Safe working in a 7-day service. Experience of hip fracture care as documented by the UK National Hip Fracture Database.

Objective: to describe differences in care and 30-day mortality of patients admitted with hip fracture on weekends (Saturday-Sunday) compared to weekdays (Monday-Friday), and their relationship to the organisation of care. Methods: data came from the National Hip Fracture Database (NHFD) linked to ONS mortality data on 52,599 patients presenting to 162 units in England between 1 January and 31 December 2014. This was combined with information on geriatrician staffing and major trauma centre (MTC) status. 30-day mortality and care were compared for patients admitted at weekends and weekdays; separately for patients treated in units grouped by the mean level of input by geriatricians, weekend geriatrician clinical cover and MTC status. Differences were adjusted for variation in patients' characteristics. Results: there was no evidence of differences in 30-day mortality between patients admitted at weekends compared to weekdays (7.2 vs 7.5%, P = 0.3) before or after adjusting for patient characteristics in either MTCs or general hospitals. The proportion receiving a preoperative geriatrician assessment was lower at weekends (42.8 vs 60.7%, P < 0.001). 30-day mortality was lower in units with higher levels of geriatrician input, but there was no weekend mortality effect associated with lower levels of input or absence of weekend cover. Conclusion: there was no evidence of a weekend mortality effect among patients treated for hip fracture in the English NHS. It appears that clinical teams provide comparably safe and effective care throughout the week. However, greater geriatrician involvement in teams was associated with overall lower mortality.

Increased orthogeriatrician involvement in hip fracture care and its impact on mortality in England.

Objectives: to describe the increase in orthogeriatrician involvement in hip fracture care in England and its association with improvements in time to surgery and mortality. Study design: analysis of Hospital Episode Statistics for 196,401 patients presenting with hip fracture to 150 hospitals in England between 1 April 2010 and 28 February 2014, combined with data on orthogeriatrician hours from a national organisational survey. Methods: we examined changes in the average number of hours worked by orthogeriatricians in orthopaedic departments per patient with hip fracture, and their potential effect on mortality within 30 days of presentation. The role of prompt surgery (on day of or day after presentation) was explored as a potential confounding factor. Associations were assessed using conditional Poisson regression models with adjustment for patients' sex, age and comorbidity and year, with hospitals treated as fixed effects. Results: between 2010 and 2013, there was an increase of 2.5 hours per patient in the median number of hours worked by orthogeriatricians-from 1.5 to 4.0 hours. An increase of 2.5 hours per patient was associated with a relative reduction in mortality of 3.4% (95% confidence interval 0.9% to 5.9%, P = 0.01). This corresponds to an absolute reduction of approximately 0.3%. Higher numbers of orthogeriatrician hours were associated with higher rates of prompt surgery, but were independently associated with lower mortality. Conclusion: in the context of initiatives to improve hip fracture care, we identified statistically significant and robust associations between increased orthogeriatrician hours per patient and reduced 30-day mortality.

The impact of a national clinician-led audit initiative on care and mortality after hip fracture in England: an external evaluation using time trends in non-audit data.

BACKGROUND: Hip fracture is the most common serious injury of older people. The UK National Hip Fracture Database (NHFD) was launched in 2007 as a national collaborative, clinician-led audit initiative to improve the quality of hip fracture care, but has not yet been externally evaluated. METHODS: We used routinely collected data on 471,590 older people (aged 60 years and older) admitted with a hip fracture to National Health Service (NHS) hospitals in England between 2003 and 2011. The main variables of interest were the use of early surgery (on day of admission, or day after) and mortality at 30 days from admission. We compared time trends in the periods 2003-2007 and 2007-2011 (before and after the launch of the NHFD), using Poisson regression models to adjust for demographic changes. FINDINGS: The number of hospitals participating in the NHFD increased from 11 in 2007 to 175 in 2011. From 2007 to 2011, the rate of early surgery increased from 54.5% to 71.3%, whereas the rate had remained stable over the period 2003-2007. Thirty-day mortality fell from 10.9% to 8.5%, compared with a small reduction from 11.5% to 10.9% previously. The annual relative reduction in adjusted 30-day mortality was 1.8% per year in the period 2003-2007, compared with 7.6% per year over 2007-2011 (P<0.001 for the difference). INTERPRETATION: The launch of a national clinician-led audit initiative was associated with substantial improvements in care and survival of older people with hip fracture in England.

Persons diagnosed with COVID-19 in England in the Clinical Practice Research Datalink (CPRD): a cohort description.

OBJECTIVE: To create case definitions for confirmed COVID-19 diagnoses, COVID-19 vaccination status and three separate definitions of high risk of severe COVID-19, as well as to assess whether the implementation of these definitions in a cohort reflected the sociodemographic and clinical characteristics of COVID-19 epidemiology in England. DESIGN: Retrospective cohort study. SETTING: Electronic healthcare records from primary care (Clinical Practice Research Datalink, CPRD) linked to secondary care data (Hospital Episode Statistics) data covering 24% of the population in England. PARTICIPANTS: 2 271 072 persons aged 1 year and older diagnosed with COVID-19 in CPRD Aurum between 1 August 2020 and 31 January 2022. MAIN OUTCOME MEASURES: Age, sex and regional distribution of COVID-19 cases and COVID-19 vaccine doses received prior to diagnosis were assessed separately for the cohorts of cases identified in primary care and those hospitalised for COVID-19 (primary diagnosis code of ICD-10 U07.1 'COVID-19'). Smoking status, body mass index and Charlson Comorbidity Index were compared for the two cohorts, as well as for three separate definitions of high risk of severe disease used in the UK (National Health Service Highest Risk, PANORAMIC trial eligibility, UK Health Security Agency Clinical Risk prioritisation for vaccination). RESULTS: Compared with national estimates, CPRD case estimates under-represented older adults in both the primary care (age 65-84: 6% in CPRD vs 9% nationally) and hospitalised (31% vs 40%) cohorts, and over-represented people living in regions with the highest median wealth areas of England (20% primary care and 20% hospital admitted cases in South East vs 15% nationally). The majority of non-hospitalised cases and all hospitalised cases had not completed primary series vaccination. In primary care, persons meeting high-risk definitions were older, more often smokers, overweight or obese, and had higher Charlson Comorbidity Index score. CONCLUSIONS: CPRD primary care data are a robust real-world data source and can be used for some COVID-19 research questions, however, limitations of the data availability should be carefully considered. Included in this publication are supplemental files for a total of over 28 000 codes to define each of three definitions of high risk of severe disease.

Health Care Resource Utilization and Costs Associated With COVID-19 Among Pediatrics Managed in the Community or Hospital Setting in England: A Population-based Cohort Study.

BACKGROUND: Although COVID-19 morbidity is significantly lower in pediatrics than in adults, the risk of severe COVID-19 may still pose substantial health care resource burden. This study aimed to describe health care resource utilization (HCRU) and costs associated with COVID-19 in pediatrics 1-17 years old in England. METHODS: A population-based retrospective cohort study of pediatrics with COVID-19 using Clinical Practice Research Datalink (CPRD Aurum) primary care data and, where available, linked Hospital Episode Statistics Admitted Patient Care secondary care data. HCRU and associated costs to the National Health Service were stratified by age, risk of severe COVID-19 and immunocompromised status, separately for those with and without hospitalization records (hospitalized cohort: COVID-19 diagnosis August 2020-March 2021; primary care cohort: COVID-19 diagnosis August 2020-January 2022). RESULTS: This study included 564,644 patients in the primary care cohort and 60 in the hospitalized cohort. Primary care consultations were more common in those 1-4 years of age (face-to-face: 4.3%; telephone: 6.0%) compared with those 5-11 (2.0%; 2.1%) and 12-17 years of age (2.2%; 2.5%). In the hospitalized cohort, mean (SD) length of stay was longer [5.0 (5.8) days] among those 12-17 years old (n = 24) than those 1-4 [n = 15; 1.8 (0.9) days] and 5-11 years old [n = 21; 2.8 (2.1) days]. CONCLUSIONS: Most pediatrics diagnosed with COVID-19 were managed in the community. However, hospitalizations were an important driver of HCRU and costs, particularly for those 12-17 years old. Our results may help optimize the management and resource allocation of COVID-19 in this population.

Cancer diagnosed by emergency admission in England: an observational study using the general practice research database.

BACKGROUND: Patients diagnosed with cancer by the emergency route often have more advanced diseases and poorer outcomes. Rates of cancer diagnosed through unplanned admissions vary within and between countries, suggesting potential inconsistencies in the quality of care. To reduce diagnoses by this route and improve patient outcomes, high risk patient groups must be identified. This cross-sectional observational study determined the incidence of first-ever diagnoses of cancer by emergency (unplanned) admission and identified patient-level risk factors for these diagnoses in England. METHODS: Data for 74,763 randomly selected patients at 457 general practices between 1999 and 2008 were obtained from the General Practice Research Database (GPRD), including integrated Hospital Episode Statistics (HES) data and Office for National Statistics (ONS) mortality data. The proportion of first-ever diagnoses by emergency admission out of all recorded first cancer diagnoses by any route was analysed by patient characteristics. RESULTS: Diagnosis by emergency admission was recorded in 13.9% of patients diagnosed with cancer for the first time (n = 817/5870). The incidence of first cases by the emergency route was 2.51 patients per 10,000 person years. In adjusted regression analyses, patients of older age (p < 0.0001), living in the most deprived areas (RR 1.93, 95% CI 1.51 to 2.47; p < 0.0001) or who had a total Charlson score of 1 compared to 0 (RR 1.34, 95% CI 1.06 to 1.69; p = 0.014) were most at risk of diagnosis by emergency admission. Patients with more prior (all-cause) emergency admissions were less at risk of subsequent diagnosis by the emergency route (RR 0.31 per prior emergency admission, 95% CI 0.20 to 0.46; p < 0.0001). CONCLUSIONS: A much lower incidence of first-ever cancer diagnoses by emergency admission was found compared with previous studies. Identified high risk groups may benefit from interventions to reduce delayed diagnosis. Further studies should include screening and cancer staging data to improve understanding of delayed or untimely diagnosis and patient care pathways.

Detecting transthyretin amyloid cardiomyopathy (ATTR-CM) using machine learning: an evaluation of the performance of an algorithm in a UK setting.

OBJECTIVE: The aim of this study was to evaluate the potential real-world application of a machine learning (ML) algorithm, developed and trained on heart failure (HF) cohorts in the USA, to detect patients with undiagnosed wild type cardiac amyloidosis (ATTRwt) in the UK. DESIGN: In this retrospective observational study, anonymised, linked primary and secondary care data (Clinical Practice Research Datalink GOLD and Hospital Episode Statistics, respectively, were used to identify patients diagnosed with HF between 2009 and 2018 in the UK. International Classification of Diseases (ICD)-10 clinical modification codes were matched to equivalent Read (primary care) and ICD-10 WHO (secondary care) diagnosis codes used in the UK. In the absence of specific Read or ICD-10 WHO codes for ATTRwt, two proxy case definitions (definitive and possible cases) based on the degree of confidence that the contributing codes defined true ATTRwt cases were created using ML. PRIMARY OUTCOME MEASURE: Algorithm performance was evaluated primarily using the area under the receiver operating curve (AUROC) by comparing the actual versus algorithm predicted case definitions at varying sensitivities and specificities. RESULTS: The algorithm demonstrated strongest predictive ability when a combination of primary care and secondary care data were used (AUROC: 0.84 in definitive cohort and 0.86 in possible cohort). For primary care or secondary care data alone, performance ranged from 0.68 to 0.78. CONCLUSION: The ML algorithm, despite being developed in a US population, was effective at identifying patients that may have ATTRwt in a UK setting. Its potential use in research and clinical care to aid identification of patients with undiagnosed ATTRwt, possibly enabling earlier diagnosis in the disease pathway, should be investigated.

Online social media poses opportunities and risks in autistic youth: implications for services from a qualitative study.

Background: Autistic people are vulnerable to developing mental health problems due to their difficulties in managing social situations and interpersonal relationships. The popular online social media (OSM) can be a potential solution to these concerns for their social lives as it allows non-face-to-face social interactions, however it remained unclear how this group is using these online platforms. This study explored their experiences of using online social media, and their perceived benefits and risks associated with this use. Method: Qualitative data was collected through in-depth face to face interviews. We recruited 13 autistic young adults who were with normal intelligence from two community centers in Hong Kong. Interviews were conducted in a semi-structured format by experienced clinical psychologist and social workers. Results: Four themes were identified from the data, namely: (1) Paradox of using OSM to supplement social needs; (2) Unpleasant social interactions in the online environment; (3) Restricted and repetitive pattern of interest leading to troubles in OSM use, and; (4) Privacy and personal safety issues. The results suggested that while OSM could be a useful tool for our participants to connect with existing friends and to meet new ones, their limitations, such as difficulties in understanding languages and social interaction as well as restricted patterns of interests could potentially put them at risk, including interpersonal conflicts, cyber-bullying, financial scams, as well as unwanted sexual experiences. These experiences not only paradoxically increased their sense of loneliness and their distance from others, but also resulted in a negative impact on their mood and functioning. Conclusion: This qualitative study provided some insights into the OSM use among autistic young adults. OSM could be a useful tool to overcome potential limitations in social interactions, but at the same time it could potentially bring detrimental consequences. In order to maximize the benefits of online social networking, there is a need for timely guidance and support to use OSM among autists, and for psychoeducation to promote awareness, and enable adequate skills and behaviors attainment associated with safe OSM use.

Healthcare resource utilisation and costs of hospitalisation and primary care among adults with COVID-19 in England: a population-based cohort study.

OBJECTIVES: To quantify direct costs and healthcare resource utilisation (HCRU) associated with acute COVID-19 in adults in England. DESIGN: Population-based retrospective cohort study using Clinical Practice Research Datalink Aurum primary care electronic medical records linked to Hospital Episode Statistics secondary care administrative data. SETTING: Patients registered to primary care practices in England. POPULATION: 1 706 368 adults with a positive SARS-CoV-2 PCR or antigen test from August 2020 to January 2022 were included; 13 105 within the hospitalised cohort indexed between August 2020 and March 2021, and 1 693 263 within the primary care cohort indexed between August 2020 and January 2022. Patients with a COVID-19-related hospitalisation within 84 days of a positive test were included in the hospitalised cohort. MAIN OUTCOME MEASURES: Primary and secondary care HCRU and associated costs ≤4 weeks following positive COVID-19 test, stratified by age group, risk of severe COVID-19 and immunocompromised status. RESULTS: Among the hospitalised cohort, average length of stay, including critical care stays, was longer in older adults. Median healthcare cost per hospitalisation was higher in those aged 75-84 (£8942) and ≥85 years (£8835) than in those aged <50 years (£7703). While few (6.0%) patients in critical care required mechanical ventilation, its use was higher in older adults (50-74 years: 8.3%; <50 years: 4.3%). HCRU and associated costs were often greater in those at higher risk of severe COVID-19 than in the overall cohort, although minimal differences in HCRU were found across the three different high-risk definitions. Among the primary care cohort, general practitioner or nurse consultations were more frequent among older adults and the immunocompromised. CONCLUSIONS: COVID-19-related hospitalisations in older adults, particularly critical care stays, were the primary drivers of high COVID-19 resource use in England. These findings may inform health policy decisions and resource allocation in the prevention and management of COVID-19.

Routinely recorded patient safety events in primary care: a literature review.

BACKGROUND: Existing patient-level data can be used to measure and monitor patient safety. Data from sources including electronic patient records are routinely collected in primary care and may be suitable for adverse event screening, such as patient safety indicators. To inform the feasibility of developing primary care measures of patient harm, information about routinely collected data is needed. OBJECTIVE: A literature review was conducted to determine the types of adverse events that are routinely recorded in primary care. METHODS: We searched ASSIA, Cochrane Library, Embase, HMIC, ISI Web of Science, Medline and PsycInfo databases, grey literature and websites. We included only original research studies in English where routinely collected patient data were used to identify adverse events occurring in primary or ambulatory care settings. Adverse events were defined as unexpected and undesirable patient outcomes arising from health care contact. RESULTS: Of 5029 citations identified, 15 were reviewed. Twelve studies used multiple data sources. Approximately 6.5% of adult emergency admissions were due to drug-related events (n = 1225). Between 0.7% and 2.3% of deaths following adverse events were attributed to treatment in primary care. A large proportion of adverse events resulting in the most severe harm may be preventable. For example, one study estimated that 42% of serious adverse drug events were avoidable. CONCLUSIONS: There is limited use of routinely collected data to measure adverse events in primary care despite large volumes of data generated. The potential for using readily available data recorded in primary care for active patient safety surveillance needs further exploration.

Serum potassium variability as a predictor of clinical outcomes in patients with cardiorenal disease or diabetes: a retrospective UK database study.

Background: Hyperkalaemia is an electrolyte abnormality associated with adverse clinical outcomes; however, few studies have investigated the relationship with patterns of hyperkalaemia over time. This study explored the impact of time spent in a hyperkalaemic state and variability of serum potassium (sK+) on major adverse cardiovascular events (MACE) and all-cause mortality in patients with chronic kidney disease (CKD), resistant hypertension, heart failure and diabetes. Methods: Cohorts comprised adult patients diagnosed with CKD stage 3+, resistant hypertension, heart failure or diabetes, and/or renin-angiotensin-aldosterone system inhibitor prescription, between 1 January 2003 and 30 June 2018, from the UK Clinical Practice Research Datalink. Associations between percentage of follow-up spent in a hyperkalaemic state (sK+ ≥5.0 mmol/L, ≥5.5 mmol/L, ≥6.0 mmol/L) or sK+ variability (standard deviation above or below median standard deviation) and all-cause mortality or MACE were investigated. Results: For sK+ ≥5.0 mmol/L, time spent in a hyperkalaemic state was associated with reduced risk of all-cause mortality across all cohorts. For higher sK+ thresholds, this trend was attenuated or reversed; for time spent in a hyperkalaemic state at sK+ ≥6.0 mmol/L, an increased risk of mortality was seen in the overall cohort and for patients with diabetes, resistant hypertension or prescribed renin-angiotensin-aldosterone system inhibitors, with no consistent association seen for patients with CKD or heart failure. Risk of MACE in the overall cohort and in patients with CKD, diabetes or resistant hypertension increased with time spent in a hyperkalaemic state at all sK+ thresholds; however, no correlation was seen in patients with heart failure or those receiving dialysis. High sK+ variability was associated with a higher risk of MACE compared with low sK+ variability across most sK+ categories in the overall population and in all disease cohorts, except patients on dialysis; however, no association between sK+ variability and all-cause mortality was observed. Conclusions: Patterns of hyperkalaemia, including time spent in hyperkalaemia and sK+ variability, are associated with adverse clinical outcomes. Regular monitoring of sK+ in high-risk populations in broader community, primary care and outpatient settings may enable guideline-recommended management of hyperkalaemia and help avoid adverse events.

Establishment of a core outcome set for burn care research: development and international consensus.

Objective: To develop a core outcome set for international burn research. Design: Development and international consensus, from April 2017 to November 2019. Methods: Candidate outcomes were identified from systematic reviews and stakeholder interviews. Through a Delphi survey, international clinicians, researchers, and UK patients prioritised outcomes. Anonymised feedback aimed to achieve consensus. Pre-defined criteria for retaining outcomes were agreed. A consensus meeting with voting was held to finalise the core outcome set. Results: Data source examination identified 1021 unique outcomes grouped into 88 candidate outcomes. Stakeholders in round 1 of the survey, included 668 health professionals from 77 countries (18% from low or low middle income countries) and 126 UK patients or carers. After round 1, one outcome was discarded, and 13 new outcomes added. After round 2, 69 items were discarded, leaving 31 outcomes for the consensus meeting. Outcome merging and voting, in two rounds, with prespecified thresholds agreed seven core outcomes: death, specified complications, ability to do daily tasks, wound healing, neuropathic pain and itch, psychological wellbeing, and return to school or work. Conclusions: This core outcome set caters for global burn research, and future trials are recommended to include measures of these outcomes.

Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomized controlled trial in England.

Aims: The aim of the PULsE-AI trial was to assess the effectiveness of a machine learning risk-prediction algorithm in conjunction with diagnostic testing for identifying undiagnosed atrial fibrillation (AF) in primary care in England. Methods and results: Eligible participants (aged ≥30 years without AF diagnosis; n = 23 745) from six general practices in England were randomized into intervention and control arms. Intervention arm participants, identified by the algorithm as high risk of undiagnosed AF (n = 944), were invited for diagnostic testing (n = 256 consented); those who did not accept the invitation, and all control arm participants, were managed routinely. The primary endpoint was the proportion of AF, atrial flutter, and fast atrial tachycardia diagnoses during the trial (June 2019-February 2021) in high-risk participants. Atrial fibrillation and related arrhythmias were diagnosed in 5.63% and 4.93% of high-risk participants in intervention and control arms, respectively {odds ratio (OR) [95% confidence interval (CI)]: 1.15 (0.77-1.73), P = 0.486}. Among intervention arm participants who underwent diagnostic testing (28.1%), 9.41% received AF and related arrhythmia diagnoses [vs. 4.93% (control); OR (95% CI): 2.24 (1.31-3.73), P = 0.003]. Conclusion: The AF risk-prediction algorithm accurately identified high-risk participants in both arms. While the proportions of AF and related arrhythmia diagnoses were not significantly different between high-risk arms, intervention arm participants who underwent diagnostic testing were twice as likely to receive arrhythmia diagnoses compared with routine care. The algorithm could be a valuable tool to select primary care groups at high risk of undiagnosed AF who may benefit from diagnostic testing.

Effectiveness of Using Mobile Technology to Improve Cognitive and Social Skills Among Individuals With Autism Spectrum Disorder: Systematic Literature Review.

BACKGROUND: Mobile technology has become a necessity in the lives of people in many countries. Its characteristics and advantages also make it a potential medium of intervention for people with autism spectrum disorder (ASD). OBJECTIVE: The objective of this review was to evaluate previous evidence, obtained in randomized controlled trials (RCTs), on the effectiveness of using mobile devices as the medium of intervention targeting social and cognitive skills among individuals with ASD. METHODS: Literature search was conducted on electronic databases including Medline, PsycInfo, PsycArticles, Education Resources Information Centre, and Social Science Citation Index. Only RCTs published in English and after year 2000 were included for this review. Data extraction was carried out by 2 independent reviewers using constant comparative methods. RESULTS: Totally 10 RCTs were identified. Most of the findings indicated that mobile devices could be an effective medium of intervention for people with ASD, among which 6 indicated significant intervention effects and 2 showed mixed findings. Effective intervention was more likely to be achieved in the studies that recruited older participants (aged over 9 years), targeting practical skills that could be readily applied in real life, or using pictures or materials that were highly relevant in daily life in the apps or mobile devices. Furthermore, the use of mobile devices was also reported to promote participation in the intervention among individuals with ASD. CONCLUSIONS: The results suggested that mobile devices could be a promising means for the delivery of interventions targeting people with ASD. Although including a small number of studies was a limitation of this review, the results provided useful implications for designing effective mobile technology-assisted interventions for the ASD population in future studies.

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study.

AIMS: To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care. METHODS: A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years. Algorithm performance metrics were sensitivity, specificity, positive predictive value, negative predictive value (NPV) and number needed to screen (NNS). Subgroup analysis of patients aged ≥65 years was also performed. RESULTS: Of 2,542,732 patients in DISCOVER, the algorithm identified 604,135 patients suitable for risk assessment. Of these, 3.0% (17,880 patients) had a diagnosis of atrial fibrillation recorded before study end. The area under the curve of the receiver operating characteristic was 0.87, compared with 0.83 in algorithm development. The NNS was nine patients, matching the CPRD cohort. In patients aged ≥30 years, the algorithm correctly identified 99.1% of patients who did not have atrial fibrillation (NPV) and 75.0% of true atrial fibrillation cases (sensitivity). Among patients aged ≥65 years (n = 117,965), the NPV was 96.7% with 91.8% sensitivity. CONCLUSIONS: This atrial fibrillation risk prediction algorithm, based on machine learning methods, identified patients at highest risk of atrial fibrillation. It performed comparably in a large, real-world population-based cohort and the developmental registry cohort. If implemented in primary care, the algorithm could be an effective tool for narrowing the population who would benefit from atrial fibrillation screening in the United Kingdom.

Recording of adverse events in English general practice: analysis of data from electronic patient records.

BACKGROUND: Although the majority of patient contact within the UK's National Health Service (NHS) occurs in primary care, relatively little is known about the safety of care in this setting compared to the safety of hospital care. Measurement methods to detect iatrogenic diseases in primary care require extensive development. Routinely collected data have been successfully applied to develop patient safety indicators in secondary care. Given the availability of electronic health data in primary care, we explored the potential to build adverse event screening tools using computerised medical record systems. OBJECTIVE: To identify the rate and types of adverse events that might be recorded in primary care through routinely collected data. The findings will inform the development of administrative data-based indicators to screen for patient harm arising from primary care contact. METHOD: Descriptive analyses were performed on data extracted from the clinical information management systems (CIMS) at NHS Brent. The data were explored according to age, sex and ethnicity of patients. Potential or actual adverse events were identified by mapping to three Read code chapters. RESULTS: Records from the calendar year 2007 were available for 69 682 registered patients from 25 practices, consisting of 680 866 consultations. A number of adverse events could be detected through terms contained in certain chapters of the Read code system. These events include injuries due to surgical and medical care (0.72 cases of per 1000 consultations) and adverse drug reactions (1.26 reactions per 1000 consultations). Patterns in the rate of harm among patients from different ethnic groups tended to reflect the proportion of the respective groups in the overall Brent population, with more injuries occurring among patients of white and Asian ethnicities. CONCLUSION: These findings suggest that there is scope to develop more accurate and reliable means of safety surveillance in general practice using data obtained from electronic patient records.

What Next After Metformin in Type 2 Diabetes? Selecting the Right Drug for the Right Patient.

INTRODUCTION: Metformin is the recommended initial treatment in type 2 diabetes mellitus (T2DM), but when this does not give adequate glucose control the choice of which second-line drug to use is uncertain as none have been found to have a better overall glycaemic response. In this real-world study dipeptidyl peptidase 4 inhibitors (DPP4i), sulphonylureas (SU), thiazolidinediones (TZD) and sodium glucose co-transporter 2 inhibitors (SGLT2i) were compared for their effectiveness in lowering glycated haemoglobin (HbA1c) levels for a particular individual based on their clinical characteristics. METHODS: A retrospective analysis was undertaken of electronic health records of people with T2DM prescribed metformin alongside a DPP4i, SU, TZD or SGLT2i at second-line. Regression modelling was used to model the changes in HbA1c from baseline at month 6 and month 12 for the individual therapies, adjusting for demographic and clinical characteristics. RESULTS: There were 7170 people included in the study. Treatment at second-line with SUs, DPP4i, TZDs and SGLT2i resulted in similar percentages of people achieving the recommended HbA1c target of < 7.5% (58 mmol/mol) at both 6 and 12 months. For those receiving SGLT2i and SUs, the greatest improvement in HbA1c was observed in relatively younger and older people, respectively. Trends were detected between other baseline characteristics and HbA1c improvement by drug class, but they were not statistically significant. Non-adherence rates were low for all drug classes. People with a higher medication possession ratio (≥ 80%) also had greater improvements in HbA1c at 12 months. CONCLUSION: This study identified patients' phenotypic characteristics that may have the potential to influence individual treatment response. Accounting for these characteristics in clinical treatment decisions may facilitate individualised prescribing by being able to select the right drug for the right patient.

Construction of the secondary care administrative records frailty (SCARF) index and validation on older women with operable invasive breast cancer in England and Wales: a cohort study.

OBJECTIVES: Studies that use national datasets to evaluate the management of older women with breast cancer are often constrained by a lack of information on patient fitness. This study constructed a frailty index for use with secondary care administrative records and evaluated its ability to improve models of treatment patterns and overall survival in women with breast cancer. DESIGN: Retrospective cohort study. PARTICIPANTS: Women aged ≥50 years with oestrogen receptor (ER) positive early invasive breast cancer diagnosed between 2014 and 2017 in England. METHODS: The secondary care administrative records frailty (SCARF) index was based on the cumulative deficit model of frailty, using International Statistical Classification of Diseases, Injuries and Causes of Death, 10th revision codes to define a set of deficits. The index was applied to administrative records that were linked to national cancer registry datasets. The ability of the SCARF index to improve the performance of regression models to explain observed variation in the rate of surgery and overall survival was evaluated using Harrell's c-statistic and decision curve analysis. External validation was performed on a dataset of similar women diagnosed in Wales. RESULTS: The SCARF index captured 32 deficits that cover functional impairment, geriatric syndromes, problems with nutrition, cognition and mood, and medical comorbidities. In the English dataset (n=67 925), the prevalence of frailty in women aged 50-69, 70-79 and ≥80 years was 15%, 28% and 47%, respectively. Adding a frailty measure to regression models containing age, tumour characteristics and comorbidity improved their ability to: (1) discriminate between whether a woman was likely to have surgery and (2) predict overall survival. Similar results were obtained when the models were applied to the Welsh cohort (n=4 230). CONCLUSION: The SCARF index provides a simple and consistent method to identify frailty in population level data and could help describe differences in breast cancer treatments and outcomes.

Addressing frailty in patients with breast cancer: A review of the literature.

Various studies have documented variation in the management of older patients with breast cancer, and some of this variation stems from different approaches to balancing the expected benefit of different treatments, with the ability of patients to tolerate them. Frailty is an emerging concept that can help to make clinical decisions for older patients more consistent, not least by providing a measure of 'biological' ageing. This would reduce reliance on 'chronological' age, which is not a reliable guide for decisions on the appropriate breast cancer care for older patients. This article examines the potential of frailty assessment to inform on breast cancer treatments. Overall, the current evidence highlights various benefits from implementing comprehensive geriatric assessment and screening for frailty in breast cancer patients. This includes a role in supporting the selection of appropriate therapies and improving physical fitness prior to treatment. However, there are challenges in implementing routine frailty assessments in a breast cancer service. Studies have used a diverse array of frailty assessment instruments, which hampers the generalisability of research findings. Consequently, a number of issues need to be addressed to clearly establish the optimal timing of frailty assessment and the role of geriatric medicine specialists in the breast cancer care pathway.

Reporting of key methodological issues in placebo-controlled trials of surgery needs improvement: a systematic review.

OBJECTIVES: To examine key methodological considerations for using a placebo intervention in randomized controlled trials (RCTs) evaluating invasive procedures, including surgery. STUDY DESIGN AND SETTING: RCTs comparing an invasive procedure with a placebo were included in this systematic review. Articles published from database inception to December 31, 2017, were retrieved from Ovid MEDLINE, Ovid EMBASE and CENTRAL electronic databases, by handsearching references and expert knowledge. Data on trial characteristics (clinical area, nature of invasive procedure, number of patients and centers) and key methodological (rationale for using placebos, minimization of risk, information provision, offering the treatment intervention to patients randomized to placebo, delivery of cointerventions, and intervention standardization and fidelity) were extracted and summarized descriptively. RESULTS: One hundred thirteen articles reporting 96 RCTs were identified. Most were conducted in gastrointestinal surgery (n = 40, 42%) and evaluated minimally invasive procedures (n = 44, 46%). Over two-thirds randomized fewer than 100 patients (n = 65, 68%) and a third were single center (n = 31, 32%). A third (n = 33, 34%) did not report a rationale for using a placebo. Most common strategies to minimize patient risk were operator skill (n = 22, 23%) and independent data monitoring (n = 28, 29%). Provision of patient information regarding placebo use was infrequently reported (n = 11, 11%). Treatment interventions were offered to patients randomized to placebo in 43 trials (45%). Cointerventions were inconsistently reported, but 64 trials (67%) stated that anesthesia was matched between groups. Attempts to standardize interventions and monitor their delivery were reported in n = 7, (7%) and n = 4, (4%) trials, respectively. CONCLUSION: Most placebo-controlled trials in surgery evaluate minor surgical procedures and currently there is inconsistent reporting of key trial methods. There is a need for guidance to optimize the transparency of trial reporting in this area.