Investigating the association between COVID-19 vaccination and care home outbreak frequency and duration.

OBJECTIVES: At the end of 2020, many countries commenced a vaccination programme against SARS-CoV-2. Public health authorities aim to prevent and interrupt outbreaks of infectious disease in social care settings. We aimed to investigate the association between the introduction of the vaccination programme and the frequency and duration of COVID-19 outbreaks in Northern Ireland (NI). STUDY DESIGN: We undertook an ecological study using routinely available national data. METHODS: We used Poisson regression to measure the relationship between the number of RT-PCR confirmed COVID-19 outbreaks in care homes, and as a measure of community COVID-19 prevalence, the Office for National Statistics COVID-19 Infection Survey estimated the number of people testing positive for COVID-19 in NI. We estimated the change in this relationship and estimated the expected number of care home outbreaks in the absence of the vaccination programme. A Cox proportional hazards model estimated the hazard ratio of a confirmed COVID-19 care home outbreak closure. RESULTS: Care home outbreaks reduced by two-thirds compared to expected following the introduction of the vaccination programme, from a projected 1625 COVID-19 outbreaks (95% prediction interval 1553-1694) between 7 December 2020 and 28 October 2021 to an observed 501. We estimated an adjusted hazard ratio of 2.53 of the outbreak closure assuming a 21-day lag for immunity. CONCLUSIONS: These findings describe the association of the vaccination with a reduction in outbreak frequency and duration across NI care homes. This indicates probable reduced harm and disruption from COVID-19 in social care settings following vaccination. Future research using individual level data from care home residents will be needed to investigate the effectiveness of the vaccines and the duration of their effects.

The epidemiology of alopecia areata: a population-based cohort study in UK primary care.

BACKGROUND: There is a lack of population-based information on the disease burden and management of alopecia areata (AA). OBJECTIVES: To describe the epidemiology of AA, focusing on incidence, demographics and patterns of healthcare utilization. METHODS: Population-based cohort study of 4·16 million adults and children, using UK electronic primary care records from the Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network database, 2009-2018. The incidence and point prevalence of AA were estimated. Variation in AA incidence by age, sex, deprivation, geographical distribution and ethnicity was examined. Patterns of healthcare utilization were evaluated in people with incident AA. RESULTS: The AA incidence rate was 0·26 per 1000 person-years. AA point prevalence in 2018 was 0·58% in adults. AA onset peaked at age 25-29 years for both sexes, although the peak was broader in females. People of nonwhite ethnicity were more likely to present with AA, especially those of Asian ethnicity [incidence rate ratio (IRR) 3·32 (95% confidence interval 3·11-3·55)]. Higher AA incidence was associated with social deprivation [IRR most vs. least deprived quintile 1·47 (1·37-1·59)] and urban living [IRR 1·23 (1·14-1·32)]. People of higher social deprivation were less likely to be referred for specialist dermatology review. CONCLUSIONS: By providing the first large-scale estimates of the incidence and point prevalence of AA, our study helps to understand the burden of AA on the population. Understanding the variation in AA onset between different population groups may give insight into the pathogenesis of AA and its management.

First-dose ChAdOx1 and BNT162b2 COVID-19 vaccines and thrombocytopenic, thromboembolic and hemorrhagic events in Scotland.

Reports of ChAdOx1 vaccine-associated thrombocytopenia and vascular adverse events have led to some countries restricting its use. Using a national prospective cohort, we estimated associations between exposure to first-dose ChAdOx1 or BNT162b2 vaccination and hematological and vascular adverse events using a nested incident-matched case-control study and a confirmatory self-controlled case series (SCCS) analysis. An association was found between ChAdOx1 vaccination and idiopathic thrombocytopenic purpura (ITP) (0-27 d after vaccination; adjusted rate ratio (aRR) = 5.77, 95% confidence interval (CI), 2.41-13.83), with an estimated incidence of 1.13 (0.62-1.63) cases per 100,000 doses. An SCCS analysis confirmed that this was unlikely due to bias (RR = 1.98 (1.29-3.02)). There was also an increased risk for arterial thromboembolic events (aRR = 1.22, 1.12-1.34) 0-27 d after vaccination, with an SCCS RR of 0.97 (0.93-1.02). For hemorrhagic events 0-27 d after vaccination, the aRR was 1.48 (1.12-1.96), with an SCCS RR of 0.95 (0.82-1.11). A first dose of ChAdOx1 was found to be associated with small increased risks of ITP, with suggestive evidence of an increased risk of arterial thromboembolic and hemorrhagic events. The attenuation of effect found in the SCCS analysis means that there is the potential for overestimation of the reported results, which might indicate the presence of some residual confounding or confounding by indication. Public health authorities should inform their jurisdictions of these relatively small increased risks associated with ChAdOx1. No positive associations were seen between BNT162b2 and thrombocytopenic, thromboembolic and hemorrhagic events.

Managing COVID-19 within and across health systems: why we need performance intelligence to coordinate a global response.

BACKGROUND: The COVID-19 pandemic is a complex global public health crisis presenting clinical, organisational and system-wide challenges. Different research perspectives on health are needed in order to manage and monitor this crisis. Performance intelligence is an approach that emphasises the need for different research perspectives in supporting health systems' decision-makers to determine policies based on well-informed choices. In this paper, we present the viewpoint of the Innovative Training Network for Healthcare Performance Intelligence Professionals (HealthPros) on how performance intelligence can be used during and after the COVID-19 pandemic. DISCUSSION: A lack of standardised information, paired with limited discussion and alignment between countries contribute to uncertainty in decision-making in all countries. Consequently, a plethora of different non-data-driven and uncoordinated approaches to address the outbreak are noted worldwide. Comparative health system research is needed to help countries shape their response models in social care, public health, primary care, hospital care and long-term care through the different phases of the pandemic. There is a need in each phase to compare context-specific bundles of measures where the impact on health outcomes can be modelled using targeted data and advanced statistical methods. Performance intelligence can be pursued to compare data, construct indicators and identify optimal strategies. Embracing a system perspective will allow countries to take coordinated strategic decisions while mitigating the risk of system collapse.A framework for the development and implementation of performance intelligence has been outlined by the HealthPros Network and is of pertinence. Health systems need better and more timely data to govern through a pandemic-induced transition period where tensions between care needs, demand and capacity are exceptionally high worldwide. Health systems are challenged to ensure essential levels of healthcare towards all patients, including those who need routine assistance. CONCLUSION: Performance intelligence plays an essential role as part of a broader public health strategy in guiding the decisions of health system actors on the implementation of contextualised measures to tackle COVID-19 or any future epidemic as well as their effect on the health system at large. This should be based on commonly agreed-upon standardised data and fit-for-purpose indicators, making optimal use of existing health information infrastructures. The HealthPros Network can make a meaningful contribution.

Sodium-glucose co-transporter-2 inhibitor cardiovascular outcome trials and generalizability to English primary care.

AIM: To identify people in English primary care with equivalent cardiovascular risk to participants in the sodium-glucose co-transporter-2 inhibitor (SGLT-2i) cardiovascular outcome trials (CVOTs). A secondary objective was to report the usage of SGLT-2is. METHODS: Cross-sectional analysis of people registered with participating practices in the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) network on the 31 December 2016. We derived: (1) proportions of the primary care population eligible for inclusion in each SGLT-2i CVOT (CANVAS, DECLARE, EMPA-REG and VERTIS); (2) characteristics of the eligible population compared with trial participants (demographics, disease duration and vascular risk); and (3) differences within the eligible population prescribed SGLT-2is. RESULTS: The proportions of people with type 2 diabetes (N = 84 394) meeting the inclusion criteria for each CVOT were: DECLARE 27% [95% confidence interval (CI) 26.5-27.1]; CANVAS 17% (16.6-17.1); VERTIS 7% (7.1-7.4); and EMPA-REG 7% (6.5-6.8). Primary care populations fulfilling inclusion criteria were 5-8 years older than trial cohorts, and <10% with inclusion criteria of each trial were prescribed an SGLT-2i; a greater proportion were men, and of white ethnicity. CONCLUSIONS: There was variation in proportions of the primary care type 2 diabetes population fulfilling inclusion criteria of SGLT-2i CVOTs. The more stringent the inclusion criteria, the lower the proportion identified in a primary care setting. Prescription rates for SGLT-2is were low in this national database, and there were demographic disparities in prescribing.

Saving bones without risking brain-bisphosphonates and risk of stroke: matched case-control study.

We investigated the association between bisphosphonate treatment and the risk of stroke using a large routine clinical dataset. We found no association between bisphosphonate treatment and risk of stroke, after adjusting for large number of clinical and demographic confounders. INTRODUCTION: There is conflicting evidence on the link between bisphosphonates and stroke with studies variously showing increased, decreased or unchanged risk. We investigated the association between bisphosphonate treatment and the risk of stroke using a large routine clinical dataset. METHODS: We used a matched nested case-control study design analysing routinely collected electronic data from patients registered at primary care practices in England participating in the Royal College of General Practitioners Research and Surveillance Centre. Cases were patients aged 18 years or over, either living or dead, recorded as having had a stroke in the period 1 January 2005 to 31 March 2016. Each case was matched to one control according to age, sex, general practice attended and calendar time. Data were analysed using Stata, version 14.2. and RStudio, version 1.1.463. Conditional logistic regression was used to determine odds ratios for stroke according to bisphosphonate treatment and duration in cases compared with controls. We adjusted for disease risk groups, cardiovascular risk factors, treatments, smoking status, alcohol consumption, ethnicity, bisphosphonate types, fracture and socioeconomic status using IMD (Index of Multiple Deprivation). RESULTS: We included 31,414 cases of stroke with an equal number of matched controls. Overall, 83.2% of cases and controls were aged 65 years or older, and there were similar proportions of females (51.5%) and males (48.5%). Bisphosphonate treatment was not associated with stroke after adjusting for the wide range of confounders considered (OR 0.86, 95% CI 0.62-1.19). CONCLUSIONS: We found no association between bisphosphonate treatment and risk of stroke, after adjusting for other confounders.

Obstructive sleep apnoea in Type 2 diabetes mellitus: increased risk for overweight as well as obese people included in a national primary care database analysis.

AIMS: To determine obstructive sleep apnoea prevalence in people with Type 2 or Type 1 diabetes in a national primary care setting, stratified by BMI category, and to explore the relationship between patient characteristics and obstructive sleep apnoea. METHODS: Using the Royal College of General Practitioners Research and Surveillance Centre database, a cross-sectional analysis was conducted. Diabetes type was identified using a seven-step algorithm and was grouped by Type 2 diabetes, Type 1 diabetes and no diabetes. The clinical characteristics of these groups were analysed, BMI-stratified obstructive sleep apnoea prevalence rates were calculated, and a multilevel logistic regression analysis was completed on the Type 2 diabetes group. RESULTS: Analysis of 1 275 461 adult records in the Royal College of General Practitioners Research and Surveillance Centre network showed that obstructive sleep apnoea was prevalent in 0.7%. In people with Type 2 diabetes, obstructive sleep apnoea prevalence increased with each increasing BMI category, from 0.5% in those of normal weight to 9.6% in those in the highest obesity class. By comparison, obstructive sleep apnoea prevalence rates for these BMI categories in Type 1 diabetes were 0.3% and 4.3%, and in those without diabetes 1.2% and 3.9%, respectively. Obstructive sleep apnoea was more prevalent in men than women in both diabetes types. When known risk factors were adjusted for, there were increased odds ratios for obstructive sleep apnoea in people with Type 2 diabetes in the overweight and higher BMI categories. CONCLUSIONS: Obstructive sleep apnoea was reported in people with both types of diabetes across the range of overweight categories and not simply in the highest obesity class.

Estimating the burden on general practitioner services in England from increases in respiratory disease associated with seasonal respiratory pathogen activity.

Understanding the burden of respiratory pathogens on health care is key to improving public health emergency response and interventions. In temperate regions, there is a large seasonal rise in influenza and other respiratory pathogens. We have examined the associations between individual pathogens and reported respiratory tract infections to estimate attributable burden. We used multiple linear regression to model the relationship between doctor consultation data and laboratory samples from week 3 2011 until week 37 2015. We fitted separate models for consultation data with in-hours and out-of-hours doctor services, stratified by different age bands. The best fitting all ages models (R2 > 80%) for consultation data resulted in the greatest burden being associated with influenza followed by respiratory syncytial virus (RSV). For models of adult age bands, there were significant associations between consultation data and invasive Streptococcus pneumoniae. There were also smaller numbers of consultations significantly associated with rhinovirus, parainfluenza, and human metapneumovirus. We estimate that a general practice with 10 000 patients would have seen an additional 18 respiratory tract infection consultations per winter week of which six had influenza and four had RSV. Our results are important for the planning of health care services to minimise the impact of winter pressures. •Respiratory pathogen incidence explains over 80% of seasonal variation in respiratory consultation data.•Influenza and RSV are associated with the biggest seasonal rises in respiratory consultation counts.•A third of consultation counts associated with respiratory pathogens were due to influenza.

Significant spike in excess mortality in England in winter 2014/15 - influenza the likely culprit.

Significant increases in excess all-cause mortality, particularly in the elderly, were observed during the winter of 2014/15 in England. With influenza A(H3N2) the dominant circulating influenza A subtype, this paper determines the contribution of influenza to this excess controlling for weather. A standardised multivariable Poisson regression model was employed with weekly all-cause deaths the dependent variable for the period 2008-2015. Adjusting for extreme temperature, a total of 26 542 (95% CI 25 301-27 804) deaths in 65+ and 1942 (95% CI 1834-2052) in 15-64-year-olds were associated with influenza from week 40, 2014 to week 20, 2015. This is compatible with the circulation of influenza A(H3N2). It is the largest estimated number of influenza-related deaths in England since prior to 2008/09. The findings highlight the potential health impact of influenza and the important role of the annual influenza vaccination programme that is required to protect the population including the elderly, who are vulnerable to a severe outcome.

Measuring Quality of Healthcare Outcomes in Type 2 Diabetes from Routine Data: a Seven-nation Survey Conducted by the IMIA Primary Health Care Working Group.

Background: The Institute of Medicine framework defines six dimensions of quality for healthcare systems: (1) safety, (2) effectiveness, (3) patient centeredness, (4) timeliness of care, (5) efficiency, and (6) equity. Large health datasets provide an opportunity to assess quality in these areas. Objective: To perform an international comparison of the measurability of the delivery of these aims, in people with type 2 diabetes mellitus (T2DM) from large datasets. Method: We conducted a survey to assess healthcare outcomes data quality of existing databases and disseminated this through professional networks. We examined the data sources used to collect the data, frequency of data uploads, and data types used for identifying people with T2DM. We compared data completeness across the six areas of healthcare quality, using selected measures pertinent to T2DM management. Results: We received 14 responses from seven countries (Australia, Canada, Italy, the Netherlands, Norway, Portugal, Turkey and the UK). Most databases reported frequent data uploads and would be capable of near real time analysis of healthcare quality.The majority of recorded data related to safety (particularly medication adverse events) and treatment efficacy (glycaemic control and microvascular disease). Data potentially measuring equity was less well recorded. Recording levels were lowest for patient-centred care, timeliness of care, and system efficiency, with the majority of databases containing no data in these areas. Databases using primary care sources had higher data quality across all areas measured. Conclusion: Data quality could be improved particularly in the areas of patient-centred care, timeliness, and efficiency. Primary care derived datasets may be most suited to healthcare quality assessment.

The emergence of enterovirus D68 in England in autumn 2014 and the necessity for reinforcing enterovirus respiratory screening.

In autumn 2014, enterovirus D68 (EV-D68) cases presenting with severe respiratory or neurological disease were described in countries worldwide. To describe the epidemiology and virological characteristics of EV-D68 in England, we collected clinical information on laboratory-confirmed EV-D68 cases detected in secondary care (hospitals), between September 2014 and January 2015. In primary care (general practitioners), respiratory swabs collected (September 2013-January 2015) from patients presenting with influenza-like illness were tested for EV-D68. In secondary care 55 EV-D68 cases were detected. Among those, 45 cases had clinical information available and 89% (40/45) presented with severe respiratory symptoms. Detection of EV-D68 among patients in primary care increased from 0.4% (4/1074; 95% CI 0.1-1.0) (September 2013-January 2014) to 0.8% (11/1359; 95% CI 0.4-1.5) (September 2014-January 2015). Characterization of EV-D68 strains circulating in England since 2012 and up to winter 2014/2015 indicated that those strains were genetically similar to those detected in 2014 in USA. We recommend reinforcing enterovirus surveillance through screening respiratory samples of suspected cases.

Glucose test provenance recording in UK primary care: was that fasted or random?

AIMS: To describe the proportion of glucose tests with unrecorded provenance in routine primary care data and identify the impact on clinical practice. METHODS: A cross-sectional analysis was conducted of blood glucose measurements from the Royal College of General Practitioner Research and Surveillance Centre database, which includes primary care records from >100 practices across England and Wales. All blood glucose results recorded during 2013 were identified. Tests were grouped by provenance (fasting, oral glucose tolerance test, random, none specified and other). A clinical audit in a single primary care practice was also performed to identify the impact of failing to record glucose provenance on diabetes diagnosis. RESULTS: A total of 2 137 098 people were included in the cross-sectional analysis. Of 203 350 recorded glucose measurements the majority (117 893; 58%) did not have any provenance information. The most commonly reported provenance was fasting glucose (75 044; 37%). The distribution of glucose values where provenance was not recorded was most similar to that of fasting samples. The glucose measurements of 256 people with diabetes in the audit practice (size 11 514 people) were analysed. The initial glucose measurement had no provenance information in 164 cases (64.1%). A clinician questioned the provenance of a result in 41 cases (16.0%); of these, 14 (34.1%) required repeating. Lack of provenance led to delays in the diagnosis of diabetes [median (range) 30 (3-614) days]. CONCLUSIONS: The recording of glucose provenance in UK primary care could be improved. Failure to record provenance causes unnecessary repeated testing, delayed diagnosis and wasted clinician time.

Association between glycaemic control and common infections in people with Type 2 diabetes: a cohort study.

AIM: To investigate the impact of glycaemic control on infection incidence in people with Type 2 diabetes. METHODS: We compared infection rates during 2014 in people with Type 2 diabetes and people without diabetes in a large primary care cohort in the UK (the Royal College of General Practitioners Research and Surveillance Centre database). We performed multilevel logistic regression to investigate the impact of Type 2 diabetes on presentation with infection, and the effect of glycaemic control on presentation with upper respiratory tract infections, bronchitis, influenza-like illness, pneumonia, intestinal infectious diseases, herpes simplex, skin and soft tissue infections, urinary tract infections, and genital and perineal infections. People with Type 2 diabetes were stratified by good [HbA1c < 53 mmol/mol (< 7%)], moderate [HbA1c 53-69 mmol/mol (7-8.5%)] and poor [HbA1c > 69 mmol/mol (> 8.5%)] glycaemic control using their most recent HbA1c concentration. Infection incidence was adjusted for important sociodemographic factors and patient comorbidities. RESULTS: We identified 34 278 people with Type 2 diabetes and 613 052 people without diabetes for comparison. The incidence of infections was higher in people with Type 2 diabetes for all infections except herpes simplex. Worsening glycaemic control was associated with increased incidence of bronchitis, pneumonia, skin and soft tissue infections, urinary tract infections, and genital and perineal infections, but not with upper respiratory tract infections, influenza-like illness, intestinal infectious diseases or herpes simplex. CONCLUSIONS: Almost all infections analysed were more common in people with Type 2 diabetes. Infections that are most commonly of bacterial, fungal or yeast origin were more frequent in people with worse glycaemic control.

Building a Privacy, Ethics, and Data Access Framework for Real World Computerised Medical Record System Data: A Delphi Study. Contribution of the Primary Health Care Informatics Working Group.

BACKGROUND: Privacy, ethics, and data access issues pose significant challenges to the timely delivery of health research. Whilst the fundamental drivers to ensure that data access is ethical and satisfies privacy requirements are similar, they are often dealt with in varying ways by different approval processes. OBJECTIVE: To achieve a consensus across an international panel of health care and informatics professionals on an integrated set of privacy and ethics principles that could accelerate health data access in data-driven health research projects. METHOD: A three-round consensus development process was used. In round one, we developed a baseline framework for privacy, ethics, and data access based on a review of existing literature in the health, informatics, and policy domains. This was further developed using a two-round Delphi consensus building process involving 20 experts who were members of the International Medical Informatics Association (IMIA) and European Federation of Medical Informatics (EFMI) Primary Health Care Informatics Working Groups. To achieve consensus we required an extended Delphi process. RESULTS: The first round involved feedback on and development of the baseline framework. This consisted of four components: (1) ethical principles, (2) ethical guidance questions, (3) privacy and data access principles, and (4) privacy and data access guidance questions. Round two developed consensus in key areas of the revised framework, allowing the building of a newly, more detailed and descriptive framework. In the final round panel experts expressed their opinions, either as agreements or disagreements, on the ethics and privacy statements of the framework finding some of the previous round disagreements to be surprising in view of established ethical principles. CONCLUSION: This study develops a framework for an integrated approach to ethics and privacy. Privacy breech risk should not be considered in isolation but instead balanced by potential ethical benefit.

Does Informatics Enable or Inhibit the Delivery of Patient-centred, Coordinated, and Quality-assured Care: a Delphi Study. A Contribution of the IMIA Primary Health Care Informatics Working Group.

BACKGROUND: Primary care delivers patient-centred and coordinated care, which should be quality-assured. Much of family practice now routinely uses computerised medical record (CMR) systems, these systems being linked at varying levels to laboratories and other care providers. CMR systems have the potential to support care. OBJECTIVE: To achieve a consensus among an international panel of health care professionals and informatics experts about the role of informatics in the delivery of patient-centred, coordinated, and quality-assured care. METHOD: The consensus building exercise involved 20 individuals, five general practitioners and 15 informatics academics, members of the International Medical Informatics Association Primary Care Informatics Working Group. A thematic analysis of the literature was carried out according to the defined themes. RESULTS: The first round of the analysis developed 27 statements on how the CMR, or any other information system, including paper-based medical records, supports care delivery. Round 2 aimed at achieving a consensus about the statements of round one. Round 3 stated that there was an agreement on informatics principles and structures that should be put in place. However, there was a disagreement about the processes involved in the implementation, and about the clinical interaction with the systems after the implementation. CONCLUSIONS: The panel had a strong agreement about the core concepts and structures that should be put in place to support high quality care. However, this agreement evaporated over statements related to implementation. These findings reflect literature and personal experiences: whilst there is consensus about how informatics structures and processes support good quality care, implementation is difficult.

Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks. Contribution of the IMIA Primary Healthcare Working Group.

BACKGROUND: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. OBJECTIVE: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. METHOD: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. RESULTS: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowdsourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the "internet of things", and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. CONCLUSIONS: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.

Uptake and impact of a new live attenuated influenza vaccine programme in England: early results of a pilot in primary school-age children, 2013/14 influenza season.

As part of the introduction and roll-out of a universal childhood live-attenuated influenza vaccination programme, 4­11 year-olds were vaccinated in seven pilot areas in England in the 2013/14 influenza season. This paper presents the uptake and impact of the programme for a range of disease indicators. End-of-season uptake was defined as the number of children in the target population who received at least one dose of influenza vaccine. Between week 40 2013 and week 15 2014, cumulative disease incidence per 100,000 population (general practitioner consultations for influenza-like illness and laboratory-confirmed influenza hospitalisations), cumulative influenza swab positivity in primary and secondary care and cumulative proportion of emergency department respiratory attendances were calculated. Indicators were compared overall and by age group between pilot and non-pilot areas. Direct impact was defined as reduction in cumulative incidence based on residence in pilot relative to non-pilot areas in 4­11 year-olds. Indirect impact was reduction between pilot and non-pilot areas in <4 year-olds and >11 year-olds. Overall vaccine uptake of 52.5% (104,792/199,475) was achieved. Although influenza activity was low, a consistent, though not statistically significant, decrease in cumulative disease incidence and influenza positivity across different indicators was seen in pilot relative to non-pilot areas in both targeted and non-targeted age groups, except in older age groups, where no difference was observed for secondary care indicators.

The Evidence-base for Using Ontologies and Semantic Integration Methodologies to Support Integrated Chronic Disease Management in Primary and Ambulatory Care: Realist Review. Contribution of the IMIA Primary Health Care Informatics WG.

BACKGROUND: Most chronic diseases are managed in primary and ambulatory care. The chronic care model (CCM) suggests a wide range of community, technological, team and patient factors contribute to effective chronic disease management. Ontologies have the capability to enable formalised linkage of heterogeneous data sources as might be found across the elements of the CCM. OBJECTIVE: To describe the evidence base for using ontologies and other semantic integration methods to support chronic disease management. METHOD: We reviewed the evidence-base for the use of ontologies and other semantic integration methods within and across the elements of the CCM. We report them using a realist review describing the context in which the mechanism was applied, and any outcome measures. RESULTS: Most evidence was descriptive with an almost complete absence of empirical research and important gaps in the evidence-base. We found some use of ontologies and semantic integration methods for community support of the medical home and for care in the community. Ubiquitous information technology (IT) and other IT tools were deployed to support self-management support, use of shared registries, health behavioural models and knowledge discovery tools to improve delivery system design. Data quality issues restricted the use of clinical data; however there was an increased use of interoperable data and health system integration. CONCLUSIONS: Ontologies and semantic integration methods are emergent with limited evidence-base for their implementation. However, they have the potential to integrate the disparate community wide data sources to provide the information necessary for effective chronic disease management.

Towards an ontology for data quality in integrated chronic disease management: a realist review of the literature.

PURPOSE: Effective use of routine data to support integrated chronic disease management (CDM) and population health is dependent on underlying data quality (DQ) and, for cross system use of data, semantic interoperability. An ontological approach to DQ is a potential solution but research in this area is limited and fragmented. OBJECTIVE: Identify mechanisms, including ontologies, to manage DQ in integrated CDM and whether improved DQ will better measure health outcomes. METHODS: A realist review of English language studies (January 2001-March 2011) which addressed data quality, used ontology-based approaches and is relevant to CDM. RESULTS: We screened 245 papers, excluded 26 duplicates, 135 on abstract review and 31 on full-text review; leaving 61 papers for critical appraisal. Of the 33 papers that examined ontologies in chronic disease management, 13 defined data quality and 15 used ontologies for DQ. Most saw DQ as a multidimensional construct, the most used dimensions being completeness, accuracy, correctness, consistency and timeliness. The majority of studies reported tool design and development (80%), implementation (23%), and descriptive evaluations (15%). Ontological approaches were used to address semantic interoperability, decision support, flexibility of information management and integration/linkage, and complexity of information models. CONCLUSION: DQ lacks a consensus conceptual framework and definition. DQ and ontological research is relatively immature with little rigorous evaluation studies published. Ontology-based applications could support automated processes to address DQ and semantic interoperability in repositories of routinely collected data to deliver integrated CDM. We advocate moving to ontology-based design of information systems to enable more reliable use of routine data to measure health mechanisms and impacts.