Characteristics of Inpatient Units Associated With Sustained Hand Hygiene Compliance.

OBJECTIVES: Following institution of a hand hygiene (HH) program at an academic medical center, HH compliance increased from 58% to 92% for 3 years. Some inpatient units modeled early, sustained increases, and others exhibited protracted improvement rates. We examined the association between patterns of HH compliance improvement and unit characteristics. METHODS: Adult inpatient units (N = 35) were categorized into the following three tiers based on their pattern of HH compliance: early adopters, nonsustained and late adopters, and laggards. Unit-based culture measures were collected, including nursing practice environment scores (National Database of Nursing Quality Indicators [NDNQI]), patient rated quality and teamwork (Hospital Consumer Assessment of Healthcare Provider and Systems), patient complaint rates, case mix index, staff turnover rates, and patient volume. Associations between variables and the binary outcome of laggard (n = 18) versus nonlaggard (n = 17) were tested using a Mann-Whitney U test. Multivariate analysis was performed using an ordinal regression model. RESULTS: In direct comparison, laggard units had clinically relevant differences in NDNQI scores, Hospital Consumer Assessment of Healthcare Provider and Systems scores, case mix index, patient complaints, patient volume, and staff turnover. The results were not statistically significant. In the multivariate model, the predictor variables explained a significant proportion of the variability associated with laggard status, (R2 = 0.35, P = 0.0481) and identified NDNQI scores and patient complaints as statistically significant. CONCLUSIONS: Uptake of an HH program was associated with factors related to a unit's safety culture. In particular, NDNQI scores and patient complaint rates might be used to assist in identifying units that may require additional attention during implementation of an HH quality improvement program.

Implementation of an enhanced safety-engineered sharp device oversight and bloodborne pathogen protection program at a large academic medical center.

OBJECTIVE: Exposure of healthcare personnel to bloodborne pathogens (BBPs) can be prevented in part by using safety-engineered sharp devices (SESDs) and other safe practices, such as double gloving. In some instances, however, safer devices and practices cannot be utilized because of procedural factors or the lack of a manufactured safety device for the specific clinical use. In these situations, a standardized system to examine requests for waiver from expected practices is necessary. DESIGN: Before-after program analysis. SETTING: Large academic medical center. INTERVENTIONS: Vanderbilt University Medical Center developed a formalized system for an improved waiver process, including an online submission and tracking site, and standards surrounding implementation of core safe practices. The program's impact on sharp device injuries and utilization of double gloving and blunt sutures was examined. RESULTS: Following implementation of the enhanced program, there was an increase in the amount of undergloves and blunt sutures purchased for surgical procedures, suggesting larger utilization of these practices. The rate of sharp device injuries of all at-risk employees decreased from 2.32% to 2.12%, but this decline was not statistically significant (P = .14). The proportion of reported injuries that were deemed preventable significantly decreased from 72.7% (386/531) before implementation to 63.9% (334/523; P = .002) after implementation of the enhanced program. CONCLUSIONS: An enhanced BBP protection program was successful at providing guidance to increase safe practices and at improving the management of SESD waiver requests and was associated with a reduction in preventable sharp device injuries.

An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records.

We describe a two-stage analytical approach for characterizing morbidity profile dissimilarity among patient cohorts using electronic medical records. We capture morbidities using the International Statistical Classification of Diseases and Related Health Problems (ICD-9) codes. In the first stage of the approach separate logistic regression analyses for ICD-9 sections (e.g., "hypertensive disease" or "appendicitis") are conducted, and the odds ratios that describe adjusted differences in prevalence between two cohorts are displayed graphically. In the second stage, the results from ICD-9 section analyses are combined into a general morbidity dissimilarity index (MDI). For illustration, we examine nine cohorts of patients representing six phenotypes (or controls) derived from five institutions, each a participant in the electronic MEdical REcords and GEnomics (eMERGE) network. The phenotypes studied include type II diabetes and type II diabetes controls, peripheral arterial disease and peripheral arterial disease controls, normal cardiac conduction as measured by electrocardiography, and senile cataracts.

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

MOTIVATION: Emergence of genetic data coupled to longitudinal electronic medical records (EMRs) offers the possibility of phenome-wide association scans (PheWAS) for disease-gene associations. We propose a novel method to scan phenomic data for genetic associations using International Classification of Disease (ICD9) billing codes, which are available in most EMR systems. We have developed a code translation table to automatically define 776 different disease populations and their controls using prevalent ICD9 codes derived from EMR data. As a proof of concept of this algorithm, we genotyped the first 6005 European-Americans accrued into BioVU, Vanderbilt's DNA biobank, at five single nucleotide polymorphisms (SNPs) with previously reported disease associations: atrial fibrillation, Crohn's disease, carotid artery stenosis, coronary artery disease, multiple sclerosis, systemic lupus erythematosus and rheumatoid arthritis. The PheWAS software generated cases and control populations across all ICD9 code groups for each of these five SNPs, and disease-SNP associations were analyzed. The primary outcome of this study was replication of seven previously known SNP-disease associations for these SNPs. RESULTS: Four of seven known SNP-disease associations using the PheWAS algorithm were replicated with P-values between 2.8 x 10(-6) and 0.011. The PheWAS algorithm also identified 19 previously unknown statistical associations between these SNPs and diseases at P < 0.01. This study indicates that PheWAS analysis is a feasible method to investigate SNP-disease associations. Further evaluation is needed to determine the validity of these associations and the appropriate statistical thresholds for clinical significance. AVAILABILITY: The PheWAS software and code translation table are freely available at http://knowledgemap.mc.vanderbilt.edu/research.