Developing a risk prediction model for 30-day unplanned hospitalization in patients receiving outpatient parenteral antimicrobial therapy

Durojaiye, Oyewole Christopher; Kritsotakis, Evangelos I.; Johnston, Paul; Kenny, T.; Ntziora, Fotinie; Cartwright, Katharine

doi:10.1016/j.cmi.2018.11.009

Cited by 27 publications

(34 citation statements)

References 22 publications

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“…Recent studies have shown implementing an OPAT "bundle" decreased 30-day readmission rates by half (13.0% vs. 26.1%, P < 0.01) [54]. Similarly, two studies developed risk prediction scores for 30-day readmission [55] and OPAT complications [56]. Potentially targeting these patient populations can improve OPAT program measures.…”

Section: Opat Metricsmentioning

confidence: 99%

Recent Updates in Antimicrobial Stewardship in Outpatient Parenteral Antimicrobial Therapy

Mahoney

Childs‐Kean

Khan

et al. 2021

Curr Infect Dis Rep

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Section: Opat Metricsmentioning

confidence: 99%

Recent Updates in Antimicrobial Stewardship in Outpatient Parenteral Antimicrobial Therapy

Mahoney

Childs‐Kean

Khan

et al. 2021

Curr Infect Dis Rep

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“…The provision of the service on an outpatient basis was seen to deliver positive outcomes for the organization in question, including reduced readmissions and incidence of nosocomial infections 45,54 .…”

Section: Organization Factorsmentioning

confidence: 99%

“…Studies also stressed the need for an organization to adopt specific measurable outcomes to verify the success of the service, including frequencies of complications and clinical cure, patient satisfaction and readmission rates amongst others 40 . Durojaiye et al went a step further by creating a predictive model based on commonly known OPAT variables to avoid unnecessary readmissions 54 . It is considered that this high level of standardization -especially at the pre-discharge OPAT phase -will help the service thrive when faced with an increasingly heterogeneous population making use of it, 27,34,35,42 especially as the range of anti-microbial agents considered for OPAT use increases 37 .…”

Section: Organization Factorsmentioning

confidence: 99%

Human Factors approaches to evaluating outpatient parenteral antimicrobial therapy services: A systematic review

Bugeja

Stewart

Strath

et al. 2020

Research in Social and Administrative Pharmacy

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Background: The expansion in terms of available treatment options and models of care has led to a growing global momentum for outpatient antimicrobial therapy (OPAT) services. A systematic review was undertaken to explore Human Factors aspects relating to OPAT service delivery and to evaluate whether OPAT is amenable to description using the Systems Engineering Initiative for Patient Safety (SEIPS 2.0) model. Method: Following a preliminary search, a search string was applied to four databases, including Medline, Cumulative Index of Nursing and Allied Health Literature, International Pharmaceutical Abstracts and PsychINFO. Inclusion criteria ensured only articles published after the year 2000 and written in English were accepted. The methodological quality of studies was assessed by three reviewers. Narrative synthesis was performed to uncover the key interactions between work system entities which underpin OPAT processes and outcomes as described using the SEIPS 2.0 model. Results: A total of twenty-seven studies were deemed eligible for the final review. Of these, most described sample populations representative of the population under study, while duration of the studies varied from a few months to years. Some studies evaluated a single model of care whilst others evaluated all three currently available models. The breadth and scope of the studies included enabled extraction of rich Human Factors data describing barriers and enablers to service provision. Conclusion: OPAT is a service which offers significant benefits to both patients and care providers. These benefits include patient satisfaction and wellbeing, as well as financial performance. OPAT is a complex sociotechnical system, and a systems approach may offer the opportunity to enhance system design, maximising system performance. This review demonstrates that the service can be better understood using the SEIPS 2.0 model to identify key work system interactions that support performance.

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“…None were used in clinical practice. CMI publishes about 4 articles per year on prediction models (4)(5)(6)(7)(8)(9)(10)(11)(12)(13). In retrospect they were heterogeneous in their hypothetical usefulness.…”

mentioning

confidence: 99%

Prediction models in CMI

Leibovici¹,

Chemaly²,

CUTLER³

et al. 2022

Clinical Microbiology and Infection

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Developing a risk prediction model for 30-day unplanned hospitalization in patients receiving outpatient parenteral antimicrobial therapy

Abstract: 0000-0002-9526-3852, Johnston, P. et al. (3 more authors) (2018) Developing a risk prediction model for 30-Day unplanned hospitalisation in patients receiving outpatient parenteral antimicrobial therapy. Clinical Microbiology and Infection.

Cited by 27 publications

References 22 publications

Recent Updates in Antimicrobial Stewardship in Outpatient Parenteral Antimicrobial Therapy

Recent Updates in Antimicrobial Stewardship in Outpatient Parenteral Antimicrobial Therapy

Human Factors approaches to evaluating outpatient parenteral antimicrobial therapy services: A systematic review

Prediction models in CMI

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