Impact of date stamping on patient safety measurement in patients undergoing CABG: Experience with the AHRQ Patient Safety Indicators

<p>Abstract</p> <p>Background</p> <p>The Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) provide information on hospital risk-adjusted rates for potentially preventable adverse events. Although designed to work with routine administrative data, it is unknown whether the PSIs can accurately distinguish between complications and pre-existing conditions. The objective of this study is to examine whether the AHRQ PSIs accurately measure hospital complication rates, using the data with present-on-admission (POA) codes to distinguish between complications and pre-existing conditions</p> <p>Methods</p> <p>Retrospective cohort study of patients undergoing isolated CABG surgery in California conducted using the 1998–2000 California State Inpatient Database. We calculated the positive predictive value of selected AHRQ PSIs using information from the POA as the gold standard, and the intra-class correlation coefficient to assess the level of agreement between the hospital risk-adjusted PSI rates with and without the information contained in the POA modifier.</p> <p>Results</p> <p>The false positive error rate, defined as one minus the positive predictive value, was greater than or equal to 20% for four of the eight PSIs examined: decubitus ulcer, failure-to-rescue, postoperative physiologic and metabolic derangement, and postoperative pulmonary embolism or deep venous thrombosis. Pairwise comparison of the hospital risk-adjusted PSI rates, with and without POA information, demonstrated almost perfect agreement for five of the eight PSI's. For decubitus ulcer, failure-to-rescue, and postoperative pulmonary embolism or DVT, the intraclass-correlation coefficient ranged between 0.63 to 0.79.</p> <p>Conclusion</p> <p>For some of the AHRQ Patient Safety Indicators, there are significant differences in the risk-adjusted rates of adverse events depending on whether the POA indicator is used to distinguish between pre-existing conditions and complications. The use of the POA indicator will increase the accuracy of the AHRQ PSIs as measures of adverse outcomes.</p

The association between nurse staffing and hospital outcomes in injured patients

The enormous fiscal pressures facing trauma centers may lead trauma centers to reduce nurse staffing and to make increased use of less expensive and less skilled personnel. The impact of nurse staffing and skill mix on trauma outcomes has not been previously reported. The goal of this study was to examine whether nurse staffing levels and nursing skill mix are associated with trauma patient outcomes. We used data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample to perform a cross-sectional study of 70,142 patients admitted to 77 Level I and Level II centers. Logistic regression models were used to examine the association between nurse staffing measures and (1) mortality, (2) healthcare associated infections (HAI), and (3) failure-to-rescue. We controlled for patient risk factors (age, gender, injury severity, mechanism of injury, comorbidities) and hospital structural characteristics (trauma center status - Level I versus Level II, hospital size, ownership, teaching status, technology level, and geographic region). A 1% increase in the ratio of licensed practical nurse (LPN) to total nursing time was associated with a 4% increase in the odds of mortality (adj OR 1.04; 95% CI: 1.02-1.06; p = 0.001) and a 6% increase in the odds of sepsis (adj OR 1.06: 1.03-1.10; p < 0.001). Hospitals in the highest quartile of LPN staffing had 3 excess deaths (95% CI: 1.2, 5.1) and 5 more episodes of sepsis (95% CI: 2.3, 7.6) per 1000 patients compared to hospitals in the lower quartile of LPN staffing. Higher hospital LPN staffing levels are independently associated with slightly higher rates of mortality and sepsis in trauma patients admitted to Level I or Level II trauma centers

The propensity to adopt evidence-based practice among physical therapists

<p>Abstract</p> <p>Background</p> <p>Many authors, as well as the American Physical Therapy Association, advocate that physical therapists adopt practice patterns based on research evidence, known as evidence-based practice (EBP). At the same time, physical therapists should be capable of integrating EBP within the day-to-day practice of physical therapy. The purpose of this study was to determine the extent to which personal characteristics and the characteristics of the social system in the workplace influence the propensity of physical therapists to adopt EBP.</p> <p>Methods</p> <p>The study used a 69 item mailed self-completion questionnaire. The questionnaire had four major sections. The first three sections were each drawn from a different theoretical framework and from different authors' work. The instrument was developed to capture the propensity of physical therapists to adopt EBP, characteristics of the social system in the workplace of physical therapists, personal characteristics of physical therapists, and selected demographic variables of physical therapists. The eligible population consisted of 3,897 physical therapists licensed by the state of Georgia in the United States of America. A random sample of 1320 potential participants was drawn.</p> <p>Results</p> <p>939 questionnaires were returned for a response rate of 73%. 831 of the participants' questionnaires were useable and became the basis for the study. There was a moderate association between desire for learning (<it>r </it>= .36, <it>r</it>²= .13), highest degree held (<it>r </it>= .29, <it>r</it>²= .08), practicality (<it>r </it>= .27, <it>r</it>²= .07) and nonconformity (<it>r </it>= .24, <it>r</it>²= .06) and the propensity to adopt EBP. A negative correlation was found between age, years licensed and percentage of time in direct patient care. The findings demonstrated that the best three variables for predicting the propensity to adopt EBP in physical therapy were: desire for learning, highest degree held, and practicality.</p> <p>Conclusion</p> <p>The study confirms there is no single factor to facilitate research evidence into day-to-day practice. Multiple practice change strategies will be needed to facilitate change in practice.</p

Impact of early psychosocial factors (childhood socioeconomic factors and adversities) on future risk of type 2 diabetes, metabolic disturbances and obesity: a systematic review

<p>Abstract</p> <p>Background</p> <p>Psychological factors and socioeconomic status (SES) have a notable impact on health disparities, including type 2 diabetes risk. However, the link between childhood psychosocial factors, such as childhood adversities or parental SES, and metabolic disturbances is less well established. In addition, the lifetime perspective including adult socioeconomic factors remains of further interest.</p> <p>We carried out a systematic review with the main question if there is evidence in population- or community-based studies that childhood adversities (like neglect, traumata and deprivation) have considerable impact on type 2 diabetes incidence and other metabolic disturbances. Also, parental SES was included in the search as risk factor for both, diabetes and adverse childhood experiences. Finally, we assumed that obesity might be a mediator for the association of childhood adversities with diabetes incidence. Therefore, we carried out a second review on obesity, applying a similar search strategy.</p> <p>Methods</p> <p>Two systematic reviews were carried out. Longitudinal, population- or community-based studies were included if they contained data on psychosocial factors in childhood and either diabetes incidence or obesity risk.</p> <p>Results</p> <p>We included ten studies comprising a total of 200,381 individuals. Eight out of ten studies indicated that low parental status was associated with type 2 diabetes incidence or the development of metabolic abnormalities. Adjustment for adult SES and obesity tended to attenuate the childhood SES-attributable risk but the association remained. For obesity, eleven studies were included with a total sample size of 70,420 participants. Four out of eleven studies observed an independent association of low childhood SES on the risk for overweight and obesity later in life.</p> <p>Conclusions</p> <p>Taken together, there is evidence that childhood SES is associated with type 2 diabetes and obesity in later life. The database on the role of psychological factors such as traumata and childhood adversities for the future risk of type 2 diabetes or obesity is too small to draw conclusions. Thus, more population-based longitudinal studies and international standards to assess psychosocial factors are needed to clarify the mechanisms leading to the observed health disparities.</p

Fetal and infant origins of asthma

Previous studies have suggested that asthma, like other common diseases, has at least part of its origin early in life. Low birth weight has been shown to be associated with increased risks of asthma, chronic obstructive airway disease, and impaired lung function in adults, and increased risks of respiratory symptoms in early childhood. The developmental plasticity hypothesis suggests that the associations between low birth weight and diseases in later life are explained by adaptation mechanisms in fetal life and infancy in response to various adverse exposures. Various pathways leading from adverse fetal and infant exposures to growth adaptations and respiratory health outcomes have been studied, including fetal and early infant growth patterns, maternal smoking and diet, children’s diet, respiratory tract infections and acetaminophen use, and genetic susceptibility. Still, the specific adverse exposures in fetal and early postnatal life leading to respiratory disease in adult life are not yet fully understood. Current studies suggest that both environmental and genetic factors in various periods of life, and their epigenetic mechanisms may underlie the complex associations of low birth weight with respiratory disease in later life. New well-designed epidemiological studies are needed to identify the specific underlying mechanisms. This review is focused on specific adverse fetal and infant growth patterns and exposures, genetic susceptibility, possible respiratory adaptations and perspectives for new studies

ICDPIC: Stata module to provide methods for translating International Classification of Diseases (Ninth Revision) diagnosis codes into standard injury categories and/or scores

The intention of the ICD Programs for Injury Categorization (ICDPIC) is to provide inexpensive methods for translating International Classification of Diseases (Ninth Revision) diagnosis codes into standard injury categories and/or scores. Programs contained in this module can provide Abbreviated Injury Scale score (AIS), ISS body region, Barell matrix category, Injury Severity Score (ISS), New Injury Severity Score (NISS), CDC categorization for E-Code mechanism and intent, Survival Rate Ratio (SRR), Independent Survival Rate Ratio (SRRi), ICISS, modified Anatomic Profile Score (APS), Revised Trauma Score (RTS), TRISS, ASCOT, Trauma Mortality Prediction Model (TMPM), an alternate version of the Charlson Score and Elixhauser categories. Version 3.0 works in Stata 11.ICD9, injury categories, trauma, survival rate

Impact of Risk Adjustment for Socioeconomic Status on Risk-adjusted Surgical Readmission Rates

OBJECTIVE: To assess whether differences in readmission rates between safety-net hospitals (SNH) and non-SNHs are due to differences in hospital quality, and to compare the results of hospital profiling with and without SES adjustment. BACKGROUND: In response to concerns that quality measures unfairly penalizes SNH, NQF recently recommended that performance measures adjust for socioeconomic status (SES) when SES is a risk factor for poor patient outcomes. METHODS: Multivariate regression was used to examine the association between SNH status and 30-day readmission after major surgery. The results of hospital profiling with and without SES adjustment were compared using the CMS Hospital Compare and the Hospital Readmissions Reduction Program (HRRP) methodologies. RESULTS: Adjusting for patient risk and SES, patients admitted to SNHs were not more likely to be readmitted compared with patients in in non-SNHs (AOR 1.08; 95% CI:0.95-1.23; P = 0.23). The results of hospital profiling based on Hospital Compare were nearly identical with and without SES adjustment (ICC 0.99, kappa 0.96). Using the HRRP threshold approach, 61% of SNHs were assigned to the penalty group versus 50% of non-SNHs. After adjusting for SES, 51% of SNHs were assigned to the penalty group. CONCLUSIONS: Differences in surgery readmissions between SNHs and non-SNHs are due to differences in the patient case mix of low-SES patients, and not due to differences in quality. Adjusting readmission measures for SES leads to changes in hospital ranking using the HRRP threshold approach, but not using the CMS Hospital Compare methodology. CMS should consider either adjusting for the effects of SES when calculating readmission thresholds for HRRP, or replace it with the approach used in Hospital Compare

The association between nurse staffing and hospital outcomes in injured patients

Abstract Background The enormous fiscal pressures facing trauma centers may lead trauma centers to reduce nurse staffing and to make increased use of less expensive and less skilled personnel. The impact of nurse staffing and skill mix on trauma outcomes has not been previously reported. The goal of this study was to examine whether nurse staffing levels and nursing skill mix are associated with trauma patient outcomes. Methods We used data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample to perform a cross-sectional study of 70,142 patients admitted to 77 Level I and Level II centers. Logistic regression models were used to examine the association between nurse staffing measures and (1) mortality, (2) healthcare associated infections (HAI), and (3) failure-to-rescue. We controlled for patient risk factors (age, gender, injury severity, mechanism of injury, comorbidities) and hospital structural characteristics (trauma center status - Level I versus Level II, hospital size, ownership, teaching status, technology level, and geographic region). Results A 1% increase in the ratio of licensed practical nurse (LPN) to total nursing time was associated with a 4% increase in the odds of mortality (adj OR 1.04; 95% CI: 1.02-1.06; p = 0.001) and a 6% increase in the odds of sepsis (adj OR 1.06: 1.03-1.10; p  Conclusions Higher hospital LPN staffing levels are independently associated with slightly higher rates of mortality and sepsis in trauma patients admitted to Level I or Level II trauma centers.</p