We use the National Health and Nutritional Examination Survey (NHANES) III to examine the effect of the availability of the school breakfast program (SBP). Our work builds on previous research in four ways: First, we develop a transparent difference-in-differences strategy to account for unobserved differences between students with access to SBP and those without. Second, we examine serum measures of nutrient in addition to intakes based on dietary recall data. Third, we ask whether the SBP improves the diet by increasing/or decreasing the intake of nutrients relative to meaningful threshold levels. Fourth, we examine the effect of the SBP on other members of the family besides the school-aged child. We have three main findings. First, the SBP helps students build good eating habits: SBP increases scores on the healthy eating index, reduces the percentage of calories from fat, and reduces the probability of low fiber intake. Second, the SBP reduces the probability of serum micronutrient deficiencies in vitamin C, vitamin E, and folate, and it increases the probability that children meet USDA recommendations for potassium and iron intakes. Since we find no effect on total calories these results indicate that the program improves the quality of food consumed. Finally, in households with school-aged children, both preschool children and adults have healthier diets and consume less fat when the SBP is available. These results suggest that school nutrition programs may be an effective way to combat both nutritional deficiencies and excess consumption among children and their families.

OBJECTIVE. To develop a set of quality indicators for the neurodevelopmental follow-up care of very low birth weight (VLBW; <1500 g) children.

METHODS. We reviewed the scientific literature on predictors of neurodevelopmental outcomes for VLBW children and the clinical practice guidelines relevant to their care after hospital discharge. An expert panel with members nominated by the American Academy of Pediatrics, the National Institute of Child Health and Human Development, the Vermont Oxford Network, and the California Children's Service was convened. We used a modified Delphi method to evaluate and select the quality-of-care indicators.

RESULTS. The panel recommended a total of 70 indicators in 5 postdischarge follow-up areas: general care; physical health; vision, hearing, speech, and language; developmental and behavioral assessment; and psychosocial issues. Of these, 58 (83%) indicators were in preventive care, 5 (7%) were in acute care, and 7 (10%) were in chronic care.

CONCLUSION. The quality indicators cover follow-up care for VLBW infants with various medical conditions. Given the elevated rates of long-term neurodevelopmental disabilities and the potential impact of poor health care, this new set of indicators provides an opportunity to assess and monitor the quality of follow-up care with the ultimate aim of improving the quality of care for this high-risk population.

The case of a 52-yr-old female with rheumatoid arthritis and HIV who developed massive, progressive, cavitary pulmonary nodules is described. Multiple diagnostic bronchoscopies and lung biopsies failed to demonstrate the presence of any microorganisms. Pathological analysis showed palisading histiocytes with necrobiosis consistent with rheumatoid nodules. The effect of co-existing HIV infection on the course and prognosis of rheumatoid arthritis is discussed, and it is concluded that the complex relationship between these two disease processes warrants further investigation.

BACKGROUND: A genome-wide association study identified 13 single-nucleotide polymorphisms (SNPs) significantly associated with Parkinson's disease. Small-scale replication studies were largely non-confirmatory, but a meta-analysis that included data from the original study could not exclude all SNP associations, leaving relevance of several markers uncertain. METHODS: Investigators from three Michael J Fox Foundation for Parkinson's Research-funded genetics consortia-comprising 14 teams-contributed DNA samples from 5526 patients with Parkinson's disease and 6682 controls, which were genotyped for the 13 SNPs. Most (88%) participants were of white, non-Hispanic descent. We assessed log-additive genetic effects using fixed and random effects models stratified by team and ethnic origin, and tested for heterogeneity across strata. A meta-analysis was undertaken that incorporated data from the original genome-wide study as well as subsequent replication studies. FINDINGS: In fixed and random-effects models no associations with any of the 13 SNPs were identified (odds ratios 0.89 to 1.09). Heterogeneity between studies and between ethnic groups was low for all SNPs. Subgroup analyses by age at study entry, ethnic origin, sex, and family history did not show any consistent associations. In our meta-analysis, no SNP showed significant association (summary odds ratios 0.95 to 1.08); there was little heterogeneity except for SNP rs7520966. INTERPRETATION: Our results do not lend support to the finding that the 13 SNPs reported in the original genome-wide association study are genetic susceptibility factors for Parkinson's disease.

Monitoring national patterns of antihypertensive drug therapy is essential to assessing adherence to treatment guidelines and the impact of major scientific publications on physician prescribing. We analyzed data from 2 US National Ambulatory Care Surveys to examine trends between 1993 and 2004 in the prescription of antihypertensive drug classes for uncomplicated hypertension and the association between thiazide and beta-blocker prescribing and physician and patient characteristics. Diuretic prescriptions remained level through 2001 (39%; 95% CI: 34% to 44%) but increased to 53% (48% to 58%) in 2003, largely because of a 72% increase in thiazide prescriptions in the first quarter of 2003 (50%; 95% CI: 40% to 59%). However, these increases did not sustain in 2004. Beta-blocker prescriptions increased modestly from 1993 (24%; 95% CI: 19% to 29%) to 2004 (33%; 95% CI: 28% to 39%). Prescription of calcium channel blockers and angiotensin-converting enzyme inhibitors declined significantly following the sixth Joint National Committee report, but both subsequently rebounded to prereport levels. Prescription of angiotensin II receptor blockers increased continuously from 1% in 1995 to 23% by 2004. Polytherapy prescriptions, particularly those involving > or = 3 drug classes, became increasingly prevalent, accounting for 60% of antihypertensive drug visits by 2004. Prescriptions of thiazides and beta-blockers were both more likely in 1998-2004 (versus 1993-1997). Blacks, women, and hospital outpatients were more likely to receive thiazides. Also, cardiologists were more likely to prescribe beta-blockers. Evidence-based guidelines for antihypertensive drug therapy do impact physician prescribing, but the impact seems to be short lived. Future interventions are imperative for promoting long-term adherence to published guidelines.

ATHENA-HTN is a clinical decision support system (CDSS) that delivers guideline-based patient-specific recommendations about hypertension management at the time of clinical decision-making. The ATHENA-HTN knowledge is stored in a knowledge-base (KB). Changes in best-practice recommendations require updates to the KB. We describe a method of offline testing to evaluate the accuracy of recommendations generated from the KB. A physician reviewed 100 test cases and made drug recommendations based on guidelines and the "Rules" (descriptions of encoded knowledge). These drug recommendations were compared to those generated by ATHENA-HTN. Nineteen drug-recommendation discrepancies were identified: ATHENA-HTN was more complete in generating recommendations (15); ambiguities in the Rules misled the physician (3); and content in the Rules was not encoded (1). Three new boundaries were identified. Three updates were made to the KB based on the results. The offline testing method was successful in identifying areas for KB improvement and led to improved accuracy of guideline-based recommendations.

Factors contributing to low adherence to clinical guidelines by clinicians are not well understood. The user interface of ATHENA-HTN, a guideline-based decision support system (DSS) for hypertension, presents a novel opportunity to collect clinician feedback on recommendations displayed at the point of care. We analyzed feedback from 46 clinicians who received ATHENA advisories as part of a 15-month randomized trial to identify potential reasons clinicians may not intensify hypertension therapy when it is recommended. Among the 368 visits for which feedback was provided, clinicians commonly reported they did not follow recommendations because: recorded blood pressure was not representative of the patient's typical blood pressure; hypertension was not a clinical priority for the visit; or patients were nonadherent to medications. For many visits, current quality-assurance algorithms may incorrectly identify clinically appropriate decisions as guideline nonadherent due to incomplete capture of relevant information. We present recommendations for how automated DSSs may help identify "apparent" barriers and better target decision support.

Numerous health decision aids (HDAs) have been developed to increase the participation of patients in shared decision-making, but many have limited accessibility and narrow applicability in clinical care. In the Health e-Decision project, we address these limitations in our work on building general HDAs targeted for older adults. Our approach uses a decision-support software architecture that enables principled methods for HDAs. We have formalized a novel knowledge-based decision model (KBDM), using Protege OWL, that developers and clinicians can instantiate to tailor the components of the architecture for a particular health problem. In this paper, we present the methods used in the architecture and the knowledgebase design; the latter encompasses influence-diagram concepts, specific health problems, health outcome states, and probabilistic relationships. We discuss how this approach improves upon prior HDA methods. We also show that our use of computer-interpretable knowledge provides a structured, customizable means of enabling patient-centered decision support.

This book focuses on the role of computers in the provision of medical services. It provides both a conceptual framework and a practical approach for the implementation and management of IT used to improve the delivery of health care. Inspired by a Stanford University training program, it fills the need for a high quality text in computers and medicine. It meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Completely revised and expanded, this work includes several new chapters filled with brand new material.

Several CHP/PCOR faculty played key roles as authors in the 3rd edition of this textbook that has served as a core reference for graduate training programs in medical informatics.