Do coder characteristics influence validity of ICD-10 hospital discharge data?
Do coder characteristics influence validity of ICD-10 hospital discharge data?
复制标题
DOI：
10.1186/1472-6963-10-99
复制
发表时间：
2010-04-21
影响因子：
2.8
通讯作者：
Beck CA
中科院分区：
文献类型：
--
作者：
Hennessy DA;Quan H;Faris PD;Beck CA
行政数据被广泛用于研究卫生系统和作出重要的卫生政策决定。然而，在这些研究中，很少有人知道编码器特性对行政数据有效性的影响。我们的目标是描述编码出院数据的几个有效性指标与1）编码员的编码量（≥ 13，000与<13，000记录），2）编码员的就业状况（全职与兼职）和3）医院类型之间的关系。这项描述性研究检查了2002年4月至2007年3月加拿大卡尔加里4家医院ICD-10编码出院记录中的6项表面效度指标。具体而言，通过编码量和就业状况以及医院类型比较编码诊断、手术、并发症、Z代码和以8或9结尾的代码的平均数量。还比较了6种不同复杂性的主要条件下编码器特征的平均诊断数。接下来，计算Kappa统计量，以评估出院数据与护理图表评审员重新提取的链接图表数据之间的一致性。跨编码器特性比较Kappas。在研究期间，由59名编码员对422，618份出院记录进行编码。每个记录的平均诊断数从2002/2003年的5.2个下降到2006/2007年的3.9个，而每年编码的记录数从69 613个增加到102 842个。三级医院的编码员编码了最多的诊断（5.0，而其他地点为3.9和3.8）。对于任何其他表面有效性指标，编码器或研究中心特征均无变化。随着主要诊断复杂性的增加，平均诊断数从1.5增加到7.9，但不随编码器特性而变化。编码数据和病历审查之间的一致性（kappa）未显示编码器特征方面的任何一致模式。这项大型研究表明，编码器的特点不影响医院出院数据的有效性。其他司法管辖区可能会受益于实施与我们类似的就业计划，例如：要求2年的大学培训计划，跨站点的单一管理结构，以及站点之间的编码员轮换。局限性包括由于隐私问题，可用于研究的编码器特性很少。
Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type. This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics. 422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics. This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.
登录
查看更多内容
影响因子：
3
作者：
Quan, H;Parsons, GA;Ghali, WA
通讯作者：
Ghali, WA
影响因子：
3
作者：
Elixhauser, A;Steiner, C;Coffey, RN
通讯作者：
Coffey, RN
影响因子：
3.4
作者：
O'Malley, KJ;Cook, KF;Ashton, CM
通讯作者：
Ashton, CM
影响因子：
2.8
作者：
De Coster, Carolyn;Quan, Hude;Ghali, William A.
通讯作者：
Ghali, William A.
影响因子：
39.2
作者：
IEZZONI, LI;BURNSIDE, S;LEVINE, PA
通讯作者：
LEVINE, PA