在电子病历中识别肌肉骨骼疾病：一项使用初级医疗保健信息传递（DELPHI）数据库的患病率及验证研究。

Identifying musculoskeletal conditions in electronic medical records: a prevalence and validation study using the Deliver Primary Healthcare Information (DELPHI) database.

作者信息

Ryan Bridget L, Maddocks Heather L, McKay Scott, Petrella Robert, Terry Amanda L, Stewart Moira

机构信息

Centre for Studies in Family Medicine, Department of Family Medicine, Department of Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry, The University of Western Ontario, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada.

Centre for Studies in Family Medicine, Department of Family Medicine, Schulich School of Medicine & Dentistry, The University of Western Ontario, 1151 Richmond Street, London, Ontario, N6A 3K7, Canada.

出版信息

BMC Musculoskelet Disord. 2019 May 3;20(1):187. doi: 10.1186/s12891-019-2568-2.

DOI:10.1186/s12891-019-2568-2

PMID:31053119

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6499985/

Abstract

BACKGROUND

Musculoskeletal (MSK) conditions are a common presentation in primary care. This study sought to determine the prevalence of MSK conditions in primary care in Ontario and to validate the extent to which health administrative date billing codes accurately represent MSK diagnoses.

METHODS

De-identified electronic medical records (EMR) from the DELPHI database in southwestern Ontario, which contains 2493 patients (55.6% female, mean age 50.3 years (SD = 22.2)) and 21,964 encounters (July 1, 2006-June 30, 2010) were used for the analyses. Outcomes included: validation measures of agreement between International Classification of Diseases (ICD-9) diagnostic codes (health administrative data) and International Classification of Primary Care (ICPC) diagnoses defined as the reference standard, time to first ICD-9 code, prevalence, and healthcare utilization.

RESULTS

There were 2940 true positive MSK encounters with primary care practitioners for 998 patients. Performance of the ICD-9 diagnostic codes included sensitivity = 76.5%, specificity = 95.2%, PPV = 94.6%, and NPV = 78.7%, compared to the ICPC reference standard. The majority of 998 patients were coded with both an ICPC and ICD-9 MSK code at their first or second encounter (67.4%). However, 23.5% of patients with the ICPC reference standard MSK were never coded with ICD-9. Four-year prevalence of MSK was 52.3% and varied by age (4.5% 0-17 years, 20.1% 18-44, 42.7% 45-64, and 32.7% 65+). Patients at MSK encounters had a higher number of: investigations (17.9% compared to 9.1%, p < .0001); referrals (17.6% compared to 14.3%, p < .0001); and prescriptions for opioids (17.2% compared to 5.3%, p < .0001).

CONCLUSIONS

This study determined the prevalence of musculoskeletal conditions in primary care in Ontario using a reference standard definition. The study highlighted the value of using primary care ICPC codes to validate a definition for musculoskeletal conditions. Health administrative data can be used to ascertain the presence of musculoskeletal conditions; however, ICD-9 codes may underrepresent the prevalence of MSK conditions.

摘要

背景

肌肉骨骼疾病是基层医疗中常见的病症。本研究旨在确定安大略省基层医疗中肌肉骨骼疾病的患病率，并验证卫生行政数据计费代码准确反映肌肉骨骼疾病诊断的程度。

方法

使用安大略省西南部DELPHI数据库中去识别化的电子病历（EMR）进行分析，该数据库包含2493名患者（女性占55.6%，平均年龄50.3岁（标准差=22.2））以及21964次就诊记录（2006年7月1日至2010年6月30日）。研究结果包括：将国际疾病分类（ICD-9）诊断代码（卫生行政数据）与定义为参考标准的初级保健国际分类（ICPC）诊断之间的一致性验证指标、首次出现ICD-9代码的时间、患病率以及医疗服务利用情况。

结果

998名患者与基层医疗从业者进行了2940次确诊为肌肉骨骼疾病的就诊。与ICPC参考标准相比，ICD-9诊断代码的表现为：敏感性=76.5%，特异性=95.2%，阳性预测值=94.6%，阴性预测值=78.7%。998名患者中的大多数在首次或第二次就诊时同时被ICPC和ICD-9肌肉骨骼疾病代码编码（67.4%）。然而，23.5%具有ICPC参考标准肌肉骨骼疾病的患者从未被ICD-9编码。肌肉骨骼疾病的四年患病率为52.3%，且因年龄而异（0-17岁为4.5%，18-44岁为20.1%，45-64岁为42.7%，65岁及以上为32.7%）。患有肌肉骨骼疾病的患者进行的检查更多（17.9%对比9.1%，p<0.0001）；转诊更多（17.6%对比14.3%，p<0.0001）；开具阿片类药物处方的比例更高（17.2%对比5.3%，p<0.0001）。