Dataset Information

The effectiveness of allied health and nurse practitioner models-of-care in managing musculoskeletal conditions in the emergency department: a systematic review and meta-analysis.

ABSTRACT:

Background

Musculoskeletal conditions are the most common health condition seen in emergency departments. Hence, the most effective approaches to managing these conditions is of interest. This systematic review aimed to evaluate the effectiveness of allied health and nursing models of care for the management of musculoskeletal pain in ED.

Methods

MEDLINE, EMBASE, CINAHL and LILACS databases were searched from inception to March 2023 for published randomised trials that compared the effectiveness of allied health and nursing models of care for musculoskeletal conditions in ED to usual ED care. Trials were eligible if they enrolled participants presenting to ED with a musculoskeletal condition including low back pain, neck pain, upper or lower limb pain and any soft tissue injury. Trials that included patients with serious pathology (e.g. malignancy, infection or cauda equina syndrome) were excluded. The primary outcome was patient-flow; other outcomes included pain intensity, disability, hospital admission and re-presentation rates, patient satisfaction, medication prescription and adverse events. Two reviewers performed search screening, data extraction, quality and certainty of evidence assessments.

Results

We identified 1746 records and included 5 randomised trials (n = 1512 patients). Only one trial (n = 260) reported on patient-flow. The study provides very-low certainty evidence that a greater proportion of patients were seen within 20 min when seen by a physician (98%) than when seen by a nurse (86%) or physiotherapist (77%). There was no difference in pain intensity and disability between patients managed by ED physicians and those managed by physiotherapists. Evidence was limited regarding patient satisfaction, inpatient admission and ED re-presentation rates, medication prescription and adverse events. The certainty of evidence for secondary outcomes ranged from very-low to low, but generally did not suggest a benefit of one model over another.

Conclusion

There is limited research to judge the effectiveness of allied health and nursing models of care for the management of musculoskeletal conditions in ED. Currently, it is unclear as to whether allied health and nurse practitioners are more effective than ED physicians at managing musculoskeletal conditions in ED. Further high-quality trials investigating the impact of models of care on service and health outcomes are needed.

SUBMITTER: Vella SP

PROVIDER: S-EPMC10795385 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Publications

The effectiveness of allied health and nurse practitioner models-of-care in managing musculoskeletal conditions in the emergency department: a systematic review and meta-analysis.

Vella Simon P SP Melman Alla A Coombs Danielle D Maher Christopher G CG Swain Michael S MS Monk Elizabeth E Machado Gustavo C GC

BMC emergency medicine 20240117 1

<h4>Background</h4>Musculoskeletal conditions are the most common health condition seen in emergency departments. Hence, the most effective approaches to managing these conditions is of interest. This systematic review aimed to evaluate the effectiveness of allied health and nursing models of care for the management of musculoskeletal pain in ED.<h4>Methods</h4>MEDLINE, EMBASE, CINAHL and LILACS databases were searched from inception to March 2023 for published randomised trials that compared th ...[more]

PMID: 38233743

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Dataset Information

The effectiveness of allied health and nurse practitioner models-of-care in managing musculoskeletal conditions in the emergency department: a systematic review and meta-analysis.

Background

Methods

Results

Conclusion

Publications

The effectiveness of allied health and nurse practitioner models-of-care in managing musculoskeletal conditions in the emergency department: a systematic review and meta-analysis.

Similar Datasets

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