Title: Real time refinement and validation of criteria and tools used in primary care to aid hospital referral decisions for patients of all ages in the event of surge during an influenza pandemic.
Funder: Department of Health and Social Care

Abstract: Design: A prospective analysis, linking criteria in a GP's assessment of patients presenting with influenza like illness, to immediate management decisions and patient outcomes. Setting: Primary care - General Practices Target Population: Adults and children presenting to primary care with influenza like illness. Health Technologies Being Assessed: Community triage tools for use during pandemic / severe acute respiratory infection surge. METHOD: GPs participating in the General Practice Research Database (GPRD) will record their assessment and management of patients (refer/keep at home) with influenza like illness in an electronic clinical record (Vision(r)/LEPIS). Most of the clinical criteria of the various triage tools are already collected in this way during a routine GP assessment: either as absolute values (e.g. respiratory rate); or as important rule-out features (e.g. normal capillary refill time), as are immediate management decisions. Notice of death and hospital discharge faxed data is entered into the same in-practice software. GPRD harvests data from Vision/LEPIS nightly. GPRD is linked to detailed Hospital Episode Summary and ONS certified caused of death data three monthly. We will also establish feasibility of anonymised linkage with the Health Protection Agency Virology results. Analysis: Weekly cumulative analyses are planned using GPRD data. Three monthly analyses are planned using linked HES data as a gold standard. Univariate and multivariate analyses using unconditional logistic regression will be used to investigate the association between triage criteria threshold values and primary outcomes (hospital admission, and death) and secondary outcomes (length of stay and augmented levels of care (high dependency / intensive care)). The threshold values of triage criteria will be refined by comparing the receiver operator characteristics at various thresholds of abnormality (e.g. respiratory rate >30, >35, >40). The discriminatory value of existing and refined triage tools will be compared using logistic regression. Triage tools will be compared for their ability to predict outcomes using Area Under the Receiver Operating Characteristic Curve (AUROC) comparisons. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) will be calculated for triage tools using different score thresholds. The virus, human behaviour, and models of health care provision in the community may change in time. Analysis will be reset between pandemic waves and appropriate comparisons made between pandemic waves. Sample size: Recruiting form all GP practices participating in GPRD (currently 629), population pool 12.9 million, 5.14 million active patients of research standard (8.3% of the UK population). Based on the limits of the clinical attack rates during the 2009 event; between 23,000 and 69,000 of these "active" people would be expected to present in the first wave. Approximately 10,000 to 30,000 of these patients will present in the first 3 months before peak activity; forming the study cohort. Based on the limits of the hospitalisation rates previous described, 130 to 750 of these people would be admitted to hospital forming the group with a positive primary outcome measures in this study.

Lay abstract: Flu pandemics occur when a new flu virus emerges, rapidly spreads and causes widespread disease in many communities in many continents. Fortunately severe pandemics are rare events. When they occur health care capacity both in the community and hospitals can be overwhelmed. When this happens doctors need to make difficult decisions about who should be admitted to hospital and who can safely be allowed to stay at home. To do this fairly, most doctors feel that the same types of patient assessments and questions are used across the wider community. This process is called triage. The ethical principle of "triage" is to do most for most in a fair way. This does not mean treating everybody equally. It means using scarce resources for those people most likely to benefit from treatment. Triage tools should help doctors identify which people are most likely to benefit from treatments only available in hospital and which people can safely be managed at home. The difficulty in designing triage tools for a future flu pandemic is that the nature of disease caused by a pandemic virus is generally unknown until that pandemic occurs. A further difficulty is that flu can affect children and adults quite differently. A one-size-fits-all tool is unlikely to work for all age groups. This study will develop processes that will test how parts of a general practitioner's questions and assessment of children and adults with flu like illness can predict who: can safely be kept at home; need hospital admission; need high dependency or intensive care; are most likely to die. The study uses the GP's routine electronic record to capture most of the information and links to the hospital record if the patient is admitted to hospital. These records are be accessed by researchers without revealing people’s identities. We will develop technology that allows records from about 600 GP surgeries across the UK to be studied automatically every week. This is quite complicated and needs to be set up in advance of a pandemic by working closely with the GPs that will ultimately use these tools. We think it will take six months to develop the information technology processes and six months to test the processes. In the event of a pandemic, the processes that have been developed will "go-live" and allow us to refine triage tools and check that they are "fit-for-purpose" in readiness for use should a pandemic become severe. The team that has planned this research is experienced in conducting research during the difficult situations presented by outbreaks, epidemics and pandemics. It is challenging work but very exciting and rewarding when it works. Our research team succeeded in carefully describing 1540 children and adults affected by the 2009 swine flue pandemic. [Myles PR, Semple MG, Lim WS, et al. Thorax (2012). doi:10.1136/thoraxjnl-2011-200266] We have already studied how triage tools would have performed if used in hospital to predict admission to high dependency units and intensive care units. [Myles PR, Nguyen-Van-Tam JS, Lim WS, et al. (2012) PLoS ONE 7(4): e34428. doi:10.1371/journal.pone.0034428 ]

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: INFECTION