Low-income

27 (12.8)

19 (12.8)

Designation e University leader (eg, president, vice president, rector)

11 (5.2)

8 (5.4)

Dean of medical school or faculty

32 (15.2)

25 (16.8)

Vice dean of medical school or faculty

11 (5.2)

11 (7.4)

Head of department or director of center

38 (18.0)

35 (23.5)

Professor

65 (31.3)

18 (32.2)

Associate professor

37 (17.5)

31 (20.8)

Assistant professor

15 (7.6)

15 (10.1)

Lecturer

19 (9.0)

17 (11.4)

Program director for medical education

17 (8.1)

13 (8.7)

Digital health researcher

29 (13.7)

28 (18.8)

Clinician

54 (25.6)

50 (33.6)

Chief medical officer

2(0.9)

2 (1.3)

Chief medical information officer or chief information officer

3 (1.4)

2. (1.3)

Other

15 (7.1)

11 (7.4)

NA

11(5.2)

0

Primary professional discipline Clinical medicine

NA

91 (62.2)

Public health

NA

9 (6.0)

Basic sciences

NA

17 (11.4)

Computer science

NA

2 (1.3)

Engineering

NA

2 (1.3)

Other

NA

28 (18.8)

Current role e Teaching role

NA

125 (83.9)

Clinical role

NA

76 (51.0)

Research role

NA

109 (73.2)

Other

NA

29 (19.5)

Place of employment e University

197 (93.4)

140 (94.0)

Hospital

73(34.6)

70 (47.0)

Private health practice

13 (6.2)

13 (8.7)

Governmental organization

20 (9.5)

20 (13.4)

Nonprofit organization (eg, nongovernmental organization or charity)

7 (3.3)

7 (4.7)

For-profit organization (eg, digital health start-up)

2 (0.9)

1 (0.7)

NA

3 (1.4)

0

14 | DALLAS MEDICAL JOURNAL

on the appropriateness of inclusion of each competency and its associated learning outcomes, the descriptions, and wordings. Items with a marginal percentage of agreement (ie, 60.0%-69.9%) were highlighted and discussed. Consensus was reached through discussion. The revised document, listing the agreed domains, competencies, and learning outcomes, was circulated to panelists for confirmation and minor wording suggestions. This process aimed to ensure that the document accurately reflected decisions made during the consensus meeting. Apart from the consensus meeting panelists, the final document was distributed to all participants who completed both rounds of the Delphi survey to seek their qualitative feedback and inquire their interest in implementing the framework at their medical schools.

RESULTS Delphi Survey and Consensus Meeting In total, 211 individuals participated in round 1 of the survey, and 149 participated in round 2 (70.6% of participants from round 1). Survey participants were from 79 countries and territories in round 1 and 68 countries in round 2, with representation from all 6 WHO regions and all 4 World Bank country income groups (eFigure in the Supplement). Of those who took part in both rounds (149 participants), 63 (42.6%) were based in highincome countries and 19 (12.8%) in low-income countries (World Bank country income classification).54 Almost two-thirds of the participants (91 participants [61.1%]) reported clinical medicine as their primary professional background. The majority reported having a teaching role (125 participants [83.9%]) and/or research role (109 participants [73.2%]), while one-half of them had a clinical role (76 participants [51.0%]). The majority (140 participants [94.0%]) also worked in a university, and more than one-half of them (83 participants [55.7%]) worked in a clinical setting.

Approximately one-third (47 participants [31.5%]) reported holding an institutional leadership position, such as president or chancellor of university, dean or vice dean of medical school, or chief medical officer of hospital. The characteristics of participants in each Delphi Survey round are reported in Table 1.

From an initial list of 4 domains, 18 competencies, and 189 learning outcomes, after round 1, 4 domains, 18 competencies, and 177 learning outcomes achieved the predefined level of consensus (ie, >70%) and were subsequently retained for round 2 (Figure). Twelve learning outcomes that did not reach the a priori consensus level were removed from the list. A total of 446 free-text suggestions were received. These pertained to framework structure, description of competencies, wording of learning outcomes, overlapping items, and suggestions for new items. Following qualitative analysis, 1 competency and 7 learning outcomes associated with this competency were removed, 16 learning outcomes were reorganized and merged (into 8 learning outcomes), 64 learning outcomes were reworded, and 2 new competencies and 19 new learning outcomes were added.

In round 2, all newly added items reached the predefined level of consensus and were included in the framework. Of the 162 learning outcomes retained from round 1 and the 19 newly added learning outcomes, 30 NA, no available data. a Completion of at least 1 full section. b According to World Health Organization regions. There were 79 countries and territories in round 1 and 68 in round 2. c Non–World Health Organization member. d Based on the World Bank. e Participants may select more than 1 answer.

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attained more than 70% agreement rates for the mandatory category, while 151 did not reach the 70% agreement rate for any single category (ie, mandatory, elective, or supplementary). These 151 learning outcomes were labeled as discretionary. Qualitative analysis of 169 free-text suggestions led to rewording of 14 learning outcomes and merging of 6 learning outcomes into 3. Following differentiation of learning outcomes in round 2, 30 learning outcomes emerged as mandatory and 148 as discretionary.

In-depth deliberations during the consensus meeting led to panelists reclassifying 4 discretionary learning outcomes with a marginal percentage of agreement (ie, 60.0%-69.9%) as mandatory and 1 mandatory learning outcome with marginal percentage agreement (ie, 70.0%-79.9%) as discretionary. After the consensus meeting, 58 of those who received the framework responded with qualitative feedback. In addition, 29 of them (50.0%) expressed willingness to adopt the DECODE framework at their medical schools, 6 (10.3%) would consider adoption with conditions, 7 (12.1%) mentioned a need for further discussion, 6 (10.3%) indicated barriers or being noncommittal to adoption, and 10 (17.2%) did not provide a direct response to this inquiry. Results of the 2-round modified Delphi survey are shown in the Figure.

Detailed results of round 1 and round 2 are presented in eTable 2 and eTable 3 in the Supplement.

Final DECODE Framework The hierarchy of the DECODE framework had 3 main terminologies: domain, competency, and learning outcome. We defined competency as a statement describing a specific ability, or set of abilities, requiring specific knowledge, skill and/or behavior, and learning outcome as the intended aggregate learner end point for a program.56-58 After the 2-round Delphi survey and the consensus meeting, a total of 4 domains, 19 competencies, 33 mandatory learning outcomes, and 145 discretionary learning outcomes were included in the final DECODE framework (eAppendix 2 in the Supplement).

The competencies were organized into 4 domains: professionalism in digital health, patient and population digital health, health information systems, and health data science (Box). Detailed descriptions of the domains are presented in Table 2. Each competency has a description and a set of associated learning outcomes, which can be mandatory or discretionary. All 178 learning outcomes were labeled as relating to medical graduates’ knowledge (119 learning outcomes [66.8%]), skill (35 learning outcomes [19.7%]), or behavior (24 learning outcomes [13.5%]). In this framework, 13 of the 19 competencies have both mandatory and discretionary learning outcomes, while the remaining 6 have only discretionary learning outcomes.

Description of Domains Domain

Importance

Description

Professionalism in digital health

The use of digital technologies in healthcare poses important professional, legal, and ethical implications, and demands a high level of medical professionalism.

This domain encompasses themes that are related to professionalism in digital health, which is described as the ability of health professionals to understand, develop, and demonstrate appropriate professional behavior when using digital technologies. Learning outcomes within this domain prepare medical graduates to become competent and responsible digital health users with an awareness of cybersecurity and ethical,legal,and regulatory guidelines and demonstrate digital intelligence. Mastery of this domain will allow them to incorporate technologies in their daily practice without compromising data of their patients.

Patient and population digital health

A wide spread availability of internet, mobile, and wearable technologies empowers patients and healthy individuals to be active participants (ie, digital health consumers) in the process of making choices about their health, rather than being recipients of services.

This trend allows for person centered care; the prerequisites for that include a focus on patient in informatics, promotion of digital health literacy,and patient education.

This domain focuses on equipping medical students with knowledge and skills in telehealth, healthapps, digital therapeutics, wearables, sensors, remote monitoring, and point-of-care and self-testing. It enables them to communicate, counsel, provide care,and motivate self-management in patients in the context of digital health technologies. lt also expands on the types of data that can be collected through digital technologies available to patients and how this may lead to better diagnoses and treatment decisions in the future. Additionally, it ensures medical students are aware of digital health literacy of patients, the broader digital determinants of health, the digital divide, and associated health inequalities.

Health information systems

Physicians,among other healthcare professionals, are key stakeholders in collecting, storing, monitoring, accessing, and sharing patient health data. Accurate and safe handling of health data extends beyond the quality and safety requirement of an individual patient’s care. Clinical decision support systems, computerized physician order entries, and other information technology solutions embedded within health information systems leverage existing health data and enhance patient care by providing automation and decision support.

Competencies in this domain prepare medical students to be competent users of health information systems and health information exchange who are aware of the design and development process of such systems. lt ensures that medical students are compliant with the standards of data governance policies Furthermore, it focuses on clinical documentation skills and electronic prescribing methods

Health data science

The growth of digitally captured, processed, and stored health data has been drastic, creating opportunities to address challenges in medicine, public health, and biomedical sciences. ln addition to data from electronic health records, patient- generated data (eg, wearables) and genome sequencing contribute substantially to the health data pool. One of the promises of this trend is the use of multiple modalities to support personalized medicine.

This domain covers competencies in health data application fields such as population health informatics, computational thinking, artificial intelligence in healthcare, and precision medicine. lt ensures medical students understand the scope of health data, the impact of data on healthcare, and how to apply data for the optimization of patient care at both the population and individual levels.

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Additional Considerations for Implementation of the DECODE Framework Considerations

Elaboration

Variations in nomenclature used

The consensus panel concurred that the interpretation of the nomenclature used within this framework may vary due to geographical, language, and other differences. There are several terminology schemes used in curriculum and instructional design in medical education globally, and these vary depending on the region, location, and organization. The panel acknowledged that different medical education institutions and accrediting bodies globally use a range of terms in curriculum design and a number of documents guide medical educators in different countries, such as the UK General Medical Council guidance for medical schools (Outcomes for Graduates), 59 the Association of American Medical Colleges Medical Schools Objectives Project, 60 and the Review of Accreditation Standards for Primary Medical Programs by the Australian Medical Council. 61 One of the challenges in creating digital health competencies for a global audience is the need to use meaningful terminology, given the diverse national and local approaches to curriculum design, terminology, and practices. The use of terms such as competencies, outcomes, and objectives is widespread, but the way these terms are defined, used, and understood varies around the world. This variation emphasizes the need for clarity, refinement, and consensus around language in the field of digital health. The consensus panel agreed that the use of working definitions in the preface of the framework would help circumvent these issues.

Distinctiveness of digital health

The consensus panel highlighted the need for a focused approach to distinguish digital health from its nondigital counterparts during the curriculum development process. This emphasis arises from the recognition that some fundamental principles, such as data privacy and security, have already existed in the predigital era and are not exclusive to digital health. The focus of the curriculum should therefore be the distinctive challenges and nuances introduced by the digital transformation of health care, as opposed to using digital as an adjective for preexisting concepts. Placing too much emphasis on general concepts applicable to both digital and nondigital contexts risks diluting the distinctiveness of digital health. Nevertheless, the consensus panel expressed concern about the potential oversight of these critical domains if not adequately covered in a specific digital health curriculum. Given the pervasiveness of digitalization in health care, digital health curricula might become the default standard for anything related to data. The assumption that this curriculum would cover data-related domains comprehensively could possibly lead to displacement and neglect of these essential aspects of data handling in other educational domains, such as population health.

The consensus panel acknowledged that digital health literacy (of health consumers) is a concept that is not universally agreed upon and is difficult to measure and therefore challenging to operationalize. In published literature, the terms digital health literacy, digital literacy, and eHealth literacy have been used to denote a common or substantially similar concept,62-64 and these terms are sometimes used interchangeably.65 While some argue that digital health

Concept of digital health literacy

literacy is the convergence of digital literacy and health literacy, “ which are 2 different constructs, they are nonetheless equally important in the context of digital health. Health and digital literacy are both well-established determinants of health. 67-69 More recently, digital health literacy was acknowledged as a superdeterminant of health with civic, digital, and health literacies as its 3 building blocks.70 This speaks to the importance of digital health literacy as a concept that should be understood and considered by all who practice modern medicine because it affects patients’ access to digital health services,71 health-related behaviors,72 and health outcomes.73 For the purpose of this study, we built upon existing definitions of digital health literacy and defined it as the skills to seek, select, appraise, understand, and apply health information from electronic sources, health care-related digital technologies, and digital health services.62-65

Curriculum space and implementation

From the curriculum implementation perspective, several experts raised concerns on the challenges in incorporating all competencies within this framework into the existing crowded medical curricula and the potential pushback that might arise. The conundrum lies within balancing the enthusiasm to cover all relevant domains with the practicality of curriculum implementation to ensure that all essential items are effectively integrated into the curriculum.

This could be achieved by focusing on foundational concepts and skills that will support medical students through clinical practice in lieu of technical skills that are likely to change as technology evolves. For example, a medical graduate should be able to recognize the strengths and limitations of artificial intelligence-supported diagnostics compared with conventional methods but not be expected to reiterate the detailed mechanism and techniques used in machine learning. One of the suggestions is for discretionary learning outcomes to be addressed through alternative educational activities such as continuing medical education programs. Other suggestions include vertical integration of the framework into preexisting curricula and step-by-step incremental introduction over time. The use of an integrated or cross-domain curriculum approach, such as in planetary health, may also facilitate implementation by expanding existing content to accommodate digital health domains.74

Inclusion of discretionary learning outcomes

Discretionary learning outcomes are important while not being mandatory. There was consideration that some of these might already be addressed in other facets of medical curricula, such as within the purview of public health or bioinformatics. This is also relevant for institutions that offer dual-degree programs such as MD-MBA (business), MD-JD (law), MD-MPH (public health), and MD-PhD, where some aspects of the DECODE framework might be covered in the combined degree program but not within the medical curriculum. For instance, digital determinants of health, given its interdisciplinary nature, could be a part of the MPH curriculum within the MD-MPH program. As such, introducing these competencies might result in redundancy. However, the presumption that certain competencies might already be encompassed elsewhere or an optimistic anticipation of their coverage within other curricula poses the risk of inadvertent oversight of these competencies. Therefore, within the scope of this study, we included all domains deemed pertinent to the domain of digital health, irrespective of their potential intersection with other disciplines, to provide medical educators globally with a comprehensive framework for consideration. Medical educators may find it prudent to include some discretionary learning outcomes as part of the digital health curriculum, especially if they are not currently addressed in other domains of the existing curriculum.

Socioeconomic inequities in digital health education

Issues pertaining to digital health equity and socioeconomic inequities in access to digital diagnostic platforms and their applicability in LMICs were raised by experts in both the Delphi survey and the consensus meeting. In resource-constrained settings, implementation of digital diagnostics remains difficult due to various barriers related to cost, trained personnel, regulation, and infrastructure.75 Because many of these platforms are not readily available in LMICs, it poses a challenge to discuss their practical application during teaching. With limited exposure and little hands-on practice, medical students may have difficulty grasping the use of these platforms. In addition, educators who lack clinical experience in using digital diagnostics may not be confident and competent to educate students on these technologies. Nevertheless, several experts recognized the tremendous potential of digital diagnostics in LMICs, highlighting that regions with the scarcest resources stand to gain substantially from the remote capabilities of digital diagnostics. Notwithstanding the potential benefits of digital diagnostics, the discourse around the feasibility and costs associated with setting up these platforms for educational purposes, along with how learners can effectively demonstrate the requisite competencies, is likely to persist for years to come. With most of its associated learning outcomes included as discretionary, our findings aptly reflect the present state of digital diagnostics, wherein most experts acknowledged its relevance in medical education but did not consider it mandatory across all settings. This was also observed in other competencies, including wearables, sensors, and the internet of medical things (competency 2.5), internet-based health interventions (competency 2.7), and health information exchange (competency 3.4).

DECODE, Digital Health Competencies in Medical Education; JD, juris doctor; LMIC, low- and middle-income countries; MBA, master of business administration; MD, doctor of medicine; MPH, master of public health; PhD, doctor of philosophy.

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Additional Considerations for Medical Educators During the Delphi survey and consensus meeting, several areas of debate arose. These discussions suggest highly relevant topics that stakeholders in medical education and health care should consider when developing or implementing digital health curricula in medical institutions. These include variations in nomenclature, distinctiveness of digital health, the concept of digital health literacy, curriculum space and implementation, inclusion of discretionary learning outcomes, and socioeconomic inequities in digital health education (Table 3).59-75 A list of additional resources can be found in eAppendix 3 in the Supplement.

DISCUSSION The DECODE framework was developed through a rigorous, multistage international consensus process. The framework is based on findings of a scoping review,29 expert consultations, a 2-round Delphi survey, a consensus meeting, and postmeeting qualitative feedback. The consensus process garnered an international panel of experts with diverse professional backgrounds, leadership roles in medical education, and geographical locations to ensure the framework’s applicability and relevance to a global audience.

The final DECODE framework comprises 4 domains, 19 competencies, and 33 mandatory and 145 discretionary learning outcomes; this allows institutions engaged in medical education to adapt their digital health curricula to their countries and jurisdiction’s specific context and requirements. To our knowledge, this is the first attempt to develop a curriculum for digital health medical education at a global scale.

A key strength of this study is the systematic approach preceding the Delphi survey that generated an initial list of competencies and learning outcomes through a scoping review.29 Next, there was a high number of participating nations with representations from both lower middle– income and low-income countries within the expert panel. Because priorities in digital health training of future physicians in these settings may differ, the involvement of experts from these countries enhanced the framework’s broader applicability and led to advocacy for elevating and incorporating digital health equity within the competencies (eg, digital determinants of health). The substantial presence of institutional leadership among Delphi participants enriched the framework with their strategic insights, ensured its alignment with broader educational and organizational needs, and may facilitate its adoption within their respective institutions.

There are several barriers to adopting a universal DHC framework.

Our group identified the following categories: geographic heterogeneity, variation in resources between regions and between institutions in the same region, variance in local needs within a given institution, and the zero-sum nature of the curriculum (ie, adopting new content requires removal of other content). We will continue to explore these issues and pragmatic approaches to adoption in future work. These may include an implementation guide (similar to the WHO Patient Safety Curriculum Guide, which outlines methods of curriculum delivery for each domain and competency), methods of assessment, and regularly updated core curricular content that could be used and adapted in each school.76 Development of an accompanying framework for evaluating the implementation and impact of the DHC framework on student competencies and patient care could also assist in refining and validating the competencies over time.

The recommended DHCs, currently absent from standardized licensing examinations, need to be included and assessed in the future.77,78

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LIMITATIONS This study has some limitations. First, the preliminary scoping review that this study was based on only included literature published in English.29 Second, the study was conducted in English due to research team’s language limitations and English being a commonly use language in medical publications; this limited participation to English speakers. Third, the absence of a neutral option in the Likert scale may have inadvertently forced the respondents to select either a positive or negative response despite their ambivalence; this could have introduced response bias. Fourth, akin to any Delphi approach, this study faces potential biases, such as selection bias from purposive sampling. Although the research team tried to minimize sampling bias by adopting a multimethod sampling approach to create a sizeable panel with geographical and disciplinary diversity, the results may not capture fully the context specificities and need of all countries. A further criticism of the Delphi approach lies in its potential constraint when experts are confined to voting on a predetermined list. Although the research team attempted to identify all possible options through the preliminary work (scoping review, iterative expert consultations, and piloting) leading up to the initial item list, exhaustiveness of the list could not be guaranteed. To mitigate this, free-text responses were allowed in the survey for experts to propose additional items, which has proven to be invaluable.

CONCLUSIONS This multistage international consensus process has produced a comprehensive DHC framework for preregistration medical education. This framework will play an enabling role in assisting individual medical institutions in developing and introducing digital health learning outcomes and appropriate learning opportunities into curricula for medical students. Adaptable to each country’s specific needs and contexts, this approach ensures both relevance and flexibility in curriculum design. The international composition of the Delphi expert panel provided a balanced perspective on digital health technologies and digital health inequities, leading to the segregation of learning outcomes into mandatory and discretionary categories to enhance their applicability in diverse educational settings. Interdisciplinary collaboration within or across departments is encouraged when coordinating its implementation. Integration of this framework into curriculum design can assist in better preparing future physicians for the ongoing digital transformation in health care. We envisage that curricula developed from this framework will be taught in an integrated manner throughout the study years. It is critically important that similar international collaborative effort should be undertaken for other health professionals, such as nurses, midwives, therapists, health technologists, and, among others, health managers, and we envisage contributing to such endeavors.

Our subsequent work will also focus on making teaching resources available widely as public goods. Going forward, this framework will need reviewing and updating to reflect the latest developments and evidence-advancement in digital health. DMJ

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The Digital Health Competencies in Medical Education Framework: An International Consensus Statement Based on a Delphi Study Article by Josip Car, MD, PhD; Qi Chwen Ong, MBBS; Tatiana Erlikh Fox, MD; Daniel Leightley, PhD; Sandra J. Kemp, PhD; Igor Švab, MD, PhD; Kelvin K. F. Tsoi, PhD; Amir H. Sam, MBBS, PhD; Fiona M. Kent, PhD; Attila J. Hertelendy, PhD; Christopher A. Longhurst, MD, MS; John Powell, MBBChir, PhD; Hossam Hamdy, MBChB, PhD; Huy V.Q. Nguyen, MD, PhD; Sola Aoun Bahous, MD, PhD; Mai Wang, MBBS, PhD; Martin Baumgartner, MSc; Yodi Mahendradhata, MD, PhD; Natasa Popovic, MD, PhD; Andy W. H. Khong, PhD; Charles G. Prober, MD; Rifat Atun, MBBS, MBA; and the Digital Health Systems Collaborative

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49. Fitch K, Bernstein SJ, Aguilar MD, et al. The RAND/UCLA appropriateness method user’s manual. Published 2001. Accessed November 20, 2024. https:/ /www.rand.org/pubs/monograph_reports/MR1269.html 50. Jünger S, Payne SA, Brine J, Radbruch L, Brearley SG. Guidance on conducting and reporting Delphi studies (CREDES) in palliative care: recommendations based on a methodological systematic review. Palliat Med. 2017;31 (8):684-706.

51. Albarqouni L, Hoffmann T, Straus S, et al. Core competencies in evidence-based practice for health professionals: consensus statement based on a systematic review and Delphi survey. JAMA Netw Open.

2018;1(2): e180281-e180281.

52. Lazarus JV, Romero D, Kopka CJ, et al; COVID-19 Consensus Statement Panel. A multinational Delphi consensus to end the COVID-19 public health threat. Nature. 2022;611(7935):332-345.

53. Vasey B, Nagendran M, Campbell B, et al; DECIDE-AI expert group. Reporting guideline for the earlystage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI. Nat Med. 2022;28(5): 924-933.

54. The World Bank. World bank country and lending groups. Accessed November 20, 2024. https:/ /datahelpdesk. worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups 55. World Health Organization. Countries. Accessed April 21, 2024. https:/ /www.who.int/countries 56. MedBiquitous. Curriculum inventory standardized instructional and assessment methods and resource types. Published March 2016. Accessed November 20, 2024. https:/ /app.oarklibrary.com/file/4/2777626d1ed3-4b61- 95f8-859956d3f9a6**b3d3205a224989013c19e4e82332dded/56658e17-234b-4ea1-a314d2eee893d5cc.pdf 57. Englander R, Cameron T, Ballard AJ, Dodge J, Bull J, Aschenbrener CA. Toward a common taxonomy of competency domains for the health professions and competencies for physicians. Acad Med. 2013;88(8): 1088-1094.

58. Harden RM, Laidlaw JM. Essential skills for a medical teacher: an introduction to teaching and learning in medicine. Elsevier Health Sciences; 2020.

59. General Medical Council. Outcomes for graduates 2018. Accessed November 20, 2024. https:/ /www. gmc-uk. org/-/media/documents/outcomes-for-graduates-2020_pdf-84622587.pdf 60. Group MSOW. Learning objectives for medical student education–guidelines for medical schools: report I of the medical school objectives project. Acad Med. 1999;74(1):13-18.

61. Australian Medical Council Limited. Review of accreditation standards for primary medical programs (medical school standards review). July 2023. Accessed November 20, 2024. https:/ /www.amc.org.au/accredited- organisations/review-of-accreditation-standards-for-primary-medical-programs/ 62. Richardson S, Lawrence K, Schoenthaler AM, Mann D. A framework for digital health equity. NPJ Digit Med. 2022;5(1):119.

63. Yang K, Hu Y, Qi H. Digital health literacy: bibliometric analysis. J Med Internet Res. 2022;24(7):e35816.

64. Yoon J, Lee M, Ahn JS, et al. Development and validation of digital health technology literacy assessment questionnaire. J Med Syst. 2022;46(2):13.

65. van der Vaart R, Drossaert C. Development of the digital health literacy instrument: measuring a broad spectrum of health 1.0 and health 2.0 skills. J Med Internet Res. 2017;19(1):e27.

66. Honeyman M, Maguire D, Evans H, Davies A. Digital technology and health inequalities: a scoping review (Wales). Health Inequalities. Published 2020. Accessed November 20, 2024. https:/ /health-inequalities.eu/ jwddb/ digital-technology-and-health-inequalities-a-scoping-review-wales/ 67. Nutbeam D, Lloyd JE. Understanding and responding to health literacy as a social determinant of health. Annu Rev Public Health. 2021;42(1):159-173.

68. Pelikan JM, Ganahl K, Roethlin F. Health literacy as a determinant, mediator and/or moderator of health: empirical models using the European Health Literacy Survey dataset. Glob Health Promot. Published online November 14, 2018.

69. Sieck CJ, Sheon A, Ancker JS, Castek J, Callahan B, Siefer A. Digital inclusion as a social determinant of health.

NPJ Digit Med. 2021;4(1):52.

70. van Kessel R, Wong BLH, Clemens T, Brand H. Digital health literacy as a super determinant of health: more than simply the sum of its parts. Internet Interv. 2022;27:100500.

71. Smith B, Magnani JW. New technologies, new disparities: The intersection of electronic health and digital health literacy. Int J Cardiol. 2019;292:280-282.

72. Kim K, Shin S, Kim S, Lee E. The relation between eHealth literacy and health-related behaviors: systematic review and meta-analysis. J Med Internet Res. 2023;25:e40778.

73. Arias López MDP, Ong BA, Borrat Frigola X, et al. Digital literacy as a new determinant of health: a scoping review. PLOS Digit Health. 2023;2(10):e0000279.

74. Lee SA, Bates OB, Cecilie Perez E, Swift CP, Stanistreet D. Integrating planetary health into the medical curriculum. Centre for Global Education. Published 2022. Accessed November 20, 2024. https:/ /www. developmenteducationreview.com/issue/issue-34/integrating-planetary-health-medical-curriculum 75. Zehra T, Parwani A, Abdul-Ghafar J, Ahmad Z. A suggested way forward for adoption of AI-Enabled digital pathology in low resource organizations in the developing world. Diagn Pathol. 2023;18(1):68.

76. World Health Organization. Patient safety curriculum guide: multi-professional edition. Published July 6, 2011. Accessed November 20, 2024. https:/ /www.who.int/publications/i/item/9789241501958 77. General Medical Council. Medical licensing assessment. Accessed November 20, 2024. https:/ /www. gmc- uk.org/mla 78. Federation of State Medical Boards of the United States, Inc; National Board of Medical Examiners.

USMLE content outline. USMLE. 2021. Accessed November 20, 2024. https:/ /www.usmle.org/sites/default/ files/2021-08/ USMLE_Content_Outline.pdf

March 2025

CERTIFICATE PROGRAM 10% COURSE DISCOUNT FOR DCMS MEMBERS

“This program offers a challenging curriculum of leadership training and self reflection. The speakers from the different sectors of healthcare were engaging and provided real examples of how our healthcare system weaves together, for better or worse. I feel more prepared as an effective leader of the teams I influence today and the teams of my future.”

Gates Colbert, MD, FASN

The Dallas County Medical Society and the UT Dallas Alliance for Physician Leadership Program (APL) are offering a physician leadership certificate that will cover timely and important topics in today’s ever-changing healthcare environment. The certificate program covers areas of focus such as physician wellness, leadership skills, value-based contracting, quality performance, emerging IT opportunities, revenue and financial management. The program is cohort style and will adapt to industry trends and the needs/topics of interest to the physician attendees.

The DCMS/APL program includes six in-person full-day sessions, a final project session, along with interim readings, case studies, and engagement with program faculty on an ongoing basis. The program design is intended to provide meaningful and focused learning with the in-person cohort, while respecting the time demands of a physician’s schedule.

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ENROLLMENT DEADLINE: AUGUST 2025 CLASSES BEGIN: S EMarch P T 2025 EMBER 2025

Ruby Blum, VP Policy & Legislative Affairs ruby@dallas-cms.org (214) 413-1424 VISIT OUR WEBSITE

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Free Alzheimer’s CME for Providers

What you need to know as a primary care provider.

Earn free online Continuing Medical Education (CME) credits developed by the Texas Department of State Health Services and physician experts on Alzheimer’s disease and related dementias. These courses will keep you up to date on the latest validated assessment and screening tools, help you direct patients to community resources, and reinforce your role in helping patients and their families manage symptoms throughout the disease process.

DSHS Alzheimer’s Disease Program Learn more at dshs.texas.gov/alzheimers-disease/provider Content on the Texas Department of State Health Services Alzheimer’s Disease Program website has been accredited by the Texas Medical Association and American Nurses Credentialing Center.

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March 2025

HEALTH ALLIES

Another important member of your team is the general contractor that will build your space. It is critical that the contractor you choose has extensive experience in constructing medical office spaces. You will want to have at least three qualified contractors provide bids for performing the work. You will want to know not only what the cost will be, but also how long it will take them to complete the work.

Other members of your team will include a real estate attorney that is experienced in reviewing medical office leases and a lender that understands the unique financial needs of medical professionals.

How to Get the Best Deal on Your Office Lease

by Evan Reynolds MOST MEDICAL PROFESSIONALS WILL FACE THE challenge of negotiating a lease for office space at some point in their careers. It can be a frustrating and confusing process, not to mention costly, if not approached in a strategic way. Fortunately, you can successfully negotiate a new lease or renewal by following a few key recommendations, detailed below.

Start Early Whether you are renegotiating your current lease or scouting for a new office, you’ll need at least six months to evaluate your alternatives and effectively negotiate lease terms. You’ll need to start even earlier if you are searching for a new office, and you must build it from scratch. Waiting until the last minute sends a message to the building landlord that you have no other options. This obviously severely diminishes your negotiating position, and enables the landlord to largely dictate the terms of the lease.

Assemble Your Team Leasing an office space is not a one-person job. You need a team of professionals that can assist you in all phases of the process. A real estate broker who specializes in working with medical professionals can help you with finding the right location and lease negotiations. Your attorney, fellow doctors, or equipment supplier may be able to steer you to such a professional. Real estate brokers exclusively represent your interests and are paid a standard commission by the building owner when the project is completed. An architect should be another key member of your lease team. You need one to draft a tentative floor plan to determine how a particular space might work for your needs, and to produce the final architectural documents.

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Develop a Vision You probably won’t have all the details nailed down as you start the process, but it is a good idea to think about what you want your practice to be, and where you want it to be located. This information will help produce a criterion that will enable your real estate broker to identify alternatives that best meet your needs.

The broker can also play a big role in developing your vision by providing demographic information, competition studies, traffic studies, etc. It is also helpful to think about the image of your practice. Do you want to be in a high-traffic retail location or in a low-visibility professional office building?

Evaluate Your Options The key to successfully negotiating the terms of a new lease or lease renewal is having options. Your broker should play a vital role in developing a negotiating strategy that will maximize your options and, consequently, maximize your negotiating leverage.

Having options produces a competitive environment, which will put you in position to make the best deal. You are not only negotiating the rental rate and improvement allowance, but also the right to renew your lease, expand your space, and influence a variety of other important terms.

The concept of negotiating leverage is particularly critical when it comes to negotiating a lease renewal. Medical professionals are seen as captive tenants by landlords. They believe you do not want to relocate because you have invested so much in your space, and you do not want to confuse your patients by moving.

It is imperative that the landlord be convinced that you have options. You can do this by performing the same market research and evaluation process that you would utilize if you wanted to relocate. Options will be generated through this process that will send a message to the landlord that you are not tied to your current space.

Most medical professionals dread dealing with office space issues.

The process can be confusing and frustrating, particularly if you are setting up an office for the first time. Fortunately, by following these key recommendations, you can find the right office space for your practice, and successfully negotiate your lease. DMJ The author is president of Medical Space Advisors (medicalspaceadvisors.com), a commercial real estate brokerage firm based in Dallas, Texas, which specializes in helping medical professionals with their office space needs.

DALLAS MEDICAL JOURNAL | 21

ADVANCEMENT

Redefining Acute Virtual Care for Overburdened Health Systems

by Michael J. Maniaci, MD1,2; Richard D. Rothman, MD1,3; Jessica A. Hohman, MD1,4 OVER THE PAST DECADE, THE CONCEPT OF delivering acute hospital-level care in the home has gained traction, particularly with advances in telemedicine and remote patient monitoring.1 The COVID-19 pandemic accelerated this shift by demonstrating the effectiveness of out-of-hospital care models in preventing health care systems from becoming overwhelmed. Several prior studies, including some systematic reviews, have highlighted that hospital-at-home models can achieve outcomes comparable with inpatient care, often with added benefits such as reduced hospital-acquired infections and improved patient satisfaction.2 Banerjee et al3 explore a novel all-virtual acute care program, called Safer@Home, implemented by Los Angeles General Medical Cen22 | DALLAS MEDICAL JOURNAL

ter, to reduce hospital stays for patients with acute illnesses.

This retrospective cohort study compared the outcomes of 876 patients who received acute virtual care at home with outcomes of 1590 patients who were treated using traditional in-hospital care for similar conditions. The study found that the Safer@Home patients spent a mean of 4 fewer days in the hospital (1.3 vs 5.3 days), without a significant increase in 30-day readmission or mortality rates. This all-virtual model effectively avoided the use of 3505 bed-days without compromising safety, both making this an impactful exploration of alternatives to traditional inpatient care as well as offering a promising alternative for underresourced health systems unable to support in-home care.

Traditional hospital-at-home models typically rely on deploying health professionals to patients’ homes, including in-person nursing visits 2 times daily—a resource-intensive process that is often untenable in large, overburdened health systems where staffing and geographic distribution pose significant barriers. The Safer@Home program addresses this gap by creating an all-virtual, outpatient-based system, eliminating the need for inMarch 2025

ADVANCEMENT

home visits while still ensuring close monitoring of patients and access to health care services. The model focuses on conditions typically requiring inpatient care, such as pneumonia, cellulitis, and heart failure exacerbation, but manages these illnesses remotely with oral or inhalational medications and routine virtual check-ins.

One of the most significant findings from this study is the marked reduction in hospital bed use. Patients in the virtual care group spent a mean of 4 fewer days in the hospital compared with those receiving traditional inpatient care. This reduction not only alleviates hospital overcrowding, but also allows hospitals to prioritize resources for patients with more severe illness and emergency cases, a crucial benefit at a time when hospitals are grappling with increasing demand and staff shortages. This finding leads into the model’s cost-saving potential. Hospital stays are resource intensive, and reducing the length of stay without compromising patient outcomes can help curb overall health care costs. This study also suggests that high-acuity outpatient virtual care, which bypasses the need for inhome nursing visits, offers a more financially sustainable alternative to traditional hospital-at-home models, which often involve significant staffing and logistical demands.

Another critical outcome is the safety of this virtual model, as demonstrated by the lack of a statistically significant difference in 30-day mortality or readmission rates between the virtual care group and the traditional care group. This finding is essential because it confirms that this level of virtual care can be provided without increasing risks to patients. This is critical, as inpatient care already has many risks associated with it.4 Although patients in the virtual care group had more outpatient urgent care visits, this was an expected outcome and an integral part of the model’s design, which emphasizes timely follow-up care without necessitating hospital readmission.

Finally, the study’s focus on a safety-net hospital highlights the potential of this model to reduce health disparities in underserved populations.

Patients who rely on safety-net services often face barriers, such as limited transportation and socioeconomic challenges, that make frequent hospital visits difficult.5 The success of the Safer@Home model in this setting suggests that similar virtual care programs could be scaled in other underserved regions, potentially improving access to care while also reducing the burden on hospital systems.

Although these findings are promising, if other health care systems wish to integrate and grow this model of care into their system, several areas must be addressed. First, patient selection played a critical role in the success of this program. Only patients who were hemodynamically stable and capable of managing oral medications were included, which suggests this care delivery model may not be suitable for patients requiring acute inpatient care. This was acknowledged by the authors, who excluded patients requiring higher-intensity services such as intravenous therapy or closer physical monitoring, both core hospital-at-home components, due to resource and logistic challenges. This brings up an important question as more care moves into the home setting: how do we define what is “continued acute inpatient care” at home vs what is “high-intensity postacute home care”? Meeting continued inpatient criteria by health care utilization review will likely be the key defining factor between the 2 forms of March 2025

care, but clearer structures will be needed as these models expand.

Guidelines are needed to better differentiate acute hospital-at-home care from other types of in-home medical care, such as high intensity postacute care or self-administered care in the home with clinical oversight.

Another important factor is the reliance on technology and infrastructure. Virtual care hinges on the availability of reliable internet access and devices for remote monitoring. For many patients who rely on safety-net services, access to such technology may be limited.

Health systems looking to implement similar models must consider strategies to address these barriers, such as providing the necessary equipment or collaborating with community organizations to ensure access as well as staffing and training to support technological literacy.

Last, operational challenges related to scalability and reimbursement could challenge the Safer@Home model. This model of care, while effective, does not currently meet Medicare’s criteria for hospital-at-home reimbursement because it lacks criteria for inpatient level of care and in-home clinical visits. Reimbursement would be based on an outpatient model, which has payment limitations for several aspects of high-acuity virtual care. For this model to be scaled nationally, adjustments to reimbursement structures and broader regulatory approval would be necessary. Health systems and policymakers should consider how to adapt current reimbursement frameworks to support innovative care models such as Safer@ Home, which have the potential to reduce hospital burden and improve patient outcomes.

Banerjee et al3 offer a compelling case for high-intensity virtual care as a safe and effective alternative to inpatient hospitalization. By significantly reducing hospital stays without compromising patient outcomes, this model presents a viable solution to the challenges of hospital overcrowding and staffing shortages. Moreover, the success of this program in a large urban safety-net hospital demonstrates its potential to improve health care delivery for underserved populations. As health systems continue to innovate in response to evolving patient needs and resource constraints, models such as Safer@ Home will play a pivotal role in shaping the future of acute care delivery. Expanding these programs, refining patient eligibility criteria, and addressing technological barriers will be key steps in realizing the full potential of virtual care. DMJ

REFERENCES

Xu S, Wang J, Wang Y, Wang M, Huang X, Huang H. Individuals’ awareness of and willingness to accept hospital-at-home services and related factors: a cross-sectional study. Front Public Health. 2022;10:823384. doi:10.3389/fpubh.2022.823384PubMedGoogle ScholarCrossref 2. Leong MQ, Lim CW, Lai YF. Comparison of hospital-at-home models: a systematic review of reviews. BMJ Open. 2021;11(1):e043285. doi:10.1136/bmjopen-2020-043285PubMedGoogle ScholarCrossref 3. Banerjee J, Lynch C, Gordon H, et al. Virtual home care for patients with acute illness. JAMA Netw Open. 2024;7(11):e2447352. doi:10.1001/jamanetworkopen.2024.47352 ArticleGoogle Scholar 4. Bates DW, Levine DM, Salmasian H, et al. The safety of inpatient health care. N Engl J Med. 2023;388(2):142-153. doi:10.1056/NEJMsa2206117PubMedGoogle ScholarCrossref 5. Knudsen J, Chokshi DA. COVID-19 and the safety net—moving from straining to sustaining. N Engl J Med. 2021;385(24):2209-2211. doi:10.1056/NEJMp2114010PubMedGoogle ScholarCrossref

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FOUNDATION

On behalf of the DCMS Foundation, we are deeply grateful for the incredible generosity of our donors. Your remarkable support fuels our mission and makes everything we do possible. Thank you for standing with us—your commitment truly makes a meaningful difference in the lives of many.

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MEMBERSHIP

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March 2025

SOCIETY

Celebrating Excellence on International Women’s Day Dr. Kristen Aliano Messina’s Trailblazing Impact in Medicine IN THE EVER-EVOLVING field of medicine, Dr. Kristen A. Aliano Messina stands at the intersection of science, innovation, and compassionate care.

As Chief of Plastic Surgery & Aesthetics at TriCelX, located at The Star in Frisco, Texas, Dr. Aliano Messina is a visionary leader shaping the future of regenerative medicine.

TriCelX is a multidisciplinary medical practice comprising three divisions: LumineX, for Photo Credit: Jenny Leigh Photography plastic surgery and aesthetics, JuveneX, for longevity and wellness, and OrthodynamiX, for sports medicine and pain management. At the core of these specialties lies a shared focus on regenerative medicine, an area where Dr. Aliano Messina and her team March 2025

are pioneering biotherapeutics to aid wounded warriors, individuals with traumatic brain injuries, burn victims, and those suffering from chronic pain and systemic conditions.

Dr. Aliano Messina’s journey to becoming a well-trained plastic surgeon began on Long Island, New York. Her academic prowess was evident early on, as she conducted genetics and molecular biology research at Cold Spring Harbor Laboratory while still in high school. She earned her undergraduate degree from Cornell University, graduating Phi Beta Kappa and magna cum laude in just 3.5 years. Following a stint at Pfizer, managing international clinical trials, she went on to graduate first in her class from the State University of New York School of Medicine.

Her medical training spanned prestigious institutions, beginning with general surgery at Stony Brook University Medical Center before she transitioned to a two-year research fellowship at the Long Island Plastic Surgery Group. She then completed her plastic surgery residency at the University of Texas Medical Branch in Galveston. Along the way, she garnered multiple scientific publications, grants, and national conference presentations.

Despite her rigorous career, Dr. Aliano Messina is deeply committed to her community in Frisco, where she resides with her husband, daughter, and soon-to-arrive second child. After navigating the challenges of establishing herself in a new city during a global pandemic, she has found immense fulfillment in both her professional and personal life, grateful for the opportunity to live and work within the same community.

With a steadfast dedication to patient care and a passion for scientific discovery, Dr. Aliano Messina continues to push the boundaries of medical innovation, ensuring a future where regenerative medicine transforms lives.

DALLAS MEDICAL JOURNAL | 27

SOCIETY

Natalie Boone, MD Specialty: Family Medicine Faculty at Methodist’s Family Medicine Residency Program Vice Chair of Family Medicine at Methodist Charlton Medical Center

Dr. Natalie Boone has made a profound impact on the field of family medicine, serving as a mentor, educator, and advocate for both her residents and the community. A native of Dallas, Texas, Dr. Boone pursued her medical education at Baylor College of Medicine before completing her residency at Adventist Health Glendale’s Family Medicine Residency Program in 2022. Upon completing her training, she returned to her hometown to join the faculty at Methodist Health System’s Family Medicine Residency Program at Methodist Charlton Medical Center, where she has since led initiatives in women’s health and wellness education.

As a faculty member, Dr. Boone has taken on critical leadership roles, including overseeing the Women’s Health and Wellness Curriculums for residents. She has also spearheaded the development of a Point of Care Ultrasound (POCUS) curriculum, enhancing the hands-on training opportunities for future family physicians. Her commitment to academic excellence is further demonstrated by her attainment of a Graduate Certificate in Academic Medicine from UNT Health Science Center, a testament to her dedication to medical education and professional growth.

Beyond her clinical and educational contributions, Dr. Boone has been a strong advocate for resident and patient well-being. She has introduced valuable initiatives such as Safe Zone training, ensuring an inclusive and supportive healthcare environment. Her efforts in these areas have not only benefited her colleagues, but they have also enriched the quality of patient care, particularly for underserved populations in South Dallas.

Her exceptional contributions have not gone unnoticed. Dr. Boone has been nominated by Dr. Kimberly Tran, a PGY-1 resident at Methodist Charlton Family Medicine Residency, for the DCMS Woman Physician recognition. This nomination is a reflection of Dr. Boone’s unwavering dedication to mentoring the next generation of physicians.

Dr. Tran, on behalf of the intern resident class, highlighted Dr. Boone’s pivotal role in their training, emphasizing her leadership in POCUS training, outpatient procedural education, the wellness committee, and the obstetrics clinic. She noted Dr. Boone’s ability to foster a learning environment that balances technical excellence with compassion and cultural competence, particularly in women’s health.

Through her mentorship, residents gain not only the clinical skills necessary for primary care, but also the empathy and critical thinking needed to provide patient-centered care.

Dr. Boone’s influence extends beyond the walls of the residency program. Her commitment to advocating for comprehensive healthcare access, particularly for women, has significantly impacted the South Dallas community. By emphasizing patient education and 28 | DALLAS MEDICAL JOURNAL

healthcare literacy, she ensures that patients receive holistic, informed, and compassionate care.

As a role model for women in medicine, Dr. Boone embodies the spirit of International Women’s Day through her dedication to education, advocacy, and leadership. Her work serves as an inspiration to her peers and trainees, highlighting the essential roles of mentorship and innovation in shaping the future of family medicine. Her nomination for the DCMS Woman Physician recognition is a well-deserved acknowledgment of her contributions to medicine and medical education.

Alexandra Callan, MD Specialty: Orthopedic Oncology Associate Professor at UT Southwestern Medical Center

Dr. Alexandra (Alex) Callan is a distinguished musculoskeletal oncologist and an associate professor, serving as the Director of Orthopaedic Oncology at UT Southwestern. In her role, she provides expert care to patients with sarcomas, metastatic bone disease, complex joint replacements, and other bone and soft tissue tumors. She extends her expertise across multiple institutions, including UT Southwestern, Children’s Health, Parkland Memorial Hospital, and Texas Scottish Rite Hospital for Children. Working collaboratively with multidisciplinary sarcoma teams, she is dedicated to delivering comprehensive, patient-centered care.

Originally from Denver, Colorado, Dr. Callan considers The Woodlands, Texas, her hometown. She earned her Bachelor of Science degree from the University of Notre Dame, where she developed a deep appreciation for Irish football. Before embarking on her medical journey, she served as a Teach for America Corps member, teaching high school science and coaching multiple sports in Houston. She later pursued her medical education at Baylor College of Medicine, where she discovered her passion for surgery.

Dr. Callan completed her Orthopaedic Surgery Residency at Vanderbilt University Medical Center in Nashville, Tennessee, followed by an Orthopaedic Oncology Fellowship at MD Anderson Cancer Center in Houston, Texas.

Since joining UT Southwestern, she has been instrumental in expanding the Sarcoma Program, and she remains committed to medical education, mentoring residents and medical students while ensuring exceptional, personalized patient care.

Her dedication and leadership have earned her recognition from peers and colleagues. Dr. Antonia Chen has nominated Dr. Callan for her outstanding contributions to orthopaedic oncology. Dr. Chen highlights Dr. Callan’s excellence in patient care, describing her as a compassionate and skilled surgeon who has profoundly impacted the lives of her patients, including helping amputees regain mobility.

Dr. Callan’s influence extends beyond the operating room. She exemplifies medical excellence, mentorship, and compassionate patient care, making a lasting impact in her field. Outside of work, she enjoys wakeboarding, live music, snowboarding, travel, and adventure. Her dedication to both professional and personal pursuits embodies the spirit of resilience and passion, making her a true role model in medicine.

March 2025

SOCIETY

Dr. Callan’s nomination is a testament to her leadership and unwavering commitment to her patients and colleagues. She continues to inspire the next generation of orthopaedic surgeons while advancing the field of musculoskeletal oncology with her expertise and compassion.

cent medicine and public health. Her nomination is a well-deserved recognition of her tireless efforts to improve healthcare for young people while inspiring and training the next generation of physicians and public health advocates.

May Lau, MD, MPH Specialty: Pediatric Adolescent Medicine Associate Professor of Pediatrics at the University of Texas Southwestern Dallas | Medical Director, Adolescent and Young Adult Medicine Program at Children’s Medical Health Dallas | Associate Dean of Student Affairs (Interim) at the O’Donnell School of Public Health

Dr. May Lau, MD, MPH, is a distinguished adolescent medicine physician and an Associate Professor in the Department of Pediatrics at the University of Texas Southwestern (UTSW) Medical Center. She serves as the medical director of the Adolescent and Young Adult (AYA) clinic at Children’s Medical Center Dallas, where she provides specialized care for adolescents and young adults. Additionally, she is currently the interim Associate Dean of Student Affairs at the UTSW O’Donnell School of Public Health, demonstrating her commitment to mentoring and guiding the next generation of healthcare professionals.

Dr. Lau’s expertise in adolescent medicine has earned her widespread recognition, including being named one of D Magazine’s top adolescent medicine specialists since 2011. She has also been honored as a Fellow of the Society of Adolescent Health and Medicine, highlighting her significant contributions to the field. Beyond her clinical work, Dr. Lau has held influential leadership positions, including serving as the former Co-Chair of the American Academy of Pediatrics (AAP) Texas Pediatric Society (TPS) Committee on Adolescent and Sports Medicine and as the Past President of the Texas Chapter of the Society of Adolescent Health and Medicine.

Nationally, Dr. Lau plays a key role in advancing adolescent health policy and advocacy. She is an elected member of the AAP Committee on Adolescent and Young Adult Executive and was the lead pediatrician on the AAP’s Blueprint for Youth Suicide Prevention. This initiative, developed in collaboration with the American Foundation for Suicide Prevention and the National Institutes of Mental Health, underscores her dedication to addressing critical mental health issues affecting young people.

At UTSW, Dr. Lau’s leadership extends to the Women in Science and Medicine Advisory Committee, where she continues to champion the advancement of women in the medical field. She is a sought-after speaker, frequently invited to present at national and regional conferences on adolescent health topics, including sexually transmitted infections, contraception, abnormal uterine bleeding, mental health, and reproductive health issues.

Dr. Lau’s impact has not gone unnoticed. She has been nominated by Dr. M. Brett Cooper for her unwavering dedication to adolescent medicine, medical education, and public health advocacy. Dr. Cooper highlights her extensive involvement in the Dallas County Medical Society (DCMS) and the Texas Medical Association (TMA) over the past decade, as well as her role in recruiting future public health professionals in her capacity as Associate Dean of Student Affairs.

Through her compassionate patient care, influential leadership, and dedication to mentorship, Dr. May Lau continues to shape the future of adolesMarch 2025

Amanda Garza, MD Specialty: General Surgery General Surgery Chief Resident at UT Southwestern

Dr. Amanda Michelle Garza, a General Surgery Chief Resident at UT Southwestern Medical Center/Parkland Memorial Hospital, has demonstrated unwavering commitment to surgical excellence, research, and mentorship. Born and raised in Laredo, Texas, Dr. Garza graduated summa cum laude from Texas A&M International University in 2014 with a bachelor’s degree in biology and chemistry. Her passion for medical research led her to the University of Texas Medical Branch at Galveston Graduate School of Biomedical Sciences, where she contributed to groundbreaking vaccine development research for the National Institutes of Health.

Continuing her education, Dr. Garza earned her medical degree from Loyola University Chicago - Stritch School of Medicine in 2020, graduating with Research Honors. During her time in medical school, she served as a board member of the Chicago Community Health Clinic, one of the largest volunteer-based health centers in the nation, reinforcing her dedication to community service and healthcare accessibility.

Throughout her surgical training, Dr. Garza has conducted extensive research on burns, breast cancer and reconstruction, hernias, and surgical outcomes. Her contributions to the field have been widely recognized, and in 2023, she was honored with the “Consultant of the Year” award by her colleagues. She is deeply committed to mentorship, guiding junior residents and medical students with the same dedication she extends to her patients.

In June 2025, Dr. Garza will further her specialization by beginning a fellowship in Plastic Surgery at UT Southwestern, where she will continue to make impactful contributions to surgical innovation and patient care.

Dr. Garza’s exceptional dedication has earned her a nomination from Dr. Sameer Halani, who praises her for her patient-centered approach and advocacy. He describes her as a compassionate and skilled surgeon who ensures that her patients feel heard and well-cared-for, particularly those facing serious ailments, limited healthcare access, or medical literacy barriers. Dr. Garza goes beyond her clinical duties, taking the time to sit by the bedsides of her patients, ensuring that they understand their medical conditions and treatment plans.

Dr. Garza embodies the qualities of an outstanding physician—compassion, expertise, and relentless advocacy for her patients. Her nomination is a testament to her profound impact on the field of surgery and the lives of those she serves. As she continues her journey into plastic surgery, her leadership and dedication will undoubtedly shape the future of surgical care and mentorship. DMJ DALLAS MEDICAL JOURNAL | 29

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Advertising Index

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Dallas County Medical Society (DCMS) does not endorse or evaluate advertised products, services, or companies nor any of the claims made by advertisers. Claims made by any advertiser or by any company advertising in the Dallas Medical Journal do not constitute legal or other professional advice. You should consult your professional advisor.

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