Title: Enhanced, Personalized and Integrated Care for Infection Management at Point of Care (EPIC IMPOC).
Funder: Department of Health and Social Care

Abstract: The prototype software product runs on a mobile tablet and is for use in critical care. It retrieves data from various NHS laboratory and patient management systems, then utilises case-based reasoning (CBR) to aid decision-making. CBR is an artificial intelligence technique that solves newly encountered problems by applying the solutions learned from solving similar problems encountered in the past. The product uses this to retrieve stored cases of previous patients with similar clinical presentations to the current patient, and then formulates an antimicrobial regime based on the success of these previous experiences. To develop this product, in the setting of a multi-site central London University hospital, six research objectives are proposed: 1) Develop the POC-DSS to support clinicians in providing personalised, optimised, infection management to hospital patients outside of critical care. The prototype POC-DSS will be adapted for use in non-critical care patients through determining and embedding cohort specific patient parameters and resistance epidemiology. Identification of cohort specific variables that influence antimicrobial prescribing will occur through (a) stakeholder analysis, and (b) clear delineation from stakeholders (through focus groups, face-to-face interviews and surveys) of important variables. The prototype POC-DSS user interface and navigation menus will re-configured for use on mulitple mobile platforms and adapted to future-proof the product for rapid diagnostic tests. Outcome measure: provision of a POC-DSS product. 2) Define decision-making processes in antimicrobial prescribing in secondary care. Performing principle component analysis via the CBR system will quantify the impact of variables on antimicrobial prescribing in each different cohort. This will iteratively optimise the CBR algorithm and enable streamlining of the user interface, as well as informing future antimicrobial stewardship interventions towards key promoters and barriers in antimicrobial prescribing. Outcome measure: optimisation of the product interface and CBR algorithm. 3) Personalise dosing to optimise therapy and minimise toxicity. Developing a dose optimisation module for the POC-DSS will incorporate a pharmaco-kinetic/dynamic model (using established Monte Carlo simulation techniques) and therapeutic drug monitoring (TDM) modelling tools building on the experience of the bioengineering team from the paradigm of insulin dosing using CBR in diabetes management. Quantitative evaluation of the impact of dose optimisation will focus on patient outcomes. Outcome measure: provision of a dose optimisation module for the product. 4) Engage and empower patients in decision making around antimicrobials. The patient module will enable patients and clinicians to discuss current infection issues (using electronic pictures and videos/animations to aid understanding) during a consultation. The clinician will then be able to select important resources from their POC-DSS and send these through to the patient. Post-development evaluation will be through qualitative methods, with face-to-face interviews of patient and clinicians users of the module. Outcome measure: provision of a patient engagement module for the product. 5) Evaluate the implementation of the product and impact on antimicrobial prescribing behaviour. Face-to-face interviews and surveys with users of the POC-DSS will provide qualitative evaluation of the impact of CBR on antimicrobial prescribing. Outcome measures: Qualitative analysis of the implementation of the POC-DSS and its impact on clinician attitudes to antimicrobial prescribing including: confidence in antimicrobial choice and dosing, confidence in communicating with other clinicians and patients about antimicrobial prescribing, and perceived need for further antimicrobial education. 6) Evaluate the impact of the product on antimicrobial prescribing and antimicrobial resistance in secondary care. Interrupted time series analysis of defined variables pre- and post- product roll out with a comparator control site, using data from electronic laboratory and pharmacy management systems and serial point prevalence studies, will enable robust analysis of impact. Outcome measures: Quantitative evaluation of impact of the POC-DSS on antimicrobial prescribing, patient outcomes and antimicrobial resistance indices.

Lay abstract: Bacteria and other microorganisms can cause infections in people outside of hospitals and also in patients admitted to hospital. The antimicrobials (drugs that kill or stop the growth of microorganisms including bacteria, thereby treating infections) commonly used to treat infections are becoming less effective over time as bacteria develop resistance to them. Antimicrobial usage itself can lead to development and spread of antimicrobial resistance. Antimicrobial resistance is now a major threat to patient safety and increasingly we are seeing patients infected with bacteria for which there are very few antimicrobials that remain effective. If untreated, these infections can be fatal in some patients. To conserve the effectiveness of antimicrobials we need to develop ways to use them more sensibly. There is a need for healthcare professionals who diagnose and treat infections to be able to access antimicrobial guidelines and test results at the patient bedside. This needs to be provided rapidly and with support to make sure that the decisions on prescribing antimicrobials are the best that can be made. Currently there is no universal way for this to occur in the NHS. A prototype system to achieve this has been developed by healthcare professionals and biomedical engineers, allowing all the necessary information required to make the correct decision be accessible at the bedside. The prototype has been designed for use in intensive care, where the risk of infection is high, but there is a need to develop and roll out this system into many other areas of patient care. Furthermore there is a key need to engage patients with how decisions are made around antimicrobial prescribing. We propose to adapt the prototype to meet these needs. This system should improve patient safety and help preserve the effectiveness of existing antimicrobials.

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