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Factors affecting patient flow in a neurosurgery department.
Irvine, S; Awan, M; Chharawala, F; Bhagawati, D; Lawrance, N; Peck, G; Peterson, D; Banerjee, S; Camp, S.
Afiliação
  • Irvine S; University Hospital North Durham, Durham, UK.
  • Awan M; Neurosurgery Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
  • Chharawala F; Neurosurgery Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
  • Bhagawati D; Neurosurgery Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
  • Lawrance N; Improvement Team, Imperial College Healthcare NHS Trust, London, UK.
  • Peck G; Major Trauma Centre, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK.
  • Peterson D; Neurosurgery Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
  • Banerjee S; Stroke Medicine, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
  • Camp S; Neurosurgery Department, Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, UK.
Ann R Coll Surg Engl ; 102(1): 18-24, 2020 Jan.
Article em En | MEDLINE | ID: mdl-31233336
ABSTRACT

INTRODUCTION:

Patient flow is the process by which movement of patients and clinical productivity is achieved. The objectives of this study were to implement and evaluate the NHS Improvement SAFER patient flow bundle, evaluate the impact of the Red2Green initiative, and assess the impact of frailty on patient flow. MATERIALS AND

METHODS:

All patients admitted to a neurosurgery unit from 1 September to 30 November 2017 were included. Using guidance set out by NHS, data were prospectively collected from daily ward lists and patient notes, including demographics, admission and discharge details, length of stay, anticipated discharge date, red days with reasons and frailty (Rockwood Clinical Frailty Scale). NHS reference costs were used for cost analyses.

RESULTS:

A total of 420 patients (55% elective) were included, totalling 3909 bed days. All patients received daily senior reviews before midday, and anticipated discharge dates were set at daily multidisciplinary team meetings. Ten per cent of patients were discharged before midday. There were 21% (837) red days, significantly more (76%) for emergency patients (639 vs 198 elective; P < 0.001); 63% red days were attributed to awaiting a bed in a local hospital; 25% (106) patients were classed as frail (50 elective), which was associated with a significantly longer length of stay (17.3 vs 6; P < 0.01), and more red days (615 vs 222; p<0.01). Considering excess bed charges and lost revenue (with penalties), red days cost over £1 million per year.

CONCLUSIONS:

SAFER has identified areas for improvement in patient flow, with obvious cost implications. It has created a platform for discussion within the referral network and identified a role for a geriatric liaison service.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal Base de dados: MEDLINE Assunto principal: Aceitação pelo Paciente de Cuidados de Saúde / Procedimentos Neurocirúrgicos / Departamentos Hospitalares Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Ann R Coll Surg Engl Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 11_ODS3_cobertura_universal Base de dados: MEDLINE Assunto principal: Aceitação pelo Paciente de Cuidados de Saúde / Procedimentos Neurocirúrgicos / Departamentos Hospitalares Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Ann R Coll Surg Engl Ano de publicação: 2020 Tipo de documento: Article