Search

Simple Summary: The platelet count is an established marker of cancer. In healthy populations, platelet count varies by age and sex; despite that variation, a single reference range is used. This study aimed to identify age- and sex-specific upper thresholds for platelet count at which cancer should be considered in primary care, using audits of primary care-based clinical data in England, Canada, and Australia. Across all three cohorts, there was a clear upwards trend in cancer incidence with increasing platelet count for both sexes and at all age groups. The appropriate threshold will vary by country and will depend on local healthcare needs and priorities. As colorectal and lung cancers predominate, initial investigation may target these sites. Further investigation, depending on the patient's symptoms, could be CT imaging, endoscopy, or CA125. The platelet count, a component of the full blood count, has been identified as a useful diagnostic marker for cancer in primary care. The reference range for the platelet count is 150 to 400 or 450 × 109/L; this range does not account for natural variation in platelet count by age and sex. This study used three primary care cohorts from England, Canada, and Australia. Patients aged 40 years and over with a full blood count were included and stratified by age (in 10-year bands), sex, (male/female), and platelet count group. Cancer incidence within one year of the test date was estimated from linked registry data. In all three countries, there was a clear upwards trend in cancer incidence with increasing platelet count for both sexes and at all age groups. Lung and colorectal were the most common sites. These results have important implications for the international application of this work; analysis of local health datasets will be crucial to determining appropriate thresholds. Appropriate upper thresholds will depend on local populations, healthcare needs, and priorities. Further research is needed to assess the likely impact of new recommendations on the healthcare system, on cancer outcomes, and patient benefit. [ABSTRACT FROM AUTHOR]

Background: Ethnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients' ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however, the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data. Methods: We describe the completeness and consistency of primary care ethnicity recording in the OpenSAFELY-TPP database, containing linked primary care and hospital records in > 25 million patients in England. We also compared the ethnic breakdown in OpenSAFELY-TPP with that of the 2021 UK census. Results: 78.2% of patients registered in OpenSAFELY-TPP on 1 January 2022 had their ethnicity recorded in primary care records, rising to 92.5% when supplemented with hospital data. The completeness of ethnicity recording was higher for women than for men. The rate of primary care ethnicity recording ranged from 77% in the South East of England to 82.2% in the West Midlands. Ethnicity recording rates were higher in patients with chronic or other serious health conditions. For each of the five broad ethnicity groups, primary care recorded ethnicity was within 2.9 percentage points of the population rate as recorded in the 2021 Census for England as a whole. For patients with multiple ethnicity records, 98.7% of the latest recorded ethnicities matched the most frequently coded ethnicity. Patients whose latest recorded ethnicity was categorised as Other were most likely to have a discordant ethnicity recording (32.2%). Conclusions: Primary care ethnicity data in OpenSAFELY is present for over three quarters of all patients, and combined with data from other sources can achieve a high level of completeness. The overall distribution of ethnicities across all English OpenSAFELY-TPP practices was similar to the 2021 Census, with some regional variation. This report identifies the best available codelist for use in OpenSAFELY and similar electronic health record data. [ABSTRACT FROM AUTHOR]

Aims: The COVID‐19 pandemic caused significant disruption to routine activity in primary care. Medication reviews are an important primary care activity ensuring safety and appropriateness of prescribing. A disruption could have significant negative implications for patient care. Using routinely collected data, our aim was first to describe codes used to record medication review activity and then to report the impact of COVID‐19 on the rates of medication reviews. Methods: With the approval of NHS England, we conducted a cohort study of 20 million adult patient records in general practice, in‐situ using the OpenSAFELY platform. For each month, between April 2019 and March 2022, we report the percentage of patients with a medication review coded monthly and in the previous 12 months with breakdowns by regional, clinical and demographic subgroups and those prescribed high‐risk medications. Results: In April 2019, 32.3% of patients had a medication review coded in the previous 12 months. During the first COVID‐19 lockdown, monthly activity decreased (−21.1% April 2020), but the 12‐month rate was not substantially impacted (−10.5% March 2021). The rate of structured medication review in the last 12 months reached 2.9% by March 2022, with higher percentages in high‐risk groups (care home residents 34.1%, age 90+ years 13.1%, high‐risk medications 10.2%). The most used medication review code was Medication review done 314530002 (59.5%). Conclusions: There was a substantial reduction in the monthly rate of medication reviews during the pandemic but rates recovered by the end of the study period. Structured medication reviews were prioritized for high‐risk patients. [ABSTRACT FROM AUTHOR]

Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services. [ABSTRACT FROM AUTHOR]

Background: During the COVID-19 pandemic many patients were switched from warfarin to direct)acting oral anticoagulants (DOACs), which require the creatinine clearance (CrCl) calculated to ensure the correct dose is prescribed to avoid bleeding or reduced efficacy. Aim: To identify the study population proportion prescribed a DOAC. Of these, the proportion with recorded: weight, estimated glomerular filtration rate (eGFR), creatinine, CrCl and atrial fibrillation (AF). To analyse the proportion of patients with recorded AF and CrCl prescribed a recommended DOAC dose. Design & setting: A retrospective cohort study of 20.5 million adult NHS patients’ electronic health records (EHRs) in England in the OpenSAFELY-TPP platform (January 2018–February 2023). Method: Patients on DOACs were analysed for age, sex, recorded weight, eGFR, creatinine, CrCl and AF. Prescribed DOAC doses in patients with recorded AF were compared with recommended doses for recorded CrCl and determined as either recommended, higher than recommended (overdose), or lower than recommended (underdose). Results: In February 2023, weight, eGFR, creatinine, CrCl, and AF were recorded in 72.8%, 92.4%, 94.3%, 73.5%, and 73.9% of study population, respectively. Both AF and CrCl were recorded for 56.7% of patients. Of these, 86.2% received the recommended, and 13.8% non-recommended, DOAC doses. Conclusion: CrCl is not recorded for a substantial number of patients on DOACs. We recommend that national organisations tasked with safety, collectively update guidance on the appropriate weight to use in the Cockcroft–Gault equation, clarify that CrCl is not equivalent to eGFR, and work with GP clinical system suppliers to standardise the calculation of CrCl in the EHR. [ABSTRACT FROM AUTHOR]

Background: Oral anticoagulation (OAC) is the mainstay of treatment for the prevention of strokes in patients with atrial fibrillation (AF). Direct oral anticoagulants (DOACs) account for increasing OAC in patients with AF. However, prescribing DOACs for patients with established AF poses various challenges and general practice pharmacists may have an important role in supporting their management. Aim: To investigate the effectiveness of pharmacist-led interventions in general practice in optimising the use of OAC therapies in AF. Design & setting: A retrospective observational study in general practices in Bradford. Method: The data were collected retrospectively from 1 November 2018–31 December 2019 using electronic health record data. The data were analysed: 1) to identify patients with AF not on OAC; 2) to describe inappropriate DOAC prescriptions; and 3) to calculate HAS-BLED scores. Results: Overall, 76.3% (n = 470) of patients with AF received OAC therapy, and of these, 63.4% received DOACs. Pharmacist-led interventions increased DOAC prescribing by 6.0% (P = 0.03). Inappropriate DOAC use was identified in 24.5% of patients with AF, with underdosed and overdosed identified in 9.7% and 14.8%, respectively. Post-intervention, inappropriate prescribing was reduced to 1.7%. The mean HAS-BLED score decreased from 3.00 to 2.22 (P<0.01). Successful transition from vitamin K antagonist (VKA) therapy to DOACs was achieved in 25.7% of patients. Conclusion: Pharmacist-led interventions have successfully improved the use of OAC therapies in patients with AF, and effectively managed the bleeding risks and transition from VKA to DOAC therapy, in line with guidelines. [ABSTRACT FROM AUTHOR]

Background: Patient portals introduced in most of England’s general practices since 2015 have the potential to improve healthcare efficiency. There is a paucity of information on the use of patient portals within the NHS general practices and the potential impact on healthcare utilisation. Aim: To investigate the association between patient portal registration and care utilisation (measured by the number of general practice consultations) among general practice patients. Design & setting: A longitudinal analysis using electronic health record data from the Clinical Practice Research Datalink (CPRD). Method: We analysed patients registered for patient portals (n = 284 666), aggregating their consultations 1 year before and 1 year after registration. We ran a multilevel negative binomial regression model to examine patient portal registration’s association with face-to-face and remote consultations. Results: Patients who registered to the portal had a small decrease in the total number of face-to-face consultations after registering to the patient portal (incidence rate ratio = 0.93, 95% confidence interval [CI] = 0.93 to 0.94). Patients who registered to the portal had an increase in the total number of remote consultations after registering to the portal (incidence rate ratio = 1.16, 95% CI = 1.15 to 1.18). Conclusion: The study found minor changes in consultation numbers post-patient portal registration, notably with an increase in remote consultations. While causality between portal registration and consultation number remains unclear, the potential link between patient portal use and healthcare utilisation warrants further investigation, especially within the NHS, where portal impacts are not well-studied. Detailed portal utilisation data could clarify this relationship. [ABSTRACT FROM AUTHOR]

Background: Long COVID potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. Methods: This study aims to assess the healthcare utilisation of individuals with long COVID. With the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. Results: We identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.29, 95% CI: 7.74–8.87), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.48–1.51). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58–29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73–16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.66, 95% CI = 7.20–8.15), with costs being 44% higher than the comparator group (cost ratio = 1.44, 95% CI: 1.39–1.50). The long COVID group costs approximately £2500 per person per year (predicted mean cost: £2562.50, 95% CI: £2335.60–£2819.22), and the comparator group costs £1500 (predicted mean cost: £1527.43, 95% CI: £1404.33–1664.45). Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. Conclusions: Long COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID. [ABSTRACT FROM AUTHOR]

Background: Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare. Aims: First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters. Methods: We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs. Results: 6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters. Conclusion: Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research. [ABSTRACT FROM AUTHOR]

Aims: Population‐wide, person‐level, linked electronic health record data are increasingly used to estimate epidemiology, guide resource allocation, and identify events in clinical trials. The accuracy of data from NHS Digital (now part of NHS England) for identifying hospitalization for heart failure (HHF), a key HF standard, is not clear. This study aimed to evaluate the accuracy of NHS Digital data for identifying HHF. Methods and results: Patients experiencing at least one HHF, as determined by NHS Digital data, and age‐ and sex‐matched patients not experiencing HHF, were identified from a prospective cohort study and underwent expert adjudication. Three code sets commonly used to identify HHF were applied to the data and compared with expert adjudication (I50: International Classification of Diseases‐10 codes beginning I50; OIS: Clinical Commissioning Groups Outcomes Indicator Set; and NICOR: National Institute for Cardiovascular Outcomes Research, used as the basis for the National Heart Failure Audit in England and Wales). Five hundred four patients underwent expert adjudication, of which 10 (2%) were adjudicated to have experienced HHF. Specificity was high across all three code sets in the first diagnosis position {I50: 96.2% [95% confidence interval (CI) 94.1–97.7%]; NICOR: 93.3% [CI 90.8–95.4%]; OIS: 95.6% [CI 93.3–97.2%]} but decreased substantially as the number of diagnosis positions expanded. Sensitivity [40.0% (CI 12.2–73.8%)] and positive predictive value (PPV) [highest with I50: 17.4% (CI 8.1–33.6%)] were low in the first diagnosis position for all coding sets. PPV was higher for the National Heart Failure Audit criteria, albeit modestly [36.4% (CI 16.6–62.2%)]. Conclusions: NHS Digital data were not able to accurately identify HHF and should not be used in isolation for this purpose. [ABSTRACT FROM AUTHOR]

Background: Temporary doctors, known as locums, are a key component of the medical workforce in the NHS but evidence on differences in quality and safety between locum and permanent doctors is limited. We aimed to examine differences in the clinical practice, and prescribing safety for locum and permanent doctors working in primary care in England. Methods: We accessed electronic health care records (EHRs) for 3.5 million patients from the CPRD GOLD database with linkage to Hospital Episode Statistics from 1st April 2010 to 31st March 2022. We used multi-level mixed effects logistic regression to compare consultations with locum and permanent GPs for several patient outcomes including general practice revisits; prescribing of antibiotics; strong opioids; hypnotics; A&E visits; emergency hospital admissions; admissions for ambulatory care sensitive conditions; test ordering; referrals; and prescribing safety indicators while controlling for patient and practice characteristics. Results: Consultations with locum GPs were 22% more likely to involve a prescription for an antibiotic (OR = 1.22 (1.21 to 1.22)), 8% more likely to involve a prescription for a strong opioid (OR = 1.08 (1.06 to 1.09)), 4% more likely to be followed by an A&E visit on the same day (OR = 1.04 (1.01 to 1.08)) and 5% more likely to be followed by an A&E visit within 1 to 7 days (OR = 1.05 (1.02 to 1.08)). Consultations with a locum were 12% less likely to lead to a practice revisit within 7 days (OR = 0.88 (0.87 to 0.88)), 4% less likely to involve a prescription for a hypnotic (OR = 0.96 (0.94 to 0.98)), 15% less likely to involve a referral (OR = 0.85 (0.84 to 0.86)) and 19% less likely to involve a test (OR = 0.81 (0.80 to 0.82)). We found no evidence that emergency admissions, ACSC admissions and eight out of the eleven prescribing safety indicators were different if patients were seen by a locum or a permanent GP. Conclusions: Despite existing concerns, the clinical practice and performance of locum GPs did not appear to be systematically different from that of permanent GPs. The practice and performance of both locum and permanent GPs is likely shaped by the organisational setting and systems within which they work. [ABSTRACT FROM AUTHOR]

Background: Palliative care aims to improve the quality of life for people with life-limiting illnesses. Advance care planning conversations that establish a patient's wishes and preferences for care are part of a person-centered approach. Internationally, electronic health record systems are digital interventions used to record and share patients' advance care plans across health care services and settings. They aim to provide tools that support electronic information sharing and care coordination. Within the United Kingdom, Electronic Palliative Care Coordination Systems (EPaCCS) are an example of this. Despite over a decade of policy promoting EPaCCS nationally, there has been limited implementation and consistently low levels of use by health professionals., Objective: The aim of this study is to explore the factors that influence the implementation of EPaCCS into routine clinical practice across different care services and settings in 2 major regions of England., Methods: A qualitative interview study design was used, guided by Normalization Process Theory (NPT). NPT explores factors affecting the implementation of complex interventions and consists of 4 primary components (coherence, cognitive participation, collective action, and reflexive monitoring). Health care and social care practitioners were purposively sampled based on their professional role and work setting. Individual web-based semistructured interviews were conducted. Data were analyzed using thematic framework analysis to explore issues which affected the implementation of EPaCCS across different settings at individual, team, organizational, and technical levels., Results: Participants (N=52) representing a range of professional roles were recruited across 6 care settings (hospice, primary care, care home, hospital, ambulatory, and community). In total, 6 themes were developed which mapped onto the 4 primary components of NPT and represented the multilevel influences affecting implementation. At an individual level, these included (1) EPaCCS providing a clear and distinct way of working and (2) collective contributions and buy-in. At a team and organizational level, these included (3) embedding EPaCCS into everyday practice and (4) championing driving implementation. At a technical level, these included (5) electronic functionality, interoperability, and access. Breakdowns in implementation at different levels led to variations in (6) confidence and trust in EPaCCS in terms of record accuracy and availability of access., Conclusions: EPaCCS implementation is influenced by individual, organizational, and technical factors. Key challenges include problems with access alongside inconsistent use and engagement across care settings. EPaCCS, in their current format as digital advance care planning systems are not consistently facilitating electronic information sharing and care coordination. A redesign of EPaCCS is likely to be necessary to determine configurations for their optimal implementation across different settings and locations. This includes supporting health care practitioners to document, access, use, and share information across multiple care settings. Lessons learned are relevant to other forms of digital advance care planning approaches being developed internationally., (©Andy Bradshaw, Jacqueline Birtwistle, Catherine J Evans, Katherine E Sleeman, Suzanne Richards, Robbie Foy, Pablo Millares Martin, Paul Carder, Matthew J Allsop, Maureen Twiddy. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 16.08.2024.)

IntroductionRespiratory sentinel surveillance systems leveraging computerised medical records (CMR) use phenotyping algorithms to identify cases of interest, such as acute respiratory infection (ARI). The Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC) is the English primary care-based sentinel surveillance network.AimThis study describes and validates the RSC's new ARI phenotyping algorithm.MethodsWe developed the phenotyping algorithm using a framework aligned with international interoperability standards. We validated our algorithm by comparing ARI events identified during the 2022/23 influenza season in England through use of both old and new algorithms. We compared clinical codes commonly used for recording ARI.ResultsThe new algorithm identified an additional 860,039 cases and excluded 52,258, resulting in a net increase of 807,781 cases (33.84%) of ARI compared to the old algorithm, with totals of 3,194,224 cases versus 2,386,443 cases. Of the 860,039 newly identified cases, the majority (63.7%) were due to identification of symptom codes suggestive of an ARI diagnosis not detected by the old algorithm. The 52,258 cases incorrectly identified by the old algorithm were due to inadvertent identification of chronic, recurrent, non-infectious and other non-ARI disease.ConclusionWe developed a new ARI phenotyping algorithm that more accurately identifies cases of ARI from the CMR. This will benefit public health by providing more accurate surveillance reports to public health authorities. This new algorithm can serve as a blueprint for other CMR-based surveillance systems wishing to develop similar phenotyping algorithms.

Background: Pharmacogenetics can impact patient care and outcomes through personalizing the selection of medicines, resulting in improved efficacy and a reduction in harmful side effects. Despite the existence of compelling clinical evidence and international guidelines highlighting the benefits of pharmacogenetics in clinical practice, implementation within the National Health Service in the United Kingdom is limited. An important barrier to overcome is the development of IT solutions that support the integration of pharmacogenetic data into health care systems. This necessitates a better understanding of the role of electronic health records (EHRs) and the design of clinical decision support systems that are acceptable to clinicians, particularly those in primary care., Objective: Explore the needs and requirements of a pharmacogenetic service from the perspective of primary care clinicians with a view to co-design a prototype solution., Methods: We used ethnographic and think-aloud observations, user research workshops, and prototyping. The participants for this study included general practitioners and pharmacists. In total, we undertook 5 sessions of ethnographic observation to understand current practices and workflows. This was followed by 3 user research workshops, each with its own topic guide starting with personas and early ideation, through to exploring the potential of clinical decision support systems and prototype design. We subsequently analyzed workshop data using affinity diagramming and refined the key requirements for the solution collaboratively as a multidisciplinary project team., Results: User research results identified that pharmacogenetic data must be incorporated within existing EHRs rather than through a stand-alone portal. The information presented through clinical decision support systems must be clear, accessible, and user-friendly as the service will be used by a range of end users. Critically, the information should be displayed within the prescribing workflow, rather than discrete results stored statically in the EHR. Finally, the prescribing recommendations should be authoritative to provide confidence in the validity of the results. Based on these findings we co-designed an interactive prototype, demonstrating pharmacogenetic clinical decision support integrated within the prescribing workflow of an EHR., Conclusions: This study marks a significant step forward in the design of systems that support pharmacogenetic-guided prescribing in primary care settings. Clinical decision support systems have the potential to enhance the personalization of medicines, provided they are effectively implemented within EHRs and present pharmacogenetic data in a user-friendly, actionable, and standardized format. Achieving this requires the development of a decoupled, standards-based architecture that allows for the separation of data from application, facilitating integration across various EHRs through the use of application programming interfaces (APIs). More globally, this study demonstrates the role of health informatics and user-centered design in realizing the potential of personalized medicine at scale and ensuring that the benefits of genomic innovation reach patients and populations effectively., (©Videha Sharma, John McDermott, Jessica Keen, Simon Foster, Pauline Whelan, William Newman. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.07.2024.)

Background: An outbreak of acute severe hepatitis of unknown aetiology (AS-Hep-UA) in children during 2022 was subsequently linked to infections with adenovirus-associated virus 2 and other 'helper viruses', including human adenovirus. It is possible that evidence of such an outbreak could be identified at a population level based on routine data captured by electronic health records (EHR)., Methods: We used anonymised EHR to collate retrospective data for all emergency presentations to Oxford University Hospitals NHS Foundation Trust in the UK, between 2016-2022, for all ages from 18 months and older. We investigated clinical characteristics and temporal distribution of presentations of acute hepatitis and of adenovirus infections based on laboratory data and clinical coding. We relaxed the stringent case definition adopted during the AS-Hep-UA to identify all cases of acute hepatitis with unknown aetiology (termed AHUA). We compared events within the outbreak period (defined as 1st Oct 2021-31 Aug 2022) to the rest of our study period., Results: Over the study period, there were 903,433 acute presentations overall, of which 391 (0.04%) were classified as AHUA. AHUA episodes had significantly higher critical care admission rates (p < 0.0001, OR = 41.7, 95% CI:26.3-65.0) and longer inpatient admissions (p < 0.0001) compared with the rest of the patient population. During the outbreak period, significantly more adults (≥ 16 years) were diagnosed with AHUA (p < 0.0001, OR = 3.01, 95% CI: 2.20-4.12), and there were significantly more human adenovirus (HadV) infections in children (p < 0.001, OR = 1.78, 95% CI:1.27-2.47). There were also more HAdV tests performed during the outbreak (p < 0.0001, OR = 1.27, 95% CI:1.17-1.37). Among 3,707 individuals who were tested for HAdV, 179 (4.8%) were positive. However, there was no evidence of more acute hepatitis or increased severity of illness in HadV-positive compared to negative cases., Conclusions: Our results highlight an increase in AHUA in adults coinciding with the period of the outbreak in children, but not linked to documented HAdV infection. Tracking changes in routinely collected clinical data through EHR could be used to support outbreak surveillance., (© 2024. The Author(s).)

Background: The National Health Service (NHS) Talking Therapies program treats people with common mental health problems in England according to "stepped care," in which lower-intensity interventions are offered in the first instance, where clinically appropriate. Limited resources and pressure to achieve service standards mean that program providers are exploring all opportunities to evaluate and improve the flow of patients through their service. Existing research has found variation in clinical performance and stepped care implementation across sites and has identified associations between service delivery and patient outcomes. Process mining offers a data-driven approach to analyzing and evaluating health care processes and systems, enabling comparison of presumed models of service delivery and their actual implementation in practice. The value and utility of applying process mining to NHS Talking Therapies data for the analysis of care pathways have not been studied., Objective: A better understanding of systems of service delivery will support improvements and planned program expansion. Therefore, this study aims to demonstrate the value and utility of applying process mining to NHS Talking Therapies care pathways using electronic health records., Methods: Routine collection of a wide variety of data regarding activity and patient outcomes underpins the Talking Therapies program. In our study, anonymized individual patient referral records from two sites over a 2-year period were analyzed using process mining to visualize the care pathway process by mapping the care pathway and identifying common pathway routes., Results: Process mining enabled the identification and visualization of patient flows directly from routinely collected data. These visualizations illustrated waiting periods and identified potential bottlenecks, such as the wait for higher-intensity cognitive behavioral therapy (CBT) at site 1. Furthermore, we observed that patients discharged from treatment waiting lists appeared to experience longer wait durations than those who started treatment. Process mining allowed analysis of treatment pathways, showing that patients commonly experienced treatment routes that involved either low- or high-intensity interventions alone. Of the most common routes, >5 times as many patients experienced direct access to high-intensity treatment rather than stepped care. Overall, 3.32% (site 1: 1507/45,401) and 4.19% (site 2: 527/12,590) of all patients experienced stepped care., Conclusions: Our findings demonstrate how process mining can be applied to Talking Therapies care pathways to evaluate pathway performance, explore relationships among performance issues, and highlight systemic issues, such as stepped care being relatively uncommon within a stepped care system. Integration of process mining capability into routine monitoring will enable NHS Talking Therapies service stakeholders to explore such issues from a process perspective. These insights will provide value to services by identifying areas for service improvement, providing evidence for capacity planning decisions, and facilitating better quality analysis into how health systems can affect patient outcomes., (©Elizabeth Yardley, Alice Davis, Chris Eldridge, Christos Vasilakis. Originally published in JMIR Mental Health (https://mental.jmir.org), 21.05.2024.)

Objectives: We aimed to use a large dataset to compare self-reported and primary care measures of insomnia symptom prevalence in England and establish whether they identify participants with similar characteristics., Design: Cross-sectional study with linked electronic health records (EHRs)., Setting: Primary care in England., Participants: 163 748 UK Biobank participants in England (aged 38-71 at baseline) with linked primary care EHRs., Outcome Measures: We compared the percentage of those self-reporting 'usually' having insomnia symptoms at UK Biobank baseline assessment (2006-2010) to those with a Read code for insomnia symptoms in their primary care records prior to baseline. We stratified prevalence in both groups by sociodemographic, lifestyle, sleep and health characteristics., Results: We found that 29% of the sample self-reported having insomnia symptoms, while only 6% had a Read code for insomnia symptoms in their primary care records. Only 10% of self-reported cases had an insomnia symptom Read code, while 49% of primary care cases self-reported having insomnia symptoms. In both primary care and self-reported data, prevalence of insomnia symptom cases was highest in females, older participants and those with the lowest household incomes. However, while snorers and risk takers were more likely to be a primary care case, they were less likely to self-report insomnia symptoms than non-snorers and non-risk takers., Conclusions: Only a small proportion of individuals experiencing insomnia symptoms have an insomnia symptom Read code in their primary care record. However, primary care data do provide a clinically meaningful measure of insomnia prevalence. In addition, the sociodemographic characteristics of people attending primary care with insomnia were consistent with those with self-reported insomnia, thus primary care records are a valuable data source for studying risk factors for insomnia. Further studies should replicate our findings in other populations and examine ways to increase discussions about sleep health in primary care., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Purpose: We aim to confirm the association between multiple deprivation and late diagnosis of glaucoma in England and to determine whether multiple deprivation is associated with rapid VF progression. Methods: A total of 602 439 records were obtained by retrospectively extracting Humphrey VFs from electronic medical records (EMRs) from five hospital eye service (HES) clinics in England in 2015. Index of Multiple Deprivation (IMD; a UK government measure for deprivation) was calculated from residential postcodes and patients were stratified into IMD "deciles". A patient was defined as having advanced VF loss if their Humphrey mean deviation (MD) was worse than −12 dB in the worse eye at their initial visit. At least ≥6 VFs and MD of worse than −1 dB per year were necessary to define a patient as having rapid VF progression. Results: In the most and least deprived IMD deciles, respectively, 18 (291/1616) and 11% (765/6951) of patients, had advanced VF loss at diagnosis, indicating a clear association. In the most and least deprived deciles, respectively (reference = fifth decile), the age‐corrected odds ratios (OR) for having advanced VF loss at entry into HES were 1.42 (95% Confidence Interval [CI]:1.21 to 1.67, p = 0.001) and 0.75 (95% [CI]: 0.66 to 0.85, p = 0.001). In the 15 094 patients with follow‐up data (median [interquartile range] of 6.9 [4.5,10.0] years) the proportion having the attribute of rapid VF progression did not differ across the IMD spectrum (age‐corrected ORs not differing from the reference value for the most and least deprived IMD decile. [p = 0.19 & p = 0.22]). Conclusion: Large‐scale VF data from English glaucoma clinics suggests deprivation is linked to the glaucoma severity at the time of diagnosis. Deprivation does not appear to be linked to a higher chance of having rapid VF progression, suggesting that hospitals provide equitable care for glaucoma patients. Keywords: visual field, index of multiple deprivation, late presentation of glaucoma. [ABSTRACT FROM AUTHOR]

Background: Life-saving emergency major resection of colorectal cancer (CRC) is a high-risk procedure. Accurate prediction of postoperative mortality for patients undergoing this procedure is essential for both healthcare performance monitoring and preoperative risk assessment. Risk-adjustment models for CRC patients often include patient and tumour characteristics, widely available in cancer registries and audits. The authors investigated to what extent inclusion of additional physiological and surgical measures, available through linkage or additional data collection, improves accuracy of risk models., Methods: Linked, routinely-collected data on patients undergoing emergency CRC surgery in England between December 2016 and November 2019 were used to develop a risk model for 90-day mortality. Backwards selection identified a 'selected model' of physiological and surgical measures in addition to patient and tumour characteristics. Model performance was assessed compared to a 'basic model' including only patient and tumour characteristics. Missing data was multiply imputed., Results: Eight hundred forty-six of 10 578 (8.0%) patients died within 90 days of surgery. The selected model included seven preoperative physiological and surgical measures (pulse rate, systolic blood pressure, breathlessness, sodium, urea, albumin, and predicted peritoneal soiling), in addition to the 10 patient and tumour characteristics in the basic model (calendar year of surgery, age, sex, ASA grade, TNM T stage, TNM N stage, TNM M stage, cancer site, number of comorbidities, and emergency admission). The selected model had considerably better discrimination compared to the basic model (C-statistic: 0.824 versus 0.783, respectively)., Conclusion: Linkage of disease-specific and treatment-specific datasets allowed the inclusion of physiological and surgical measures in a risk model alongside patient and tumour characteristics, which improves the accuracy of the prediction of the mortality risk for CRC patients having emergency surgery. This improvement will allow more accurate performance monitoring of healthcare providers and enhance clinical care planning., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Objective: To describe the experiences and opinions of general practitioners (GPs) in England regarding patients having access to their full online GP health records., Design: Convenience sample, online survey., Participants: 400 registered GPs in England., Main Outcome Measures: Investigators measured GPs' experiences and opinions about online record access (ORA), including patient care and their practice., Results: A total of 400 GPs from all regions of England responded. A minority (130, 33%) believed ORA was a good idea. Most GPs believed a majority of patients would worry more (364, 91%) or find their GP records more confusing than helpful (338, 85%). Most GPs believed a majority of patients would find significant errors in their records (240, 60%), would better remember their care plan (280, 70%) and feel more in control of their care (243, 60%). The majority believed they will/already spend more time addressing patients' questions outside of consultations (357, 89%), that consultations will/already take significantly longer (322, 81%) and that they will be/already are less candid in their documentation (289, 72%) after ORA. Nearly two-thirds of GPs believed ORA would increase their litigation (246, 62%)., Conclusions: Similar to clinicians in other countries, GPs in our sample were sceptical of ORA, believing patients would worry more and find their records more confusing than helpful. Most GPs also believed the practice would exacerbate work burdens. However, the majority of GPs in this survey also agreed there were multiple benefits to patients having online access to their primary care health records. The findings of this survey also contribute to a growing body of contrastive research from countries where ORA is advanced, demonstrating clinicians are sceptical while studies indicate patients appear to derive multiple benefits., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Addressing the wider determinants of mental health alongside psychological therapy could improve mental health service outcomes and population mental health., Objectives: To estimate the effectiveness of an enhanced 'Improving Access to Psychological Therapies' (IAPT) mental health service compared with traditional IAPT in England. Alongside traditional therapy treatment, the enhanced service included well-being support and community service links., Design: A real-world evaluation using IAPT's electronic health records., Setting: Three National Health Service IAPT services in England., Participants: Data from 17 642 service users classified as having a case of depression and/or anxiety at baseline., Intervention: We compared the enhanced IAPT service (intervention) to an IAPT service in a different region providing traditional treatment only (geographical control), and the IAPT service with traditional treatment before additional support was introduced (historical control)., Primary Outcome Measures: Patient Health Questionnaire-9 (PHQ-9) Depression Scale (score range: 0-27) and Generalised Anxiety Disorder-7 (GAD-7) Anxiety Scale (score range: 0-21); for both, lower scores indicate better mental health. Propensity scores were used to estimate inverse probability of treatment weights, subsequently used in mixed effects regression models., Results: Small improvements (mean, 95% CI) were observed for PHQ-9 (depression) (-0.21 to -0.32 to -0.09) and GAD-7 (anxiety) (-0.23 to -0.34 to -0.13) scores in the intervention group compared with the historical control. There was little evidence of statistically significant differences between intervention control and geographical control., Conclusions: Embedding additional health and well-being (H&W) support into standard IAPT services may lead to improved mental health outcomes. However, the lack of improved outcomes compared with the geographical control may instead reflect a more general improvement to the intervention IAPT service. It is not clear from our findings whether an IAPT service with additional H&W support is clinically superior to traditional IAPT models., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Objectives: To address the lack of individual-level socioeconomic information in electronic healthcare records, we linked the 2011 census of England and Wales to patient records from a large mental healthcare provider. This paper describes the linkage process and methods for mitigating bias due to non-matching., Setting: South London and Maudsley NHS Foundation Trust (SLaM), a mental healthcare provider in Southeast London., Design: Clinical records from SLaM were supplied to the Office of National Statistics for linkage to the census through a deterministic matching algorithm. We examined clinical (International Classification of Disease-10 diagnosis, history of hospitalisation, frequency of service contact) and socio-demographic (age, gender, ethnicity, deprivation) information recorded in Clinical Record Interactive Search (CRIS) as predictors of linkage success with the 2011 census. To assess and adjust for potential biases caused by non-matching, we evaluated inverse probability weighting for mortality associations., Participants: Individuals of all ages in contact with SLaM up until December 2019 (N=459 374)., Outcome Measures: Likelihood of mental health records' linkage to census., Results: 220 864 (50.4%) records from CRIS linked to the 2011 census. Young adults (prevalence ratio (PR) 0.80, 95% CI 0.80 to 0.81), individuals living in more deprived areas (PR 0.78, 95% CI 0.78 to 0.79) and minority ethnic groups (eg, Black African, PR 0.67, 0.66 to 0.68) were less likely to match to census. After implementing inverse probability weighting, we observed little change in the strength of association between clinical/demographic characteristics and mortality (eg, presence of any psychiatric disorder: unweighted PR 2.66, 95% CI 2.52 to 2.80; weighted PR 2.70, 95% CI 2.56 to 2.84)., Conclusions: Lower response rates to the 2011 census among people with psychiatric disorders may have contributed to lower match rates, a potential concern as the census informs service planning and allocation of resources. Due to its size and unique characteristics, the linked data set will enable novel investigations into the relationship between socioeconomic factors and psychiatric disorders., Competing Interests: Competing interests: MH is principal investigator of the RADAR-CNS, a precompetitive public–private collaboration on mobile health funded by the Innovative Medicine Initiative with cash and in-kind contributions paid to the university from Janssen, Lundbeck, UCB, MSD and Biogen. RS declares research support in the last 3 years from Janssen, GSK and Takeda., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

Introduction: Heart failure (HF) is increasingly common and associated with excess morbidity, mortality, and healthcare costs. Treatment of HF can alter the disease trajectory and reduce clinical events in HF. However, many cases of HF remain undetected until presentation with more advanced symptoms, often requiring hospitalisation. Predicting incident HF is challenging and statistical models are limited by performance and scalability in routine clinical practice. An HF prediction model implementable in nationwide electronic health records (EHRs) could enable targeted diagnostics to enable earlier identification of HF., Methods and Analysis: We will investigate a range of development techniques (including logistic regression and supervised machine learning methods) on routinely collected primary care EHRs to predict risk of new-onset HF over 1, 5 and 10 years prediction horizons. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation (training and testing) and the CPRD-AURUM dataset for external validation. Both comprise large cohorts of patients, representative of the population of England in terms of age, sex and ethnicity. Primary care records are linked at patient level to secondary care and mortality data. The performance of the prediction model will be assessed by discrimination, calibration and clinical utility. We will only use variables routinely accessible in primary care., Ethics and Dissemination: Permissions for CPRD-GOLD and CPRD-AURUM datasets were obtained from CPRD (ref no: 21&#95;000324). The CPRD ethical approval committee approved the study. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences., Trial Registration Details: The study was registered on Clinical Trials.gov (NCT05756127). A systematic review for the project was registered on PROSPERO (registration number: CRD42022380892)., Competing Interests: Competing interests: YMN reports a study grant from Bayer, outside the submitted work. JM reports personal fees from Bayer. He is the President of the Primary Care Cardiovascular Society. CG reports personal fees from AstraZeneca, Amgen, Bayer, Boehrinher-Ingelheim, Daiichi Sankyo, Vifor, Pharma, Menarini, Wondr Medical, Raisio Group and Oxford University Press. He has received educational and research grants from BMS, Abbott inc., the British Heart Foundation, National Institute of Health Research, Horizon 2020, and from the European Society of Cardiology, outside the submitted work. All other authors declare no competing interests., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: The National Congenital Anomaly and Rare Disease Registration Service (NCARDRS), part of National Disease Registration Service in National Health Service England, quality assures, curates and analyses individual data on the pregnancies, fetuses, babies, children and adults with congenital anomalies and rare diseases across England. The congenital anomaly (CA) register provides a resource for patients and their families, clinicians, researchers and public health professionals in furthering the understanding of CAs., Participants: NCARDRS registers CAs occurring in babies born alive and stillborn, fetal losses and terminations in England. NCARDRS collects data from secondary and tertiary healthcare providers, private providers and laboratories covering fetal medicine, maternity or paediatric services. Data describe the pregnancy, mother, baby and anomaly. Established in 2015, NCARDRS expanded CA registration coverage from 22% of total births in England in 2015 to national coverage, which was achieved in 2018. Prior to 2015, data collection was performed independently by regional registers in England; these data are also held by NCARDRS., Findings to Date: NCARDRS registers approximately 21 000 babies with CAs per year with surveillance covering around 600 000 total births, the largest birth coverage for a CA register globally. Data on prevalence, risk factors and survival for children with CAs are available. Data have been used in several peer-reviewed publications. Birth prevalence statistics, including public health indicators such as the association with maternal age, infant and perinatal mortality, are published annually. NCARDRS supports clinical audit for screening programmes and service evaluation., Future Plans: NCARDRS provides a valuable resource for the understanding of the epidemiology, surveillance, prevention and treatment of CAs. Currently, approximately 21 000 new registrations of babies or fetuses with suspected or confirmed CAs are added each year. Identifiers are collected, enabling linkage to routinely collected healthcare and population statistics, further enhancing the value of the data., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)