The metabolic syndrome and cardiovascular risk: implications for clinical practice.

OBJECTIVE: The clinical importance of the metabolic syndrome (MeS) is confused by the existence of at least three different definitions proposed by prominent organizations, and by a lack of information about the prognostic value of diagnosing a person as having the syndrome by any of the definitions. DESIGN AND SUBJECTS: We used the US National Health and Nutrition Evaluation Survey (NHANES) to determine the prevalence in the United States of the variables used to define the MeS and cardiovascular disease (CVD), and to create a simulated population that matched the US population with respect to all the important characteristics, risk factors and treatments for CVD. We then used the Archimedes model to calculate the long-term CVD outcomes for each person in the simulated population. RESULTS: The definitions implied an increased risk of CVD of 1.5-1.6. The definitions varied considerably in their ability to identify people at risk of myocardial infarctions (MIs); the proportion of people destined to have a future MI captured by the different definitions varied from 57 to 77%. The definitions also varied widely in how well they ruled out future MIs; failure to have MeS by a definition still left a chance of a future MI ranging from 23 to 42%. The definitions differed importantly in which people they identified as having MeS; 34% of those who met the ATP definition did not meet the WHO definition, 30% of those who met the WHO definition did not meet the ATP definition and 28% of those who met the IDF definition did not meet the ATP definition. Of the components of the definitions, the most important single factor for identifying a person at risk of future CVD was high glucose, with hypertension, obesity, high triglycerides and low HDL following in that order. High glucose, by itself, was as good as any definition of the MeS in predicting risk of future MI. Whichever definition was used, individuals who met the definition varied widely in their risk of CVD. CONCLUSIONS: For assessing a particular person's risk of future CVD and for making treatment decisions a diagnosis of MeS by any of the definitions added little if anything to assessing each person's risk factors.

Enhancing performance measurement: NCQA's road map for a health information framework. National Committee for Quality Assurance.

Measuring the quality of health care delivery is one of the most critical challenges facing US health care. Performance measurement can be used to track the quality of care that health plans and medical groups deliver, but effective performance measurement requires timely access to detailed and accurate data. In 1996, the National Committee for Quality Assurance (NCQA) commissioned a report to learn what actions would improve health plans' capacity to electronically report performance data for the Health Plan Employer Data and Information Set (HEDIS). Tracking clinical performance will require not just clinical data stored in information systems, but an integrated health information framework. Seven features are essential to this framework: (1) it specifies data elements; (2) it establishes linkage capability among data elements and records; (3) it standardizes the element definitions; (4) it is automated to the greatest possible extent; (5) it specifies procedures for continually assessing data quality; (6) it maintains strict controls for protecting security and confidentiality of the data; and (7) it specifies protocols for sharing data across institutions under appropriate and well-defined circumstances. Health plans should anticipate the use of computerized patient records and prepare their data management for an information framework by (1) expanding and improving the capture and use of currently available data; (2) creating an environment that rewards the automation of data; (3) improving the quality of currently automated data; (4) implementing national standards; (5) improving clinical data management practices; (6) establishing a clear commitment to protecting the confidentiality of enrollee information; and (7) careful capital planning. Health care purchasers can provide the impetus for implementing the information framework if they demand detailed, accurate data on the quality of care.

Performance measurement: problems and solutions.

Recent efforts to measure performance have established its feasibility and value. However, its full potential is currently limited by several problems. They include the probabilistic nature, rarity, and confounding of many health outcomes; the inadequacies of information systems; the multiplicity of measures and measures; the complexity of health plans; and the availability of funding. Solutions are to rely more on process measures; to justify every measure with a formal, evidence-based rationale; to improve information systems; to supplement population-based measures with case-based measures; to develop a single, nationally standardized set of measures; and to provide nonpolitical, public funding for the design and administration of measures.

Importance of professional nursing values: a national study of baccalaureate programs.

Research about professional nursing values is scarce. The purpose of this study was to determine if there were different perceptions about professional nursing values between senior baccalaureate nursing students and their faculty. The Professional Nursing Behavior Instrument (PNB) used in this research was based on the nursing role behaviors identified in the AACN's (1986) Essentials Report as exemplars of seven essential values. A national sample of 10 public and 16 private baccalaureate programs resulted in a return of 656 students (57%) and 350 faculty (70%). Faculty values were significantly higher than students' (p < .045) with faculty valuing equality, human dignity, and freedom more highly. Enrollment or employment in a public or private institution or studying ethics, theology, and philosophy did not significantly affect values. Faculty with more teaching experience had higher value scores (p < .004).