Classification of support staff in a consortium medical library: a case study.

A representative committee of Houston Academy of Medicine-Texas Medical Center Library staff and faculty, under the direction of the library administration, successfully redesigned a job classification system for the library's nonprofessional staff. In the new system all nonprofessionals are assigned to one of five grade levels, each with a corresponding salary range. To determine its appropriate grade level each job is analyzed and assigned a numerical value using a point system based on a set of five factors, each of which is assigned a relative number of points. The factors used to measure jobs are: education and experience, complexity of work, administrative accountability, manual skill, and contact with users. Each factor is described according to degrees, so that a job can be given partial credit for a factor. An advisory staff classification committee now participates in the ongoing administration of the classification system.

Clinical decision support capabilities of commercially-available clinical information systems.

BACKGROUND: The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems. METHODS: The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features. RESULTS: Six of the nine reviewed systems offered all the applicable event-driven, action-oriented, real-time clinical decision support triggers required for initiating clinical decision support interventions. Five of the nine systems could access all the patient-specific data items identified as necessary. Six of the nine systems supported all the intervention types identified as necessary to allow clinical information systems to tailor their interventions based on the severity of the clinical situation and the user's workflow. Only one system supported all the offered choices identified as key to allowing physicians to take action directly from within the alert. Discussion The principal finding relates to system-by-system variability. The best system in our analysis had only a single missing feature (from 42 total) while the worst had eighteen.This dramatic variability in CDS capability among commercially available systems was unexpected and is a cause for concern. CONCLUSIONS: These findings have implications for four distinct constituencies: purchasers of clinical information systems, developers of clinical decision support, vendors of clinical information systems and certification bodies.

Baseline evaluation of environmental physical activity and nutrition support of Texas Medical Center hospital worksites

Background: Obesity is a major health problem in the United States that has reached epidemic proportions. With most U.S adults spending the majority of their waking hours at work, the influence of the workplace environment on obesity is gaining in importance. Recent research implicates worksites as providing an 'obesogenic' environment as they encourage overeating and reduce the opportunity for physical activity. Objective: The aim of this study is to describe the nutrition and physical activity environment of Texas Medical Center (TMC) hospitals participating in the Shape Up Houston evaluation study to develop a scoring system to quantify the environmental data collected using the Environmental Assessment Tool (EAT) survey and to assess the inter-observer reliability of using the EAT survey. Methods: A survey instrument that was adapted from the Environmental Assessment Tool (EAT) developed by Dejoy DM et al in 2008 to measure the hospital environmental support for nutrition and physical activity was used for this study. The inter-observer reliability of using the EAT survey was measured and total percent agreement scores were computed. Most responses on the EAT survey are dichotomous (Yes and No) and these responses were coded with a '0' for a 'no' response and a '1' for a 'yes' response. A summative scoring system was developed to quantify these responses. Each hospital was given a score for each scale and subscale on the EAT survey in addition to a total score. All analyses were conducted using Stata 11 software. Results: High inter-observer reliability is observed using EAT. The percentage agreement scores ranged from 94.4%–100%. Only 2 of the 5 hospitals had a fitness facility onsite and scores for exercise programs and outdoor facilities available for hospital employees ranged from 0–62% and 0–37.5%, respectively. The healthy eating percentage for hospital cafeterias range from 42%–92% across the different hospitals while the healthy vending scores were 0%–40%. The total TMC 'healthy hospital' score was 49%. Conclusion: The EAT survey is a reliable instrument for measuring the physical activity and nutrition support environment of hospital worksites. The study results showed a large variability among the TMC hospitals in the existing physical activity and nutrition support environment. This study proposes cost effective policy changes that can increase environmental support to healthy eating and active living among TMC hospital employees.^