How do advanced nurse practitioners enhance healthcare outcomes in frail older patients living in care homes?
Bibliographic record
Abstract
Background: As the UK healthcare service strains to meet the demand from its ageing population for 24-hour care, there is an increased need to develop an effective way to provide quality care to frail residents living in care homes. The role of the advanced nurse practitioner (ANP) has evolved over the last 20 years, developing in part to meet the shortfall of GPs and geriatric specialist doctors. Despite research having been previously conducted in the US and Canada into how the ANP role can function within care homes, there has been limited exploration into how the role can enhance UK healthcare outcomes in relation to the 2019 NHS Long-Term Plan, which aimed to provide care closer to home for ageing patients. Aims: This paper was designed to critically review published primary research papers and evaluate the impact of the ANP role on healthcare outcomes for frail elderly care home residents. Its objective was to help guide future healthcare delivery policy within the UK. Methods: A saturated systematic search of primary research literature was conducted. An inclusion/exclusion criterion was also utilised. Key papers identified were subject to critical synthesis, using ratified critical appraisal tools from the Joanna Briggs Institute and mixed-method appraisal tool by Hong et al (2018) . A thematic/narrative approach was employed to evaluate the findings of the mixed-method heterogenic-style research. Results: A total of 14 primary research papers met the criteria, which included mixed methods of study from across four English language-speaking countries. Five outcome themes were recurrent throughout the synthesis of the results, including, in order of prevalence: improved/equivalent quality of care; successful collaborative role; reduced hospitalisations; timely access to primary/secondary care; colleague/patient/family satisfaction. Discussion: Following the review of the highlighted themes, there was a consensus that ANPs positively influence the care quality of elderly patients living within care homes. Although no superiority over a physician approach was found, there was indication of supplementary benefits when including ANPs in the care home setting. These include instilling positive role models into the healthcare environment, increasing the general knowledge and education capacity of care staff, and streamlining communication—especially within advanced care planning and coordination of care. These qualities clearly encompass the current NHS priorities of the 2019 Long-Term Plan and the Enhanced Health in Care Homes Framework, which are set to be fully achieved by 2024.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 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".