Validation of GPT-4 for clinical event classification: A comparative analysis with ICD codes and human reviewers.

BACKGROUND AND AIM: Effective clinical event classification is essential for clinical research and quality improvement. The validation of artificial intelligence (AI) models like Generative Pre-trained Transformer 4 (GPT-4) for this task and comparison with conventional methods remains unexplored. METHODS: We evaluated the performance of the GPT-4 model for classifying gastrointestinal (GI) bleeding episodes from 200 medical discharge summaries and compared the results with human review and an International Classification of Diseases (ICD) code-based system. The analysis included accuracy, sensitivity, and specificity evaluation, using ground truth determined by physician reviewers. RESULTS: GPT-4 exhibited an accuracy of 94.4% in identifying GI bleeding occurrences, outperforming ICD codes (accuracy 63.5%, P < 0.001). GPT-4's accuracy was either slightly lower or statistically similar to individual human reviewers (Reviewer 1: 98.5%, P < 0.001; Reviewer 2: 90.8%, P = 0.170). For location classification, GPT-4 achieved accuracies of 81.7% and 83.5% for confirmed and probable GI bleeding locations, respectively, with figures that were either slightly lower or comparable with those of human reviewers. GPT-4 was highly efficient, analyzing the dataset in 12.7 min at a cost of 21.2 USD, whereas human reviewers required 8-9 h each. CONCLUSION: Our study indicates GPT-4 offers a reliable, cost-efficient, and faster alternative to current clinical event classification methods, outperforming the conventional ICD coding system and performing comparably to individual expert human reviewers. Its implementation could facilitate more accurate and granular clinical research and quality audits. Future research should explore scalability, prompt and model tuning, and ethical implications of high-performance AI models in clinical data processing.

The Impact of Point-of-Care Testing for Influenza on Antimicrobial Stewardship (PIAMS) in UK Primary Care: Protocol for a Mixed Methods Study.

BACKGROUND: Molecular point-of-care testing (POCT) used in primary care can inform whether a patient presenting with an acute respiratory infection has influenza. A confirmed clinical diagnosis, particularly early in the disease, could inform better antimicrobial stewardship. Social distancing and lockdowns during the COVID-19 pandemic have disturbed previous patterns of influenza infections in 2021. However, data from samples taken in the last quarter of 2022 suggest that influenza represents 36% of sentinel network positive virology, compared with 24% for respiratory syncytial virus. Problems with integration into the clinical workflow is a known barrier to incorporating technology into routine care. OBJECTIVE: This study aims to report the impact of POCT for influenza on antimicrobial prescribing in primary care. We will additionally describe severe outcomes of infection (hospitalization and mortality) and how POCT is integrated into primary care workflows. METHODS: The impact of POCT for influenza on antimicrobial stewardship (PIAMS) in UK primary care is an observational study being conducted between December 2022 and May 2023 and involving 10 practices that contribute data to the English sentinel network. Up to 1000 people who present to participating practices with respiratory symptoms will be swabbed and tested with a rapid molecular POCT analyzer in the practice. Antimicrobial prescribing and other study outcomes will be collected by linking information from the POCT analyzer with data from the patient's computerized medical record. We will collect data on how POCT is incorporated into practice using data flow diagrams, unified modeling language use case diagrams, and Business Process Modeling Notation. RESULTS: We will present the crude and adjusted odds of antimicrobial prescribing (all antibiotics and antivirals) given a POCT diagnosis of influenza, stratifying by whether individuals have a respiratory or other relevant diagnosis (eg, bronchiectasis). We will also present the rates of hospital referrals and deaths related to influenza infection in PIAMS study practices compared with a set of matched practices in the sentinel network and the rest of the network. We will describe any difference in implementation models in terms of staff involved and workflow. CONCLUSIONS: This study will generate data on the impact of POCT testing for influenza in primary care as well as help to inform about the feasibility of incorporating POCT into primary care workflows. It will inform the design of future larger studies about the effectiveness and cost-effectiveness of POCT to improve antimicrobial stewardship and any impact on severe outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46938.

Prevalence of electronic screening for sepsis in National Health Service acute hospitals in England.

Sepsis is a worldwide public health problem. Rapid identification is associated with improved patient outcomes-if followed by timely appropriate treatment. OBJECTIVES: Describe digital sepsis alerts (DSAs) in use in English National Health Service (NHS) acute hospitals. METHODS: A Freedom of Information request surveyed acute NHS Trusts on their adoption of electronic patient records (EPRs) and DSAs. RESULTS: Of the 99 Trusts that responded, 84 had an EPR. Over 20 different EPR system providers were identified as operational in England. The most common providers were Cerner (21%). System C, Dedalus and Allscripts Sunrise were also relatively common (13%, 10% and 7%, respectively). 70% of NHS Trusts with an EPR responded that they had a DSA; most of these use the National Early Warning Score (NEWS2). There was evidence that the EPR provider was related to the DSA algorithm. We found no evidence that Trusts were using EPRs to introduce data driven algorithms or DSAs able to include, for example, pre-existing conditions that may be known to increase risk.Not all Trusts were willing or able to provide details of their EPR or the underlying algorithm. DISCUSSION: The majority of NHS Trusts use an EPR of some kind; many use a NEWS2-based DSA in keeping with national guidelines. CONCLUSION: Many English NHS Trusts use DSAs; even those using similar triggers vary and many recreate paper systems. Despite the proliferation of machine learning algorithms being developed to support early detection of sepsis, there is little evidence that these are being used to improve personalised sepsis detection.

Assessing the Clinical and Socioeconomic Burden of Respiratory Syncytial Virus in Children Aged Under 5 Years in Primary Care: Protocol for a Prospective Cohort Study in England and Report on the Adaptations of the Study to the COVID-19 Pandemic.

BACKGROUND: Respiratory syncytial virus (RSV) commonly causes lower respiratory tract infections and hospitalization in children. In 2019-2020, the Europe-wide RSV ComNet standardized study protocol was developed to measure the clinical and socioeconomic disease burden of RSV infections among children aged <5 years in primary care. RSV has a recognized seasonality in England. OBJECTIVE: We aimed to describe (1) the adaptations of the RSV ComNet standardized study protocol for England and (2) the challenges of conducting the study during the COVID-19 pandemic. METHODS: This study was conducted by the Oxford-Royal College of General Practitioners Research and Surveillance Centre-the English national primary care sentinel network. We invited all (N=248) general practices within the network that undertook virology sampling to participate in the study by recruiting eligible patients (registered population: n=3,056,583). Children aged <5 years with the following case definition of RSV infection were included in the study: those consulting a health care practitioner in primary care with symptoms meeting the World Health Organization's definition of acute respiratory illness or influenza-like illness who have laboratory-confirmed RSV infection. The parents/guardians of these cases were asked to complete 2 previously validated questionnaires (14 and 30 days postsampling). A sample size of at least 100 RSV-positive cases is required to estimate the percentage of children that consult in primary care who need hospitalization. Assuming a swab positivity rate of 20% in children aged <5 years, we estimated that 500 swabs are required. We adapted our method for the pandemic by extending sampling planned for winter 2020-2021 to a rolling data collection, allowing verbal consent and introducing home swabbing because of increased web-based consultations during the COVID-19 pandemic. RESULTS: The preliminary results of the data collection between International Organization for Standardization (ISO) weeks 1-41 in 2021 are described. There was no RSV detected in the winter of 2020-2021 through the study. The first positive RSV swab collected through the sentinel network in England was collected in ISO week 17 and then every week since ISO week 25. In total, 16 (N=248, 6.5%) of the virology-sampling practices volunteered to participate; these were high-sampling practices collecting the majority of eligible swabs across the sentinel network-200 (43.8%) out of 457 swabs, of which 54 (N=200, 27%) were positive for RSV. CONCLUSIONS: Measures to control the COVID-19 pandemic meant there was no circulating RSV last winter; however, RSV has circulated out of season, as detected by the sentinel network. The sentinel network practices have collected 40% (200/500) of the required samples, and 27% (54/200) were RSV positive. We have demonstrated the feasibility of implementing a European-standardized RSV disease burden study protocol in England during a pandemic, and we now need to recruit to this adapted protocol. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/38026.

Computer-generated structured electronic medical records are preferable to conventional medical records for patients with acute abdominal pain - a prospective, double-blinded study.

OBJECTIVES: Structured medical records improve readability and ensure the inclusion of information necessary for correct diagnosis and treatment. This is the first study to assess the quality of computer-generated structured medical records by comparing them to conventional medical records on patients with acute abdominal pain. MATERIALS AND METHODS: A prospective double-blinded study was conducted in a tertiary referral center emergency department between January 2018 and June 2018. Patients were examined by emergency department physicians and by experience and inexperienced researcher. The researchers used a new electronical medical records system, which gathered data during the examination and the system generate structured medical records containing natural language. Conventional medical records dictated by physician and computer-generated medical records were compared by a group of independent clinicians. RESULTS: Ninety-nine patients were included. The overall quality of the computer-generated medical records was better than the quality of conventional human-generated medical records - the structure was similar or better in 99% of cases and the readability was similar or better in 86% of cases, p < 0.001. The quality of medical history, current illness, and findings of physical examinations were likewise better with the computer-generated recording. The results were similar when patients were examined by experienced or inexperienced researcher using the computer-generated recording. DISCUSSION: The quality of computer-generated structured medical records was superior to that of conventional medical records. The quality remained similar regardless of the researcher's level of experience. The system allows automatic risk scoring and easy access for quality control of patient care. We therefore consider that it would be useful in wider practice.

Comparative Effectiveness of Direct-Acting Antivirals for Posttraumatic Stress Disorder in Veterans Affairs Patients With Hepatitis C Virus Infection.

We recently conducted an exploratory study that indicated that several direct-acting antivirals (DAAs), highly effective medications for hepatitis C virus (HCV) infection, were also associated with improvement in posttraumatic stress disorder (PTSD) among a national cohort of US Department of Veterans Affairs (VA) patients treated between October 1, 1999, and September 30, 2019. Limiting the same cohort to patients with PTSD and HCV, we compared the associations of individual DAAs with PTSD symptom improvement using propensity score weighting. After identifying patients who had available baseline and endpoint PTSD symptom data as measured with the PTSD Checklist (PCL), we compared changes over the 8-12 weeks of DAA treatment. The DAAs most prescribed in conjunction with PCL measurement were glecaprevir/pibrentasvir (GLE/PIB; n = 54), sofosbuvir/velpatasvir (SOF/VEL; n = 54), and ledipasvir/sofosbuvir (LDV/SOF; n = 145). GLE/PIB was superior to LDV/SOF, with a mean difference in improvement of 7.3 points on the PCL (95% confidence interval (CI): 1.1, 13.6). The mean differences in improvement on the PCL were smaller between GLE/PIB and SOF/VEL (3.0, 95% CI: -6.3, 12.2) and between SOF/VEL and LDV/SOF (4.4, 95% CI: -2.4, 11.2). While almost all patients were cured of HCV (92.5%) regardless of the agent received, PTSD outcomes were superior for those receiving GLE/PIB compared with those receiving LDV/SOF, indicating that GLE/PIB may merit further investigation as a potential PTSD treatment.

Value of the Electronic Medical Record for Hospital Care: Update From the Literature.

BACKGROUND: Electronic records could improve quality and efficiency of health care. National and international bodies propagate this belief worldwide. However, the evidence base concerning the effects and advantages of electronic records is questionable. The outcome of health care systems is influenced by many components, making assertions about specific types of interventions difficult. Moreover, electronic records itself constitute a complex intervention offering several functions with possibly positive as well as negative effects on the outcome of health care systems. OBJECTIVE: The aim of this review is to summarize empirical studies about the value of electronic medical records (EMRs) for hospital care published between 2010 and spring 2019. METHODS: The authors adopted their method from a series of literature reviews. The literature search was performed on MEDLINE with "Medical Record System, Computerized" as the essential keyword. The selection process comprised 2 phases looking for a consent of both authors. Starting with 1345 references, 23 were finally included in the review. The evaluation combined a scoring of the studies' quality, a description of data sources in case of secondary data analyses, and a qualitative assessment of the publications' conclusions concerning the medical record's impact on quality and efficiency of health care. RESULTS: The majority of the studies stemmed from the United States (19/23, 83%). Mostly, the studies used publicly available data ("secondary data studies"; 17/23, 74%). A total of 18 studies analyzed the effect of an EMR on the quality of health care (78%), 16 the effect on the efficiency of health care (70%). The primary data studies achieved a mean score of 4.3 (SD 1.37; theoretical maximum 10); the secondary data studies a mean score of 7.1 (SD 1.26; theoretical maximum 9). From the primary data studies, 2 demonstrated a reduction of costs. There was not one study that failed to demonstrate a positive effect on the quality of health care. Overall, 9/16 respective studies showed a reduction of costs (56%); 14/18 studies showed an increase of health care quality (78%); the remaining 4 studies missed explicit information about the proposed positive effect. CONCLUSIONS: This review revealed a clear evidence about the value of EMRs. In addition to an awesome majority of economic advantages, the review also showed improvements in quality of care by all respective studies. The use of secondary data studies has prevailed over primary data studies in the meantime. Future work could focus on specific aspects of electronic records to guide their implementation and operation.

Adverse events of interest following influenza vaccination, a comparison of cell culture-based with egg-based alternatives: English sentinel network annual report paper 2019/20.

BACKGROUND: The cell-based quadrivalent influenza vaccine (QIVc) is now offered as an alternative to egg-based quadrivalent (QIVe) and adjuvanted trivalent (aTIV) influenza vaccines in the UK. While post-licensure studies show non-inferiority of cell-based vaccines, it is not known how its safety profile compares to other types of vaccines in real-world use. METHODS: We conducted a retrospective cohort study using computerised medical records from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network database. We used a self-controlled case series design and calculated the relative incidence (RI) of adverse events of interest (AEIs) over different risk periods. We then compared the RIs of AEIs within seven days of vaccination overall and between QIVc and QIVe in the 18-64 years age group, and between QIVc and aTIV in the ≥65 years age group. FINDINGS: The majority of AEIs occurred within seven days of vaccination, and a seasonal effect was observed. Using QIVc as the reference group, QIVe showed similar incidence of AEIs whereas live attenuated influenza vaccine (LAIV) and aTIV had lower incidence of AEIs. In the stratified analyses, QIVe and aTIV were associated with a 16% lower incidence of AEIs in the seven days post-vaccination in both the 18-64 years and ≥65 years age groups. INTERPRETATION: Routine sentinel network data allow comparisons of safety profiles of equally suitable seasonal influenza vaccines. The higher incidence of AEIs associated with QIVc suggest monitoring of several seasons would allow robust comparisons to be made. FUNDING: Public Health England.

PRINCIPLE trial demonstrates scope for in-pandemic improvement in primary care antibiotic stewardship: a retrospective sentinel network cohort study.

BACKGROUND: The Platform Randomised trial of INterventions against COVID-19 In older peoPLE (PRINCIPLE) has provided in-pandemic evidence that azithromycin and doxycycline were not beneficial in the early primary care management of coronavirus 2019 disease (COVID-19). AIM: To explore the extent of in-pandemic azithromycin and doxycycline use, and the scope for trial findings impacting on practice. DESIGN & SETTING: Crude rates of prescribing and respiratory tract infections (RTI) in 2020 were compared with 2019, using the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). METHOD: Negative binomial models were used to compare azithromycin and doxycycline prescribing, lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), and influenza-like illness (ILI) in 2020 with 2019; reporting incident rate ratios (IRR) between years, and 95% confidence intervals (95% CI). RESULTS: Azithromycin prescriptions increased 7% in 2020 compared with 2019, whereas doxycycline decreased by 7%. Concurrently, LRTI and URTI incidence fell by over half (58.3% and 54.4%, respectively) while ILI rose slightly (6.4%). The overall percentage of RTI-prescribed azithromycin rose from 0.51% in 2019 to 0.72% in 2020 (risk difference 0.214%; 95% CI = 0.211 to 0.217); doxycycline rose from 11.86% in 2019 to 15.79% in 2020 (risk difference 3.93%; 95% CI = 3.73 to 4.14). The adjusted IRR showed azithromycin prescribing was 22% higher in 2020 (IRR = 1.22; 95% CI = 1.19 to 1.26; P<0.0001). For every unit rise in confirmed COVID-19 there was an associated 3% rise in prescription (IRR = 1.03; 95% CI = 1.02 to 1.03; P<0.0001); whereas these measures were static for doxycycline. CONCLUSION: PRINCIPLE demonstrates scope for improved antimicrobial stewardship during a pandemic.

Role of real-world digital data for orthopedic implant automated surveillance: a systematic review.

INTRODUCTION: Data collection automation through the reuse of real-world digital data from clinical data warehouses (CDW) could represent a great opportunity to improve medical device monitoring. For instance, this approach is starting to be used for the design of automated decision support systems for joint replacement monitoring. However, a number of obstacles remains, such as data quality and interoperability through the use of common and regularly updated terminologies, and the use of a Unique Device Identifier (UDI). AREAS COVERED: To present the existing models of automated surveillance of orthopedic devices, a systematic review of initiatives using real-world digital health data to monitor joint replacement surgery was performed following the PRISMA 2020 guidelines. The main objective was to identify the data sources, the target populations, the population size, the device location, and the main results of studies on such initiatives. EXPERT OPINION: Analysis of the identified studies showed that real-world digital data offer many opportunities for improving the automation of monitoring in orthopedics. The contribution of real-world data, especially through natural language processing, UDI use in CDW and the integration of device databases, is needed for automated and more robust health surveillance.

A commentary on the value of hospital data for covid-19 pandemic surveillance and planning.

Hospital data for covid-19 surveillance, planning and modelling are challenging to find worldwide in public aggregation portals. Detailed covid-19 hospital data provides insights into covid-19's health burden including identifying which sociodemographic groups are at greatest risk of covid-19 morbidity and mortality. Timely hospital data is the best source of information for actionable forecasts and projection models of hospital capacity, including critical resources such as intensive care unit beds and ventilators that take time to plan or procure. A challenge to generate timely and detailed hospital data is the reliance on separation or discharge abstracts and census counts. What are needed are well-maintained lists of patients hospitalized with covid-19. From the standpoint of public health and health services researchers and practitioners, we describe the role of hospital data for studying covid-19, why admission data are hard to find, and how improved data infrastructure can meet surveillance and planning needs in the near future. Modern hospital electronic health records can create covid-19 patient lists and these decision support tools are increasingly used for research. These tools can generate patient lists that are transmitted and combined with public health data systems.

Arquitectura de información para la gestión de la historia clínica digital en oftalmopediatría / Information architecture for the management of computerized medical records for pediatric-ophthalmological specialty

RESUMEN Introducción: la Historia Clínica es un instrumento que contiene la información del paciente que debe ser procesable, almacenada y trasmitida de forma segura y accesible, por lo que resulta necesario el empleo de recursos y estrategias para facilitar el cuidado de la salud, entre las que puede figurar un software. Objetivo: desarrollar la arquitectura de información para la gestión de una historia clínica electrónica para uso en la consulta de Oftalmopediatría del Hospital Pediátrico Provincial Docente "Pepe Portilla" de Pinar del Río. Métodos: estudio cuali-cuantitativo, con métodos teóricos y empíricos para analizar la evolución y desarrollo de la historia clínica de Oftalmopediatría, caracterizar la situación actual, así como la introducción de las tecnologías de la información y las comunicaciones en esta disciplina en Cuba. Resultados: se creó un prototipo de software de gestión de historia clínica electrónica en Oftalmopediatría, con un gran impacto social para las entidades donde se implemente el sistema, que beneficia tanto al paciente como a los profesionales. Conclusión: la implementación de una herramienta informática es una decisión estratégica que puede simplificar el trabajo, optimizar tiempo, recursos, y mejorar en organización, gestión y seguridad.

ABSTRACT Introduction: the Medical History is a tool that contains the information of patients, which should able to be processed, stored and transmitted in a safe and accessible way, thus it is necessary to use resources and strategies to facilitate healthcare services, among which software designs can be included. Objective: to develop the information architecture for the management of an computerized medical record to be used in the Pediatric Ophthalmology Office at Pepe Portilla Provincial Pediatric Teaching Hospital in Pinar del Rio. Methods: a qualitative-quantitative study was conducted, applying theoretical and empirical methods to analyze the evolution and development of a pediatric-ophthalmological history, to characterize the current situation, as well as the introduction of information and communication technologies into this specialty in Cuba. Results: the design of a prototype of software for the management of a computerized medical record in the Pediatric Ophthalmology Office, with a great social impact for the healthcare institutions where the system is implemented, which benefit both the patient and the professionals. Conclusion: the implementation of a computerized tool is a strategic decision that can simplify work, optimize time and resources, improving organizational process, management and safety.

Componente de software para el proceso de solicitudes de evaluación de estudios neurofisiológicos para el Sistema XAVIA HIS / Software component for the process of requests for evaluation of neurophysiological studies in the XAVIA HIS System

Introducción: la especialidad de neurofisiología se ocupa del estudio, la evaluación del sistema nervioso (central y periférico), su modificación funcional, de los órganos sensoriales y musculares, tanto en condiciones normales como patológicas. La normalización de la información sobre esta especialidad es compleja, porque cada institución hospitalaria cubana tiene sus propias fuentes de gestión. Esta situación dificulta la homogeneización de los datos, la recopilación de información estadística y su inclusión en el registro médico digital único del paciente cubano. Objetivo: presentar un componente de software que informatiza las solicitudes de estudios neurofisiológicos para las instituciones de salud cubanas, que utilizan el Sistema de Información Hospitalaria XAVIA HIS. Método: se entrevistaron a especialistas del Centro Cubano de Neurociencias CNEURO, para definir el proceso de gestión de las solicitudes de estudios neurofisiológicos. Se aplicó la entrevista semiestructurada, que permitió la adaptación a los entrevistados para aclarar términos, identificar ambigüedades y reducir los formalismos. Para el desarrollo se utilizaron herramientas de software libre (JBoss Developer Studio como entorno integrado de desarrollo, Java como lenguaje de programación orientado a objetos, JBoss como servidor de aplicaciones y PostgreSQL v9.4 como sistema de gestión de bases de datos), que garantizan las políticas de desarrollo de software y soberanía tecnológica de Cuba. Resultados: las solicitudes de estudios neurofisiológicos en el sistema XAVIA HIS, se informatizaron a partir de un componente de software, basado en el estándar HL7-CDA para documentos clínicos. Conclusiones: los especialistas en neurofisiología disponen de funcionalidades para la estandarización, almacenamiento y gestión de la información de la especialidad, lo cual conduce al enriquecimiento de la historia clínica digital del sistema XAVIA HIS(AU)

Introduction: The Neurophysiology specialty deals with the nervous system (central and peripheral) study and assessment and its functional modification and the sense and muscular organs, both in normal and pathological conditions. Information standardization on this specialty is complex because each Cuban hospital institution has its own management sources. This situation makes it difficult to homogenize the data, gather statistical information and include it in the Cuban patient unique digital medical record. Objective: Describe a software component that computerizes neurophysiological studies requests for Cuban health institutions that use the XAVIA HIS Hospital Information System. Method: Specialists from the Cuban Neuroscience Center CNEURO were interviewed to define the neurophysiological studies requests management process. The semi-structured interview was applied, which allowed the adaptation to the interviewees in order to clarify terms, identify ambiguities and reduce formalisms. Free software tools were used for development (JBoss Developer Studio as an integrated development environment, Java as an object-oriented programming language, JBoss as an application server and PostgreSQL v9.4 as a database management system) that guarantee the Cuban software development and technological sovereignty policies. Results: Neurophysiological studies requests in the XAVIA HIS system were computerized using a software component, based on the HL7-CDA standard for clinical documents. Conclusions: Neurophysiology specialists have functionalities for the specialty information standardization, storage, and management, which leads to the XAVIA HIS system digital medical record enrichment(AU)

Evolution of polypharmacy in a spanish population (2005-2015): A database study.

PURPOSE: To analyze the evolution of the prevalence of polypharmacy and excessive polypharmacy in a Spanish population, and to improve the identification of patients with polypharmacy. METHODS: A descriptive, annual cross-sectional observational study was carried out. PATIENTS: individuals over 14 years of age included in a multiregional primary care database of the Spanish population (BIFAP). ANALYSIS: prescription data. Period 2005-2015. VARIABLES: proportion of patients with polypharmacy (simultaneous prescription of ≥5 drugs) and excessive polypharmacy (≥10 drugs) for at least 6 months, according to sex and age groups. A trend analysis of the studied period was performed (overall, and by sex and age groups). RESULTS: The data are reported on a comparative basis (2005 vs 2015). Number of patients analyzed: 2664743 vs 4 002 877. The prevalence of polypharmacy increased significantly (2.5% vs 8.9%, P-value for trend <0.001), being greater in females throughout the study period and in the group aged ≥80 years (P-value for trends <0.001). The prevalence of excessive polypharmacy also increased significantly (0.1% vs 1%, P-value for trend <0.001), being higher in the group aged ≥80 years (P-value for trend <0.001). The proportion of patients with no chronic treatment decreased (80.2% vs 63.1%). CONCLUSIONS: The prevalence of polypharmacy in this Spanish population has tripled in the period 2005-2015, while excessive polypharmacy has increased 10-fold. These increments are seen in both sexes and in all age groups, particularly in individuals over 80 years of age. The proportion of patients without chronic treatments has decreased.

An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment.

BACKGROUND: We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome. METHODS: Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (n=91), multivariable binary logistic regression analysis models were used to determine the independent associates with a delayed response (taking ≥6.0 hours for entering a glucose range of 70 to 180 mg/dL). The CII protocol was adjusted in silico according to the EHR-based parameters obtained in the first 3 hours of CII. RESULTS: Use of the CII protocol was associated with fewer subjects with hypoglycemia alert values (P=0.003), earlier (P=0.002), and more stable (P=0.017) achievement of a glucose range of 70 to 180 mg/dL. Initial glucose level (P=0.001), change in glucose during the first 2 hours (P=0.026), and change in insulin infusion rate during the first 3 hours (P=0.029) were independently associated with delayed responses. Increasing the insulin infusion rate temporarily according to these parameters in silico significantly reduced delayed responses (P<0.0001) without hypoglycemia, especially in refractory patients. CONCLUSION: Our CII protocol enabled faster and more stable glycemic control than conventional care with minimized risk of hypoglycemia. An EHR-based adjustment was simulated to reduce delayed responses without increased incidence of hypoglycemia.

An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment

BACKGROUND: We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome.METHODS: Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (n=91), multivariable binary logistic regression analysis models were used to determine the independent associates with a delayed response (taking ≥6.0 hours for entering a glucose range of 70 to 180 mg/dL). The CII protocol was adjusted in silico according to the EHR-based parameters obtained in the first 3 hours of CII.RESULTS: Use of the CII protocol was associated with fewer subjects with hypoglycemia alert values (P=0.003), earlier (P=0.002), and more stable (P=0.017) achievement of a glucose range of 70 to 180 mg/dL. Initial glucose level (P=0.001), change in glucose during the first 2 hours (P=0.026), and change in insulin infusion rate during the first 3 hours (P=0.029) were independently associated with delayed responses. Increasing the insulin infusion rate temporarily according to these parameters in silico significantly reduced delayed responses (P<0.0001) without hypoglycemia, especially in refractory patients.CONCLUSION: Our CII protocol enabled faster and more stable glycemic control than conventional care with minimized risk of hypoglycemia. An EHR-based adjustment was simulated to reduce delayed responses without increased incidence of hypoglycemia.

Enhanced Safety Surveillance of Influenza Vaccines in General Practice, 2015-16: Feasibility Study.

BACKGROUND: The European Medicines Agency (EMA) requires vaccine manufacturers to conduct enhanced real-time surveillance of seasonal influenza vaccination. The EMA has specified a list of adverse events of interest to be monitored. The EMA sets out 3 different ways to conduct such surveillance: (1) active surveillance, (2) enhanced passive surveillance, or (3) electronic health record data mining (EHR-DM). English general practice (GP) is a suitable setting to implement enhanced passive surveillance and EHR-DM. OBJECTIVE: This study aimed to test the feasibility of conducting enhanced passive surveillance in GP using the yellow card scheme (adverse events of interest reporting cards) to determine if it has any advantages over EHR-DM alone. METHODS: A total of 9 GPs in England participated, of which 3 tested the feasibility of enhanced passive surveillance and the other 6 EHR-DM alone. The 3 that tested EPS provided patients with yellow (adverse events) cards for patients to report any adverse events. Data were extracted from all 9 GPs' EHRs between weeks 35 and 49 (08/24/2015 to 12/06/2015), the main period of influenza vaccination. We conducted weekly analysis and end-of-study analyses. RESULTS: Our GPs were largely distributed across England with a registered population of 81,040. In the week 49 report, 15,863/81,040 people (19.57% of the registered practice population) were vaccinated. In the EPS practices, staff managed to hand out the cards to 61.25% (4150/6776) of the vaccinees, and of these cards, 1.98% (82/4150) were returned to the GP offices. Adverse events of interests were reported by 113 /7223 people (1.56%) in the enhanced passive surveillance practices, compared with 322/8640 people (3.73%) in the EHR-DM practices. CONCLUSIONS: Overall, we demonstrated that GPs EHR-DM was an appropriate method of enhanced surveillance. However, the use of yellow cards, in enhanced passive surveillance practices, did not enhance the collection of adverse events of interests as demonstrated in this study. Their return rate was poor, data entry from them was not straightforward, and there were issues with data reconciliation. We concluded that customized cards prespecifying the EMA's adverse events of interests, combined with EHR-DM, were needed to maximize data collection. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2016-015469.

Data Challenges With Real-Time Safety Event Detection And Clinical Decision Support.

BACKGROUND: The continued digitization and maturation of health care information technology has made access to real-time data easier and feasible for more health care organizations. With this increased availability, the promise of using data to algorithmically detect health care-related events in real-time has become more of a reality. However, as more researchers and clinicians utilize real-time data delivery capabilities, it has become apparent that simply gaining access to the data is not a panacea, and some unique data challenges have emerged to the forefront in the process. OBJECTIVE: The aim of this viewpoint was to highlight some of the challenges that are germane to real-time processing of health care system-generated data and the accurate interpretation of the results. METHODS: Distinct challenges related to the use and processing of real-time data for safety event detection were compiled and reported by several informatics and clinical experts at a quaternary pediatric academic institution. The challenges were collated from the experiences of the researchers implementing real-time event detection on more than half a dozen distinct projects. The challenges have been presented in a challenge category-specific challenge-example format. RESULTS: In total, 8 major types of challenge categories were reported, with 13 specific challenges and 9 specific examples detailed to provide a context for the challenges. The examples reported are anchored to a specific project using medication order, medication administration record, and smart infusion pump data to detect discrepancies and errors between the 3 datasets. CONCLUSIONS: The use of real-time data to drive safety event detection and clinical decision support is extremely powerful, but it presents its own set of challenges that include data quality and technical complexity. These challenges must be recognized and accommodated for if the full promise of accurate, real-time safety event clinical decision support is to be realized.

Serological surveillance of influenza in an English sentinel network: pilot study protocol.

BACKGROUND: Rapidly undertaken age-stratified serology studies can produce valuable data about a new emerging infection including background population immunity and seroincidence during an influenza pandemic. Traditionally seroepidemiology studies have used surplus laboratory sera with little or no clinical information or have been expensive detailed population based studies. We propose collecting population based sera from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), a sentinel network with extensive clinical data. AIM: To pilot a mechanism to undertake population based surveys that collect serological specimens and associated patient data to measure seropositivity and seroincidence due to seasonal influenza, and create a population based serology bank. METHODS AND ANALYSIS: Setting and Participants: We will recruit 6 RCGP RSC practices already taking nasopharyngeal virology swabs. Patients who attend a scheduled blood test will be consented to donate additional blood samples. Approximately 100-150 blood samples will be collected from each of the following age bands - 18- 29, 30- 39, 40- 49, 50- 59, 60- 69 and 70+ years. METHODS: We will send the samples to the Public Health England (PHE) Seroepidemiology Unit for processing and storage. These samples will be tested for influenza antibodies, using haemagglutination inhibition assays. Serology results will be pseudonymised, sent to the RCGP RSC and combined using existing processes at the RCGP RSC secure hub. The influenza seroprevalence results from the RCGP cohort will be compared against those from the annual PHE influenza residual serosurvey. ETHICS AND DISSEMINATION: Ethical approval was granted by the Proportionate Review Sub- Committee of the London - Camden & Kings Cross on 6 February 2018. This study received approval from Health Research Authority on 7 February 2018. On completion the results will be made available via peer-reviewed journals.