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Objective: Authors evaluated whether displaying context sensitive links to infrequently accessed educational materials and patient information via the user interface of an inpatient computerized care provider order entry (CPOE) system would affect access rates to the materials.Design: The CPOE of Vanderbilt University Hospital (VUH) included "baseline" clinical decision support advice for safety and quality. Authors augmented this with seven new primarily educational decision support features. A prospective, randomized, controlled trial compared clinicians' utilization rates for the new materials via two interfaces. Control subjects could access study-related decision support from a menu in the standard CPOE interface. Intervention subjects received active notification when study-related decision support was available through context sensitive, visibly highlighted, selectable hyperlinks.Measurements: Rates of opportunities to access and utilization of study-related decision support materials from April 1999 through March 2000 on seven VUH Internal Medicine wards.Results: During 4,466 intervention subject-days, there were 240,504 (53.9/subject-day) opportunities for study-related decision support, while during 3,397 control subject-days, there were 178,235 (52.5/subject-day) opportunities for such decision support, respectively (p = 0.11). Individual intervention subjects accessed the decision support features at least once on 3.8% of subject-days logged on (278 responses); controls accessed it at least once on 0.6% of subject-days (18 responses), with a response rate ratio adjusted for decision support frequency of 9.17 (95% confidence interval 4.6-18, p < 0.0005). On average, intervention subjects accessed study-related decision support materials once every 16 days individually and once every 1.26 days in aggregate.Conclusion: Highlighting availability of context-sensitive educational materials and patient information through visible hyperlinks significantly increased utilization rates for study-related decision support when compared to "standard" VUH CPOE methods, although absolute response rates were low. [ABSTRACT FROM AUTHOR]

Consensus is growing that a health care information and communication infrastructure is one key to fixing the crisis in the United States in health care quality, cost, and access. The National Health Information Infrastructure (NHII) is an initiative of the Department of Health and Human Services receiving bipartisan support. There are many possible courses toward its objective. Decision makers need to reflect carefully on which approaches are likely to work on a large enough scale to have the intended beneficial national impacts and which are better left to smaller projects within the boundaries of health care organizations. This report provides a primer for use by informatics professionals as they explain aspects of that dividing line to policy makers and to health care leaders and front-line providers. It then identifies short-term, intermediate, and long-term steps that might be taken by the NHII initiative. [ABSTRACT FROM AUTHOR]

Nine secondary cases of tuberculosis and 59 tuberculin skin test conversions occurred after exposure to a hospitalized patient with a large tuberculous abscess of the hip and thigh. Among 442 tuberculin-negative hospital employees, the relative risk of skin test conversion associated with recalled exposure to the patient was 14.0 (95% confidence limits, 6.8, 28.7). Four of 5 surgical suite employees who assisted with incision and debridement of the abscess had skin test conversions, as did 85% of 33 employees on a general medical floor who recalled exposure to the patient and 30% of 20 intensive care unit employees who recalled exposure. The prevalence of tuberculin reactivity in visitors and other patients on two floors also showed a strong association with exposure to the patient. A high concentration of Mycobacterium tuberculosis in the abscessed tissue, disturbance of the surface of liquid drainage from the abscess by irrigations and by the agitated behavior of the patient, and positive air pressure in the patient's room are factors that appear to have contributed to the high risk of tuberculosis transmission. [ABSTRACT FROM AUTHOR]

Objective: Sepsis is one of the most serious hospital conditions associated with high mortality. Sepsis is the result of a dysregulated immune response to infection that can lead to multiple organ dysfunction and death. Due to the wide variability in the causes of sepsis, clinical presentation, and the recovery trajectories, identifying sepsis sub-phenotypes is crucial to advance our understanding of sepsis characterization, to choose targeted treatments and optimal timing of interventions, and to improve prognostication. Prior studies have described different sub-phenotypes of sepsis using organ-specific characteristics. These studies applied clustering algorithms to electronic health records (EHRs) to identify disease sub-phenotypes. However, prior approaches did not capture temporal information and made uncertain assumptions about the relationships among the sub-phenotypes for clustering procedures., Methods: We developed a time-aware soft clustering algorithm guided by clinical variables to identify sepsis sub-phenotypes using data available in the EHR., Results: We identified six novel sepsis hybrid sub-phenotypes and evaluated them for medical plausibility. In addition, we built an early-warning sepsis prediction model using logistic regression., Conclusion: Our results suggest that these novel sepsis hybrid sub-phenotypes are promising to provide more accurate information on sepsis-related organ dysfunction and sepsis recovery trajectories which can be important to inform management decisions and sepsis prognosis., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Anru Zhang reports financial support and administrative support were provided by Duke University. Anru Zhang reports a relationship with Duke University that includes: employment. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The rising popularity of artificial intelligence in healthcare is highlighting the problem that a computational model achieving super-human clinical performance at its training sites may perform substantially worse at new sites. In this perspective, we argue that we should typically expect this failure to transport, and we present common sources for it, divided into those under the control of the experimenter and those inherent to the clinical data-generating process. Of the inherent sources we look a little deeper into site-specific clinical practices that can affect the data distribution, and propose a potential solution intended to isolate the imprint of those practices on the data from the patterns of disease cause and effect that are the usual target of probabilistic clinical models., (© 2024. The Author(s).)

Motivation: Phecodes are widely used and easily adapted phenotypes based on International Classification of Diseases codes. The current version of phecodes (v1.2) was designed primarily to study common/complex diseases diagnosed in adults; however, there are numerous limitations in the codes and their structure., Results: Here, we present phecodeX, an expanded version of phecodes with a revised structure and 1,761 new codes. PhecodeX adds granularity to phenotypes in key disease domains that are under-represented in the current phecode structure-including infectious disease, pregnancy, congenital anomalies, and neonatology-and is a more robust representation of the medical phenome for global use in discovery research., Availability and Implementation: phecodeX is available at https://github.com/PheWAS/phecodeX., (© The Author(s) 2023. Published by Oxford University Press.)

Objective: Knowledgebases are needed to clarify correlations observed in real-world electronic health record (EHR) data. We posit design principles, present a unifying framework, and report a test of concept., Materials and Methods: We structured a knowledge framework along 3 axes: condition of interest, knowledge source, and taxonomy. In our test of concept, we used hypertension as our condition of interest, literature and VanderbiltDDx knowledgebase as sources, and phecodes as our taxonomy. In a cohort of 832 566 deidentified EHRs, we modeled blood pressure and heart rate by sex and age, classified individuals by hypertensive status, and ran a Phenome-wide Association Study (PheWAS) for hypertension. We compared the correlations from PheWAS to the associations in our knowledgebase., Results: We produced PhecodeKbHtn: a knowledgebase comprising 167 hypertension-associated diseases, 15 of which were also negatively associated with blood pressure (pos+neg). Our hypertension PheWAS included 1914 phecodes, 129 of which were in the PhecodeKbHtn. Among the PheWAS association results, phecodes that were in PhecodeKbHtn had larger effect sizes compared with those phecodes not in the knowledgebase., Discussion: Each source contributed unique and additive associations. Models of blood pressure and heart rate by age and sex were consistent with prior cohort studies. All but 4 PheWAS positive and negative correlations for phecodes in PhecodeKbHtn may be explained by knowledgebase associations, hypertensive cardiac complications, or causes of hypertension independently associated with hypotension., Conclusion: It is feasible to assemble a knowledgebase that is compatible with EHR data to aid interpretation of clinical correlation research., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Electronic Health Record (EHR) data are captured over time as patients receive care. Accordingly, variations among patients, such as when a patient presents for care during the course of a disease, introduce bias into standard longitudinal EHR data analysis methods. We, therefore, aim to provide an alignment method that reduces this bias. We structure this task as a registration problem. While limited prior research on longitudinal EHR data considered registration, we propose a robust registration method to provide better data alignment by estimating the optimum time shift at each time point. We validate the proposed method for mortality prediction. We utilize a Recurrent Neural Network (RNN), time-varying Cox regression model, and Logistic Regression (LR) for mortality prediction. Results suggest our proposed registration method enhances mortality prediction with at least a 1-2% increase in major evaluation metrics utilized., (©2023 AMIA - All rights reserved.)

The Integrated Academic/Advanced Information Systems (IAIMS) program began in 1983 and was based on a study by the Association of American Medical Colleges (AAMC). Donald A.B. Lindberg M.D. was a member of the AAMC Advisory Committee. The U.S. National Library of Medicine (NLM) grants for IAIMS were initiated in 1984 the same year Dr. Lindberg became Director of the NLM. This chapter presents an overview of IAIMS and its progression through three stages with Dr. Lindberg's leadership., (© 2022 – The authors. Published by IOS Press.)

Importance: Numerous prognostic models of suicide risk have been published, but few have been implemented outside of integrated managed care systems., Objective: To evaluate performance of a suicide attempt risk prediction model implemented in a vendor-supplied electronic health record to predict subsequent (1) suicidal ideation and (2) suicide attempt., Design, Setting, and Participants: This observational cohort study evaluated implementation of a suicide attempt prediction model in live clinical systems without alerting. The cohort comprised patients seen for any reason in adult inpatient, emergency department, and ambulatory surgery settings at an academic medical center in the mid-South from June 2019 to April 2020., Main Outcomes and Measures: Primary measures assessed external, prospective, and concurrent validity. Manual medical record validation of coded suicide attempts confirmed incident behaviors with intent to die. Subgroup analyses were performed based on demographic characteristics, relevant clinical context/setting, and presence or absence of universal screening. Performance was evaluated using discrimination (number needed to screen, C statistics, positive/negative predictive values) and calibration (Spiegelhalter z statistic). Recalibration was performed with logistic calibration., Results: The system generated 115 905 predictions for 77 973 patients (42 490 [54%] men, 35 404 [45%] women, 60 586 [78%] White, 12 620 [16%] Black). Numbers needed to screen in highest risk quantiles were 23 and 271 for suicidal ideation and attempt, respectively. Performance was maintained across demographic subgroups. Numbers needed to screen for suicide attempt by sex were 256 for men and 323 for women; and by race: 373, 176, and 407 for White, Black, and non-White/non-Black patients, respectively. Model C statistics were, across the health system: 0.836 (95% CI, 0.836-0.837); adult hospital: 0.77 (95% CI, 0.77-0.772); emergency department: 0.778 (95% CI, 0.777-0.778); psychiatry inpatient settings: 0.634 (95% CI, 0.633-0.636). Predictions were initially miscalibrated (Spiegelhalter z = -3.1; P = .001) with improvement after recalibration (Spiegelhalter z = 1.1; P = .26)., Conclusions and Relevance: In this study, this real-time predictive model of suicide attempt risk showed reasonable numbers needed to screen in nonpsychiatric specialty settings in a large clinical system. Assuming that research-valid models will translate without performing this type of analysis risks inaccuracy in clinical practice, misclassification of risk, wasted effort, and missed opportunity to correct and prevent such problems. The next step is careful pairing with low-cost, low-harm preventive strategies in a pragmatic trial of effectiveness in preventing future suicidality.

Executive Summary: Patient-reported outcome measures (PROMs) are used in research and have the potential to improve clinical care. We sought to develop a strategy for integrating PROMs into routine clinical care at an academic health center. The implementation strategy consisted of three phases. The first, exploratory phase, focused on engaging leadership and conducting an inventory of current efforts to collect PROMs. The inventory revealed 87 patient-reported outcome efforts, 47 of which used validated PROMs (62% for research, 21% for clinical care, 17% for quality). In the second, preparatory phase, we identified three pilot implementation sites chosen with facilitators determined in the exploratory phase. Using data from local needs assessments at the pilot sites, we constructed a timeline for inclusion of PROM efforts across the clinical enterprise. In the third phase, we adapted a technology platform for capturing PROMs using the electronic health record and began implementing this platform at the pilot sites. We found that integrating PROMs into routine clinical practice is highly complex. This complexity necessitates change management at the enterprise level.

Introduction: Social and behavioral factors play important roles in physical and mental health; however, they are not routinely assessed in the healthcare system. A brief panel of measures of social and behavioral determinants of health (SBDs) were recommended in a National Academy of Medicine report for use in electronic health records. Initial testing of the panel established feasibility of use and robustness of the measures. This study evaluates their convergent and divergent validity in relation to self-reported physical and mental health and social desirability bias., Methods: Adults, aged ≥18 years, were recruited through Qualtrics online panel survey platform in 2015 (data analyzed in 2015-2016). Participants completed the (1) panel of SBD measures; (2) 12-Item Short Form Health Survey to assess associations with global physical and mental health; and (3) Marlowe-Crowne Social Desirability Scale short form to assess whether social desirability influenced associations between SBD measures and self-reported health., Results: The sample included 513 participants (mean age, 47.9 [SD=14.2] years; 65.5% female). Several SBD domain measures were associated with physical and mental health. Adjusting for age, poorer physical and mental health were observed among participants reporting higher levels of financial resource strain, stress, depression, physical inactivity, current tobacco use, and a positive score for intimate partner violence. These associations remained significant after adjustment for social desirability bias., Conclusions: SBD domains were associated with global measures of physical and mental health and were not impacted by social desirability bias. The panel of SBD measures should now be tested in clinical settings., (Copyright © 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Condon, Weston, and Hill (2017) and Rossiter (2017) expressed concerns about the recommended panel of psychosocial vital signs that should be included in electronic health records (EHRs). Condon et al. (2017) would prefer a broader array of measures and Rossiter (2017) a set of optimal measures based on consensus. Our task was to identify a core set of measures to be used now in all EHRs based on usefulness and low burden. We anticipate that with new evidence, changing needs, and greater input from stakeholders, the recommended measures will be elaborated or modified. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Introduction: Social and behavioral factors are known to affect health but are not routinely assessed in medical practice. To date, no studies have assessed a parsimonious panel of measures of social and behavioral determinants of health (SBDs). This study evaluated the panel of SBD measures recommended by the Institute of Medicine and examined the effect of question order., Methods: Adults, aged ≥18 years, were recruited using ResearchMatch.org for this randomized, parallel design study conducted in 2015 (data analyzed in 2015-2016). Three versions of the SBD measures, sharing the same items but in different orders of presentation (Versions 1-3), were developed. Randomized to six groups, participants completed each version at least 1 week apart (Weeks 1-3). Version order was counterbalanced across each administration and randomization was stratified by gender, race, and age. Main outcomes were effect of question order, completion time, and non-response rates., Results: Of 781 participants, 624 (80%) completed the Week 1 questionnaire; median completion time for answering all SBD questions was 5 minutes, 583/624 participants answered all items, and no statistically significant differences associated with question order were observed when comparing responses across all versions. No significant differences in responses within assignment groups over time were found, with the exception of the stress measure for Group 5 (p=0.036)., Conclusion: Question order did not significantly impact participant responses. Time to complete the questionnaire was brief, and non-response rate was low. Findings support the feasibility of using the Institute of Medicine-recommended questionnaire to capture SBDs., (Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Academic health centers (AHCs) are the nation's primary resource for healthcare discovery, innovation, and training. US healthcare revenue growth has declined sharply since 2009, and is forecast to remain well below historic levels for the foreseeable future. As the cost of education and research at nearly all AHCs is heavily subsidized through large transfers from clinical care margins, our institutions face a mounting crisis. Choices centering on how to increase the cost-effectiveness of the AHC enterprise require unprecedented levels of alignment to preserve an environment that nurtures creativity. Management processes require governance models that clarify decision rights while harnessing the talents and the intellectual capital of a large, diverse enterprise to nimbly address unfamiliar organizational challenges. This paper describes key leadership tactics aimed at propelling AHCs along this journey - one that requires from all leaders a commitment to resilience, optimism, and willingness to embrace change., Competing Interests: Potential Conflicts of Interest: None disclosed.

Social, psychological, and behavioral factors are recognized as key contributors to health, but they are rarely measured in a systematic way in health care settings. Electronic health records (EHRs) can be used in these settings to routinely collect a standardized set of social, psychological, and behavioral determinants of health. The expanded use of EHRs provides opportunities to improve individual and population health, and offers new ways for the psychological community to engage in health promotion and disease prevention efforts. This article addresses 3 issues. First, it discusses what led to current efforts to include measures of psychosocial and behavioral determinants of health in EHRs. Second, it presents recommendations of an Institute of Medicine committee regarding inclusion in EHRS of a panel of measures that meet a priori criteria. Third, it identifies new opportunities and challenges these recommendations present for psychologists in practice and research. (PsycINFO Database Record, ((c) 2016 APA, all rights reserved).)

Consistent collection and use of social and behavioral determinants of health can improve clinical care, prevention and general health, patient satisfaction, research, and public health. A recent Institute of Medicine committee defined a panel of 11 domains and 12 measures to be included in electronic health records. Incorporating the panel into practice creates a number of informatics research opportunities as well as challenges. The informatics issues revolve around standardization, efficient collection and review, decision support, and support for research. The informatics community can aid the effort by simultaneously optimizing the collection of the selected measures while also partnering with social science researchers to develop and validate new sources of information about social and behavioral determinants of health., (© The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objectives: To address the overuse of testing that complicates patient care, diminishes quality, and increases costs by implementing the diagnostic management team, a multidisciplinary system for the development and deployment of diagnostic testing guidelines for hematologic malignancies., Methods: The team created evidence-based standard ordering protocols (SOPs) for cytogenetic and molecular testing that were applied by pathologists to bone marrow biopsy specimens on adult patients. Testing on 780 biopsy specimens performed during the six months before SOP implementation was compared with 1,806 biopsy specimens performed during the subsequent 12 months., Results: After implementation, there were significant decreases in tests discordant with SOPs, omitted tests, and the estimated cost of testing to payers. The fraction of positive tests increased. Clinicians reported acceptance of the new procedures and perceived time savings., Conclusions: This process is a model for optimizing complex and personalized diagnostic testing.

The explosive growth of biomedical complexity calls for a shift in the paradigm of medical decision making-from a focus on the power of an individual brain to the collective power of systems of brains. This shift alters professional roles and requires biomedical informatics and information technology (IT) infrastructure. The authors illustrate this future role of medical informatics with a vignette and summarize the evolving understanding of both beneficial and deleterious effects of informatics-rich environments on learning, clinical care, and research. The authors also provide a framework of core informatics competencies for health professionals of the future and conclude with broad steps for faculty development. They recommend that medical schools advance on four fronts to prepare their faculty to teach in a biomedical informatics-rich world: (1) create academic units in biomedical informatics; (2) adapt the IT infrastructure of academic health centers (AHCs) into testing laboratories; (3) introduce medical educators to biomedical informatics sufficiently for them to model its use; and (4) retrain AHC faculty to lead the transformation to health care based on a new systems approach enabled by biomedical informatics. The authors propose that embracing this collective and informatics-enhanced future of medicine will provide opportunities to advance education, patient care, and biomedical science., (© by the Association of American Medical Colleges.)

Clinical documentation is central to patient care. The success of electronic health record system adoption may depend on how well such systems support clinical documentation. A major goal of integrating clinical documentation into electronic heath record systems is to generate reusable data. As a result, there has been an emphasis on deploying computer-based documentation systems that prioritize direct structured documentation. Research has demonstrated that healthcare providers value different factors when writing clinical notes, such as narrative expressivity, amenability to the existing workflow, and usability. The authors explore the tension between expressivity and structured clinical documentation, review methods for obtaining reusable data from clinical notes, and recommend that healthcare providers be able to choose how to document patient care based on workflow and note content needs. When reusable data are needed from notes, providers can use structured documentation or rely on post-hoc text processing to produce structured data, as appropriate.

A closed-loop control process assures that a system performs within control limits by direct feedback of the system's output to change the system's inputs. We developed methods for the closed-loop control of system-based practice, using ventilator management as a model or test bed. The control system has three components: 1) an explicit end-to-end plan; 2) a record of what is done as it is done; and 3) an instant display of the status of each patient against the plan for that patient. The status display provides process control by showing the clinical team where corrections are needed while the team still has the time needed to act prospectively. We are extending these methods to the management of chronic disease. Their extension requires engagement of the patient as a member of the team, a coordinated plan across the care continuum, informatics algorithms to stratify individual patients according to co-morbidities and their current level of control, and a means of detecting the presence or absence of a reaction to each action taken by the team.

One hundred years after Flexner wrote his report for the Carnegie Foundation, calls are heard for another "Flexnerian revolution," a reform movement that would overhaul an approach to medical education that is criticized for its expense and inefficiency, its failure to respond to the health needs of our communities, and the high cost and inefficiency of the health care system it supports. To address these concerns, a group of Vanderbilt educators, national experts, administrators, residents, and students attended a retreat in November 2008. The goal of this meeting was to craft a new vision of physician learning based on the continuous development and assessment of competencies needed for effective and compassionate care under challenging circumstances. The vision that emerged from this gathering was that of a health care workforce comprised of physicians and other professionals, all capable of assessing practice outcomes, identifying learning needs, and engaging in continuous learning to achieve the best care for their patients. Several principles form the foundation for this vision. Learning should be competency based and embedded in the workplace. It should be linked to patient needs and undertaken by individual providers, by teams, and by institutions. Health professionals should be trained in this new model from the start of the educational experience, leading to true interprofessional education, with shared facilities and the same basic coursework. Multiple entry and exit points would provide flexibility and would allow health professionals to redirect their careers as their goals evolved. This article provides a detailed account of the model developed at the retreat and the obstacles that might be encountered in attempting to implement it.

Clinical notes summarize interactions that occur between patients and healthcare providers. With adoption of electronic health record (EHR) and computer-based documentation (CBD) systems, there is a growing emphasis on structuring clinical notes to support reusing data for subsequent tasks. However, clinical documentation remains one of the most challenging areas for EHR system development and adoption. The current manuscript describes the Vanderbilt experience with implementing clinical documentation with an EHR system. Based on their experience rolling out an EHR system that supports multiple methods for clinical documentation, the authors recommend that documentation method selection be made on the basis of clinical workflow, note content standards and usability considerations, rather than on a theoretical need for structured data.

A closed loop control process assures that a system performs within control limits. In closed loop control, the system's output feeds back directly to change the system's inputs. We describe an approach to planning and monitoring care that uses closed loop control to assure the desired performance using examples from Vanderbilt University Medical Center's ventilator management initiative. The approach has three components: an explicit end-to-end plan; a record of what is done as it is done; and an instant display of the status of each patient against their plan. The status display provides process control by showing the clinical team where correction is needed while they have time to act prospectively. Plans, displays and performance evolve together iteratively until the desired performance is achieved.

Health care information technology changes the ecosystem of a practice. Human roles, process work flow, and technology infrastructure are tightly interrelated. Medical errors may increase if a change in one is not accommodated by a change in the others. Introduction of information technology should be approached as an iterative process of care improvement rather than as a one-time insertion of an information system into established practice. Information technology supports a family of technological approaches, each with distinct mechanisms of action, benefits, and side effects. By matching technological approach to task and staging introduction into practice, initial benefit can be obtained more quickly, at reduced cost, while managing risk of a misfit. A staged approach to turning direct access by patients to their health information into more effective care is presented as an example of this strategy.

Setting: A prison system with an average year-end census of 9084 inmates., Objective: To determine transmission dynamics of tuberculosis over a long period; to establish whether Mycobacterium tuberculosis strains responsible for disease in a prison system persist; and to determine whether patients in a community whose isolates cluster with those in a prison system are linked., Design: Retrospective epidemiologic analysis was performed on tuberculosis cases reported in a prison system over a 9-year period. In addition, IS6110 RFLP patterns of M. tuberculosis isolates obtained from prisoners were compared with those of other cases from the state at large. The results of the RFLP analysis and the epidemiologic investigation were compared., Results: Approximately 80% of tuberculosis cases in the prison system were clustered. Over 9 years, a single strain of M. tuberculosis accounted for more than 50% of cases. Patients from the community at large who were infected with the same strain were linked to the prison system., Conclusion: In spite of intensive tuberculosis control efforts, a single strain of M. tuberculosis has persisted in the prison system. Its persistence is accounted for by activation of latent infection in patients who, prior to being diagnosed and treated, infected other patients, who then sustained the transmission chain.

A cluster of tuberculosis cases in a rural community in Arkansas persisted from 1991 to 1999. The cluster had 13 members, 11 linked epidemiologically. Old records identified 24 additional patients for 40 linked cases during a 54-year period. Residents of this neighborhood represent a population at high risk who should be considered for tuberculin testing and treatment for latent tuberculosis infection.

Objective: To test the hypothesis that vulnerability to infection by Mycobacterium tuberculosis is the norm for mankind but innate resistance to the infection is common in the USA today as a legacy of TB epidemics survived by one's ancestors., Measurements: A reaction of 10 mm or more to a tuberculin skin test (TST) was used to determine the prevalence of infection following community outbreaks of the disease. For further information, a survey was conducted of prevalence of tuberculin reactivity among health-care workers with frequent exposures to tuberculosis patients during bronchoscopy and sputum collection., Results: Sixty per cent of African Americans exposed in 26 community outbreaks were TST positive compared to only 40% of whites following comparable exposures. Similarly only 56 (41.2%) of 136 heavily exposed white health-care workers were TST positive., Conclusions: When considered in conjunction with contrasting ancestral histories of exposure to TB, these observations suggest a difference in frequency of an innate ability to respond protectively to M. tuberculosis and to mount an effective mechanism to destroy it. This is best explained as a process of natural selection among largely separate heavily exposed ancestors. Several recent reports have identified genetically mediated mechanisms of immunity that could be involved with reduced vulnerability to tuberculosis. An understanding of these processes could aid in the development of immunomodulatory agents or vaccines.