Gadzhanova Svetla, Iankov Ivan I, Warren James R, Stanek Jan, Misan Gary M, Baig Zak, Ponte Lorenzo
Computer Science--Tamaki Campus, The University of Auckland, Private Bag 92019, Auckland, New Zealand.
J Am Med Inform Assoc. 2007 Jan-Feb;14(1):100-9. doi: 10.1197/jamia.M2169. Epub 2006 Oct 26.
This paper presents a model for analysis of chronic disease prescribing action over time in terms of transitions in status of therapy as indicated in electronic prescribing records. The quality of alerts derived from these therapeutic state transitions is assessed in the context of antihypertensive prescribing.
A set of alert criteria is developed based on analysis of state-transition in past antihypertensive prescribing of a rural Australian General Practice. Thirty active patients coded as hypertensive with alerts on six months of previously un-reviewed prescribing, and 30 hypertensive patients without alerts, are randomly sampled and independently reviewed by the practice's two main general practice physicians (GPs), each GP reviewing 20 alert and 20 non-alert cases (providing 10 alert and 10 non-alert cases for agreement assessment).
GPs provide blind assessment of quality of hypertension management and retrospective assessment of alert relevance.
Alerts were found on 66 of 611 cases with coded hypertension with 37 alerts on the 30 sampled alert cases. GPs assessed alerting sensitivity as 74% (CI 52% - 89%) and specificity as 61% (CI 45% - 74%) for the sample, which is estimated as 26% sensitivity and 93% specificity for the antihypertensive population. Agreement between the GPs on assessment of alert relevance was fair (kappa = 0.37).
Data-driven development of alerts from electronic prescribing records using analysis of therapeutic state transition shows promise for derivation of high-specificity alerts to improve the quality of chronic disease management activities.
本文提出了一个模型，用于根据电子处方记录中所示的治疗状态转变，分析慢性病随时间的处方行为。在抗高血压处方的背景下，评估从这些治疗状态转变中得出的警示的质量。
基于对澳大利亚一个乡村全科诊所过去抗高血压处方的状态转变分析，制定了一组警示标准。从该诊所中随机抽取30名有警示的活跃高血压患者（其六个月前未审查的处方有警示）和30名无警示的高血压患者，并由该诊所的两名主要全科医生（GP）进行独立审查，每位全科医生审查20例有警示病例和20例无警示病例（提供10例有警示病例和10例无警示病例用于一致性评估）。
全科医生对高血压管理质量进行盲法评估，并对警示相关性进行回顾性评估。
在611例编码为高血压的病例中，有66例发现了警示，在30例抽样的有警示病例中有37例警示。对于该样本，全科医生评估警示的敏感性为74%（可信区间52% - 89%），特异性为61%（可信区间45% - 74%），估计抗高血压人群的敏感性为26%，特异性为93%。全科医生在警示相关性评估上的一致性一般（kappa = 0.37）。
通过治疗状态转变分析，从电子处方记录中进行数据驱动的警示开发，显示出有望得出高特异性警示以改善慢性病管理活动的质量。
