Alan J. Poots

A pilot survey of junior doctors’ attitudes and awareness around medication review: time to change our educational approach?

Objectives Our aim was to explore junior doctors’ attitudes and awareness around concepts related to medication review, in order to find ways to change the culture for reviewing, altering and stopping inappropriate or unnecessary medicines. Having already demonstrated the value of team working with senior doctors and pharmacists and the use of a medication review tool, we are now looking to engage first year clinicians and undergraduates in the process. Method An online survey about medication review was distributed among all 42 foundation year one (FY1) doctors at the Chelsea and Westminster Hospital NHS Foundation Trust in November 2014. Descriptive statistics were used for analysis. Results Twenty doctors completed the survey (48%). Of those, 17 believed that it was the pharmacists duty to review medicines; and 15 of 20 stated the general practitioner (GP). Sixteen of 20 stated that they would consult a senior doctor first before stopping medication. Eighteen of 20 considered the GP and consultant to be responsible for alterations, rather than themselves. Sixteen of 20 respondents were not aware of the availability of a medication review tool. Seventeen of 20 felt that more support from senior staff would help them become involved with medication review. Conclusions Junior doctors report feeling uncomfortable altering mediations without consulting a senior first. They appear to be building confidence with prescribing in their first year but not about the medication review process or questioning the drugs already prescribed. Consideration should be given to what we have termed a ‘bottom-up’ educational approach to provide early experience of and change the culture around medication review, to include the education of undergraduate and foundation doctors and pharmacists.

Quantifying the prevalence of frailty in English hospitals

Objectives Population ageing has been associated with an increase in comorbid chronic disease, functional dependence, disability and associated higher health care costs. Frailty Syndromes have been proposed as a way to define this group within older persons. We explore whether frailty syndromes are a reliable methodology to quantify clinically significant frailty within hospital settings, and measure trends and geospatial variation using English secondary care data set Hospital Episode Statistics (HES). Setting National English Secondary Care Administrative Data HES. Participants All 50 540 141 patient spells for patients over 65 years admitted to acute provider hospitals in England (January 2005—March 2013) within HES. Primary and secondary outcome measures We explore the prevalence of Frailty Syndromes as coded by International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) over time, and their geographic distribution across England. We examine national trends for admission spells, inpatient mortality and 30-day readmission. Results A rising trend of admission spells was noted from January 2005 to March 2013(daily average admissions for month rising from over 2000 to over 4000). The overall prevalence of coded frailty is increasing (64 559 spells in January 2005 to 150 085 spells by Jan 2013). The majority of patients had a single frailty syndrome coded (10.2% vs total burden of 13.9%). Cognitive impairment and falls (including significant fracture) are the most common frailty syndromes coded within HES. Geographic variation in frailty burden was in keeping with known distribution of prevalence of the English elderly population and location of National Health Service (NHS) acute provider sites. Overtime, in-hospital mortality has decreased (>65 years) whereas readmission rates have increased (esp.>85 years). Conclusions This study provides a novel methodology to reliably quantify clinically significant frailty. Applications include evaluation of health service improvement over time, risk stratification and optimisation of services.

Mapping mental health service access: achieving equity through quality improvement

BACKGROUND Improving access to psychological therapies (IAPTs) services deliver evidence-based care to people with depression and anxiety. A quality improvement (QI) initiative was undertaken by an IAPT service to improve referrals providing an opportunity to evaluate equitable access. METHODS QI methodologies were used by the clinical team to improve referrals to the service. The collection of geo-coded data allowed referrals to be mapped to small geographical areas according to deprivation. RESULTS A total of 6078 patients were referred to the IAPT service during the period of analysis and mapped to 120 unique lower super output areas (LSOAs). The average weekly referral rate rose from 17 during the baseline phase to 43 during the QI implementation phase. Spatial analysis demonstrated all 15 of the high deprivation/low referral LSOAs were converted to high deprivation/high or medium referral LSOAs following the QI initiative. CONCLUSION This work highlights the importance of QI in developing clinical services aligned to the needs of the population through the analysis of routine data matched to health needs. Mapping can be utilized to communicate complex information to inform the planning and organization of clinical service delivery and evaluate the progress and sustainability of QI initiatives.

Developing and validating a risk prediction model for acute care based on frailty syndromes

Objectives Population ageing may result in increased comorbidity, functional dependence and poor quality of life. Mechanisms and pathophysiology underlying frailty have not been fully elucidated, thus absolute consensus on an operational definition for frailty is lacking. Frailty scores in the acute medical care setting have poor predictive power for clinically relevant outcomes. We explore the utility of frailty syndromes (as recommended by national guidelines) as a risk prediction model for the elderly in the acute care setting. Setting English Secondary Care emergency admissions to National Health Service (NHS) acute providers. Participants There were N=2 099 252 patients over 65 years with emergency admission to NHS acute providers from 01/01/2012 to 31/12/2012 included in the analysis. Primary and secondary outcome measures Outcomes investigated include inpatient mortality, 30-day emergency readmission and institutionalisation. We used pseudorandom numbers to split patients into train (60%) and test (40%). Receiver operator characteristic (ROC) curves and ordering the patients by deciles of predicted risk was used to assess model performance. Using English Hospital Episode Statistics (HES) data, we built multivariable logistic regression models with independent variables based on frailty syndromes (10th revision International Statistical Classification of Diseases, Injuries and Causes of Death (ICD-10) coding), demographics and previous hospital utilisation. Patients included were those >65 years with emergency admission to acute provider in England (2012). Results Frailty syndrome models exhibited ROC scores of 0.624–0.659 for inpatient mortality, 0.63–0.654 for institutionalisation and 0.57–0.63 for 30-day emergency readmission. Conclusions Frailty syndromes are a valid predictor of outcomes relevant to acute care. The models predictive power is in keeping with other scores in the literature, but is a simple, clinically relevant and potentially more acceptable measurement for use in the acute care setting. Predictive powers of the score are not sufficient for clinical use.

Model-driven approach to data collection and reporting for quality improvement

Graphical abstract

Statistical process control for data without inherent order

BackgroundThe XmR chart is a powerful analytical tool in statistical process control (SPC) for detecting special causes of variation in a measure of quality. In this analysis a statistic called the average moving range is used as a measure of dispersion of the data. This approach is correct for data with natural underlying order, such as time series data. There is however conflict in the literature over the appropriateness of the XmR chart to analyse data without an inherent ordering.MethodsWe derive the maxima and minima for the average moving range in data without inherent ordering, and show how to calculate this for any data set. We permute a real world data set and calculate control limits based on these extrema.ResultsIn the real world data set, permuting the order of the data affected an absolute difference of 109 percent in the width of the control limits.DiscussionWe prove quantitatively that XmR chart analysis is problematic for data without an inherent ordering, and using real-world data, demonstrate the problem this causes for calculating control limits. The resulting ambiguity in the analysis renders it unacceptable as an approach to making decisions based on data without inherent order.ConclusionThe XmR chart should only be used for data endowed with an inherent ordering, such as a time series. To detect special causes of variation in data without an inherent ordering we suggest that one of the many well-established approaches to outlier analysis should be adopted. Furthermore we recommend that in all SPC analyses authors should consistently report the type of control chart used, including the measure of variation used in calculating control limits.

Improving mental health outcomes: achieving equity through quality improvement

Objective To investigate equity of patient outcomes in a psychological therapy service, following increased access achieved by a quality improvement (QI) initiative. Design Retrospective service evaluation of health outcomes; data analysed by ANOVA, chi-squared and Statistical Process Control. Setting A psychological therapy service in Westminster, London, UK. Participants People living in the Borough of Westminster, London, attending the service (from either healthcare professional or self-referral) between February 2009 and May 2012. Intervention(s) Social marketing interventions were used to increase referrals, including the promotion of the service through local media and through existing social networks. Main Outcome Measure(s) (i) Severity of depression on entry using Patient Health Questionnaire-9 (PHQ9). (ii) Changes to severity of depression following treatment (ΔPHQ9). (iii) Changes in attainment of a meaningful improvement in condition assessed by a key performance indicator. Results Patients from areas of high deprivation entered the service with more severe depression (M = 15.47, SD = 6.75), compared with patients from areas of low (M = 13.20, SD = 6.75) and medium (M = 14.44, SD = 6.64) deprivation. Patients in low, medium and high deprivation areas attained similar changes in depression score (ΔPHQ9: M = −6.60, SD = 6.41). Similar proportions of patients achieved the key performance indicator across initiative phase and deprivation categories. Conclusions QI methods improved access to mental health services; this paper finds no evidence for differences in clinical outcomes in patients, regardless of level of deprivation, interpreted as no evidence of inequity in the service with respect to this outcome.

Acceptability and necessity of HIV and other blood-borne virus testing in a psychiatric setting

Studies in North America and Europe indicate that the prevalence of blood-borne viruses (BBVs) is elevated in individuals with severe mental illness; there are no comparable data for the UK. We offered routine testing for HIV, and hepatitis B and C in an inner-London in-patient psychiatric unit as a service improvement. Of the patients approached 83% had mental capacity to provide informed consent for testing and 66% of patients offered testing accepted. Although it was not our objective to establish the prevalence of BBVs, 18% of patients had serological evidence of a current or previous BBV infection. We found that offering routine testing in an in-patient psychiatric setting is both practical and acceptable to patients.

The impact of changing the 4 h emergency access standard on patient waiting times in emergency departments in England

Objective To determine whether the process of emergency care waiting in England has changed following the modification of the operational standard for the 4 h waiting time target from 98% to 95% in June 2010. Design Retrospective analysis of publicly available ‘total time spent in accident and emergency’ data from Department of Health. Setting and participants Patients attending emergency departments (EDs) in England between October 2002 and September 2011. In 2005, the government set an operational standard that 98% of patients should wait <4 h in ED. In June 2010, the government announced that the operating standard would change to 95% immediately. Outcome measures Percentage of patients waiting <4 h (weekly and quarterly), and total number of patients waiting >4 h. Results The average percentage of patients waiting <4 h fell from 98% to 95% almost immediately following the operational standard change. Consequently, between October 2010 and September 2011, approximately 383 000 additional patients in England EDs waited in excess of 4 h than had the 98% standard been attained. The emergency care system appears to have been stabilised at this new level. Conclusions The policy change for waiting times in EDs in England has resulted in the process of emergency care in England adjusting to the new operational standard of 95% of patients waiting <4 h. As a result, more patients are waiting >4 h to receive the care they need; consequently, outcomes are likely to suffer.

A retrospective observational analysis to identify patient and treatment-related predictors of outcomes in a community mental health programme

Objectives This study aims to identify patient and treatment factors that affect clinical outcomes of community psychological therapy through the development of a predictive model using historic data from 2 services in London. In addition, the study aims to assess the completeness of data collection, explore how treatment outcomes are discriminated using current criteria for classifying recovery, and assess the feasibility and need for undertaking a future larger population analysis. Design Observational, retrospective discriminant analysis. Setting 2 London community mental health services that provide psychological therapies for common mental disorders including anxiety and depression. Participants A total of 7388 patients attended the services between February 2009 and May 2012, of which 4393 (59%) completed therapy, or there was an agreement to end therapy, and were included in the study. Primary and secondary outcome measures Different combinations of the clinical outcome scores for anxiety Generalised Anxiety Disorder-7 and depression Patient Health Questionnaire-9 were used to construct different treatment outcomes. Results The predictive models were able to assign a positive or negative clinical outcome to each patient based on 5 independent pre-treatment variables, with an accuracy of 69.4% and 79.3%, respectively: initial severity of anxiety and depression, ethnicity, deprivation and gender. The number of sessions attended/missed were also important factors identified in recovery. Conclusions Predicting whether patients are likely to have a positive outcome following treatment at entry might allow suitable modification of scheduled treatment, possibly resulting in improvements in outcomes. The model also highlights factors not only associated with poorer outcomes but inextricably linked to prevalence of common mental disorders, emphasising the importance of social determinants not only in poor health but also poor recovery.