Increased sensitivity of ETEC detection in stool cultures by increasing the number of E. coli colonies tested

The cause of infection of about a third of all travelers' diarrhea patients studied is not identified. Stools of these diarrhea patients tested for known enteric pathogens are shown to be negative, and identified as pathogen negative stools. We proposed that the third of these diarrhea patients might not only include at present unknown pathogens, but also known pathogens that go undetected. Conventionally, a probability sample of five E. coli colonies are used detect enterotoxigenic E. coli (ETEC) and other diarrhea-producing E. coli from stool cultures. We compared this conventional method of using five E. coli colonies, to the use of up to twenty E. coli colonies. Testing for up to fifteen E. coli colonies detected about twice as many ETEC when compared to the detection of ETEC, testing for five E. coli colonies. When the number of E. coli colonies tested was increased from 5 to 15, the detection of ETEC increased from 19.0% to 38.8%. The sensitivity of the assay with 5 E. coli colonies was statistically significantly different to the sensitivity of the assay with 10 E. coli colonies, suggesting that for the detection of ETEC at least 10 colonies of E. coli should be tested.^

Assessing the impact of electronic health record technology adoption on hospital labor efficiency

Information technology (IT) in the hospital organization is fast becoming a key asset, particularly in light of recent reform legislation in the United States calling for expanding the role of IT in our health care system. Future payment reductions to hospitals included in current health reform are based on expected improvements in hospital operating efficiency. Since over half of hospital expenses are for labor, improved efficiency in use of labor resources can be critical in meeting this challenge. Policy makers have touted the value of IT investments to improve efficiency in response to payment reductions. ^ This study was the first to directly examine the relationship between electronic health record (EHR) technology and staffing efficiency in hospitals. As the hospital has a myriad of outputs for inpatient and outpatient care, efficiency was measured using an industry standard performance metric – full time equivalent employees per adjusted occupied bed (FTE/AOB). Three hypotheses were tested in this study.^ To operationalize EHR technology adoption, we developed three constructs to model adoption, each of which was tested by separate hypotheses. The first hypothesis that a larger number of EHR applications used by a hospital would be associated with greater staffing efficiency (or lower values of FTE/AOB) was not accepted. Association between staffing efficiency and specific EHR applications was the second hypothesis tested and accepted with some applications showing significant impacts on observed values for FTE/AOB. Finally, the hypothesis that the longer an EHR application was used in a hospital would be associated with greater labor efficiency was not accepted as the model showed few statistically significant relationships to FTE/AOB performance. Generally, there does not appear a strong relationship between EHR usage and improved labor efficiency in hospitals.^ While returns on investment from EHR usage may not come from labor efficiencies, they may be better sought using measures of quality, contribution to an efficient and effective local health care system, and improved customer satisfaction through greater patient throughput.^