Getting to 100%: Research Priorities and Unanswered Questions to Inform the US Debate on Universal Health Insurance Coverage

A majority of Americans favor universal health insurance, but there is uncertainty over how best to achieve this goal. Whatever the insurance design that is implemented, additional details that must be considered include breadth of services covered, restrictions and limits on volumes of services, cost-sharing for individuals, and pricing. In the hopes that research can inform this ongoing debate, we review evidence supporting different models for achieving universal coverage in the US and identify areas where additional research and stakeholder input is needed. Key areas in need of further research include how care should be organized, how costs can be reduced, and what healthcare services universal insurance should cover.

Adaptive Biomedical Innovation: Evolving Our Global System to Sustainably and Safely Bring New Medicines to Patients in Need

The current system of biomedical innovation is unable to keep pace with scientific advancements. We propose to address this gap by reengineering innovation processes to accelerate reliable delivery of products that address unmet medical needs. Adaptive biomedical innovation (ABI) provides an integrative, strategic approach for process innovation. Although the term "ABI" is new, it encompasses fragmented "tools" that have been developed across the global pharmaceutical industry, and could accelerate the evolution of the system through more coordinated application. ABI involves bringing stakeholders together to set shared objectives, foster trust, structure decision-making, and manage expectations through rapid-cycle feedback loops that maximize product knowledge and reduce uncertainty in a continuous, adaptive, and sustainable learning healthcare system. Adaptive decision-making, a core element of ABI, provides a framework for structuring decision-making designed to manage two types of uncertainty - the maturity of scientific and clinical knowledge, and the behaviors of other critical stakeholders.

Preliminary competencies for comparative effectiveness research

The Clinical and Translational Science Award (CTSA) Workgroup for Comparative Effectiveness Research (CER) Education, Training, and Workforce Development identified a need to delineate the competencies that practitioners and users of CER for patient-centered outcomes research, should acquire. With input from CTSA representatives and collaborators, we began by describing the workforce. We recognize the workforce that conducts CER and the end users who use CER to improve the health of individuals and communities. We generated a preliminary set of competencies and solicited feedback from the CER representatives at each member site of the CTSA consortium. We distinguished applied competencies (i.e., skills needed by individuals who conduct CER) from foundational competencies that are needed by the entire CER workforce, including end users of CER. Key competency categories of relevance to both practitioners and users of CER were: (1) asking relevant research questions; (2) recognizing or designing ideal CER studies; (3) executing or using CER studies; (4) using appropriate statistical analyses for CER; and (5) communicating and disseminating CER study results to improve health. Although CER is particularly broad concept, we anticipate that these preliminary, relatively generic competencies will be used in tailoring curricula to individual learners from a variety of programmatic perspectives.

Preparedness of the CTSA's structural and scientific assets to support the mission of the National Center for Advancing Translational Sciences (NCATS)

The formation of the National Center for Advancing Translational Sciences (NCATS) brings new promise for moving basic science discoveries to clinical practice, ultimately improving the health of the nation. The Clinical and Translational Science Award (CTSA) sites, now housed with NCATS, are organized and prepared to support in this endeavor. The CTSAs provide a foundation for capitalizing on such promise through provision of a disease-agnostic infrastructure devoted to clinical and translational (C&T) science, maintenance of training programs designed for C&T investigators of the future, by incentivizing institutional reorganization and by cultivating institutional support.

Comparative effectiveness research in lung diseases and sleep disorders: recommendations from the National Heart, Lung, and Blood Institute workshop

The Division of Lung Diseases of the National Heart, Lung, and Blood Institute (NHLBI) held a workshop to develop recommendations on topics, methodologies, and resources for comparative effectiveness research (CER) that will guide clinical decision making about available treatment options for lung diseases and sleep disorders. A multidisciplinary group of experts with experience in efficacy, effectiveness, implementation, and economic research identified (a) what types of studies the domain of CER in lung diseases and sleep disorders should include, (b) the criteria and process for setting priorities, and (c) current resources for and barriers to CER in lung diseases. Key recommendations were to (1) increase efforts to engage stakeholders in developing CER questions and study designs; (2) invest in further development of databases and other infrastructure, including efficient methods for data sharing; (3) make full use of a broad range of study designs; (4) increase the appropriate use of observational designs and the support of methodologic research; (5) ensure that committees that review CER grant applications include persons with appropriate perspective and expertise; and (6) further develop the workforce for CER by supporting training opportunities that focus on the methodologic and practical skills needed.

Training and career development for comparative effectiveness research workforce development: CTSA Consortium Strategic Goal Committee on comparative effectiveness research workgroup on workforce development

As comparative effectiveness research (CER) increasingly becomes a national priority, there are increased needs for training and workforce development in this area. Particularly important CER competencies include clinical epidemiology, biomedical informatics, economic analyses, systematic reviews, clinical practice guideline development, use of large databases and electronic health records for research, practice-based research, implementation and dissemination, health services research, and decision analysis. Institutions funded by Clinical and Translational Science Awards (CTSAs) should be one of the central stakeholders in providing training and career development in CER. Survey results regarding the current CER capacity and needs of CTSAs are presented, and recommendations are provided. Volume 5: 258-262.

Admission prediction of expected final myocardial infarct size using weighted ST-segment, Q wave, and T wave measurements

Formulas for predicting final acute myocardial infarction (MI) size from ST-segment deviation on an initial electrocardiogram were proposed by Aldrich et al. for anterior and inferior infarct locations. This study of 529 patients who did not receive thrombolytic therapy was performed to determine the effectiveness of the Aldrich formulas for predicting final QRS MI size; to propose new formulas for predicting final MI size using ST-segment deviation, Q wave, and T wave information in a development population of 322 patients; and to evaluate the new formulas in a randomly selected population of 207 patients. The Aldrich formulas achieved correlations with final infarct size of r = .40 for anterior and r = .43 for inferior MI locations in the present population which are weaker than those previously reported. Formulas that consider electrocardiographic parameters in addition to ST-segment deviation were proposed for both anterior and inferior final MI size. In the test set of 207 patients, these models explained 16.9% and 15.2% of the variation in final MI size for anterior and inferior locations respectively. They may prove useful in assessing the extent of myocardial salvage where interventions are to be tested.

Do older internists use more hospital resources than younger internists for patients hospitalized with chest pain? A study of patients hospitalized in the coronary care and intermediate care units

OBJECTIVES

Recent concern about escalating healthcare expenditures has prompted healthcare payers and hospitals to identify physicians whose hospital resource consumption exceeds expected norms. The goals of this study were to determine whether analyses of practice patterns in this manner may a) systematically identify older physicians as big resource "spenders," and b) provide misleading information caused by the failure to adjust utilization data for severity of illness.

DESIGN

A prospective, observational study.

SETTING

The coronary care and intermediate care unit in an 1,100-bed community hospital.

PATIENTS

A total of 217 patients hospitalized for chest pain cared for by noncardiologists.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

On initial inspection, it appeared that the patients of older physicians had longer lengths of stay and greater charge expenditures than the patients of younger physicians. However, further evaluation demonstrated that older physicians cared for older (76 vs. 67 yrs old, p = .0001) and more severely ill patients (judged by risk of complications, risk of acute ischemic heart disease, and disease staging). Older physicians cared for more severely ill myocardial infarction patients than did younger physicians (Killip Classification 2.0 vs. 1.1, p less than .00003). After adjusting for severity of illness, there were fewer differences in hospital charges and consultant use between older and younger physicians, although the patients of older physicians remained hospitalized longer.

CONCLUSIONS

There is little difference in resource utilization between patients cared for by older and younger internists after controlling for severity of illness. This investigation highlights the potential hazards of ignoring severity of illness when judging physician efficiency in the coronary care unit.

An aid for diagnosing acute ischemic heart disease in the emergency room

A five-year study was undertaken to develop a valid mathematical model that could aid in diagnosing acute ischemic heart disease in the emergency room, thus reducing inappropriate admissions to the coronary care unit. The study was divided into two substudies. In the first, variables significantly predictive of ischemic heart disease were identified and a logistic function was developed and tested. In the second, a six-hospital study, the variables of the first substudy were validated and a final logistic regression was developed and tested prospectively. This model's availability proved to be successful in improving diagnostic accuracy and specificity and in reducing false positive predictive rates and admissions to coronary care units.