Communication practices in physician decision-making for an unstable critically ill patient with end-stage cancer.

BACKGROUND: Shared decision-making has become the standard of care for most medical treatments. However, little is known about physician communication practices in the decision making for unstable critically ill patients with known end-stage disease. OBJECTIVE: To describe communication practices of physicians making treatment decisions for unstable critically ill patients with end-stage cancer, using the framework of shared decision-making. DESIGN: Analysis of audiotaped encounters between physicians and a standardized patient, in a high-fidelity simulation scenario, to identify best practice communication behaviors. The simulation depicted a 78-year-old man with metastatic gastric cancer, life-threatening hypoxia, and stable preferences to avoid intensive care unit (ICU) admission and intubation. Blinded coders assessed the encounters for verbal communication behaviors associated with handling emotions and discussion of end-of-life goals. We calculated a score for skill at handling emotions (0-6) and at discussing end of life goals (0-16). SUBJECTS: Twenty-seven hospital-based physicians. RESULTS: Independent variables included physician demographics and communication behaviors. We used treatment decisions (ICU admission and initiation of palliation) as a proxy for accurate identification of patient preferences. Eight physicians admitted the patient to the ICU, and 16 initiated palliation. Physicians varied, but on average demonstrated low skill at handling emotions (mean, 0.7) and moderate skill at discussing end-of-life goals (mean, 7.4). We found that skill at discussing end-of-life goals was associated with initiation of palliation (p = 0.04). CONCLUSIONS: It is possible to analyze the decision making of physicians managing unstable critically ill patients with end-stage cancer using the framework of shared decision-making.

Do diabetic veterans use the Internet? Self-reported usage, skills, and interest in using My HealtheVet Web portal.

OBJECTIVE: The Veterans Health Administration has developed My HealtheVet (MHV), a Web-based portal that links veterans to their care in the veteran affairs (VA) system. The objective of this study was to measure diabetic veterans' access to and use of the Internet, and their interest in using MHV to help manage their diabetes. MATERIALS AND METHODS: Cross-sectional mailed survey of 201 patients with type 2 diabetes and hemoglobin A(1c) > 8.0% receiving primary care at any of five primary care clinic sites affiliated with a VA tertiary care facility. Main measures included Internet usage, access, and attitudes; computer skills; interest in using the Internet; awareness of and attitudes toward MHV; demographics; and socioeconomic status. RESULTS: A majority of respondents reported having access to the Internet at home. Nearly half of all respondents had searched online for information about diabetes, including some who did not have home Internet access. More than a third obtained "some" or "a lot" of their health-related information online. Forty-one percent reported being "very interested" in using MHV to help track their home blood glucose readings, a third of whom did not have home Internet access. Factors associated with being "very interested" were as follows: having access to the Internet at home (p < 0.001), "a lot/some" trust in the Internet as a source of health information (p = 0.002), lower age (p = 0.03), and some college (p = 0.04). Neither race (p = 0.44) nor income (p = 0.25) was significantly associated with interest in MHV. CONCLUSIONS: This study found that a diverse sample of older VA patients with sub-optimally controlled diabetes had a level of familiarity with and access to the Internet comparable to an age-matched national sample. In addition, there was a high degree of interest in using the Internet to help manage their diabetes.

Making sense of health information technology implementation: A qualitative study protocol.

BACKGROUND: Implementing new practices, such as health information technology (HIT), is often difficult due to the disruption of the highly coordinated, interdependent processes (e.g., information exchange, communication, relationships) of providing care in hospitals. Thus, HIT implementation may occur slowly as staff members observe and make sense of unexpected disruptions in care. As a critical organizational function, sensemaking, defined as the social process of searching for answers and meaning which drive action, leads to unified understanding, learning, and effective problem solving -- strategies that studies have linked to successful change. Project teamwork is a change strategy increasingly used by hospitals that facilitates sensemaking by providing a formal mechanism for team members to share ideas, construct the meaning of events, and take next actions. METHODS: In this longitudinal case study, we aim to examine project teams' sensemaking and action as the team prepares to implement new information technology in a tiertiary care hospital. Based on management and healthcare literature on HIT implementation and project teamwork, we chose sensemaking as an alternative to traditional models for understanding organizational change and teamwork. Our methods choices are derived from this conceptual framework. Data on project team interactions will be prospectively collected through direct observation and organizational document review. Through qualitative methods, we will identify sensemaking patterns and explore variation in sensemaking across teams. Participant demographics will be used to explore variation in sensemaking patterns. DISCUSSION: Outcomes of this research will be new knowledge about sensemaking patterns of project teams, such as: the antecedents and consequences of the ongoing, evolutionary, social process of implementing HIT; the internal and external factors that influence the project team, including team composition, team member interaction, and interaction between the project team and the larger organization; the ways in which internal and external factors influence project team processes; and the ways in which project team processes facilitate team task accomplishment. These findings will lead to new methods of implementing HIT in hospitals.

Analysis of traumatic injuries presenting to a referral hospital emergency department in Moshi, Tanzania.

BACKGROUND: Injuries represent a significant and growing public health concern in the developing world, yet their impact on patients and the emergency health-care system in the countries of East Africa has received limited attention. This study evaluates the magnitude and scope of injury related disorders in the population presenting to a referral hospital emergency department in northern Tanzania. METHODS: A retrospective chart review of patients presenting to the emergency department at Kilimanjaro Christian Medical Centre was performed. A standardized data collection form was used for data abstraction from the emergency department logbook and the complete medical record for all injured patients. Patient demographics, mechanism of injury, location, type and outcomes were recorded. RESULTS: Ten thousand six hundred twenty-two patients presented to the emergency department for evaluation and treatment during the 7-month study period. One thousand two hundred twenty-four patients (11.5%) had injuries. Males and individuals aged 15 to 44 years were most frequently injured, representing 73.4% and 57.8%, respectively. Road traffic injuries were the most common mechanism of injury, representing 43.9% of injuries. Head injuries (36.5%) and extremity injuries (59.5%) were the most common location of injury. The majority of injured patients, 59.3%, were admitted from the emergency department to the hospital wards, and 5.6%, required admission to an intensive care unit. Death occurred in 5.4% of injured patients. CONCLUSIONS: These data give a detailed and more robust picture of the patient demographics, mechanisms of injury, types of injury and patient outcomes from similar resource-limited settings.

Socio-economic status and malaria-related outcomes in Mvomero District, Tanzania.

While policies often target malaria prevention and treatment - proximal causes of malaria and related health outcomes - too little attention has been given to the role of household- and individual-level socio-economic status (SES) as a fundamental cause of disease risk in developing countries. This paper presents a conceptual model outlining ways in which SES may influence malaria-related outcomes. Building on this conceptual model, we use household data from rural Mvomero, Tanzania, to examine empirical relationships among multiple measures of household and individual SES and demographics, on the one hand, and malaria prevention, illness, and diagnosis and treatment behaviours, on the other. We find that access to prevention and treatment is significantly associated with indicators of households' wealth; education-based disparities do not emerge in this context. Meanwhile, reported malaria illness shows a stronger association with demographic variables than with SES (controlling for prevention). Greater understanding of the mechanisms through which SES and malaria policies interact to influence disease risk can help to reduce health disparities and reduce the malaria burden in an equitable manner.

Reduced length of hospital stay in colorectal surgery after implementation of an enhanced recovery protocol.

BACKGROUND: Enhanced recovery after surgery (ERAS) is a multimodal approach to perioperative care that combines a range of interventions to enable early mobilization and feeding after surgery. We investigated the feasibility, clinical effectiveness, and cost savings of an ERAS program at a major U. S. teaching hospital. METHODS: Data were collected from consecutive patients undergoing open or laparoscopic colorectal surgery during 2 time periods, before and after implementation of an ERAS protocol. Data collected included patient demographics, operative, and perioperative surgical and anesthesia data, need for analgesics, complications, inpatient medical costs, and 30-day readmission rates. RESULTS: There were 99 patients in the traditional care group, and 142 in the ERAS group. The median length of stay (LOS) was 5 days in the ERAS group compared with 7 days in the traditional group (P < 0.001). The reduction in LOS was significant for both open procedures (median 6 vs 7 days, P = 0.01), and laparoscopic procedures (4 vs 6 days, P < 0.0001). ERAS patients had fewer urinary tract infections (13% vs 24%, P = 0.03). Readmission rates were lower in ERAS patients (9.8% vs 20.2%, P = 0.02). DISCUSSION: Implementation of an enhanced recovery protocol for colorectal surgery at a tertiary medical center was associated with a significantly reduced LOS and incidence of urinary tract infection. This is consistent with that of other studies in the literature and suggests that enhanced recovery programs could be implemented successfully and should be considered in U.S. hospitals.

Systematic review and metasummary of attitudes toward research in emergency medical conditions

Emergency departments are challenging research settings, where truly informed consent can be difficult to obtain. A deeper understanding of emergency medical patients' opinions about research is needed. We conducted a systematic review and meta-summary of quantitative and qualitative studies on which values, attitudes, or beliefs of emergent medical research participants influence research participation. We included studies of adults that investigated opinions toward emergency medicine research participation. We excluded studies focused on the association between demographics or consent document features and participation and those focused on non-emergency research. In August 2011, we searched the following databases: MEDLINE, EMBASE, Google Scholar, Scirus, PsycINFO, AgeLine and Global Health. Titles, abstracts and then full manuscripts were independently evaluated by two reviewers. Disagreements were resolved by consensus and adjudicated by a third author. Studies were evaluated for bias using standardised scores. We report themes associated with participation or refusal. Our initial search produced over 1800 articles. A total of 44 articles were extracted for full-manuscript analysis, and 14 were retained based on our eligibility criteria. Among factors favouring participation, altruism and personal health benefit had the highest frequency. Mistrust of researchers, feeling like a 'guinea pig' and risk were leading factors favouring refusal. Many studies noted limitations of informed consent processes in emergent conditions. We conclude that highlighting the benefits to the participant and society, mitigating risk and increasing public trust may increase research participation in emergency medical research. New methods for conducting informed consent in such studies are needed.

An online daily diary study of alcohol use using Amazon's mechanical turk

Introduction and Aims: In recent years, unprecedented levels of Internet access and the widespread growth of emergent communication technologies have resulted in significantly greater population access for substance use researchers. Despite the research potential of such technologies, the use of the Internet to recruit individuals for participation in event-level research has been limited. The purpose of this paper is to provide a brief account of the methods and results from an online daily diary study of alcohol use. Design and Methods: Participants were recruited using Amazon's Mechanical Turk. Eligible participants completed a brief screener assessing demographics and health behaviours, with a subset of individuals subsequently recruited to participate in a 2 week daily diary study of alcohol use. Results: Multilevel models of the daily alcohol data derived from the Mechanical Turk sample (n=369) replicated several findings commonly reported in daily diary studies of alcohol use. Discussion and Conclusions: Results demonstrate that online participant recruitment and survey administration can be a fruitful method for conducting daily diary alcohol research. © 2014 Australasian Professional Society on Alcohol and other Drugs.

Veterans health administration hepatitis B testing and treatment with anti-CD20 antibody administration.

AIM: To evaluate pretreatment hepatitis B virus (HBV) testing, vaccination, and antiviral treatment rates in Veterans Affairs patients receiving anti-CD20 Ab for quality improvement. METHODS: We performed a retrospective cohort study using a national repository of Veterans Health Administration (VHA) electronic health record data. We identified all patients receiving anti-CD20 Ab treatment (2002-2014). We ascertained patient demographics, laboratory results, HBV vaccination status (from vaccination records), pharmacy data, and vital status. The high risk period for HBV reactivation is during anti-CD20 Ab treatment and 12 mo follow up. Therefore, we analyzed those who were followed to death or for at least 12 mo after completing anti-CD20 Ab. Pretreatment serologic tests were used to categorize chronic HBV (hepatitis B surface antigen positive or HBsAg+), past HBV (HBsAg-, hepatitis B core antibody positive or HBcAb+), resolved HBV (HBsAg-, HBcAb+, hepatitis B surface antibody positive or HBsAb+), likely prior vaccination (isolated HBsAb+), HBV negative (HBsAg-, HBcAb-), or unknown. Acute hepatitis B was defined by the appearance of HBsAg+ in the high risk period in patients who were pretreatment HBV negative. We assessed HBV antiviral treatment and the incidence of hepatitis, liver failure, and death during the high risk period. Cumulative hepatitis, liver failure, and death after anti-CD20 Ab initiation were compared by HBV disease categories and differences compared using the χ(2) test. Mean time to hepatitis peak alanine aminotransferase, liver failure, and death relative to anti-CD20 Ab administration and follow-up were also compared by HBV disease group. RESULTS: Among 19304 VHA patients who received anti-CD20 Ab, 10224 (53%) had pretreatment HBsAg testing during the study period, with 49% and 43% tested for HBsAg and HBcAb, respectively within 6 mo pretreatment in 2014. Of those tested, 2% (167/10224) had chronic HBV, 4% (326/7903) past HBV, 5% (427/8110) resolved HBV, 8% (628/8110) likely prior HBV vaccination, and 76% (6022/7903) were HBV negative. In those with chronic HBV infection, ≤ 37% received HBV antiviral treatment during the high risk period while 21% to 23% of those with past or resolved HBV, respectively, received HBV antiviral treatment. During and 12 mo after anti-CD20 Ab, the rate of hepatitis was significantly greater in those HBV positive vs negative (P = 0.001). The mortality rate was 35%-40% in chronic or past hepatitis B and 26%-31% in hepatitis B negative. In those pretreatment HBV negative, 16 (0.3%) developed acute hepatitis B of 4947 tested during anti-CD20Ab treatment and follow-up. CONCLUSION: While HBV testing of Veterans has increased prior to anti-CD20 Ab, few HBV+ patients received HBV antivirals, suggesting electronic health record algorithms may enhance health outcomes.

Bias on the Bench: How Judges’ Legal Backgrounds Influence Their Decisions

The ideal conception of a judge is that of a neutral arbitrator. However, there exist good reasons to believe that personal characteristics, including professional experiences, bias judges. Such suspicions inspired two hypotheses: (1) judges that are former prosecutors are biased in favor of the government in criminal appeals; (2) judges that are former criminal defense attorneys are biased in favor of the criminal appellant. These hypotheses were tested by gathering professional information about state supreme court judges in the south during the years from 1995 until 1998. That was then matched to an existing database that recorded those judges’ demographics and decisions in criminal appeals during that time. Logistic regressions of that data revealed that despite when other characteristics, including gender, race, and legal experience, were accounted for, criminal defense remained a statistically significant predictor. Judges with a background in criminal defense were more likely to reverse criminal court decisions. In contrast, prosecutorial experience was not a good predictor of how a judge ruled. Judges that had backgrounds in prosecution did not rule much differently than those that did not have such a background.

HomeBank: An Online Repository of Daylong Child-Centered Audio Recordings.

HomeBank is introduced here. It is a public, permanent, extensible, online database of daylong audio recorded in naturalistic environments. HomeBank serves two primary purposes. First, it is a repository for raw audio and associated files: one database requires special permissions, and another redacted database allows unrestricted public access. Associated files include metadata such as participant demographics and clinical diagnostics, automated annotations, and human-generated transcriptions and annotations. Many recordings use the child-perspective LENA recorders (LENA Research Foundation, Boulder, Colorado, United States), but various recordings and metadata can be accommodated. The HomeBank database can have both vetted and unvetted recordings, with different levels of accessibility. Additionally, HomeBank is an open repository for processing and analysis tools for HomeBank or similar data sets. HomeBank is flexible for users and contributors, making primary data available to researchers, especially those in child development, linguistics, and audio engineering. HomeBank facilitates researchers' access to large-scale data and tools, linking the acoustic, auditory, and linguistic characteristics of children's environments with a variety of variables including socioeconomic status, family characteristics, language trajectories, and disorders. Automated processing applied to daylong home audio recordings is now becoming widely used in early intervention initiatives, helping parents to provide richer speech input to at-risk children.

Role of patient factors, preferences, and distrust in health care and access to liver transplantation and organ donation.

Despite major improvements in access to liver transplantation (LT), disparities remain. Little is known about how distrust in medical care, patient preferences, and the origins shaping those preferences contribute to differences surrounding access. We performed a single-center, cross-sectional survey of adults with end-stage liver disease and compared responses between LT listed and nonlisted patients as well as by race. Questionnaires were administered to 109 patients (72 nonlisted; 37 listed) to assess demographics, health care system distrust (HCSD), religiosity, and factors influencing LT and organ donation (OD). We found that neither HCSD nor religiosity explained differences in access to LT in our population. Listed patients attained higher education levels and were more likely to be insured privately. This was also the case for white versus black patients. All patients reported wanting LT if recommended. However, nonlisted patients were significantly less likely to have discussed LT with their physician or to be referred to a transplant center. They were also much less likely to understand the process of LT. Fewer blacks were referred (44.4% versus 69.7%; P = 0.03) or went to the transplant center if referred (44.4% versus 71.1%; P = 0.02). Fewer black patients felt that minorities had as equal access to LT as whites (29.6% versus 57.3%; P < 0.001). For OD, there were more significant differences in preferences by race than listing status. More whites indicated OD status on their driver's license, and more blacks were likely to become an organ donor if approached by someone of the same cultural or ethnic background (P < 0.01). In conclusion, our analysis demonstrates persistent barriers to LT and OD. With improved patient and provider education and communication, many of these disparities could be successfully overcome. Liver Transplantation 22 895-905 2016 AASLD.

Combining Information from Multiple Sources in Bayesian Modeling

Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.