A systematic review to investigate the effect of digital antimicrobial stewardship tools on antimicrobial usage, length of stay, mortality and cost
Bibliographic record
Abstract
Abstract Introduction Antimicrobial drug resistance has been recognised by the World Health Organisation as ‘One of the biggest threats to global health today’.1 As the use of digital systems in the NHS increases, there is huge potential to use systems such as electronic prescribing and clinical decision support as part of Antimicrobial Stewardship Programmes (ASPs) i.e., initiatives to change prescribing practices to promote and monitor use of antimicrobials and preserve their future effectiveness. However, there is a lack of research that has investigated the impact of digital tools as part of ASPs. Aim We aimed to review the literature available on the use of digital antimicrobial stewardship tools on individual outcomes such as antimicrobial usage, length of stay, mortality and cost. Methods A systematic search was performed across three databases (Embase, MEDLINE and CINAHL) using MESH terms and key words relating to antimicrobial stewardship, hospitals, length of stay (LOS), clinical outcomes, cost and mortality. Duplicates were removed and articles screened at the title, abstract and full text stage by two authors (NT and RK) according to our inclusion and exclusion criteria. We included primary research articles that: had implemented an ASPs in an adult hospital setting for at least 6 months, reported antimicrobial usage as defined daily dose per 1000 patient days (DDD/1000) and at least one of the following outcomes: LOS, mortality or cost and discussed an ASP that included a digital component. Risk of bias assessment was performed using the Newcastle-Ottawa scale. We calculated the percentage change to determine the impact of digital ASPs across all outcomes using the formula (After - Before)/Before x 100 = % Change. Before=pre-implementation results; after= results post-implementation Results We identified 3997 papers across all databases, and included 14 full texts that explored the impact of ASPs including a digital component (Figure 1). Of these, 14 papers reported the DDD/1000, 7 on mortality, 8 on LoS and 6 reported on cost. All studies evaluating DDD/1000 reported a decrease in antimicrobial usage ranging from -8.42% to -61.30%. Reductions in mortality (0 to -79%), LoS (25 to -27%) and costs (-8.42% to -69.19%) were also found. All ASPs utilised a digital component alongside a range of other interventions, such as the creation of formularies, guidelines and education emphasising the importance of using a combined approach in antimicrobial stewardship. Different interventions were found to have their own advantages, for example, education was key to sustainability and feedback was essential to improve prescribing practices. Users of the digital tools found that the tools were generally simple and user friendly, which facilitated their acceptance. Conclusion Our found that ASPs including a digital component were associated with reductions in antimicrobial usage, mortality, length of stay and cost. The positive effects were seen when such tools were combined with other approaches such as education and feedback approaches. We were unable to perform a meta-analysis due to the absence of confidence intervals and odds ratios in many of the included studies. Further research is needed to evaluate the cost-benefit associated with digital ASPs and whether sharing ASPs across multiple sites could reduce the maintenance burden for individual organisations. References 1. World Health Organisation (2020), Antibiotic Resistance Factsheet, https://www.who.int/news-room/fact-sheets/detail/antibiotic-resistance [accessed on 18th October 2020]
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".