Using routine referral data for patients with knee and hip pain to improve access to specialist care
作者: Kate ButtonIrena SpasićRebecca PlayleDavid OwenMandy LauLiam HannawayStephen Jones
作者单位: 1School of Healthcare Sciences, Cardiff University, Eastgate House, Newport Road, CF24 0AB, Cardiff, UK
2Physiotherapy Department, Cardiff and Vale University Health Board, Cardiff, UK
3School of Computer Science & Informatics, Cardiff University, Cardiff, UK
4Centre for Trials Research, Cardiff University, Cardiff, UK
5Brynderwen Surgery, St Mellons, Cardiff, UK
6Trauma and Orthopaedics, Cardiff and Vale Orthopaedic Centre, University Hospital Llandough, Cardiff and Vale UHB, Cardiff, UK
刊名: BMC Musculoskeletal Disorders, 2020, Vol.21 (6), pp.341-351
来源数据库: Springer Nature Journal
DOI: 10.1186/s12891-020-3087-x
关键词: KneeHipMusculoskeletalCare pathwayText mining
原始语种摘要: Abstract(#br)Background(#br)Referral letters from primary care contain a large amount of information that could be used to improve the appropriateness of the referral pathway for individuals seeking specialist opinion for knee or hip pain. The primary aim of this study was to evaluate the content of the referral letters to identify information that can independently predict an optimal care pathway. Methods(#br)Using a prospective longitudinal design, a convenience sample of patients with hip or knee pain were recruited from orthopaedic, specialist general practice and advanced physiotherapy practitioner clinics. Individuals completed a Knee or hip Osteoarthritis Outcome Score at initial consultation and after 6 months. Participant demographics, body mass index, medication and co-morbidity...
全文获取路径: Springer Nature  (合作)
影响因子:1.875 (2012)