Second, do less harm: The state of states' medical error reporting programs

Statement of the problem and public health significance. Hospitals were designed to be a safe haven and respite from disease and illness. However, a large body of evidence points to preventable errors in hospitals as the eighth leading cause of death among Americans. Twelve percent of Americans, or over 33.8 million people, are hospitalized each year. This population represents a significant portion of at risk citizens exposed to hospital medical errors. Since the number of annual deaths due to hospital medical errors is estimated to exceed 44,000, the magnitude of this tragedy makes it a significant public health problem. ^ Specific aims. The specific aims of this study were threefold. First, this study aimed to analyze the state of the states' mandatory hospital medical error reporting six years after the release of the influential IOM report, "To Err is Human." The second aim was to identify barriers to reporting of medical errors by hospital personnel. The third aim was to identify hospital safety measures implemented to reduce medical errors and enhance patient safety. ^ Methods. A descriptive, longitudinal, retrospective design was used to address the first stated objective. The study data came from the twenty-one states with mandatory hospital reporting programs which report aggregate hospital error data that is accessible to the public by way of states' websites. The data analysis included calculations of expected number of medical errors for each state according to IOM rates. Where possible, a comparison was made between state reported data and the calculated IOM expected number of errors. A literature review was performed to achieve the second study aim, identifying barriers to reporting medical errors. The final aim was accomplished by telephone interviews of principal patient safety/quality officers from five Texas hospitals with more than 700 beds. ^ Results. The state medical error data suggests vast underreporting of hospital medical errors to the states. The telephone interviews suggest that hospitals are working at reducing medical errors and creating safer environments for patients. The literature review suggests the underreporting of medical errors at the state level stems from underreporting of errors at the delivery level. ^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Maternal and neonatal outcomes by labor onset type and gestational age.

OBJECTIVE: We sought to determine maternal and neonatal outcomes by labor onset type and gestational age. STUDY DESIGN: We used electronic medical records data from 10 US institutions in the Consortium on Safe Labor on 115,528 deliveries from 2002 through 2008. Deliveries were divided by labor onset type (spontaneous, elective induction, indicated induction, unlabored cesarean). Neonatal and maternal outcomes were calculated by labor onset type and gestational age. RESULTS: Neonatal intensive care unit admissions and sepsis improved with each week of gestational age until 39 weeks (P < .001). After adjusting for complications, elective induction of labor was associated with a lower risk of ventilator use (odds ratio [OR], 0.38; 95% confidence interval [CI], 0.28-0.53), sepsis (OR, 0.36; 95% CI, 0.26-0.49), and neonatal intensive care unit admissions (OR, 0.52; 95% CI, 0.48-0.57) compared to spontaneous labor. The relative risk of hysterectomy at term was 3.21 (95% CI, 1.08-9.54) with elective induction, 1.16 (95% CI, 0.24-5.58) with indicated induction, and 6.57 (95% CI, 1.78-24.30) with cesarean without labor compared to spontaneous labor. CONCLUSION: Some neonatal outcomes improved until 39 weeks. Babies born with elective induction are associated with better neonatal outcomes compared to spontaneous labor. Elective induction may be associated with an increased hysterectomy risk.

Risk Index Score (RISc)

The main objective of this study was to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that can be translated into a simple scoring system in order to ascertain stroke cases using hospital admission medical records data. This algorithm, the Risk Index Score (RISc), was developed using data collected prospectively by the Brain Attack Surveillance in Corpus Christ (BASIC) project. The validity of the RISc was evaluated by estimating the concordance of scoring system stroke ascertainment to stroke ascertainment accomplished by physician review of hospital admission records. The goal of this study was to develop a rapid, simple, efficient, and accurate method to ascertain the incidence of stroke from routine hospital admission hospital admission records for epidemiologic investigations. ^ The main objectives of this study were to develop and validate a computer-based statistical algorithm based on a multivariable logistic model that could be translated into a simple scoring system to ascertain stroke cases using hospital admission medical records data. (Abstract shortened by UMI.)^

The use of invasive myocardial revascularization procedures following myocardial infarction and the effectiveness of these procedures in the biethnic community of Nueces County, Texas, 1988--1991

High levels of poverty and unemployment, and low levels of health insurance coverage may pose barriers to obtaining cardiac care by Mexican Americans. We undertook this study to investigate differences in the use of invasive myocardial revascularization procedures received within the 4-month period following hospitalization for a myocardial infarction (MI) between Mexican Americans and non-Hispanic whites in the Corpus Christi Heart Project (CCHP). The CCHP is a population-based surveillance program for hospitalized MI, percutaneous transluminal coronary angioplasty (PTCA), and aortocoronary bypass surgery (ACBS). Medical record data were available for 1706 patients identified over a three-year period. Mexican Americans had significantly lower rates of receiving a PTCA following MI than non-Hispanic Whites (RR: 0.56, 95% CI: 0.44-0.70). No meaningful ethnic difference was seen in the rates of ACBS use. History of PTCA use appeared to interact with ethnicity. Among patients without a history of PTCA use, Mexican Americans were less likely to receive a PTCA than non-Hispanic whites (RR: 0.59; 95% CI: 0.46-0.76). Among patients with a history of PTCA use, however, Mexican Americans were more likely to receive a PTCA than non-Hispanic whites (RR: 1.47; 95% CI: 0.75-2.87).^ Differences in the effectiveness of a first-time PTCA and first-time ACBS between Mexican Americans and non-Hispanic whites in the CCHP were also investigated. Mexican Americans were more likely to receive a 2nd PTCA (RR: 1.56, 95% CI: 1.11-2.17) and suffer a subsequent MI (RR: 1.42, 95% CI: 1.03-1.96) following a first-time PTCA than non-Hispanic whites. No meaningful ethnic differences were found in the rates of death and rates of ACBS following a first-time PTCA. Also, no significant ethnic differences were found in the rates of any of the events following a first-time ACBS. After adjusting for potential demographic, socioeconomic, clinical and angiographic confounders using Cox regression analysis, Mexican Americans were still more likely to receive a 2nd PTCA (HR: 1.38; 95% CI: 0.99-1.93) following a first-time PTCA than non-Hispanic whites. A significant difference in the rates of a subsequent MI following a first-time PTCA persisted (HR: 1.39, 95% CI: 1.01-1.93). (Abstract shortened by UMI.) ^

Lab animal allergy surveillance at a private medical school in three dissimilar animal research facilities

Very few studies have described MUP-1 concentrations and measured prevalence of Laboratory Animal Allergy (LAA) at such a diverse institution as the private medical school (MS) that is the focus of this study. Air sampling was performed in three dissimilar animal research facilities at MS and quantitated using a commercially available ELISA. Descriptive data was obtained from an anonymous laboratory animal allergy survey given to both animal facility employees and the researchers who utilize these facilities alike. Logistic regression analysis was then implemented to investigate specific factors that may be predictive of developing LAA as well as factors influencing the reporting of LAA symptoms to the occupational health program. Concentrations of MUP-1 detected ranged from below detectable levels (BDL) to a peak of 22.64 ng/m3 . Overall, 68 employees with symptoms claimed they improved while away from work and only 25 employees reported their symptoms to occupational health. Being Vietnamese, a smoker, not wearing a mask, and working in any facility longer than one year were all significant predictors of having LAA symptoms. This study suggests a LAA monitoring system that relies on self-reporting can be inadequate in estimating LAA problems. In addition, efforts need to be made to target training and educational materials for non-native English speaking employees to overcome language and cultural barriers and address their specific needs. ^

Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain?

BACKGROUND: Follow-up of abnormal outpatient laboratory test results is a major patient safety concern. Electronic medical records can potentially address this concern through automated notification. We examined whether automated notifications of abnormal laboratory results (alerts) in an integrated electronic medical record resulted in timely follow-up actions. METHODS: We studied 4 alerts: hemoglobin A1c > or =15%, positive hepatitis C antibody, prostate-specific antigen > or =15 ng/mL, and thyroid-stimulating hormone > or =15 mIU/L. An alert tracking system determined whether the alert was acknowledged (ie, provider clicked on and opened the message) within 2 weeks of transmission; acknowledged alerts were considered read. Within 30 days of result transmission, record review and provider contact determined follow-up actions (eg, patient contact, treatment). Multivariable logistic regression models analyzed predictors for lack of timely follow-up. RESULTS: Between May and December 2008, 78,158 tests (hemoglobin A1c, hepatitis C antibody, thyroid-stimulating hormone, and prostate-specific antigen) were performed, of which 1163 (1.48%) were transmitted as alerts; 10.2% of these (119/1163) were unacknowledged. Timely follow-up was lacking in 79 (6.8%), and was statistically not different for acknowledged and unacknowledged alerts (6.4% vs 10.1%; P =.13). Of 1163 alerts, 202 (17.4%) arose from unnecessarily ordered (redundant) tests. Alerts for a new versus known diagnosis were more likely to lack timely follow-up (odds ratio 7.35; 95% confidence interval, 4.16-12.97), whereas alerts related to redundant tests were less likely to lack timely follow-up (odds ratio 0.24; 95% confidence interval, 0.07-0.84). CONCLUSIONS: Safety concerns related to timely patient follow-up remain despite automated notification of non-life-threatening abnormal laboratory results in the outpatient setting.

An innovative approach to impacting student academic achievement and attitudes: Pilot study of the HEADS UP Virtual Molecular Biology Lab

Objective. To evaluate the HEADS UP Virtual Molecular Biology Lab, a computer-based simulated laboratory designed to teach advanced high school biology students how to create a mouse model. ^ Design. A randomized clinical control design of forty-four students from two science magnet high schools in Mercedes, Texas was utilized to assess knowledge and skills of molecular laboratory procedures, attitudes towards science and computers as a learning tool, and usability of the program. ^ Measurements. Data was collected using five paper-and-pencil formatted questionnaires and an internal "lab notebook." ^ Results. The Virtual Lab was found to significantly increase student knowledge over time (p<0.005) and with each use (p<0.001) as well as positively increase attitudes towards computers (p<0.001) and skills (p<0.005). No significant differences were seen in science attitude scores.^ Conclusion. These results provide evidence that the HEADS UP Virtual Molecular Biology Lab is a potentially effective educational tool for high school molecular biology education.^

Automated soldier medical readiness: Prevalence of " medically not ready" using data from the electronic soldier readiness processing system (ESRP)

Identifying accurate numbers of soldiers determined to be medically not ready after completing soldier readiness processing may help inform Army leadership about ongoing pressures on the military involved in long conflict with regular deployment. In Army soldiers screened using the SRP checklist for deployment, what is the prevalence of soldiers determined to be medically not ready? Study group. 15,289 soldiers screened at all 25 Army deployment platform sites with the eSRP checklist over a 4-month period (June 20, 2009 to October 20, 2009). The data included for analysis included age, rank, component, gender and final deployment medical readiness status from MEDPROS database. Methods.^ This information was compiled and univariate analysis using chi-square was conducted for each of the key variables by medical readiness status. Results. Descriptive epidemiology Of the total sample 1548 (9.7%) were female and 14319 (90.2%) were male. Enlisted soldiers made up 13,543 (88.6%) of the sample and officers 1,746 (11.4%). In the sample, 1533 (10.0%) were soldiers over the age of 40 and 13756 (90.0%) were age 18-40. Reserve, National Guard and Active Duty made up 1,931 (12.6%), 2,942 (19.2%) and 10,416 (68.1%) respectively. Univariate analysis. Overall 1226 (8.0%) of the soldiers screened were determined to be medically not ready for deployment. Biggest predictive factor was female gender OR (2.8; 2.57-3.28) p<0.001. Followed by enlisted rank OR (2.01; 1.60-2.53) p<0.001. Reserve component OR (1.33; 1.16-1.53) p<0.001 and Guard OR (0.37; 0.30-0.46) p<0.001. For age > 40 demonstrated OR (1.2; 1.09-1.50) p<0.003. Overall the results underscore there may be key demographic groups relating to medical readiness that can be targeted with programs and funding to improve overall military medical readiness.^

Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

An Innovative Approach to Impacting Student Academic Achievement and Attitudes: Pilot Study of the HEADS UP Virtual Molecular Biology Lab

Introduction: The Virtual Molecular Biology Lab is an innovative, computer-based educational program designed to teach advanced high school biology students how to create a transgenic mouse model in a simulated laboratory setting. It was created in an effort to combat the current decrease in adolescent enthusiasm for and academic achievement in science and science careers, especially in Hispanic students. Because studies have found that hands-on learning, particularly computer-based instruction, is effective in enhancing science achievement, the Virtual Lab is a potential tool for increasing the number of Hispanic students that choose to enter science fields. [See PDF for complete abstract]

Rigorously assessing whether the data backs the back school.

A rigorous between-subjects methodology employing independent random samples and having broad clinical applicability was designed and implemented to evaluate the effectiveness of back safety and patient transfer training interventions for both hospital nurses and nursing assistants. Effects upon self-efficacy, cognitive, and affective measures are assessed for each of three back safety procedures. The design solves the problem of obtaining randomly assigned independent controls where all experimental subjects must participate in the training interventions.

The Houston Academy of Medicine--Texas Medical Center Library management information system.

A management information system (MIS) provides a means for collecting, reporting, and analyzing data from all segments of an organization. Such systems are common in business but rare in libraries. The Houston Academy of Medicine-Texas Medical Center Library developed an MIS that operates on a system of networked IBM PCs and Paradox, a commercial database software package. The data collected in the system include monthly reports, client profile information, and data collected at the time of service requests. The MIS assists with enforcement of library policies, ensures that correct information is recorded, and provides reports for library managers. It also can be used to help answer a variety of ad hoc questions. Future plans call for the development of an MIS that could be adapted to other libraries' needs, and a decision-support interface that would facilitate access to the data contained in the MIS databases.