The Outcomes Group in the Department of Anesthesiology conducts healthcare research to improve quality of care. Our work focuses on outcomes measurement and risk-adjustment.
Research Focus: Laurent Glance, M.D.
Dr. Laurent Glance’s primary research interests are focused on understanding the opportunities and limitations of health care quality reporting. His work has focused on the implications of using the Present-on-Admission Indicator (POA) in administrative data (data fields that indicate whether a secondary diagnosis was present on admission) to differentiate preexisting conditions from complications. This work led to publications showing that the addition of the POA indicator enhances the ability of existing comorbidity algorithms (Charlson Index and Elixhauser algorithm) to map ICD-9-CM codes to diagnostic categories accurately, and that the use of routine administrative data without POA indicators to construct hospital quality report cards may result in the misidentification of hospital quality outliers. Dr. Glance’s work has also focused on exploring the impact of non-public outcomes reporting on hospitals caring for injured patients. His group used the National Trauma Databank to construct the Trauma Mortality Probability Model (TMPM), and conducted an AHRQ-funded study to prospectively investigate the impact of providing benchmarking information on trauma outcomes. He is now helping to spearhead the development of a collaborative effort between the American Society of Anesthesiologists (ASA) and the American Congress of Obstetricians and Gynecologists (ACOG) to create a national benchmarking platform to measure and improve obstetrical outcomes in the United States: the ACOG-ASA Maternal Quality Improvement Program (ACOG-ASA MQIP). These data will be used to improve the quality of maternal care at the local level, establish national performance metrics for obstetrics and obstetrical anesthesia, and facilitate comparative effectiveness research.
Understanding the Limitations of Risk Adjustments for Measuring Quality-of-Care. Dr. Glance was the recipient of a Research Career Development Grant (K08 HS11295) from AHRQ, which focused on the optimization of risk-adjustment methodologies for measuring Intensive Care Unit quality. We found that intensive care unit (ICU) scoring systems used to benchmark ICU performance flagged the majority of ICUs as high-quality outliers because these risk-adjustment models were developed using historical data that did not reflect contemporary ICU outcomes. However, even after model customization to contemporary data, different ICU scoring systems frequently disagreed on which hospitals were quality outliers. We also examined the sensitivity of hospital quality identification to the choice of statistical methodology.
a. Glance LG, Osler TM, Dick A. Rating the quality of ICUs – Is it a function of the ICU scoring system? Critical Care Medicine 2002 30(9):1976-1982.
b. Glance LG, Osler TM, Dick A. Identifying quality outliers in a large multi-institutional database using customized versions of SAPS II and MPM II. Critical Care Medicine 2002 30(9): 1995-2002.
c. Glance LG, Dick AW, Osler TM, Li Y, Mukamel DB. Impact of Changing the Statistical Methodology on Hospital and Surgeon Ranking: The Case of the NYS Cardiac Surgery Report Card. Medical Care 2006; 44: 311-319.
d. Glance LG, Osler TM, Mukamel DB, Dick AW. Use of a Matching Algorithm to Evaluate Hospital CABG Performance as an Alternative to Conventional Risk Adjustment. Medical Care 2007; 45: 292-299.
The Impact of the Present-on-Admission Indicator on Quality Reporting. With funding from AHRQ (R01 HS 13617), we focused on the implications of the present-on-admission (POA) indicator in administrative data to differentiate preexisting conditions from complications. This work led to publications showing that the addition of the present-on-admission (POA) indicator enhances the ability of existing comorbidity algorithms to map ICD-9-CM codes to diagnostic categories accurately, and that the use of routine administrative data without POA information to construct hospital quality report cards may result in the misidentification of hospital quality outliers.
a. Glance LG, Dick AW, Osler TM, Mukamel DB. Does Date Stamping ICD-9-CM Codes Increase the Value of Clinical Information in Administrative Data? Health Services Research 2006; 41:231-251. PMCID: 1681527
b. Glance LG, Dick AW, Osler TM, Mukamel DB. Accuracy of Hospital Report Cards Based on administrative Data. Health Services Research 2006; 41: 1413-1437. PMCID:1797077
c. Glance LG, Osler TM, Mukamel DB, Dick AW. Impact of the Present-on-Admission Indicator on Hospital Quality Measurement: Experience with the AHRQ Inpatient Quality Indicators. Medical Care 46(2): 112-119, 2008 February.
Optimizing Injury Severity Scoring. With funding from AHRQ (R01 HS016737), we used the National Trauma Databank as a platform to determine whether providing hospitals with trauma report cards will lead to improved population outcomes in trauma. This work has led to the development of a highly innovative empiric-based approach to trauma injury scoring using either clinical data or ICD-9-CM codes, published in the Annals of Surgery, as an alternative to the expert-based injury severity scoring system currently in use. The Trauma Mortality Prediction Model, developed through this grant, has been adopted for use by the Massachusetts Department of Public Health. To address one of the primary limitations of trauma registry data, this project also validated the use of multiple imputation for handling missing data in the context of quality measurement. This grant also examined whether higher-quality trauma care is associated with lower cost and whether failure-to-rescue is an important mechanism driving outcome differences across trauma center. The project also explored the relationship between (1) National Quality Forum safety practices and trauma outcomes; and (2) American College of Surgeons Committee on Trauma Quality Indicators and trauma outcomes.
a. Glance LG, Osler TM, Mukamel DB, Meredith W, Dick AW. TMPM-ICD9: A Trauma Prediction Model Based on ICD-9-CM Codes. Annals of Surgery 249(6):1032-9, 2009 Jun.
b. Glance LG, Osler TM, Mukamel DB, Meredith W, Dick AW. Impact of Statistical Approaches for Handling Missing Data on Trauma Center Quality. Annals of Surgery 2009 Jan; 249(1): 143-8.
c. Glance LG, Dick AW, Osler TM, Meredith W, Mukamel DB. The association between cost and quality in trauma: is greater spending associated with higher-quality care? Annals of Surgery 2010 Aug; 252(2): 217-22.
d. Glance LG, Dick AW, Meredith W, Mukamel D. Variation in Hospital Complication Rates and Failure-to-Rescue for Trauma Patients. Annals of Surgery 2011 Apr; 253(4) 811-6.
Impact of Non-public reporting on Trauma Outcomes. As part of our AHRQ-funded R01, we conducted a prospective observational study to examine the impact of non-public reporting on trauma outcomes. We also examined the validity of trauma severity scoring by examining the ability of past hospital performance to predict future hospital performance. Finally, we also examined the association between hospital structural characteristics and trauma outcomes.
a. Glance LG, Dick AW, Osler TM, Mukamel DB, Li Y, Stone PW. The Association between Nurse Staffing and Hospital Outcomes in Injured Patients. BMC Health Services Research 2012 Aug 9;12(1):247. PMCID: PMC344311
b. Glance LG, Osler TM, Mukamel DB, Meredith JW, Dick AW. Effectiveness of nonpublic report cards for reducing trauma mortality. JAMA Surgery. 2014 Feb;149:137-143.
c. Glance LG, Mukamel DB, Osler TM, Dick AW. Ranking trauma center quality: Can past performance predict future performance? Annals Surgery. 2014 April; 259:682-686.
Quality Reporting in Obstetrics. Using a large nationally representative sample of more than 750,000 obstetrical deliveries in the U.S., we found that patients delivering vaginally at low-performing hospitals experienced twice the rate of serious complications. This large quality gap in obstetrical care led me to help spearhead the development of the ACOG-ASA Maternal Quality Improvement Program (MQIP): a partnership between the American Society of Anesthesiologists (ASA) and the American Congress of Obstetricians and Gynecologists (ACOG) to collect outcomes data using the electronic medical record on the clinical course of childbirth in the US. These data will be used to improve the quality of maternal care at the local level, establish national performance benchmarks for obstetrics and obstetrical anesthesia, and facilitate comparative effectiveness research.
a. Glance LG, Dick AW, Glantz JC, Wissler RN, Qian F, Marroquin BM, Mukamel DB, Kellermann AL. Rates of major obstetrical complications vary almost fivefold among us hospitals. Health Affairs (Millwood). 2014;33:1330-1336.
View a Complete List of Published Works in Dr Glance's Bibliography
Research Focus: Raymond Zollo, M.D.
Dr. Raymond Zollo’s general area of interest as the founding Director of the Center for Perioperative Medicine is how factors in the perioperative system (patient, provider, clinic, operating room, medical center, and perioperative home) can influence patient outcomes. This has profound implications for patient safety and operating room management, particularly as our patient population ages, and their co-morbidities increase. To this end, Dr. Zollo has studied patient education and doctor-patient communication, medical education at all levels, as well as sophisticated statistical methods that may be used to improve patient outcomes as well as the efficiency of the perioperative process.
Dr. Zollo also has interests in medical and research ethics and the role of true informed consent in allowing patients to make informed decisions regarding their therapeutic care, and allowing research subjects to make informed decisions regarding their willingness to participate in research while avoiding therapeutic misconception.