Nivel (Netherlands Institute for Health Services Research), Department of Primary Care, Utrecht, The Netherlands.
Department of General Practice and Elderly Care Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.
Eur J Gen Pract. 2020 Dec;26(1):189-195. doi: 10.1080/13814788.2020.1854719.
Patients with multimorbidity who frequently contact the general practice, use emergency care or have unplanned hospitalisations, may benefit from a proactive integrated care intervention. General practitioners are not always aware of who these 'high need' patients are. Electronic medical records are a potential source to identify them.
To find predictors of high care needs in general practice electronic medical records of patients with multimorbidity and assess their predictive value.
General practice electronic medical records of 245,065 patients with ≥2 chronic diseases were linked to hospital claims data. Probit regression analysis was conducted to predict i) having at least 12 general practice contacts per year, ii) emergency department visit(s), and iii) unplanned hospitalisation(s). Predictors were patients' age, sex, morbidity, health services and medication use in the previous year.
11% of multimorbid patients had ≥12 general practice contacts, which could be reliably predicted by the number of contacts in the previous year (PPV 42%). The model containing all predictors had only slightly better predictive value (PPV 44%). Emergency department visits and unplanned hospitalisations (12% and 7% of multimorbid patients, respectively) could be predicted less accurately (PPV 27% and 20%). Those with frequent contact with the general practice hardly overlapped with ED visitors (29%) or persons with unplanned hospitalisations (17%).
Among multimorbid populations various 'high need' groups exist. Patients with high needs for general practice care can be identified by their previous use of general practice care. To identify frequent ED visitors and persons with unplanned hospitalisations, additional information is needed.
患有多种疾病且经常与全科医生联系、使用急诊护理或计划性住院治疗的患者可能受益于主动的综合护理干预。全科医生并不总是知道哪些患者是“高需求”患者。电子病历可能是识别这些患者的潜在来源。
在患有多种疾病的患者的全科医生电子病历中找到高护理需求的预测因素,并评估其预测价值。
将 245065 名患有≥2 种慢性疾病的患者的全科医生电子病历与住院索赔数据相关联。进行概率回归分析,以预测 i)每年至少有 12 次全科医生就诊,ii)急诊就诊,iii)计划性住院。预测因素为患者前一年的年龄、性别、疾病负担、卫生服务和药物使用情况。
11%的患有多种疾病的患者每年至少有 12 次全科医生就诊,这可以通过前一年的就诊次数可靠地预测(PPV 42%)。包含所有预测因素的模型仅略有更好的预测价值(PPV 44%)。急诊就诊和计划性住院(分别为 12%和 7%的患有多种疾病的患者)的预测精度较低(PPV 27%和 20%)。那些与全科医生有频繁接触的患者与急诊就诊者(29%)或计划性住院患者(17%)几乎没有重叠。
在患有多种疾病的人群中存在各种“高需求”群体。通过患者之前对全科医生护理的使用,可以识别出高需求的全科医生护理患者。要识别出频繁的急诊就诊者和计划性住院患者,还需要其他信息。