“It’s hard to tell”. The challenges of scoring patients on standardised outcome measures by multidisciplinary teams: a case study of Neurorehabilitation

Background Interest is increasing in the application of standardised outcome measures in clinical practice. Measures designed for use in research may not be sufficiently precise to be used in monitoring individual patients. However, little is known about how clinicians and in particular, multidisciplinary teams, score patients using these measures. This paper explores the challenges faced by multidisciplinary teams in allocating scores on standardised outcome measures in clinical practice. Methods Qualitative case study of an inpatient neurorehabilitation team who routinely collected standardised outcome measures on their patients. Data were collected using non participant observation, fieldnotes and tape recordings of 16 multidisciplinary team meetings during which the measures were recited and scored. Eleven clinicians from a range of different professions were also interviewed. Data were analysed used grounded theory techniques. Results We identified a number of instances where scoring the patient was 'problematic'. In 'problematic' scoring, the scores were uncertain and subject to revision and adjustment. They sometimes required negotiation to agree on a shared understanding of concepts to be measured and the guidelines for scoring. Several factors gave rise to this problematic scoring. Team members' knowledge about patients' problems changed over time so that initial scores had to be revised or dismissed, creating an impression of deterioration when none had occurred. Patients had complex problems which could not easily be distinguished from each other and patients themselves varied in their ability to perform tasks over time and across different settings. Team members from different professions worked with patients in different ways and had different perspectives on patients' problems. This was particularly an issue in the scoring of concepts such as anxiety, depression, orientation, social integration and cognitive problems. Conclusion From a psychometric perspective these problems would raise questions about the validity, reliability and responsiveness of the scores. However, from a clinical perspective, such characteristics are an inherent part of clinical judgement and reasoning. It is important to highlight the challenges faced by multidisciplinary teams in scoring patients on standardised outcome measures but it would be unwarranted to conclude that such challenges imply that these measures should not be used in clinical practice for decision making about individual patients. However, our findings do raise some concerns about the use of such measures for performance management

Quality assurance in psychiatry: quality indicators and guideline implementation

In many occasions, routine mental health care does not correspond to the standards that the medical profession itself puts forward. Hope exists to improve the outcome of severe mental illness by improving the quality of mental health care and by implementing evidence-based consensus guidelines. Adherence to guideline recommendations should reduce costly complications and unnecessary procedures. To measure the quality of mental health care and disease outcome reliably and validly, quality indicators have to be available. These indicators of process and outcome quality should be easily measurable with routine data, should have a strong evidence base, and should be able to describe quality aspects across all sectors over the whole disease course. Measurement-based quality improvement will not be successful when it results in overwhelming documentation reducing the time for clinicians for active treatment interventions. To overcome difficulties in the implementation guidelines and to reduce guideline non-adherence, guideline implementation and quality assurance should be embedded in a complex programme consisting of multifaceted interventions using specific psychological methods for implementation, consultation by experts, and reimbursement of documentation efforts. There are a number of challenges to select appropriate quality indicators in order to allow a fair comparison across different approaches of care. Carefully used, the use of quality indicators and improved guideline adherence can address suboptimal clinical outcomes, reduce practice variations, and narrow the gap between optimal and routine care

Predicting Return to Work in Workers with All-Cause Sickness Absence Greater than 4 Weeks: A Prospective Cohort Study

Introduction Long-term sickness absence is a major public health and economic problem. Evidence is lacking for factors that are associated with return to work (RTW) in sick-listed workers. The aim of this study is to examine factors associated with the duration until full RTW in workers sick-listed due to any cause for at least 4 weeks. Methods In this cohort study, health-related, personal and job-related factors were measured at entry into the study. Workers were followed until 1 year after the start of sickness absence to determine the duration until full RTW. Cox proportional hazards regression analyses were used to calculate hazard ratios (HR). Results Data were collected from N = 730 workers. During the first year after the start of sickness absence, 71% of the workers had full RTW, 9.1% was censored because they resigned, and 19.9% did not have full RTW. High physical job demands (HR .562, CI .348–.908), contact with medical specialists (HR .691, CI .560–.854), high physical symptoms (HR .744, CI .583–.950), moderate to severe depressive symptoms (HR .748, CI .569–.984) and older age (HR .776, CI .628–.958) were associated with a longer duration until RTW in sick-listed workers. Conclusions Sick-listed workers with older age, moderate to severe depressive symptoms, high physical symptoms, high physical job demands and contact with medical specialists are at increased risk for a longer duration of sickness absence. OPs need to be aware of these factors to identify workers who will most likely benefit from an early intervention

Effect of tube diameter and capillary number on platelet margination and near-wall dynamics

The effect of tube diameter $D$ and capillary number $Ca$ on platelet margination in blood flow at $\approx 37\%$ tube haematocrit is investigated. The system is modelled as three-dimensional suspension of deformable red blood cells and nearly rigid platelets using a combination of the lattice-Boltzmann, immersed boundary and finite element methods. Results show that margination is facilitated by a non-diffusive radial platelet transport. This effect is important near the edge of the cell-free layer, but it is only observed for $Ca > 0.2$, when red blood cells are tank-treading rather than tumbling. It is also shown that platelet trapping in the cell-free layer is reversible for $Ca \leq 0.2$. Only for the smallest investigated tube ($D = 10 \mu\text{m}$) margination is essentially independent of $Ca$. Once platelets have reached the cell-free layer, they tend to slide rather than tumble. The tumbling rate is essentially independent of $Ca$ but increases with $D$. Tumbling is suppressed by the strong confinement due to the relatively small cell-free layer thickness at $\approx 37\%$ tube haematocrit.Comment: 16 pages, 10 figure

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe