Quality by Any Other Name?: A Comparison of Three Profiling Systems for Assessing Health Care Quality

Many performance measurement systems are designed to identify differences in the quality provided by health plans or facilities. However, we know little about whether different methods of performance measurement provide similar answers about the quality of care of health care organizations. To examine this question, we used three different measurement approaches to assess quality of care delivered in veteran affairs (VA) facilities. Data Sources/Study Setting . Medical records for 621 patients at 26 facilities in two VA regions. Study Design . We examined agreements in quality conclusions using: focused explicit (38 measures for six conditions/prevention), global explicit (372 measures for 26 conditions/prevention), and structured implicit review physician-rated care (a single global rating of care for three chronic conditions and overall acute, chronic and preventive care). Trained nurse abstractors and physicians reviewed all medical records. Correlations between scores from the three systems were adjusted for measurement error in each using multilevel regression models. Results . Intercorrelations of scores were generally moderate to high across all three systems, and rose with adjustment for measurement error. Site-level correlations for prevention and diabetes care were particularly high. For example, adjusted for measurement error at the site level, prevention quality was correlated at 0.89 between the implicit and global systems, 0.67 between implicit and focused, and 0.73 between global and focused systems. Conclusions . We found moderate to high agreement in quality scores across the three profiling systems for most clinical areas, indicating that all three were measuring a similar construct called “quality.” Adjusting for measurement error substantially enhanced our ability to identify this underlying construct.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73479/1/HESR_730_sm_Appendix1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/73479/2/HESR+730+Appendix+2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/73479/3/j.1475-6773.2007.00730.x.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/73479/4/HESR_730_sm_Appendix2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/73479/5/HESR+730+Appendix+1.pd

The validity of using ICD-9 codes and pharmacy records to identify patients with chronic obstructive pulmonary disease

Background: Administrative data is often used to identify patients with chronic obstructive pulmonary disease (COPD), yet the validity of this approach is unclear. We sought to develop a predictive model utilizing administrative data to accurately identify patients with COPD. Methods: Sequential logistic regression models were constructed using 9573 patients with postbronchodilator spirometry at two Veterans Affairs medical centers (2003-2007). COPD was defined as: 1) FEV1/FVC <0.70, and 2) FEV1/FVC < lower limits of normal. Model inputs included age, outpatient or inpatient COPD-related ICD-9 codes, and the number of metered does inhalers (MDI) prescribed over the one year prior to and one year post spirometry. Model performance was assessed using standard criteria. Results: 4564 of 9573 patients (47.7%) had an FEV1/FVC < 0.70. The presence of ≥1 outpatient COPD visit had a sensitivity of 76% and specificity of 67%; the AUC was 0.75 (95% CI 0.74-0.76). Adding the use of albuterol MDI increased the AUC of this model to 0.76 (95% CI 0.75-0.77) while the addition of ipratropium bromide MDI increased the AUC to 0.77 (95% CI 0.76-0.78). The best performing model included: ≥6 albuterol MDI, ≥3 ipratropium MDI, ≥1 outpatient ICD-9 code, ≥1 inpatient ICD-9 code, and age, achieving an AUC of 0.79 (95% CI 0.78-0.80). Conclusion: Commonly used definitions of COPD in observational studies misclassify the majority of patients as having COPD. Using multiple diagnostic codes in combination with pharmacy data improves the ability to accurately identify patients with COPD.Department of Veterans Affairs, Health Services Research and Development (DHA), American Lung Association (CI- 51755-N) awarded to DHA, the American Thoracic Society Fellow Career Development AwardPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/84155/1/Cooke - ICD9 validity in COPD.pd

The health disparities cancer collaborative: a case study of practice registry measurement in a quality improvement collaborative

<p>Abstract</p> <p>Background</p> <p>Practice registry measurement provides a foundation for quality improvement, but experiences in practice are not widely reported. One setting where practice registry measurement has been implemented is the Health Resources and Services Administration's Health Disparities Cancer Collaborative (HDCC).</p> <p>Methods</p> <p>Using practice registry data from 16 community health centers participating in the HDCC, we determined the completeness of data for screening, follow-up, and treatment measures. We determined the size of the change in cancer care processes that an aggregation of practices has adequate power to detect. We modeled different ways of presenting before/after changes in cancer screening, including count and proportion data at both the individual health center and aggregate collaborative level.</p> <p>Results</p> <p>All participating health centers reported data for cancer screening, but less than a third reported data regarding timely follow-up. For individual cancers, the aggregate HDCC had adequate power to detect a 2 to 3% change in cancer screening, but only had the power to detect a change of 40% or more in the initiation of treatment. Almost every health center (98%) improved cancer screening based upon count data, while fewer (77%) improved cancer screening based upon proportion data. The aggregate collaborative appeared to increase breast, cervical, and colorectal cancer screening rates by 12%, 15%, and 4%, respectively (p < 0.001 for all before/after comparisons). In subgroup analyses, significant changes were detectable among individual health centers less than one-half of the time because of small numbers of events.</p> <p>Conclusions</p> <p>The aggregate HDCC registries had both adequate reporting rates and power to detect significant changes in cancer screening, but not follow-up care. Different measures provided different answers about improvements in cancer screening; more definitive evaluation would require validation of the registries. Limits to the implementation and interpretation of practice registry measurement in the HDCC highlight challenges and opportunities for local and aggregate quality improvement activities.</p

Performance reporting for consumers: issues for the Australian private hospital sector

A group of consumers of private hospital services and their carers collaborated with staff of a Melbourne private hospital and with industry representatives to develop a consumer-driven performance report on cardiac services. During the development process participating consumers identified situational and structural barriers to their right to be informed of costs, to choice and to quality care. Their growing appreciation of these barriers led them to a different perspective on performance reporting, which resulted in their redirecting the project. The consumer participants no longer wanted a performance report that provided comparative quantitative data. Instead they designed a report that outlined the structures, systems and processes the hospital had in place to address the quality and safety of services provided. In addition, consumer participants developed a decision support tool for consumers to use in navigating the private health care sector. The journey of these consumers in creating a consumer driven performance report for a private hospital service may assist those responsible for governance of Australia's health system in choosing appropriate strategies and mechanisms to enhance private hospital accountability. The situational and institutional industry barriers to choice, information and quality identified by these consumers need to be addressed before public performance reporting for private hospitals is introduced in Australia

A simulation model approach to analysis of the business case for eliminating health care disparities

<p>Abstract</p> <p>Background</p> <p>Purchasers can play an important role in eliminating racial and ethnic disparities in health care. A need exists to develop a compelling "business case" from the employer perspective to put, and keep, the issue of racial/ethnic disparities in health care on the quality improvement agenda for health plans and providers.</p> <p>Methods</p> <p>To illustrate a method for calculating an employer business case for disparity reduction and to compare the business case in two clinical areas, we conducted analyses of the direct (medical care costs paid by employers) and indirect (absenteeism, productivity) effects of eliminating known racial/ethnic disparities in mammography screening and appropriate medication use for patients with asthma. We used Markov simulation models to estimate the consequences, for defined populations of African-American employees or health plan members, of a 10% increase in HEDIS mammography rates or a 10% increase in appropriate medication use among either adults or children/adolescents with asthma.</p> <p>Results</p> <p>The savings per employed African-American woman aged 50-65 associated with a 10% increase in HEDIS mammography rate, from direct medical expenses and indirect costs (absenteeism, productivity) combined, was $50. The findings for asthma were more favorable from an employer point of view at approximately$1,660 per person if raising medication adherence rates in African-American employees or dependents by 10%.</p> <p>Conclusions</p> <p>For the employer business case, both clinical scenarios modeled showed positive results. There is a greater potential financial gain related to eliminating a disparity in asthma medications than there is for eliminating a disparity in mammography rates.</p

The Impact of Health Plan Delivery System Organization on Clinical Quality and Patient Satisfaction

OBJECTIVE: The purpose of this study was to examine the extent to which measures of health plan clinical performance and measures of patient perceptions of care are associated with health plan organizational characteristics, including the percentage of care provided based on a group or staff model delivery system, for-profit (tax) status, and affiliation with a national managed care firm. DATA SOURCES: Data describing health plans on region, age of health plan, for-profit status, affiliation with a national managed care firm, percentage of Medicare business, total enrollment, ratio of primary care physicians to specialists, HMO penetration, and form of health care delivery system (e.g., IPA, network, mixed, staff, group) were obtained from InterStudy. Clinical performance measures for women's health screening rates, child and adolescent immunization rates, heart disease screening rates, diabetes screening rates, and smoking cessation were developed from HEDIS® data. Measures of patient perceptions of care are obtained from CAHPS® survey data submitted as Healthplan Employer Data and Information Set, Consumer Assessment of Health Plans 2.0 H. STUDY DESIGN: Multivariate regression cross-sectional analysis of 272 health plans was used to evaluate the relationship of health plan characteristics with measures of clinical performance and patient perceptions of care. PRINCIPAL FINDINGS: The form of delivery system, measured by percent of care delivered by staff and group model systems, is significantly related (p ≤ .05) with four of the five clinical performance indices but none of the three satisfaction performance indices. Other variables significantly associated with performance were being geographically located in the Northeast, having nonprofit status, and for patient satisfaction, not being part of a larger insurance company. CONCLUSIONS: These comparative results provide evidence suggesting that the type of delivery system used by health plans is related to many clinical performance measures but is not related to patient perceptions of care. These findings underscore the importance of the form of the delivery system and the need for further inquiry that examines the relationship between organizational form and performance