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Background: In 2011, the American Board of Medical Specialties established clinical informatics (CI) as a subspecialty in medicine, jointly administered by the American Board of Pathology and the American Board of Preventive Medicine. Subsequently, many institutions created CI fellowship training programs to meet the growing need for informaticists. Although many programs share similar features, there is considerable variation in program funding and administrative structures., Objectives: The aim of our study was to characterize CI fellowship program features, including governance structures, funding sources, and expenses., Methods: We created a cross-sectional online REDCap survey with 44 items requesting information on program administration, fellows, administrative support, funding sources, and expenses. We surveyed program directors of programs accredited by the Accreditation Council for Graduate Medical Education between 2014 and 2021., Results: We invited 54 program directors, of which 41 (76%) completed the survey. The average administrative support received was $27,732/year. Most programs (85.4%) were accredited to have two or more fellows per year. Programs were administratively housed under six departments: Internal Medicine (17; 41.5%), Pediatrics (7; 17.1%), Pathology (6; 14.6%), Family Medicine (6; 14.6%), Emergency Medicine (4; 9.8%), and Anesthesiology (1; 2.4%). Funding sources for CI fellowship program directors included: hospital or health systems (28.3%), clinical departments (28.3%), graduate medical education office (13.2%), biomedical informatics department (9.4%), hospital information technology (9.4%), research and grants (7.5%), and other sources (3.8%) that included philanthropy and external entities., Conclusion: CI fellowships have been established in leading academic and community health care systems across the country. Due to their unique training requirements, these programs require significant resources for education, administration, and recruitment. There continues to be considerable heterogeneity in funding models between programs. Our survey findings reinforce the need for reformed federal funding models for informatics practice and training., Competing Interests: None declared., (Thieme. All rights reserved.)

Background: Clinical Informatics (CI) fellowship programs utilize the Electronic Residency Application Service (ERAS) to gather applications but until recently used an American Medical Informatics Association (AMIA) member-developed, simultaneous offer-acceptance process to match fellowship applicants to programs. In 2021, program directors collaborated with the AMIA to develop a new match to improve the process., Objective: Describe the results of the first 2 years of the match and address opportunities for improvement., Methods: We obtained applicant data for fellowship applicants in 2021 and 2022 from the ERAS and match data for the same years from the AMIA. We analyzed our data using descriptive statistics., Results: There were 159 unique applicants over the 2-year period. Applicants submitted 2,178 applications with a median of 10 per applicant (interquartile range [IQR] 3-20). One hundred and four applicants (65.4%) participated in the match and ranked a median of seven programs (2-12). Forty-two programs in 2021 and 47 programs in 2022 offered a combined total 153 positions in the match. Participating programs ranked a median of eight applicants per year (IQR 5-11). Of participating applicants, 95 (91.3%) successfully matched and of those 66 (69.5%) received their top choice. Thirty-two programs (76.2%) matched at least one candidate in 2021 and 33 programs (70.2%) matched at least one candidate in 2022. In both years, 24 programs filled all available slots (57.1% in 2021 and 51.1% in 2022)., Conclusion: Applicants were extremely successful in the new match, which successfully addressed most of the challenges of the simultaneous offer-acceptance process identified by program directors. However, applicant attrition resulted in a quarter of programs going unmatched. Although many programs still filled slots outside the match, fellowship slots may remain unfilled while the CI practice pathway remains open., Competing Interests: All authors are current or past members of the Clinical Informatics Program Directors Match Subcommittee.J.D.H. chairs the Match Subcommittee.M.L. is the past chair of the Match Subcommittee and helped develop the AMIA match algorithm., (Thieme. All rights reserved.)

Board certified clinical informaticians provide expertise in leveraging health IT (HIT) and health data for patient care and quality improvement. Clinical Informatics experts possess the requisite skills and competencies to make systems-level improvements in care delivery using HIT, workflow and data analytics, knowledge acquisition, clinical decision support, data visualization, and related informatics tools. However, these physicians lack structured and sustained funding because they have no billing codes. The sustainability and growth of this new and promising medical subspecialty is threatened by outdated and inconsistent funding models that fail to support the education and professional growth of clinical informaticians. The Clinical Informatics Program Directors' Community is calling upon the Centers for Medicare and Medicaid Services to consider novel funding structures and programs through its Innovation Center for Clinical Informatics Fellowship training. Only through structural and sustained funding for Clinical Informatics fellows will be able to fully develop the potential of electronic health records to improve the quality, safety, and cost of clinical care., Competing Interests: C.U.L. reports that he is designated to be the Fellowship program director, UT Southwestern. J.S. reports that he was employed by the American Medical Informatics Association, which serves as the professional home for Clinical Informatics Fellows., (Thieme. All rights reserved.)

In 2013, the American Board of Preventive Medicine (ABPM) and the American Board of Pathology (ABPath) offered the first board certification examination in Clinical Informatics to eligible physicians in the United States. In 2022, the Practice Pathway will expire and in 2023 only candidates eligible through the Fellowship Pathway will be eligible for the board certification. To date, Clinical Informatics as a specialty has not had a regular match process and used a controlled offer-acceptance process that does not meet candidates' or programs' needs. Fellows may not be offered a position with their top choice program initially, and they may accept offers from other programs to avoid risk by ensuring that they have a fellowship position. Programs have to consider losing an applicant in the first round in the ranking of applicants. The process is open to manipulation including early agreements between program directors and candidates. In this open letter to the ABPM, program directors make the case for a third-party match and are calling on the ABPM to leverage its status as the Clinical Informatics certifying body and its existing infrastructure to implement a Clinical Informatics match., Competing Interests: C.U.L. reports support from the International Medical Informatics Association, Thieme, and Springer, outside the submitted work. M.G.L. reports working with a workgroup of program directors to define the requirements for the match, and to create an algorithm to implement the match. He intends to “donate” the algorithm to the host organization and not to profit from this algorithm. The other authors have nothing to report., (Georg Thieme Verlag KG Stuttgart · New York.)

Introduction: The emerging operational role of the "Chief Clinical Informatics Officer" (CCIO) remains heterogeneous with individuals deriving from a variety of clinical settings and backgrounds. The CCIO is defined in title, responsibility, and scope of practice by local organizations. The term encompasses the more commonly used Chief Medical Informatics Officer (CMIO) and Chief Nursing Informatics Officer (CNIO) as well as the rarely used Chief Pharmacy Informatics Officer (CPIO) and Chief Dental Informatics Officer (CDIO)., Background: The American Medical Informatics Association (AMIA) identified a need to better delineate the knowledge, education, skillsets, and operational scope of the CCIO in an attempt to address the challenges surrounding the professional development and the hiring processes of CCIOs., Discussion: An AMIA task force developed knowledge, education, and operational skillset recommendations for CCIOs focusing on the common core aspect and describing individual differences based on Clinical Informatics focus. The task force concluded that while the role of the CCIO currently is diverse, a growing body of Clinical Informatics and increasing certification efforts are resulting in increased homogeneity. The task force advised that 1.) To achieve a predictable and desirable skillset, the CCIO must complete clearly defined and specified Clinical Informatics education and training. 2.) Future education and training must reflect the changing body of knowledge and must be guided by changing day-to-day informatics challenges., Conclusion: A better defined and specified education and skillset for all CCIO positions will motivate the CCIO workforce and empower them to perform the job of a 21st century CCIO. Formally educated and trained CCIOs will provide a competitive advantage to their respective enterprise by fully utilizing the power of Informatics science.

Background: Older adults are at risk for inadequate emergency department (ED) pain care. Unrelieved acute pain is associated with poor outcomes. Clinical decision support systems (CDSS) hold promise to improve patient care, but CDSS quality varies widely, particularly when usability evaluation is not employed., Objective: To conduct an iterative usability and redesign process of a novel geriatric abdominal pain care CDSS. We hypothesized this process would result in the creation of more usable and favorable pain care interventions., Methods: Thirteen emergency physicians familiar with the Electronic Health Record (EHR) in use at the study site were recruited. Over a 10-week period, 17 1-hour usability test sessions were conducted across 3 rounds of testing. Participants were given 3 patient scenarios and provided simulated clinical care using the EHR, while interacting with the CDSS interventions. Quantitative System Usability Scores (SUS), favorability scores and qualitative narrative feedback were collected for each session. Using a multi-step review process by an interdisciplinary team, positive and negative usability issues in effectiveness, efficiency, and satisfaction were considered, prioritized and incorporated in the iterative redesign process of the CDSS. Video analysis was used to determine the appropriateness of the CDS appearances during simulated clinical care., Results: Over the 3 rounds of usability evaluations and subsequent redesign processes, mean SUS progressively improved from 74.8 to 81.2 to 88.9; mean favorability scores improved from 3.23 to 4.29 (1 worst, 5 best). Video analysis revealed that, in the course of the iterative redesign processes, rates of physicians' acknowledgment of CDS interventions increased, however most rates of desired actions by physicians (such as more frequent pain score updates) decreased., Conclusion: The iterative usability redesign process was instrumental in improving the usability of the CDSS; if implemented in practice, it could improve geriatric pain care. The usability evaluation process led to improved acknowledgement and favorability. Incorporating usability testing when designing CDSS interventions for studies may be effective to enhance clinician use.

Background: Dissemination and adoption of clinical decision support (CDS) tools is a major initiative of the Affordable Care Act's Meaningful Use program. Adoption of CDS tools is multipronged with personal, organizational, and clinical settings factoring into the successful utilization rates. Specifically, the diffusion of innovation theory implies that 'early adopters' are more inclined to use CDS tools and younger physicians tend to be ranked in this category., Objective: This study examined the differences in adoption of CDS tools across providers' training level., Participants: From November 2010 to 2011, 168 residents and attendings from an academic medical institution were enrolled into a randomized controlled trial., Intervention: The intervention arm had access to the CDS tool through the electronic health record (EHR) system during strep and pneumonia patient visits., Main Measures: The EHR system recorded details on how intervention arm interacted with the CDS tool including acceptance of the initial CDS alert, completion of risk-score calculators and the signing of medication order sets. Using the EHR data, the study performed bivariate tests and general estimating equation (GEE) modeling to examine the differences in adoption of the CDS tool across residents and attendings., Key Results: The completion rates of the CDS calculator and medication order sets were higher amongst first year residents compared to all other training levels. Attendings were the less likely to accept the initial step of the CDS tool (29.3%) or complete the medication order sets (22.4%) that guided their prescription decisions, resulting in attendings ordering more antibiotics (37.1%) during an CDS encounter compared to residents., Conclusion: There is variation in adoption of CDS tools across training levels. Attendings tended to accept the tool less but ordered more medications. CDS tools should be tailored to clinicians' training levels.

Objective: To understand clinician adoption of CDS tools as this may provide important insights for the implementation and dissemination of future CDS tools., Materials and Methods: Clinicians (n=168) at a large academic center were randomized into intervention and control arms to assess the impact of strep and pneumonia CDS tools. Intervention arm data were analyzed to examine provider adoption and clinical workflow. Electronic health record data were collected on trigger location, the use of each component and whether an antibiotic, other medication or test was ordered. Frequencies were tabulated and regression analyses were used to determine the association of tool component use and physician orders., Results: The CDS tool was triggered 586 times over the study period. Diagnosis was the most frequent workflow trigger of the CDS tool (57%) as compared to chief complaint (30%) and diagnosis/antibiotic combinations (13%). Conversely, chief complaint was associated with the highest rate (83%) of triggers leading to an initiation of the CDS tool (opening the risk prediction calculator). Similar patterns were noted for initiation of the CDS bundled ordered set and completion of the entire CDS tool pathway. Completion of risk prediction and bundled order set components were associated with lower rates of antibiotic prescribing (OR 0.5; CI 0.2-1.2 and OR 0.5; CI 0.3-0.9, respectively)., Discussion: Different CDS trigger points in the clinician user workflow lead to substantial variation in downstream use of the CDS tool components. These variations were important as they were associated with significant differences in antibiotic ordering., Conclusions: These results highlight the importance of workflow integration and flexibility for CDS success.

Objectives: Issues related to lack of system usability and potential safety hazards continue to be reported in the health information technology (HIT) literature. Usability engineering methods are increasingly used to ensure improved system usability and they are also beginning to be applied more widely for ensuring the safety of HIT applications. These methods are being used in the design and implementation of many HIT systems. In this paper we describe evidence-based approaches to applying usability engineering methods., Methods: A multi-phased approach to ensuring system usability and safety in healthcare is described. Usability inspection methods are first described including the development of evidence-based safety heuristics for HIT. Laboratory-based usability testing is then conducted under artificial conditions to test if a system has any base level usability problems that need to be corrected. Usability problems that are detected are corrected and then a new phase is initiated where the system is tested under more realistic conditions using clinical simulations. This phase may involve testing the system with simulated patients. Finally, an additional phase may be conducted, involving a naturalistic study of system use under real-world clinical conditions., Results: The methods described have been employed in the analysis of the usability and safety of a wide range of HIT applications, including electronic health record systems, decision support systems and consumer health applications. It has been found that at least usability inspection and usability testing should be applied prior to the widespread release of HIT. However, wherever possible, additional layers of testing involving clinical simulations and a naturalistic evaluation will likely detect usability and safety issues that may not otherwise be detected prior to widespread system release., Conclusion: The framework presented in the paper can be applied in order to develop more usable and safer HIT, based on multiple layers of evidence.