The current study refers to the affinity analysis of a prescription and diagnosis dataset and focuses on how prescription behavior changes after the detection of a disorder. Using a subset of patients that have been diagnosed, at least once, with hypertension and hyperlipidemia, examines the prescription behavior of the doctor after the detection of gastroesophageal reflux (K21), or insulin-dependent diabetes mellitus (E10). Diagnosis and prescription data were collected during consecutive visits of 4473 patients in a 3 years period. The analysis of the prescription data before and after the diagnosis of K21 and E10 reveals the popular substances for each disorder, such as Metformin for E10, or Omeprazole for K21 and substances that are discontinued including the same popular substances as well. It also reveals that substances that treat the main disorders of the group, such as Simvastatin and Hydrochlorothiazide are discontinued after the diagnosis of K21 and E10. Apart from the medical findings, which must be subject of further research, the proposed methodology can be employed for studying the prescription behavior of physicians and how it changes after specific diagnoses.

当前的研究涉及处方和诊断数据集的亲和力分析，并着重于检测到疾病后处方行为如何变化。使用至少被诊断患有高血压和高脂血症的一部分患者，在检测到胃食管反流（K21）或胰岛素依赖型糖尿病（E10）后检查医生的处方行为。在3年内连续访问4473名患者的过程中收集了诊断和处方数据。对K21和E10诊断之前和之后的处方数据进行分析，可以发现每种疾病的流行物质，例如E10的二甲双胍或K21的奥美拉唑，以及已停产的包括相同流行物质的物质。它还显示，在诊断出K21和E10后，已停止治疗该组主要疾病的物质，例如辛伐他汀和氢氯噻嗪。除了必须做进一步研究的医学发现之外，提出的方法还可以用于研究医生的处方行为以及特定诊断后其变化。