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ref="pagearea=logo&amp;targetsite=external&amp;targetcat=link&amp;targettype=publisher"><img class="source-thumb" src="/corehtml/pmc/pmcgifs/bookshelf/thumbs/th-techrev4-lrg.png" alt="Cover of Refinement of the HCUP Quality Indicators" /></a></div><div class="bkr_bib"><h1 id="_NBK43831_"><span itemprop="name">Refinement of the HCUP Quality Indicators</span></h1><p><i>Technical Reviews, No. 4</i></p><p class="contrib-group"><h4>Authors</h4>Core Project Team: <span itemprop="author">Sheryl M Davies</span>, MA, <span itemprop="author">Jeffrey Geppert</span>, JD, <span itemprop="author">Mark McClellan</span>, MD, PhD, <span itemprop="author">Kathryn M McDonald</span>, MM, <span itemprop="author">Patrick S Romano</span>, MD, MPH, and <span itemprop="author">Kaveh G Shojania</span>, MD.</p><h4>Affiliations</h4><div class="affiliation"><sup>1</sup> UCSF-Stanford Evidence-based Practice Center</div><div class="half_rhythm">Rockville (MD): <a href="http://www.ahrq.gov/" ref="pagearea=meta&amp;targetsite=external&amp;targetcat=link&amp;targettype=publisher"><span itemprop="publisher">Agency for Healthcare Research and Quality (US)</span></a>; <span itemprop="datePublished">2001 May</span>.<div class="small">Report No.: 01-0035</div></div><div><a href="/books/about/copyright/">Copyright Notice</a></div><a class="btn wsprkl bkr_rd" href="/books/n/techrev4/A549/?report=reader">Read</a></div><div class="bkr_clear"></div></div><div class="bkr_bottom_sep bkr_bottom_margin body-content whole_rhythm"><div itemprop="description"><h2>Structured Abstract</h2><div id="A532"><h4 class="inline">Objectives:</h4><p>In 1994, the Agency for Healthcare Research and Quality (AHRQ) developed the
Healthcare Cost and Utilization Project (HCUP) Quality Indicators (QIs), in
response to the increasing demand for information regarding the quality of
health care. These measures, based on discharge data, were intended to flag
potential quality problems in hospitals or regions. The purpose of this project
is to refine the original set of HCUP QIs (HCUP I) and recommend a revised
indicator set (HCUP II). Specifically this project aims to 1) identify quality
indicators reported in the literature and in use by health care organizations,
2) evaluate both HCUP I QIs and other indicators using literature review and
novel empirical methods, and 3) make recommendations for the HCUP II QI set and
further research. The project deferred evaluation of indicators of complications
to a separate study and report.</p></div><div id="A533"><h4 class="inline">Evaluation framework:</h4><p>Potential and current QIs were evaluated according to six criteria:</p><p>Face validity. An adequate QI must have sound clinical and or
empirical rationale for its use, and measure an important aspect of
quality that is subject to provider or health care system
control.</p><p>Precision. An adequate QI should have relatively large variation
among providers that is not due to random variation or patient
characteristics.</p><p>Minimum bias. The indicator should not be affected by systematic
differences in patient case-mix. In instances where such systematic
differences exist, an adequate risk adjustment system should be
available based on HCUP discharge data.</p><p>Construct validity. The indicator should be supported by evidence of
a relationship to quality, and should be related to other indicators
intended to measure the same or related aspects of quality.</p><p>Fosters real quality improvement. The indicator should not create
incentives or rewards for providers to improve measured performance
without truly improving quality of care.</p><p>Application. The indicator should have been used effectively in the
past, and/or have high potential for working well with other
indicators currently in use.</p></div><div id="A540"><h4 class="inline">Literature review:</h4><p>Two separate literature reviews were performed using MEDLINE. The first search
(Phase 1) utilized a structured methodology, designed to locate quality
indicators developed since 1994 and reported in the literature. The search terms
used were "hospital, statistic and methods" and "quality indicator." Indicators
were also identified through web searches and contacts with quality measurement
experts.A second search (Phase 2) was used to evaluate each indicator according
to the evaluation framework above. MEDLINE (1990-2001) was searched for relevant
articles discussing one of the six evaluation framework criterion for selected
QIs.</p></div><div id="A541"><h4 class="inline">Empirical evaluation:</h4><p>Selected indicators were tested using a series of empirical analyses designed to
test precision (signal variance, provider- or area-level variance,
signal-to-noise ratio, and R-square), minimum bias (impact of risk adjustment
measured by Spearman's rank correlation, percentage remaining in extreme
deciles, absolute change in performance, and percent changing more than two
deciles), and construct validity (Pearson correlation and factor analysis). Each
indicator was assigned a summary score for empirical performance using results
from the precision, and to a lesser extent bias tests.</p></div><div id="A542"><h4 class="inline">Selection criteria:</h4><p>Due to resource constraints, only a portion of the over 200 identified indicators
were evaluated comprehensively (all empirical analyses tests and detailed
literature review). Indicators were selected for comprehensive evaluation based
on the following criteria: the indicator must have adequate clinical rationale; the measured event must be somewhat frequent and occur in an adequate number of providers or areas; the indicator must perform adequately well on preliminary tests of precision.</p></div><div id="A546"><h4 class="inline">Main results:</h4><p>Forty-five indicators were recommended for use in the HCUP II QI set, including
volume, mortality, utilization and ambulatory care sensitive condition measures.
Each indicator is appropriate for use as a "quality screen," meaning as an
initial tool to identify potential quality problems. These indicators would not
be expected to definitively distinguish low quality providers or areas from high
quality providers or areas. The empirical performance of each indicator was
evaluated; summary empirical scores ranged from 3 to 23 out of a possible 26.
All indicators are recommended with specific caveats of use, identified
primarily through literature review. Most volume and utilization indicators are
best used as proxy measures of quality. Some indicators carry substantial
selection bias due to the elective nature of some admissions and procedures.
Other indicators are subject to information bias, due to the inability to track
post-hospitalization mortality rates. Confounding bias, due to systematic
differences in case mix, was found to be a concern for some indicators. Further,
many indicators have limited evidence supporting their construct validity;
others are somewhat imprecise and require smoothing techniques. Finally, some
indicators may create perverse incentives for over- or under-utilization..
Specifics of the caveats of use can be found in the Executive Summary of this
report. Ten indicators are recommended for use only in conjunction with other
indicators.</p><p>Twenty-five of the indicators are provider level indicators, meaning that they
evaluate quality of care at the provider (in this case, hospital) level. These
indicators include seven procedure volume indicators (AAA repair, carotid
endarterectomy, CABG, esophageal resection, pancreatic resection, pediatric
heart surgery, and PTCA), five procedure utilization indicators (Cesarean
section rate, incidental appendectomy rate, bi-lateral heart catheterization
rate, VBAC rate, and laparoscopic cholecystectomy rate), six in-hospital medical
mortality indicators (AMI, CHF, GI hemorrhage, hip fracture, pneumonia and
stroke), and seven in-hospital provider mortality indicators (AAA repair, CABG,
craniotomy, esophageal resection, hip replacement, pancreatic resection, and
pediatric heart surgery).</p><p>Twenty of the recommended indicators are area-level indicators, meaning that they
have population denominators and likely measure quality of the health care
system in an area. These indicators include four procedure utilization
indicators (CABG, hysterectomy, laminectomy, and PTCA), and sixteen ambulatory
care sensitive condition indicators (dehydration, bacterial pneumonia, urinary
tract infection, perforated appendix, angina, asthma, COPD, CHF, diabetes short
term complications, uncontrolled diabetes, diabetes long term complications,
lower extremity amputation in diabetics, hypertension, low birth weight,
pediatric asthma and pediatric gastroenteritis).</p></div><div id="A547"><h4 class="inline">Conclusions and future research:</h4><p>This project identified 45 indicators that are promising for use as quality
screens, demonstrating through literature review and empirical analyses that
useful information regarding quality of health care can be gleaned from
routinely collected administrative data. However, these indicators have
important limitations and could benefit from further research. Techniques such
as risk adjustment and multivariate smoothing are currently available to reduce
the impact of some of these limitations, but other limitations remain.</p><p>There are two major recommendations for further action and research - (1) the
improvement of HCUP data and subsequently the HCUP QIs to address some of the
noted limitations, and (2) further research into quality measurement and the
reality of these limitations. The HCUP QIs could benefit from the inclusion of
additional data, some of which is now routinely available in some states.
Important additions to data include hospital outpatient; emergency room and
ambulatory surgery data; linkages to vital statistics such as death records to
track post-hospitalization deaths for mortality indicators or birth records for
better obstetric risk adjustment; and additional clinical data to improve the
risk adjustment available. In addition, research into quality measurement should
continue. The relationships underlying the validity of volume measures and
utilization measures needs to be revisited periodically to assure validity.
Further, research surrounding the construct validity of indicators is essential.
Finally, further research is needed regarding risk adjustment of indicators, and
how alternative risk adjustment methods affect indicators.</p></div></div></div></div><div class="fm-sec"><div><p>Contributors: Amber Barnato, MD, Paul Collins, BA, Bradford Duncan, MD, Michael Gould, MD, MS, Paul Heidenreich, MD, Corinna Haberland, MD, Paul Matz, MD, Courtney Maclean, BA, Susana Martins, MD, Kristine McCoy, MPH, Suzanne Olson, MA, L LaShawndra Pace, BA, Mark Schleinitz, MD, Herb Szeto, MD, Carol Vorhaus, MBA, Peter Weiss, MD, Meghan Wheat, BA. Consultant: Douglas Staiger, PhD. AHRQ Contributors: Anne Elixhauser, PhD, Margaret Coopey, RN, MGA, MPS.</p></div><div><p>Prepared for: Agency for Healthcare Research and
Quality, U.S. Department of Health and Human Services.<a href="#address"><sup>1</sup></a>
Contract No. 290-97-0013. Prepared by: UCSF-Stanford Evidence-based Practice Center.</p></div><div><h4 class="inline">Suggested citation:</h4><p>Davies SM, Geppert J, McClellan M, et al. Refinement of the HCUP Quality Indicators. Technical Review Number 4 (Prepared by UCSF-Stanford Evidence-based Practice Center under Contract No. 290-97-0013). AHRQ Publication No. 01-0035. Rockville, MD: Agency for Healthcare Research and Quality. May 2001.</p></div><div><p>The authors of this report are responsible for its content. Statements in the report
should not be construed as endorsement by the Agency for Healthcare Research and
Quality or the U.S. Department of Health and Human Services of a particular drug,
device, test, treatment, or other clinical service.</p><p>The Agency does not guarantee the accuracy of this report. Questions regarding the content of this report, including all tables, figures, copyrights, and reference citations must be directed to the Evidence-based Practice Center that developed the report.</p></div><div><dl class="temp-labeled-list small"><dl class="bkr_refwrap"><dt>1</dt><dd><div id="address"><p class="no_top_margin">2101 East Jefferson Street, Rockville, MD 20852. <a href="http://www.ahrq.gov/" ref="pagearea=body&amp;targetsite=external&amp;targetcat=link&amp;targettype=uri">www<wbr style="display:inline-block"></wbr>&#8203;.ahrq.gov</a>
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