Are Volume Standards Accurate Measures of Quality?

描述(由申请人提供)：为了响应国际移民组织患者安全议程，AHRQ赞助的一份报告将“将特定的手术和程序本地化到大容量中心”指定为患者安全研究的高度优先领域。在没有国家质量成绩单的情况下，高风险手术主张有选择地将患者转诊到高容量医院，理由是程序量是质量的代替品。随着LeapFrog Group安全倡议的发起，这些政策建议现正在私营部门实施。然而，对于支持体积-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”标准选择性地将病人转介到医院的影响。为了验证这一假设，我们将首先使用增强的管理数据来开发经风险调整的质量衡量标准。然后，我们将在模拟中使用这些质量指标来测试主要假设，即通过将患者从低质量中心分流来将高风险手术区域化将比从低流量中心分流患者带来更好的总体结果。该项目的一个次要产品将解决与使用行政数据确定业绩基准有关的另一个核心问题--即二次诊断通常不区分并发症和先前存在的情况。无法将两者分开，可能会导致有偏见的风险调整和不准确的质量衡量。这项研究将使用加利福尼亚州住院患者数据库(SID)进行。该数据集中的所有ICD-9-CM代码都标有日期戳，以区分入院时存在的情况和入院后出现的情况。只有两个州，加利福尼亚州和纽约州，在所有二次诊断上都有日期戳。没有日期戳的发现对质量衡量有偏见，这一发现将支持其他州采用日期戳。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合理的高风险手术区域化政策提供信息。

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.