Dataset Information

Factors influencing antibiotic prescribing in long-term care facilities: a qualitative in-depth study.

ABSTRACT:

Background

Insight into factors that influence antibiotic prescribing is crucial when developing interventions aimed at a more rational use of antibiotics. We examined factors that influence antibiotic prescribing in long-term care facilities, and present a conceptual model that integrates these factors.

Methods

Semi-structured qualitative interviews were conducted with physicians (n?=?13) and nursing staff (n?=?13) in five nursing homes and two residential care homes in the central-west region of the Netherlands. An iterative analysis was applied to interviews with physicians to identify and categorize factors that influence antibiotic prescribing, and to integrate these into a conceptual model. This conceptual model was triangulated with the perspectives of nursing staff.

Results

The analysis resulted in the identification of six categories of factors that can influence the antibiotic prescribing decision: the clinical situation, advance care plans, utilization of diagnostic resources, physicians' perceived risks, influence of others, and influence of the environment. Each category comprises several factors that may influence the decision to prescribe or not prescribe antibiotics directly (e.g. pressure of patients' family leading to antibiotic prescribing) or indirectly via influence on other factors (e.g. unfamiliarity with patients resulting in a higher physician perceived risk of non-treatment, in turn resulting in a higher tendency to prescribe antibiotics).

Conclusions

Our interview study shows that several non-rational factors may affect antibiotic prescribing decision making in long-term care facilities, suggesting opportunities to reduce inappropriate antibiotic use. We developed a conceptual model that integrates the identified categories of influencing factors and shows the relationships between those categories. This model may be used as a practical tool in long-term care facilities to identify local factors potentially leading to inappropriate prescribing, and to subsequently intervene at the level of those factors to promote appropriate antibiotic prescribing.

SUBMITTER: van Buul LW

PROVIDER: S-EPMC4289541 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Publications

Factors influencing antibiotic prescribing in long-term care facilities: a qualitative in-depth study.

van Buul Laura W LW van der Steen Jenny T JT Doncker Sarah M M M SM Achterberg Wilco P WP Schellevis François G FG Veenhuizen Ruth B RB Hertogh Cees M P M CM

BMC geriatrics 20141216

<h4>Background</h4>Insight into factors that influence antibiotic prescribing is crucial when developing interventions aimed at a more rational use of antibiotics. We examined factors that influence antibiotic prescribing in long-term care facilities, and present a conceptual model that integrates these factors.<h4>Methods</h4>Semi-structured qualitative interviews were conducted with physicians (n = 13) and nursing staff (n = 13) in five nursing homes and two residential care homes in the centr ...[more]

PMID: 25514874

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Project description:BackgroundShared decision-making, a communicative process to reach decisions based on informed preferences, evidence, and co-created goals, improves care satisfaction and patients' quality of life. However, shared decision-making has not been widely implemented in long-term care facilities, and few studies have examined how to promote the shared decision-making practice. This study aimed to identify the influencing factors of shared decision-making based on the Person-centered Practice Framework in long-term care facilities.MethodsA total of 300 staff (nursing staff, social workers, and personal care workers) in 13 Korean long-term care facilities participated in this study. Data from 280 respondents were finally analyzed, excluding respondents with missing values. Data were collected using structured questionnaires that included items on shared decision-making, personal factors (e.g., knowledge about dementia, person-centered care education, person-centered attitude, communication behavior, and job tenure), and care environment factors (e.g., person-centered climate, staffing level, effective staff relationships, supportive supervisors, and power-sharing). Multilevel linear regression analyses were performed using Mplus Version 8.8.ResultsThe mean shared decision-making score was 35.78 (range 8-45). Staff with experience of person-centered care education (β = 0.198, p = 0.034), a higher person-centered attitude score (β = 0.201, p = 0.007), and a higher communication behavior score (β = 0.242, p < 0.001) were more likely to report a higher shared decision-making score. In addition, staff who viewed their care environment as more person-centered were more likely to report a higher shared decision-making score (β = 0.416, p < 0.001).ConclusionsThis study highlights that personal (e.g., person-centered care education, person-centered attitude, and communication behavior) and care environment (e.g., person-centered climate) factors could influence shared decision-making for long-term care residents. These findings could be foundational evidence for facilitating shared decision-making practice in long-term care settings.

Project description:BackgroundOveruse of antibiotics has contributed to antimicrobial resistance; a growing public health threat. In long-term care facilities, levels of inappropriate prescribing are as high as 75%. Numerous interventions targeting long-term care facilities' antimicrobial stewardship have been reported with varying, and largely unexplained, effects. Therefore, this review aimed to apply behavioural science frameworks to specify the component behaviour change techniques of stewardship interventions in long-term care facilities and identify those components associated with improved outcomes.MethodA systematic review (CRD42018103803) was conducted through electronic database searches. Two behavioural science frameworks, the Behaviour Change Wheel and Behaviour Change Technique Taxonomy were used to classify intervention descriptions into intervention types and component behaviour change techniques used. Study design and outcome heterogeneity prevented meta-analysis and meta-regression. Interventions were categorised as 'very promising' (all outcomes statistically significant), 'quite promising' (some outcomes statistically significant), or 'not promising' (no outcomes statistically significant). 'Promise ratios' (PR) were calculated for identified intervention types and behaviour change techniques by dividing the number of (very or quite) promising interventions featuring the intervention type or behaviour change technique by the number of interventions featuring the intervention type or behaviour change technique that were not promising. Promising intervention types and behaviour change techniques were defined as those with a PR ≥ 2.ResultsTwenty studies (of19 interventions) were included. Seven interventions (37%) were 'very promising', eight 'quite promising' (42%) and four 'not promising' (21%). Most promising intervention types were 'persuasion' (n = 12; promise ratio (PR) = 5.0), 'enablement' (n = 16; PR = 4.33) and 'education' (n = 19; PR = 3.75). Most promising behaviour change techniques were 'feedback on behaviour' (n = 9; PR = 8.0) and 'restructuring the social environment' (e.g. staff role changes; n = 8; PR = 7.0).ConclusionSystematic identification of the active ingredients of antimicrobial stewardship in long-term care facilities was facilitated through the application of behavioural science frameworks. Incorporating environmental restructuring and performance feedback may be promising intervention strategies for antimicrobial stewardship interventions within long-term care facilities.

Dataset Information

Factors influencing antibiotic prescribing in long-term care facilities: a qualitative in-depth study.

Background

Methods

Results

Conclusions

Publications

Factors influencing antibiotic prescribing in long-term care facilities: a qualitative in-depth study.

Similar Datasets

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