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<title>American Journal of Medical Quality</title>
<url>http://ajm.sagepub.com:80/icons/banner/title.gif</url>
<link>http://ajm.sagepub.com</link>
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<item rdf:about="http://ajm.sagepub.com/cgi/reprint/24/3/182?rss=1">
<title><![CDATA[The Inequality in Health Care Quality]]></title>
<link>http://ajm.sagepub.com/cgi/reprint/24/3/182?rss=1</link>
<description><![CDATA[]]></description>
<dc:creator><![CDATA[Abouzaid, S., Maio, V.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609334172</dc:identifier>
<dc:title><![CDATA[The Inequality in Health Care Quality]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>184</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>182</prism:startingPage>
<prism:section>Article</prism:section>
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<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/185?rss=1">
<title><![CDATA[A Novel Method to Link and Validate Routinely Collected Emergency Department Clinical Data to Measure Quality of Care]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/185?rss=1</link>
<description><![CDATA[<p><b>The objective was to develop and validate a method to link routinely captured electronic data for the measurement of emergency department (ED) quality indicators. Electronic ED data were linked to calculate time to antibiotics and time to electrocardiogram (ECG) for pneumonia and chest pain patients, respectively; validation was by comparison with chart data. Linked electronic data correctly identified 40/40 pneumonia and 65/65 chest pain patients. The median difference in time to antibiotics calculated from linked electronic data versus chart data was 6 minutes (standard deviation [SD] = 14.0); for time to ECG it was 0 minutes (SD = 70). The percentage of ED patients meeting target time to antibiotics was 47% with electronic data versus 44% with charts; for time to ECG, 8% met target time with electronic data versus 11% with charts. A simple computer algorithm for linking routine ED electronic data for quality-of-care measurement was validated.</b></p>]]></description>
<dc:creator><![CDATA[Yip, A., Leduc, M., Teo, V., Timmons, M., Schull, M. J.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609333880</dc:identifier>
<dc:title><![CDATA[A Novel Method to Link and Validate Routinely Collected Emergency Department Clinical Data to Measure Quality of Care]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>191</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>185</prism:startingPage>
<prism:section>Article</prism:section>
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<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/192?rss=1">
<title><![CDATA[Learning From Defects to Enhance Morbidity and Mortality Conferences]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/192?rss=1</link>
<description><![CDATA[<p><b>While required by the Accreditation Council for Graduate Medical Education (ACGME) and recommended by the Institute of Medicine, there are few published studies demonstrating that morbidity and mortality conferences (MMCs) are an effective strategy to improve patient care. To learn from medical incidents and improve patient care, care-givers need to: (1) elicit input from all staff involved in the incident, (2) use a structured framework to investigate all underlying contributing factors, and (3) assign responsibility for management and follow-up on recommendations. Many MMCs lack these key elements. The specific aims of this article are to describe the use of the learning from a defect tool as a strategy to meet ACGME requirements, advance medical education, and enhance traditional MMCs in one fellowship program at an academic medical institution. In addition, this approach improved patient care and provided a foundation for our fellows to use to address patient safety defects after fellowship.</b></p>]]></description>
<dc:creator><![CDATA[Berenholtz, S. M., Hartsell, T. L., Pronovost, P. J.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332370</dc:identifier>
<dc:title><![CDATA[Learning From Defects to Enhance Morbidity and Mortality Conferences]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>195</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>192</prism:startingPage>
<prism:section>Article</prism:section>
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<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/196?rss=1">
<title><![CDATA[Systematic Review of Handoff Mnemonics Literature]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/196?rss=1</link>
<description><![CDATA[<p><b>A systematic review of published English-language articles on handoffs is conducted (1987 to June 4, 2008). Forty-six articles describing 24 handoff mnemonics are identified by trained reviewers. The majority (82.6%) have been published in the last 3 years (2006-2008), and SBAR (Situation, Background, Assessment, Recommendation) is the most frequently cited mnemonic (69.6%). Of 7 handoff research articles, only 4 study mnemonics. All 4 of these studies have relatively small sample sizes (10-100) and lack validated instruments. Only 1 study has obtained IRB approval. Scientifically rigorous research studies are needed to assess the effectiveness of handoff mnemonics. These should be published in the peer-reviewed literature using the Standards for QUality Improvement Reporting Excellence (SQUIRE) guidelines.</b></p>]]></description>
<dc:creator><![CDATA[Riesenberg, L. A., Leitzsch, J., Little, B. W.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332512</dc:identifier>
<dc:title><![CDATA[Systematic Review of Handoff Mnemonics Literature]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>204</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>196</prism:startingPage>
<prism:section>Article</prism:section>
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<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/205?rss=1">
<title><![CDATA[Hand Hygiene Compliance Rates in the United States--A One-Year Multicenter Collaboration Using Product/Volume Usage Measurement and Feedback]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/205?rss=1</link>
<description><![CDATA[<p><b>Hand hygiene (HH) is the single most important factor in the prevention of health care-acquired infections. The 3 most frequently reported methods of measuring HH compliance are: (1) direct observation, (2) self-reporting by health care workers (HCWs), and (3) indirect calculation based on HH product usage. This article presents the results of a 12-month multicenter collaboration assessing HH compliance rates at US health care facilities by measuring product usage and providing feedback about HH compliance. Our results show that HH compliance at baseline was 26% for intensive care units (ICUs) and 36% for non-ICUs. After 12 months of measuring product usage and providing feedback, compliance increased to 37% for ICUs and 51% for non-ICUs. (ICU,</b> <I>P</I> = <b>.0119; non-ICU,</b> <I>P</I> &lt; <b>.001). HH compliance in the United States can increase when monitoring is combined with feedback. However, HH still occurs at or below 50% compli- ance for both ICUs and non-ICUs.</b></p>]]></description>
<dc:creator><![CDATA[McGuckin, M., Waterman, R., Govednik, J.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332369</dc:identifier>
<dc:title><![CDATA[Hand Hygiene Compliance Rates in the United States--A One-Year Multicenter Collaboration Using Product/Volume Usage Measurement and Feedback]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>213</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>205</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/214?rss=1">
<title><![CDATA[A Patient Safety Curriculum for Graduate Medical Education: Results From a Needs Assessment of Educators and Patient Safety Experts]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/214?rss=1</link>
<description><![CDATA[<p><b>Graduate medical education (GME) has traditionally focused on the diagnosis and management of disease with little attention devoted to patient safety and systems thinking. In this article, we describe the results of a needs assessment conducted to develop a patient safety curriculum for GME. Eight program directors, 10 patient safety experts, and 9 experts in education technology were interviewed for this project. A total of 21 patient safety topics were identified in the categories of cultural, cognitive, and technical content and included communications and handoffs, sentinel event reporting and management, calling for help when in doubt, hand hygiene, universal protocol, fatigue, and the culture of safety and transparency. Objective structured clinical examinations and experiential learning (including simulation) were viewed as the most effective methods for teaching and assessing competence in patient safety. The results of this study provide a framework for the development of patient safety curricula in GME.</b></p>]]></description>
<dc:creator><![CDATA[Varkey, P., Karlapudi, S., Rose, S., Swensen, S.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332905</dc:identifier>
<dc:title><![CDATA[A Patient Safety Curriculum for Graduate Medical Education: Results From a Needs Assessment of Educators and Patient Safety Experts]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>221</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>214</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/222?rss=1">
<title><![CDATA[End-of-Life Decision Making in the Intensive Care Unit: Physician and Nurse Perspectives]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/222?rss=1</link>
<description><![CDATA[<p><b>End-of-life decision making, including consideration of advance directives and code status, is taking place more frequently in critical care units. There is a need to identify how nurses and physicians perceive end-of-life care so that nurse-physician understanding and communication can be improved. A total of 96 physicians and nurses completed a survey about their general beliefs and practices related to end-of-life care in the intensive care unit. Nurses were more likely to ask if there was a living will and to read it. Only 53% of physicians read living wills; however 90% of physicians consider the wishes in the living will when making recommendations to the family. Physicians were more likely to discuss do-not-resuscitate (DNR) orders only when a prognosis was poor. Family dynamics and medical/legal concerns most often affect decisions to obtain/write a DNR order for a critically ill patient. Suggested approaches for improving physician and nurse collaboration about end-of-life decision making are discussed.</b></p>]]></description>
<dc:creator><![CDATA[Westphal, D. M., McKee, S. A.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860608330825</dc:identifier>
<dc:title><![CDATA[End-of-Life Decision Making in the Intensive Care Unit: Physician and Nurse Perspectives]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>228</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>222</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/229?rss=1">
<title><![CDATA[Resident, Nursing Home, and State Factors Affecting the Reliability of Minimum Data Set Quality Measures]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/229?rss=1</link>
<description><![CDATA[<p><b>Nursing home quality measures impact policy decisions such as reimbursement or consumer choice. Quality indicators in the United States are collected through the federally mandated Minimum Data Set (MDS). Bias in MDS data collection or coding can thus have a negative impact on policy applications. To understand whether bias was present in coding, the authors studied 5174 pairs of MDS assessments that were independently collected by nursing home staff and study nurses from 206 nursing homes. The authors developed multivariate multilevel models to identify nursing home and resident characteristics that were significantly associated with the data quality of multiple MDS measures of nursing home quality. The outcomes were coding differences between nursing home staff and study nurses. Resident characteristics explained little of the variation in coding differences among facilities, while facilities characteristics explained 4% to 20% of the variation and state location further explained 13% to 34% of the variation. A generalized effect of nursing home state location tended to be consistent across measures. States that overidentified problems also tended to have worse quality indicators and vice versa. Comparisons of MDS-based quality indicators reflect differences in assessment practices at least as much as true quality differences. Efforts to standardize assessment practices across states are needed.</b></p>]]></description>
<dc:creator><![CDATA[Wu, N., Mor, V., Roy, J.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332510</dc:identifier>
<dc:title><![CDATA[Resident, Nursing Home, and State Factors Affecting the Reliability of Minimum Data Set Quality Measures]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>240</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>229</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/241?rss=1">
<title><![CDATA[Effect of Smoking Cessation Advice on Cardiovascular Disease]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/241?rss=1</link>
<description><![CDATA[<p><b>Performance measures and guidelines encourage physicians to advise smokers to quit. The effect of these efforts on the morbidity, mortality, and cost of cardiovascular disease is not known. This article analyzes the effects of offering smoking cessation advice in the US population. The Archimedes model is used to simulate several clinical trials in which basic advice and medication advice are offered and to calculate the rates of myocardial infarctions, congestive heart disease deaths, strokes, life years, quality-adjusted life years (QALYs), costs, and cost/ QALY. The simulated population is a representative sample of the US population drawn from the Third National Health and Nutrition Survey conducted just before the performance measures and guidelines were introduced. The results show that offering basic advice and medication advice can prevent about 13% and 19% of myocardial infarctions and strokes, respectively. The 30-year cost/QALY is approximately $3000 less than the base-case assumptions and less than $10 000 under pessimistic assumptions.</b></p>]]></description>
<dc:creator><![CDATA[Eddy, D. M., Peskin, B., Shcheprov, A., Pawlson, G., Shih, S., Schaaf, D.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332509</dc:identifier>
<dc:title><![CDATA[Effect of Smoking Cessation Advice on Cardiovascular Disease]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>249</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>241</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/content/abstract/24/3/250?rss=1">
<title><![CDATA[Medicare's Value-Based Payment Initiatives: Impact on and Implications for Improving Physician Documentation and Coding]]></title>
<link>http://ajm.sagepub.com/cgi/content/abstract/24/3/250?rss=1</link>
<description><![CDATA[<p><b>Medicare has introduced a number of new payment initiatives that will have a profound effect on hospital reimbursement and quality and safety ratings. The new medical severity diagnosis&mdash;related group (MS-DRG) payment system adds a number of new DRG categories to more adequately account for patient severity. The new present-on-admission (POA) initiative is designed to withhold additional reimbursement for selected complications that were not recorded as being POA but that occurred during the course of the hospitalization. The recovery audit contract requires hospitals to repay Medicare for services deemed not clinically necessary based on retrospective chart review. Reimbursement and quality rankings for each of these initiatives are based on the extent and thoroughness of physician chart documentation. Physicians must understand the importance of their role and responsibilities in this process and embrace what needs to be done through appropriate education, coaching, and guidance, which leads to more effective chart documentation.</b></p>]]></description>
<dc:creator><![CDATA[Rosenstein, A. H., O'Daniel, M., White, S., Taylor, K.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609332511</dc:identifier>
<dc:title><![CDATA[Medicare's Value-Based Payment Initiatives: Impact on and Implications for Improving Physician Documentation and Coding]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>258</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>250</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/reprint/24/3/259?rss=1">
<title><![CDATA[More Work Is Needed to Protect Medical Residents From Fatigue and Potential Errors, IOM Report Finds]]></title>
<link>http://ajm.sagepub.com/cgi/reprint/24/3/259?rss=1</link>
<description><![CDATA[]]></description>
<dc:creator><![CDATA[Clancy, C. M.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609334614</dc:identifier>
<dc:title><![CDATA[More Work Is Needed to Protect Medical Residents From Fatigue and Potential Errors, IOM Report Finds]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>261</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>259</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/reprint/24/3/262?rss=1">
<title><![CDATA[Pie in the Sky--or a Grassroots Call to Action?]]></title>
<link>http://ajm.sagepub.com/cgi/reprint/24/3/262?rss=1</link>
<description><![CDATA[]]></description>
<dc:creator><![CDATA[Callan, C. M.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609333866</dc:identifier>
<dc:title><![CDATA[Pie in the Sky--or a Grassroots Call to Action?]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>263</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>262</prism:startingPage>
<prism:section>Article</prism:section>
</item>

<item rdf:about="http://ajm.sagepub.com/cgi/reprint/24/3/264?rss=1">
<title><![CDATA[Literature Review]]></title>
<link>http://ajm.sagepub.com/cgi/reprint/24/3/264?rss=1</link>
<description><![CDATA[]]></description>
<dc:creator><![CDATA[Royo, M. B., Goldfarb, N. I.]]></dc:creator>
<dc:date>2009-05-20</dc:date>
<dc:identifier>info:doi/10.1177/1062860609334074</dc:identifier>
<dc:title><![CDATA[Literature Review]]></dc:title>
<dc:publisher>American College of Medical Quality</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>24</prism:volume>
<prism:endingPage>266</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>264</prism:startingPage>
<prism:section>Article</prism:section>
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