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The Met Office in the United Kingdom has developed a completely new probabilistic postprocessing system called IMPROVER to operate on outputs from its operational numerical weather prediction (NWP) forecasts and precipitation nowcasts. The aim is to improve weather forecast information to the public and other stakeholders while better exploiting the current and future generations of underpinning kilometer-scale NWP ensembles. We wish to provide seamless forecasts from nowcasting to medium range, provide consistency between gridded and site-specific forecasts, and be able to verify every stage of the processing. The software is written in a modern modular framework that is easy to maintain, develop, and share. IMPROVER allows forecast information to be provided with greater spatial and temporal detail and a faster update frequency than previous postprocessing. Independent probabilistic processing chains are constructed for each meteorological variable consisting of a series of processing stages that operate on predefined grids and blend outputs from several NWP inputs to give a frequently updated, probabilistic forecast solution. Probabilistic information is produced as standard, with the option of extracting a most likely or yes–no outcome if required. Verification can be performed at all stages, although it is only currently switched on for the most significant stages when run in real time. IMPROVER has been producing real-time output since March 2021 and became operational in spring 2022.

Background: Major depression is found in around ten percent of patients attending cancer clinics. One of the symptoms of major depression, defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM), is ‘thoughts of death or suicide’. In order to implement depression screening programs for patients with cancer, we need to know the prevalence not only of this broadly defined symptom, but also of more specific suicidal thoughts, as only the latter clearly indicates the need for specialist psychiatric assessment and management of suicide risk. Methods: We analyzed data from a routine two-stage depression screening program that operated in three UK cancer centers, linked with demographic and clinical data obtained from a national cancer registry. We included data on 2,217 patients with common cancers and comorbid, interview-diagnosed, major depression. We determined the percentage of patients with: (a) the DSM-IV symptom ‘thoughts of death or suicide’ and (b) suicidal thoughts, defined as an affirmative response to the question ‘have you had thoughts of ending your life?’ We investigated the associations of patients’ demographic and clinical characteristics with each of these using logistic regression models. Results: We found that 29% (641/2,217) of patients had the DSM symptom ‘thoughts of death or suicide’ and 9% (207/2,217) had suicidal thoughts. Of the demographic and clinical characteristics that we studied, none had statistically significant associations with having the DSM symptom. Only younger age and primary cancer were associated with having suicidal thoughts. Conclusions: We found that almost one third of patients with cancer and comorbid major depression, have the DSM symptom ‘thoughts of death or suicide’. However, only a third of the patients with this symptom report suicidal thoughts. These findings suggest that around one in ten patients found by a screening program to have major depression will have suicidal thoughts requiring a psychiatric assessment. The staffing of depression screening programs should be designed with these data in mind.

Objective To systematically review randomized trials of the effectiveness of inpatient Consultation-Liaison (C-L) Psychiatry service models in improving patient outcomes, reducing length of hospital stay and decreasing healthcare costs. Method We searched databases including Ovid Medline, Ovid Embase, Ovid PsycINFO and EBSCO CINAHL for relevant trials. Two independent reviewers assessed articles and extracted data. The review is registered with PROSPERO, number CRD42019120827. Results Eight trials were eligible for inclusion. All had methodological limitations and all were published more than ten years ago. None reported clear evidence that the C-L Psychiatry service model evaluated was more effective than usual medical care alone. All the service models tested focused on providing a consultation for patients identified by screening. Clinical heterogeneity precluded meta-analysis. Conclusion Whilst we found no evidence that any of the inpatient C-L Psychiatry service models evaluated is effective, the sparseness of the literature and its methodological limitations preclude strong conclusions. The trials do, however, suggest that purely consultation-based service models may not be effective. A new generation of robust clinical trials of a wider range of C-L Psychiatry service models is now required to inform future service developments.

Objectives: To describe the implementation of a collaborative care (CC) screening and treatment program for major depression in people with cancer, found to be effective in clinical trials, into routine outpatient care of a cancer center. Method: A mixed-methods observational study guided by the RE-AIM implementation framework using quantitative and qualitative data collected over five years. Results: Program set-up took three years and required more involvement of CC experts than anticipated. Barriers to implementation were uncertainty about whether oncology or psychiatry owned the program and the hospital's organizational complexity. Selecting and training CC team members was a major task. 90% (14,412/16,074) of patients participated in depression screening and 61% (136/224) of those offered treatment attended at least one session. Depression outcomes were similar to trial benchmarks (61%; 78/127 patients had a treatment response). After two years the program obtained long-term funding. Facilitators of implementation were strong trial evidence, effective integration into cancer care and ongoing clinical and managerial support. Conclusion: A CC program for major depression, designed for the cancer setting, can be successfully implemented into routine care, but requires time, persistence and involvement of CC experts. Once operating it can be an effective and valued component of medical care.

Objective To describe a new service model for the psychiatric care of general hospital inpatients, called Proactive Integrated Consultation-Liaison Psychiatry (‘Proactive Integrated Psychological Medicine’ in the UK). Method The new service model was developed especially for general hospital inpatient populations with multimorbidity, such as older medical inpatients. Its design was informed by the published literature and the clinical experience of C-L psychiatrists. It was operationalized by a process of iterative piloting. Results The rationale for the new model and the principles underpinning it are outlined. Details of how to implement it, including a service manual and associated workbook, are provided. The training of clinicians to deliver it is described. The effectiveness and cost-effectiveness of this new service model is being evaluated. Whilst we have found it feasible to deliver and well-accepted by ward teams, potential challenges to its wider implementation are discussed. Conclusion Proactive Integrated Consultation-Liaison Psychiatry (PICLP) is a fusion of proactive consultation and integrated care, operationalized in a field-tested service manual. Initial experience indicates that it is feasible to deliver. Its effectiveness and cost effectiveness for older patients on acute medical wards is currently being evaluated in a large multicentre randomized controlled trial (The HOME Study).

Background The impact of COVID-19 on physical and mental health and employment after hospitalisation with acute disease is not well understood. The aim of this study was to determine the effects of COVID-19-related hospitalisation on health and employment, to identify factors associated with recovery, and to describe recovery phenotypes. Methods The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a multicentre, long-term follow-up study of adults (aged ≥18 years) discharged from hospital in the UK with a clinical diagnosis of COVID-19, involving an assessment between 2 and 7 months after discharge, including detailed recording of symptoms, and physiological and biochemical testing. Multivariable logistic regression was done for the primary outcome of patient-perceived recovery, with age, sex, ethnicity, body-mass index, comorbidities, and severity of acute illness as covariates. A post-hoc cluster analysis of outcomes for breathlessness, fatigue, mental health, cognitive impairment, and physical performance was done using the clustering large applications k-medoids approach. The study is registered on the ISRCTN Registry (ISRCTN10980107). Findings We report findings for 1077 patients discharged from hospital between March 5 and Nov 30, 2020, who underwent assessment at a median of 5·9 months (IQR 4·9–6·5) after discharge. Participants had a mean age of 58 years (SD 13); 384 (36%) were female, 710 (69%) were of white ethnicity, 288 (27%) had received mechanical ventilation, and 540 (50%) had at least two comorbidities. At follow-up, only 239 (29%) of 830 participants felt fully recovered, 158 (20%) of 806 had a new disability (assessed by the Washington Group Short Set on Functioning), and 124 (19%) of 641 experienced a health-related change in occupation. Factors associated with not recovering were female sex, middle age (40–59 years), two or more comorbidities, and more severe acute illness. The magnitude of the persistent health burden was substantial but only weakly associated with the severity of acute illness. Four clusters were identified with different severities of mental and physical health impairment (n=767): very severe (131 patients, 17%), severe (159, 21%), moderate along with cognitive impairment (127, 17%), and mild (350, 46%). Of the outcomes used in the cluster analysis, all were closely related except for cognitive impairment. Three (3%) of 113 patients in the very severe cluster, nine (7%) of 129 in the severe cluster, 36 (36%) of 99 in the moderate cluster, and 114 (43%) of 267 in the mild cluster reported feeling fully recovered. Persistently elevated serum C-reactive protein was positively associated with cluster severity. Interpretation We identified factors related to not recovering after hospital admission with COVID-19 at 6 months after discharge (eg, female sex, middle age, two or more comorbidities, and more acute severe illness), and four different recovery phenotypes. The severity of physical and mental health impairments were closely related, whereas cognitive health impairments were independent. In clinical care, a proactive approach is needed across the acute severity spectrum, with interdisciplinary working, wide access to COVID-19 holistic clinical services, and the potential to stratify care. Funding UK Research and Innovation and National Institute for Health Research.

Objective To determine the prevalence of anxiety in general hospital inpatients by conducting a systematic review and meta-analysis of all relevant published studies. Method We searched Ovid Medline, Ovid Embase and Ovid PsycINFO from inception to December 2020. We included studies of the prevalence of anxiety symptoms of clinically significant severity (using cut-off scores on rating scales) and of the prevalence of anxiety disorders (using diagnostic interviews) in general hospital inpatients. Two independent reviewers assessed articles and extracted data. The review is registered with PROSPERO, number CRD42020189722. Results We included 32 studies. Pooled prevalence estimates in random-effects meta-analyses were: anxiety symptoms 28% (95% CI 19% to 38%, 95% prediction interval 5% to 72%), any anxiety disorder 8% (95% CI 5% to 12%, 95% prediction interval 2% to 33%), panic disorder 3% (95% CI 2% to 4%, 95% prediction interval 1% to 8%), generalized anxiety disorder 5% (95% CI 3% to 8%, 95% prediction interval 1% to 23%). There was high heterogeneity in prevalence, little of which was explained in exploratory analyses of a limited number of potential determinants. Conclusion Anxiety symptoms of clinically significant severity affect more than one in four inpatients and anxiety disorders affect nearly one in ten.

The aurora is a readily visible phenomenon of interest to many members of the public. However, the aurora and associated phenomena can also significantly impact communications, ground-based infrastructure, and high-altitude radiation exposure. Forecasting the location of the auroral oval is therefore a key component of space weather forecast operations. A version of the OVATION-Prime 2013 auroral precipitation model (Newell et al., 2014, https://doi.org/10.1002/2014sw001056) was used by the UK Met Office Space Weather Operations Centre (MOSWOC). The operational implementation of the OVATION-Prime 2013 model at the UK Met Office delivered a 30-min forecast of the location of the auroral oval and the probability of observing the aurora. Using weather forecast evaluation techniques, we evaluate the ability of the OVATION-Prime 2013 model forecasts to predict the location and probability of the aurora occurring by comparing the forecasts with auroral boundaries determined from data from the IMAGE satellite between 2000 and 2002. Our analysis shows that the operational model performs well at predicting the location of the auroral oval, with a relative operating characteristic (ROC) score of 0.82. The model performance is reduced in the dayside local time sectors (ROC score = 0.59) and during periods of higher geomagnetic activity (ROC score of 0.55 for Kp = 8). As a probabilistic forecast, OVATION-Prime 2013 tends to underpredict the occurrence of aurora by a factor of 1.1–6, while probabilities of over 90% are overpredicted.

The UK Inshore Waters Forecast predicts wind speeds, sea states, weather conditions and visibilities for marine areas within 12 nautical miles of the UK coast. In addition to the now-common web-based outlets of most public forecast products, this very high profile forecast product is also broadcast by the BBC on national radio and television. It is the enviable task of Operational Meteorologists, based at UK Met Office sites in Exeter and Aberdeen, to issue these forecasts every six hours for the vitally important purpose of protecting lives in the coastal waters surrounding the UK. Currently, the production process involves a marine forecaster comprehensively inspecting deterministic model fields, prior to manual text generation. However, direct utilisation of an ensemble model-based product has the potential to make this task considerably more efficient and possibly make the forecast more accurate.Raw output from the Met Office Global and Regional Ensemble Prediction System (MOGREPS) is used routinely throughout the Met Office to assist forecasters. Furthermore, a recent project to develop and improve the techniques used to statistically post-process this data (IMPROVER) is now employed to further reduce identified errors within MOGREPS data.This session describes the latest work to exploit both raw MOGREPS and post-processed data for the generation of the wind component to the Inshore Waters Forecast. This component is verified against post-processed nowcast analysis fields to determine its accuracy and the results are compared against the equivalent performance currently achieved by Operational Maritime Meteorologists. The outcome of this assessment will help to determine whether either of these data-sources are suitable as a guide for the production of this high-profile forecast product.

The UK Met Office manages its commitment to the public through the Public Weather Service and an important factor in public safety and concern is extreme weather events. Therefore, a new Key Performance Indicator is being introduced, related to the ability with which extreme events are correctly identified. The Threshold Weighted Continuous Ranked Probability Score (twCRPS) is used to make this assessment by determining how well site-specific Met Office ensemble-based probabilistic forecast solutions predict relative-extreme events. The threshold weighted version of the Mean Absolute Error (twMAE) is the deterministic equivalent to the twCRPS. The twMAE is used for the assessment of the deterministic model output that currently appears on the Met Office App and website.Gridded numerical ensemble model data is generated by MOGREPS (the Met Office Global and Regional Ensemble Prediction System). A new program of post-processing work has been undertaken in recent years (IMPROVER) to replace the system of post-processing currently employed by the Met Office. IMPROVER applies a series of post-processing steps to generate both probabilistic and deterministic forecasts and site-specific data is generated from these model fields. Verification of the model output is undertaken at each post-processing stage to ensure that every step is having the expected impact on the performance of the model. To date however, these assessments have concentrated on the performance of more typical conditions rather than the ability with which more extreme events are identified.This session outlines very recent work to assess the ability with which raw MOGREPS data and data generated by various of the post-processing stages of IMPROVER, predict relative-extreme events at observation sites throughout the UK. The twMAE and twCRPS are used for this assessment, where in both cases, the threshold weighting function is defined in terms of a distribution formed by sampling the numerical value corresponding to a chosen relatively extreme percentile from the observed 30-year climatology of each UK site.

Background Prolonged acute hospital stays are a major problem for older people and for health services. Failure to effectively manage the psychological and social aspects of illness is an important cause of prolonged hospital stays. Proactive Psychological Medicine (PPM) is a new way of providing psychiatry services to medical wards. PPM is proactive, focussed, intensive and integrated with medical care. A major aim of PPM is to reduce the time older people spend in hospital because of unmanaged psychological and social problems. The HOME Study will test the effectiveness and cost-effectiveness of PPM. Methods/design A two-arm parallel-group randomised controlled superiority trial, with a linked health economic analysis and an embedded process evaluation, will be conducted at three sites. A total of 3588 participants will be recruited and randomised to usual care or usual care plus PPM. The primary outcome is the number of days spent as an inpatient in a general hospital in the month (30 days) post-randomisation. Secondary outcomes for each participant (measured at 1 and 3 months) include quality of life, independent functioning, symptoms of anxiety and depression, cognitive function, and their experience of the hospital stay. Discussion The trial has been designed to produce findings that are generalisable to all older medical inpatients (including those with cognitive impairment). It will provide information on the effectiveness and cost-effectiveness of PPM, which we hope will be of value to patients, clinicians, managers and service planners. Trial registration ISRCTN86120296. Registered on 3 January 2018. Electronic supplementary material The online version of this article (10.1186/s13063-019-3502-5) contains supplementary material, which is available to authorized users.

The full range of ensemble forecast members, expressed in percentile format, can give additional valuable information to users compared to a deterministic solution. This study contains the first rigorous assessment of the operational U.K. site-specific percentile forecast generated by the Met Office. Maximum meteorological summer daytime temperature forecasts issued between 2014 and 2016 are analyzed using the ranked probability score (RPS), ranked probability skill score (RPSS), categorized mean squared error (MSE), quantile skill score (QSS), and relative economic value (REV). Site-specific observed climatology is used to define the temperature threshold for each category (where applicable) thereby ensuring identical categorical event base rates across all 99 sites considered. Forecast ranges between 6 and 120 h are assessed, with the RPS decomposition indicating no perceivable change in the reliability yet an almost linear decrease with forecast range solely due to a near-linear increase in the resolution. Using the categorized MSE (the deterministic equivalent to the RPS), the probabilistic forecast is shown to possess more skill than its deterministic counterpart and the disparity between these scores increases with the forecast range. This finding is reinforced by a REV assessment; this indicates that the economic value associated with the probabilistic envelope is greater than that associated with the deterministic solution at the majority of cost–loss ratios. The QSS appears to be well correlated with the RPSS (rs = 0.852 at T + 24) and identifies the outlying quantiles of the probabilistic forecast as being the least skillful.

OBJECTIVE: The question of whether depression is associated with worse survival in people with cancer remains unanswered because of methodological criticism of the published research on the topic. We aimed to study the association in a large methodologically robust study. METHODS: We analyzed data on 20,582 patients with breast, colorectal, gynecological, lung, and prostate cancers who had attended cancer outpatient clinics in Scotland, United Kingdom. Patients had completed two-stage screening for major depression as part of their cancer care. These data on depression status were linked to demographic, cancer, and subsequent mortality data from national databases. We estimated the association of major depression with survival for each cancer using Cox regression. We adjusted for potential confounders and interactions between potentially time-varying confounders and the interval between cancer diagnosis and depression screening, and used multiple imputation for missing depression and confounder data. We pooled the cancer-specific results using fixed-effects meta-analysis. RESULTS: Major depression was associated with worse survival for all cancers, with similar adjusted hazard ratios (HRs): breast cancer (HR = 1.42, 95% confidence interval [CI] = 1.15-1.75), colorectal cancer (HR = 1.47, 95% CI = 1.11-1.94), gynecological cancer (HR = 1.36, 95% CI = 1.08-1.71), lung cancer (HR = 1.39, 95% CI = 1.24-1.56), and prostate cancer (HR = 1.76, 95% CI = 1.08-2.85). The pooled HR was 1.41 (95% CI = 1.29-1.54, p < .001, I2 = 0%). These findings were not materially different when we only considered the deaths (90%) that were attributed to cancer. CONCLUSIONS: Major depression is associated with worse survival in patients with common cancers. The mechanisms of this association and the clinical implications require further study.

BACKGROUND: The indirect impact of the COVID-19 pandemic on cancer outcomes is of increasing concern. However, the extent to which key treatment modalities have been affected is unclear. We aimed to assess the impact of the pandemic on radiotherapy activity in England. METHODS: In this population-based study, data relating to all radiotherapy delivered for cancer in the English NHS, between Feb 4, 2019, and June 28, 2020, were extracted from the National Radiotherapy Dataset. Changes in mean weekly radiotherapy courses, attendances (reflecting fractions), and fractionation patterns following the start of the UK lockdown were compared with corresponding months in 2019 overall, for specific diagnoses, and across age groups. The significance of changes in radiotherapy activity during lockdown was examined using interrupted time-series (ITS) analysis. FINDINGS: In 2020, mean weekly radiotherapy courses fell by 19·9% in April, 6·2% in May, and 11·6% in June compared with corresponding months in 2019. A relatively greater fall was observed for attendances (29·1% in April, 31·4% in May, and 31·5% in June). These changes were significant on ITS analysis (p

This chapter describes how the collaborative care model can be used to integrate psychosocial care into cancer care. It also describes the evolution of, and evidence for, the collaborative care approach in cancer services. Collaborative care consists of systematic identification of need, integrated delivery of psychosocial care by care managers with specialist supervision, and the stepping up of care based on the systematic measurement of outcomes. Trials of this approach for the management of depression and pain in patients with cancer have found it to be feasible to deliver, effective in improving outcomes, and cost-effective. The chapter describes how to overcome patient, provider, and institutional challenges in providing psychosocial care in diverse oncology settings. It concludes by proposing practical steps for implementing and sustaining an integrated psychosocial oncology service based on the principles of collaborative care.

Background Prolonged acute hospital stays are a problem for older people and for health services. Failure to effectively manage the psychological and social aspects of illness is an important cause of prolonged hospital stay. Proactive Psychological Medicine (PPM) is a new way of providing psychiatry services to medical wards which is proactive, focussed, intensive and integrated with medical care. The primary aim of PPM is to reduce the time older people spend in hospital because of unmanaged psychological and social problems. The HOME Study will test the effectiveness and cost-effectiveness of PPM. Methods/design The study is a two-arm, parallel-group, randomised, controlled superiority trial with linked health economic analysis and an embedded process evaluation. The target population is people aged 65 years and older admitted to acute hospitals. Participants will be randomly allocated to either usual care plus PPM or usual care alone. The primary outcome is the number of days spent as an inpatient in a general hospital in the month following randomisation. Secondary outcomes include quality of life, cognitive function, independent functioning, symptoms of anxiety and depression, and experience of hospital stay. The cost-effectiveness of usual care plus PPM compared with usual care alone will be assessed using quality-adjusted life-years as an outcome as well as costs from the NHS perspective. Discussion This update to the published trial protocol gives a detailed plan of the statistical and economic analysis of The HOME Study. Trial registration ISRCTN registry, ISRCTN86120296. Registered on 3 January 2018.

Objective Depression and anxiety have both been reported to predict worse subsequent survival in people with cancer. However, depression and anxiety are mutually associated and we lack understanding of their independent associations with survival. We therefore aimed to investigate these in a large sample of patients with common cancers. Methods We analysed data on 19,966 patients with common cancers (breast, colorectal, gynaecological, lung and prostate) who had attended specialist NHS outpatient clinics in Scotland, UK. Hospital Anxiety and Depression Scale (HADS) data were linked with demographic, cancer and mortality data. We estimated the independent associations of depression (HADS depression score) and anxiety (HADS anxiety score) with survival by fitting (separately for each cancer) Cox proportional hazards models which incorporated cubic splines to allow for non-linear associations. We also adjusted for potential confounders. Results The median time from HADS completion to death or censoring was 1.9 years. Greater depression was found to be strongly associated with worse survival from all cancers. When adjusted for anxiety, this association remained in males and increased in females. Greater anxiety was also associated with worse survival in nearly all cancers. However, when adjusted for depression, the association of anxiety with worse survival was lost. In females the association reversed direction so that greater anxiety was associated with better survival. Conclusion Although often considered together as aspects of ‘emotional distress’, depression and anxiety have different independent associations with survival in patients with cancer and should therefore be considered separately.

Objectives Validated diagnostic interviews are required to classify depression status and estimate prevalence of disorder, but screening tools are often used instead. We used individual participant data meta-analysis to compare prevalence based on standard Hospital Anxiety and Depression Scale – depression subscale (HADS-D) cutoffs of ≥8 and ≥11 versus Structured Clinical Interview for DSM (SCID) major depression and determined if an alternative HADS-D cutoff could more accurately estimate prevalence. Methods We searched Medline, Medline In-Process & Other Non-Indexed Citations via Ovid, PsycINFO, and Web of Science (inception-July 11, 2016) for studies comparing HADS-D scores to SCID major depression status. Pooled prevalence and pooled differences in prevalence for HADS-D cutoffs versus SCID major depression were estimated. Results 6005 participants (689 SCID major depression cases) from 41 primary studies were included. Pooled prevalence was 24.5% (95% Confidence Interval (CI): 20.5%, 29.0%) for HADS-D ≥8, 10.7% (95% CI: 8.3%, 13.8%) for HADS-D ≥11, and 11.6% (95% CI: 9.2%, 14.6%) for SCID major depression. HADS-D ≥11 was closest to SCID major depression prevalence, but the 95% prediction interval for the difference that could be expected for HADS-D ≥11 versus SCID in a new study was −21.1% to 19.5%. Conclusions HADS-D ≥8 substantially overestimates depression prevalence. Of all possible cutoff thresholds, HADS-D ≥11 was closest to the SCID, but there was substantial heterogeneity in the difference between HADS-D ≥11 and SCID-based estimates. HADS-D should not be used as a substitute for a validated diagnostic interview.

Physical symptoms are not always associated with disease. In secondary medical care as many as a third of patients present with symptoms unexplained by disease. Such ‘medically unexplained symptoms’ pose a challenge for clinical services that focus on identifying and treating disease. The principles of effective management are to: (a) avoid overinvestigation and giving speculative treatment for disease; (b) take a positive approach with the patient, accepting the reality of the symptoms while explaining clearly that they do not indicate disease; (c) identify and provide treatment for associated depression and anxiety disorders; (d) refer for psychiatric or psychological treatment when required. Complex cases with multiple persistent medically unexplained symptoms are at particular risk of iatrogenic harm and require active multidisciplinary management. Psychological treatments such as cognitive behaviour therapy may be effective.

All physicians experience situations in which they need the knowledge, skills, and attitudes commonly thought of as belonging to psychiatry. This section of the book aims to help physicians to acquire these. It includes: (1) guidance on how to assess medical patients for psychiatric illness; (2) information about psychiatric presentations and the differential diagnoses most relevant to general medical practice; (3) brief reviews of the psychiatric disorders most commonly seen in general medical practice and the practical management of these; (4) guidance on the use of psychotropic drugs and psychological treatments when given as part of general medical care; (5) evidence-based strategies for helping patients who are smoking, using alcohol excessively, or who are overweight.

Conversion disorder (now also called functional neurological symptom disorder) describes symptoms (of motor and sensory dysfunction such as limb weakness, tremor, visual loss, with or without ‘blackouts’), which can be positively identified as being inconsistent with neurological disease. The disorder is common in neurological services and frequently seen by psychiatrists working in such settings. It is often associated with chronic severe disability. The diagnosis previously hinged on the neurologist’s demonstration of the lack of disease and the psychiatrist’s hypothesis of a ‘conversion’ of stress into a physical symptom. It is now based on positive findings on neurological assessment supplemented by a psychiatric assessment to confirm the diagnosis. Comorbid anxiety and depression disorders are common. Treatment is multi-disciplinary. Explanation of the condition to the patient is a crucial initial step supplemented, where necessary, by psychological treatment (especially for dissociative or non-epileptic attacks) and physiotherapy for functional motor symptoms. The prognosis without treatment is poor once the disability is established.

Psychiatry first developed as a separate medical specialty about 150 years ago when physicians were recruited to staff the new lunatic asylums. It later embraced psychotherapy and more recently has adopted community rather than hospital-based working. The fact that psychiatry remains largely separate from other areas of medicine, together with the increasing focus on technical procedures in medicine, has led to sometimes inadequate psychiatric care for medical patients. Measures to address this shortcoming began 50 years ago with the ad hoc development of liaison psychiatry teams, providing in-reach psychiatric services from mental hospitals to general hospitals. A more recent innovation is to reintegrate psychiatrists into medical teams as specialists in psychological medicine to provide joined up medical and psychiatric care.

Somatic symptom disorder is a diagnosis for patients who have marked concern about physical symptoms that appears to be disproportionate to the severity of any associated disease. In conversion disorder the patient’s symptom is loss of a function, such as movement of a limb. This does not mean that the symptoms are not real. Somatic symptom disorder incorporates the older diagnoses of somatoform disorder, somatization disorder, Briquet’s syndrome, and hypochondriasis. Somatic symptom disorder of mild severity is common in medical clinics; it usually responds to simple explanation and reassurance. More severe somatic symptom disorder with multiple symptoms and severe disability is less common, but important to diagnose because these patients are at substantial risk of iatrogenic harm from excessive investigation and speculative medical or surgical treatment. Severe somatic symptom disorder usually requires multidisciplinary care, including liaison psychiatry.

Medically ill patients often have psychiatric illness. Physicians can and should detect and diagnose these illnesses during their standard medical assessment. All that is required is knowledge of key questions to ask patients, awareness of the clinical signs that may be observed, and an appreciation of the value of additional information from relatives, other clinicians, and the medical record. The aims are to detect and diagnose psychiatric disorders; assess the risk of self-harm or harm to others; establish the need for treatment or referral for a psychiatric opinion; provide the basis for clear and effective communication with a psychiatrist; and to communicate to the patient that you are interested in all aspects of their suffering and thereby establish a clinically effective relationship with them.

Illness is conventionally categorized into two main types: ‘medical’ or ‘psychiatric’. This dichotomization is such an accepted feature of current medical practice that we take it for granted. But is it really the best way to think about and manage illness? In order to answer these questions, the chapter reviews what is meant by ‘medical’ and ‘psychiatric’ illness and considers the assumptions underpinning this division. The chapter then outlines alternative and more unified conceptualizations of illness, as well as the development of integrated models of clinical care.

Objective Two previous individual participant data meta-analyses (IPDMAs) found that different diagnostic interviews classify different proportions of people as having major depression overall or by symptom levels. We compared the odds of major depression classification across diagnostic interviews among studies that administered the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). Methods Data accrued for an IPDMA on HADS-D diagnostic accuracy were analysed. We fit binomial generalized linear mixed models to compare odds of major depression classification for the Structured Clinical Interview for DSM (SCID), Composite International Diagnostic Interview (CIDI), and Mini International Neuropsychiatric Interview (MINI), controlling for HADS-D scores and participant characteristics with and without an interaction term between interview and HADS-D scores. Results There were 15,856 participants (1942 [12%] with major depression) from 73 studies, including 15,335 (97%) non-psychiatric medical patients, 164 (1%) partners of medical patients, and 357 (2%) healthy adults. The MINI (27 studies, 7345 participants, 1066 major depression cases) classified participants as having major depression more often than the CIDI (10 studies, 3023 participants, 269 cases) (adjusted odds ratio [aOR] = 1.70 (0.84, 3.43)) and the semi-structured SCID (36 studies, 5488 participants, 607 cases) (aOR = 1.52 (1.01, 2.30)). The odds ratio for major depression classification with the CIDI was less likely to increase as HADS-D scores increased than for the SCID (interaction aOR = 0.92 (0.88, 0.96)). Conclusion Compared to the SCID, the MINI may diagnose more participants as having major depression, and the CIDI may be less responsive to symptom severity.

BackgroundComorbid depression in the medically ill is clinically important. Admission to a general hospital offers an opportunity to identify and initiate treatment for depression. However, we first need to know how common depression is in general hospital inpatients. We aimed to address this question by systematically reviewing the relevant literature.MethodsWe reviewed published prevalence studies in any language which had used diagnostic interviews of general hospital inpatients and met basic methodological quality criteria. We focussed on interview-based studies in order to estimate the proportion of patients with a diagnosis of depressive illness.ResultsOf 158 relevant articles, 65 (41%) describing 60 separate studies met our inclusion criteria. The 31 studies that focussed on general medical and surgical inpatients reported prevalence estimates ranging from 5% to 34%. There was substantial, highly statistically significant, heterogeneity between studies which was not materially explained by the covariates we were able to consider. The average of the reported prevalences was 12% (95% CI 10–15), with a 95% prediction interval of 4–32%. The remaining 29 studies, of a variety of specific clinical populations, are described.ConclusionsThe available evidence suggests a likely prevalence high enough to make it worthwhile screening hospital inpatients for depression and initiating treatment where appropriate. Further, higher quality, research is needed to clarify the prevalence of depression in specific settings and to further explore the reasons for the observed heterogeneity in estimates.

ObjectivesTo determine, for doctors looking after older medical inpatients: (1) how difficult they find discussions about ‘do not attempt cardiopulmonary resuscitation’ (DNACPR); (2) whether difficulty is associated with doctors’ personal and professional characteristics; (3) how frequently DNACPR discussions are made more difficult by practical issues and by doctors’ uncertainties.MethodsSurvey of hospital doctors working on the acute medical wards of a UK NHS teaching hospital.Results171/200 (86%) of eligible doctors participated. 165 had experience of DNACPR discussions with older inpatients and/or their families and were included in our analysis. ‘Difficulty’ (defined as finding discussions ‘fairly difficult’ or ‘difficult’) was experienced by 52/165 (32%) for discussions with patients and 60/165 (36%) for discussions with families. Doctors with specific training in DNACPR discussions were less likely to have difficulty in discussions with patients. Older, more experienced doctors were less likely to have difficulty in discussions with families. Lack of time and place, and uncertainty about prognosis were the most frequently reported causes of difficulty.ConclusionsMany doctors have difficulty in DNACPR discussions. Training needs to include managing discussions with families, as well as with patients, and doctors need time and space to deliver this important part of their job.

The Met Office Space Weather Operations Centre was founded in 2014 and part of its remit is a daily Space Weather Technical Forecast to help the UK build resilience to space weather impacts; guidance includes 4 day geomagnetic storm forecasts (GMSF) and X-ray flare forecasts (XRFF). It is crucial for forecasters, users, modelers, and stakeholders to understand the strengths and weaknesses of these forecasts; therefore, it is important to verify against the most reliable truth data source available. The present study contains verification results for XRFFs using Geo-Orbiting Earth Satellite 15 satellite data and GMSF using planetary K-index (Kp) values from the GFZ Helmholtz Centre. To assess the value of the verification results, it is helpful to compare them against a reference forecast and the frequency of occurrence during a rolling prediction period is used for this purpose. An analysis of the rolling 12 month performance over a 19 month period suggests that both the XRFF and GMSF struggle to provide a better prediction than the reference. However, a relative operating characteristic and reliability analysis of the full 19 month period reveals that although the GMSF and XRFF possess discriminatory skill, events tend to be overforecast.