Are Volume Standards Accurate Measures of Quality?

描述（由申请人提供）：为了响应IOM患者安全议程，ahrq赞助的一份报告指定“将特定手术和程序本地化到高容量中心”作为患者安全研究的优先领域。在缺乏国家质量报告卡的情况下，由于手术数量是质量的代表，因此提倡将患者选择性地转介到大容量医院进行高风险手术。随着Leapfrog集团安全倡议的启动，这些政策建议现在正在私营部门实施。然而，对于支持数量-结果关系的证据的强度，提出了重要的问题。拟议项目的主要目标是调查使用“数量”标准而不是“质量”标准有选择地将病人转诊到医院的影响。为了验证这一假设，我们将首先使用增强的管理数据来制定风险调整的质量措施。然后，我们将在模拟中使用这些质量测量来验证主要假设，即通过从低质量中心转移患者来实现高风险手术的区域化将比从低容量中心转移患者带来更好的人群结果。该项目的一个次要产品将解决另一个与使用行政数据作为基准性能有关的中心问题，即次要诊断通常不能区分并发症和先前存在的疾病。无法将两者分开很可能导致有偏见的风险调整和不准确的质量度量。本研究将使用加州住院病人数据库（SID）进行。该数据集中的所有ICD-9-CM代码都标有日期戳，以区分入院时出现的病症和入院后出现的病症。只有两个州，加利福尼亚和纽约，在所有的二次诊断上都有日期戳。研究发现，日期戳的缺失会影响质量测量，这将为其他州采用日期戳提供支持。从该项目中获得的知识将推动质量测量领域的发展，并将为在全国范围内制定高风险手术区域化的合理政策提供信息支持。

DESCRIPTION (provided by applicant): In response to the IOM patient safety agenda, an AHRQ-sponsored report has designated "localizing specific surgeries and procedures to high volume centers" as a high priority area for patient safety research. In the absence of a national quality report card, selective referral of patients to high-volume hospitals has been advocated for high-risk surgery on the grounds that procedure volume is a quality proxy. With the launching of the Leapfrog Group safety initiative, these policy recommendations are now being implemented in the private sector. Significant questions, however, have been raised regarding the strength of the evidence supporting the volume-outcome relationship. The primary objective of the proposed project is to investigate the implications of selectively referring patients to hospitals using "volume" standards as opposed to "quality" criteria. To test this hypothesis, we will first use enhanced administrative data to develop risk-adjusted measures of quality. We will then use these quality measures in a simulation to test the primary hypothesis that Regionalizing high-risk surgery by diverting patients from low-quality centers will lead to better population outcomes than diverting patients from low-volume centers. A secondary product of this project will address another central issue pertaining to the use of administrative data for bench-marking performance - namely, that secondary diagnoses do not typically distinguish between complications and preexisting conditions. The inability to separate the two is likely to lead to biased risk adjustment and inaccurate quality measures. This study will be conducted using the California State Inpatient Databases (SID). All ICD-9-CM codes within this data set are date stamped, distinguishing conditions present at the time of admission from conditions that developed following hospital admission. Only two states, California and New York, include a date stamp on all secondary diagnoses. The finding that the absence of date stamping biases quality measurement would lend support to the adoption of date stamping in other states. The knowledge gained from this project will advance the field of quality measurement and will provide information in support of rational policy making regarding the regionalization of high-risk surgery on a national scale.