School of Healthcare Sciences, Cardiff University, Eastgate House, Newport Road, Cardiff, CF24 0AB, UK.
Physiotherapy Department, Cardiff and Vale University Health Board, Cardiff, UK.
BMC Musculoskelet Disord. 2020 Feb 3;21(1):66. doi: 10.1186/s12891-020-3087-x.
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.
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 data were extracted from the referral letters. Free text of the referral letters was mapped automatically onto the Unified Medical Language System to identify relevant clinical variables. Treatment outcomes were extracted from the consultation letters. Each outcome was classified as being an optimal or sub-optimal pathway, where an optimal pathway was defined as the one that results in the right treatment at the right time. Logistic regression was used to identify variables that were independently associated with an optimal pathway.
A total of 643 participants were recruited, 419 (66.7%) were classified as having an optimal pathway. Variables independently associated with having an optimal care pathway were lower body mass index (OR 1.0, 95% CI 0.9 to 1.0 p = 0.004), named disease or syndromes (OR 1.8, 95% CI 1.1 to 2.8, p = 0.02) and taking pharmacologic substances (OR 1.8, 95% CI 1.0 to 3.3, p = 0.02). Having a single diagnostic procedure was associated with a suboptimal pathway (OR 0.5, 95% CI 0.3 to 0.9 p < 0.001). Neither Knee nor Hip Osteoarthritis Outcome scores were associated with an optimal pathway. Body mass index was found to be a good predictor of patient rated function (coefficient - 0.8, 95% CI -1.1, - 0.4 p < 0.001).
Over 30% of patients followed sub-optimal care pathway, which represents potential inefficiency and wasted healthcare resource. A core data set including body mass index should be considered as this was a predictor of optimal care and patient rated pain and function.
初级保健医生的转诊信包含大量信息，这些信息可用于改善因膝关节或髋关节疼痛而寻求专家意见的个体的转诊途径的适当性。本研究的主要目的是评估转诊信的内容，以确定可独立预测最佳治疗途径的信息。
采用前瞻性纵向设计，从骨科、专科全科医生和高级物理治疗师诊所招募了膝关节或髋关节疼痛的便利样本患者。个体在初次就诊和 6 个月后完成膝关节或髋关节骨关节炎结局评分。从转诊信中提取参与者的人口统计学、体重指数、药物和合并症数据。将转诊信的自由文本自动映射到统一医学语言系统中，以识别相关的临床变量。从咨询信中提取治疗结果。将每个结果分类为最佳或次优途径，其中最佳途径定义为在正确的时间进行正确的治疗。使用逻辑回归识别与最佳途径独立相关的变量。
共招募了 643 名参与者，其中 419 名（66.7%）被归类为具有最佳途径。与最佳护理途径相关的独立变量包括较低的体重指数（OR 1.0，95%CI 0.9 至 1.0，p=0.004）、明确的疾病或综合征（OR 1.8，95%CI 1.1 至 2.8，p=0.02）和服用药物（OR 1.8，95%CI 1.0 至 3.3，p=0.02）。单一诊断程序与次优途径相关（OR 0.5，95%CI 0.3 至 0.9，p<0.001）。膝关节或髋关节骨关节炎结局评分均与最佳途径无关。体重指数被发现是患者自评功能的良好预测指标（系数-0.8，95%CI-1.1，-0.4，p<0.001）。
超过 30%的患者遵循次优的护理途径，这代表潜在的效率低下和浪费医疗资源。应考虑包含体重指数在内的核心数据集，因为这是最佳护理和患者自评疼痛和功能的预测指标。
