Gender, flexibility and workforce in the NHS: A qualitative study.

Data from the General Medical Council show that the number of female doctors registered to practise in the UK continues to grow at a faster rate than the number of male doctors. Our research critically discusses the impact of this gender-based shift, considering how models of medical training are still ill-suited to supporting equity and inclusivity within the workforce, with particular impacts for women despite this gender shift. Drawing on data from our research project Mapping underdoctored areas: the impact of medical training pathways on NHS workforce distribution and health inequalities, this paper explores the experiences of doctors working in the NHS, considering how policies around workforce and beyond have impacted people's willingness and ability to continue in their chosen career path. There is clear evidence that women are underrepresented in some specialties such as surgery, and at different career stages including in senior leadership roles, and our research focuses on the structural factors that contribute to reinforcing these under-representations. Medical education and training are known to be formative points in doctors' lives, with long-lasting impacts for NHS service provision. By understanding in detail how these pathways inadvertently shape where doctors live and work, we will be able to consider how best to change existing systems to provide patients with timely and appropriate access to healthcare. We take a cross-disciplinary theoretical approach, bringing historical, spatiotemporal and sociological insights to healthcare problems. Here, we draw on our first 50 interviews with practising doctors employed in the NHS in areas that struggle to recruit and retain doctors, and explore the gendered nature of career biographies. We also pay attention to the ways in which doctors carve their own career pathways out of, or despite of, personal and professional disruptions.

Who cares where the doctors are? The expectation of mobility and its effect on health outcomes.

Doctors are typically portrayed as active agents in their work lives. However, this paper argues that this construction of agency ignores the effects of the healthcare structures that constrain choice, which in turn affects population health outcomes. Medical training pathways, regional boundaries, and rationalisation all have a long-lasting impact on the provision of healthcare. Using a mobilities lens to examine the movement of doctors, this paper examines how the expectation of movement built into training programmes perpetuates unequal access to healthcare. Long waiting times, poor care quality and lack of preventative care all perpetuate health inequalities; as one of the socio-economic determinants, access to healthcare affects health outcomes.

Why are some cases not on track? An item analysis of the Assessment for Signal Cases during inpatient psychotherapy.

Within the Routine Outcome Monitoring system "OQ-Analyst," the questionnaire "Assessment for Signal Cases" (ASC) supports therapists in detecting potential reasons for not-on-track trajectories. Factor analysis and a machine learning algorithm (LASSO with 10-fold cross-validation) were applied, and potential predictors of not-on-track classifications were tested using logistic multilevel modeling methods. The factor analysis revealed a shortened (30 items) version of the ASC with good internal consistency (α = 0.72-0.89) and excellent predictive value (area under the curve = 0.98; positive predictive value = 0.95; negative predictive value = 0.94). Item-level analyses showed that interpersonal problems captured by specific ASC items (not feeling able to speak about problems with family members; feeling rejected or betrayed) are the most important predictors of not-on-track trajectories. It should be considered that our results are based on analyses of ASC items only. Our findings need to be replicated in future studies including other potential predictors of not-on-track trajectories (e.g., changes in medication, specific therapeutic techniques, or treatment adherence), which were not measured this study.

The economic cost of preventable disease in Australia: a systematic review of estimates and methods.

OBJECTIVE: The aim of this literature review was to establish the economic burden of preventable disease in Australia in terms of attributable health care costs, other costs to government and reduced productivity. METHODS: A systematic review was conducted to establish the economic cost of preventable disease in Australia and ascertain the methods used to derive these estimates. Nine databases and the grey literature were searched, limited to the past 10 years, and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines were followed to identify, screen and report on eligible studies. RESULTS: Eighteen studies were included. There were at least three studies examining the attributable costs and economic impact for each risk factor. The greatest costs were related to the productivity impacts of preventable risk factors. Estimates of the annual productivity loss that could be attributed to individual risk factors were between $840 million and $14.9 billion for obesity; up to $10.5 billion due to tobacco; between $1.1 billion and $6.8 billion for excess alcohol consumption; up to $15.6 billion due to physical inactivity and $561 million for individual dietary risk factors. Productivity impacts were included in 15 studies and the human capital approach was the method most often employed (14 studies) to calculate this. CONCLUSIONS: Substantial economic burden is caused by lifestyle-related risk factors. Implications for public health: The significant economic burden associated with preventable disease provides an economic rationale for action to reduce the prevalence of lifestyle-related risk factors. New analysis of the economic burden of multiple risk factors concurrently is needed.

The health burden of preventable disease in Australia: a systematic review.

OBJECTIVE: A systematic review was conducted to determine the health burden of preventable disease in Australia. METHODS: The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement guidelines were followed to identify, screen and describe the protocols used in the systematic review. RESULTS: Eleven studies were included in the review. Data on the health burden associated with lifestyle-related risk factors were extracted by disease with outcomes reported in attributable number and proportion of deaths, years of life lost, years lived with disability and disability-adjusted life years (DALYs). Around one-third of DALYs was attributed to all modifiable risk factors. The range of estimates of DALYs attributable to each prioritised risk factor was: combined dietary risk factors, 7.2% to 9.7%; tobacco, 7.9% to 9.0%; alcohol, 5.1% to 12.2%; high body mass, 5.5% to 8.3%; and physical inactivity, 1.2% to 5.5%. CONCLUSIONS: Although the methods used to estimate preventable health burden varied greatly between studies, all found that a substantial amount of death and disability was attributable to lifestyle-related risk factors. Implications for public health: There is a large health burden in Australia caused by modifiable risk factors and further action is warranted to address this burden.

Cross-informant and cross-national equivalence using item-response theory (IRT) linking: A case study using the behavioral assessment for children of African heritage in the United States and Jamaica.

Cross-national study of adolescents' psychological adjustment requires measures that permit reliable and valid assessment across informants and nations, but such measures are virtually nonexistent. Item-response-theory-based linking is a promising yet underutilized methodological procedure that permits more accurate assessment across informants and nations. To demonstrate this procedure, the Resilience Scale of the Behavioral Assessment for Children of African Heritage (Lambert et al., 2005) was administered to 250 African American and 294 Jamaican nonreferred adolescents and their caregivers. Multiple items without significant differential item functioning emerged, allowing scale linking across informants and nations. Calibrating item parameters via item response theory linking can permit cross-informant cross-national assessment of youth.

Using the Assessment for Signal Clients as a feedback tool for reducing treatment failure.

OBJECTIVE: The Clinical Support Tools (CSTs) were developed to help therapists organize and target potential problems that might account for negative outcomes in psychotherapy. The core of CST feedback is the Assessment for Signal Clients. The purpose of this study was to describe and identify patterns of problems that typically characterize off-track cases. METHOD: The responses and scores from 107 off-track clients from a hospital-based outpatient clinic were analyzed. RESULTS: A cluster analysis of the 107 off-track clients revealed three client types: those whose problems were characterized by alliance and motivational difficulties; those characterized by social support and life event difficulties; and those whose problems had an indistinguishable pattern. Log-linear modeling showed that if patients had less therapeutic alliance problems they were also less likely to have motivational problems. Findings were also consistent with the cluster analysis, which showed that a relatively higher percentage of not-on-track participants received signal alerts for the social support items and scale. CONCLUSIONS: Individuals whose progress goes off-track while in psychotherapy appear to have their greatest difficulty with social support, followed closely by motivation for therapy and therapeutic alliance.

An investigation of self-assessment bias in mental health providers.

Previous research has consistently found self-assessment bias (an overly positive assessment of personal performance) to be present in a wide variety of work situations. The present investigation extended this area of research with a multi-disciplinary sample of mental health professionals. Respondents were asked to: (a) compare their own overall clinical skills and performance to others in their profession, and (b) indicate the percentage of their clients who improved, remained the same, or deteriorated as a result of treatment with them. Results indicated that 25% of mental health professionals viewed their skill to be at the 90th percentile when compared to their peers, and none viewed themselves as below average. Further, when compared to the published literature, clinicians tended to overestimate their rates of client improvement and underestimate their rates of client deterioration. The implications of this self-assessment bias for improvement of psychotherapy outcomes are discussed.

Evaluation of a risk-based environmental hot spot delineation algorithm.

Following remedial investigations of hazardous waste sites, remedial strategies may be developed that target the removal of "hot spots," localized areas of elevated contamination. For a given exposure area, a hot spot may be defined as a sub-area that causes risks for the whole exposure area to be unacceptable. The converse of this statement may also apply: when a hot spot is removed from within an exposure area, risks for the exposure area may drop below unacceptable thresholds. The latter is the motivation for a risk-based approach to hot spot delineation, which was evaluated using Monte Carlo simulation. Random samples taken from a virtual site ("true site") were used to create an interpolated site. The latter was gridded and concentrations from the center of each grid box were used to calculate 95% upper confidence limits on the mean site contaminant concentration and corresponding hazard quotients for a potential receptor. Grid cells with the highest concentrations were removed and hazard quotients were recalculated until the site hazard quotient dropped below the threshold of 1. The grid cells removed in this way define the spatial extent of the hot spot. For each of the 100,000 Monte Carlo iterations, the delineated hot spot was compared to the hot spot in the "true site." On average, the algorithm was able to delineate hot spots that were collocated with and equal to or greater in size than the "true hot spot." When delineated hot spots were mapped onto the "true site," setting contaminant concentrations in the mapped area to zero, the hazard quotients for these "remediated true sites" were on average within 5% of the acceptable threshold of 1.

Evaluation of statistical methods for left-censored environmental data with nonuniform detection limits.

Monte Carlo simulations were used to evaluate statistical methods for estimating 95% upper confidence limits of mean constituent concentrations for left-censored data with nonuniform detection limits. Two primary scenarios were evaluated: data sets with 15 to 50% nondetected samples and data sets with 51 to 80% nondetected samples. Sample size and the percentage of nondetected samples were allowed to vary randomly to generate a variety of left-censored data sets. All statistical methods were evaluated for efficacy by comparing the 95% upper confidence limits for the left-censored data with the 95% upper confidence limits for the noncensored data and by determining percent coverage of the true mean (micro). For data sets with 15 to 50% nondetected samples, the trimmed mean, Winsorization, Aitchison's, and log-probit regression methods were evaluated. The log-probit regression was the only method that yielded sufficient coverage (99-100%) of micro, as well as a high correlation coefficient (r2 = 0.99) and small average percent residuals (-0.1%) between upper confidence limits for censored versus noncensored data sets. For data sets with 51 to 80% nondetected samples, a bounding method was effective (r2 = 0.96 - 0.99, average residual = -5% to -7%, 95-98% coverage of micro), except when applied to distributions with low coefficients of variation (standard deviation/micro < 0.5). Thus, the following recommendations are supported by this research: data sets with 15 to 50% nondetected samples--log-probit regression method and use of Chebyshev theorem to estimate 95% upper confidence limits; data sets with 51 to 80% nondetected samples-bounding method and use of Chebyshev theorem to estimate 95% upper confidence limits.

Identifying highly effective psychotherapists in a managed care environment.

OBJECTIVE: To investigate the variability and stability of psychotherapists' effectiveness and the implications of this differential effectiveness for quality improvement in a managed care environment. STUDY DESIGN: Subset archival outcome data for patients receiving behavioral health treatment were divided into 2 time periods to cross-validate the treating therapists' effectiveness. After categorizing the therapists as "highly effective" and "others" during the baseline period, the stability of their individual effectiveness was cross-validated in the remaining time period. METHODS: Outcomes for 10 812 patients (76.0% adults, 24.0% children and adolescents) treated by 281 therapists were included. Patients initiated treatment between January 1999 and June 2004. Mean residual change scores obtained by multiple regression were used to adjust for differences in case mix among therapists. Raw change scores as well as mean residualized change scores were compared between the 71 psychotherapists identified as highly effective (25%) and those identified as other (remaining 75%). RESULTS: During the cross-validation period, mean differences in residualized change score between highly effective therapists and others were statistically significant (difference = 2.8; P < .001), which corresponded to an average of 53.3% more change in raw change scores with the highly effective therapists. Results could not be explained by case mix differences in diagnosis, age, sex, intake scores, prior outpatient treatment history, length of treatment, or therapist training/experience. CONCLUSION: Behavioral health outcomes for a large system of care could be significantly improved by measuring clinical outcomes and referring patients to therapists with superior outcomes.

Performance, training, quality assurance, and reimbursement of emergency physician-performed ultrasonography at academic medical centers.

OBJECTIVE: To determine the current state of bedside emergency physician-performed ultrasonography in terms of prevalence, training, quality assurance, and reimbursement at emergency medicine residency programs. METHODS: The link to a 10-question Web-based survey was e-mailed to ultrasound/residency directors at 122 emergency medicine residency programs in the United States. RESULTS: The overall response rate was 84%. Ninety-two percent of programs reported 24-hour emergency physician-performed ultrasonography availability. Fifty-one percent of programs reported that a credentialing/privileging plan was in place at their hospital, and 71% of programs had a quality assurance/image review procedure in place. Emergency medicine specialty-specific guidelines of 150 ultrasonographic examinations and 40 hours of didactic instruction were met by 39% and 22% of residencies, respectively, although only 13.7% of programs were completing the 300 examinations recommended by the American Institute of Ultrasound in Medicine. Sixteen programs (16%) reported that they were currently billing for emergency physician-performed ultrasonography; of those not billing, 10 (12%) planned to bill within 1 year, and 32 (37%) planned to bill at some point in the future. CONCLUSIONS: Performance and training in emergency physician-performed ultrasonography at academic medical centers continues to increase. The number of emergency medicine residency programs meeting specialty-specific guidelines has more than doubled in the last 4 years, but only a small number are meeting American Institute of Ultrasound in Medicine guidelines. Although only 16% of programs reported that they were currently billing for emergency physician-performed ultrasonography, most had plans to bill in the future.

An evaluation of the dose-response relationship in naturalistic treatment settings using survival analysis.

To date, few studies have been published on the dose-response relationship in psychotherapy. The current study addresses limitations of previous research by using (1) clinical significance methodology to address the meaningfulness of patient change, (2) survival analysis to assess change across time, (3) assessment of patient change on a session-by-session basis, and (4) a large data set representing a variety of treatment settings. A total of 4,761 patients representing standard treatment settings in the United States were tracked at each session of therapy. A survival analysis of this data reveals that between 15 and 19 sessions of therapy are required for a 50% recovery rate using clinical significance methodology. The results of this study provide a useful overview of time-to-change in naturalistic settings that can be used to estimate reliable treatment expectations and as a baseline for comparison when modifications are made within treatment delivery systems.

Seven-year outcomes of patients evaluated for suicidality.

This study assessed the seven-year outcomes of 137 patients who presented with suicidality. Forty-five of the patients were contingently suicidal, that is, they originally presented with suicidal threats designed to gain hospital admission; 92 patients were noncontingently suicidal. Administrative and clinical records were examined for adverse outcomes, and suspicious cases were further investigated. Significant differences were found between the groups in overall mortality and serious suicide attempts. Although no suicides were identified in the contingently suicidal group, ten suicides were confirmed or highly suspected among the noncontingently suicidal patients. This group also had higher overall death rates. These results argue for evaluation of contingency in suicide risk assessments.