Joan Keesey

Variations in the Use of Medical and Surgical Services By the Medicare Population

We measured geographic differences in the use of medical and surgical services during 1981 by Medicare beneficiaries (age greater than or equal to 65) in 13 large areas of the United States. The average number of Medicare beneficiaries per site was 340,000. We found large and significant differences in the use of services provided by all medical and surgical specialties. Of 123 procedures studied, 67 showed at least threefold differences between sites with the highest and lowest rates of use. Use rates were not consistently high in one site, but rates for procedures used to diagnose and treat a specific disease varied together, as did alternative treatments for the same condition. These results cannot be explained by the actions of a small number of physicians. We do not know whether physicians in high-use areas performed too many procedures, whether physicians in low-use areas performed too few, or whether neither or both of these explanations are accurate. However, we do know that the differences are too large to ignore and that unless they are understood at a clinical level, uninformed policy decisions that have adverse effects on the health of the elderly may be made.

Comparison of Quality of Care for Patients in the Veterans Health Administration and Patients in a National Sample

As methods for measuring the quality of medical care have matured, widespread quality problems have become increasingly evident (1, 2). The solution to these problems is much less obvious, however, particularly with regard to large delivery systems. Many observers have suggested that improved information systems, systematic performance monitoring, and coordination of care are necessary to enhance the quality of medical care (3). Although the use of integrated information systems (including electronic medical records) and performance indicators has become more common throughout the U.S. health care system, most providers are not part of a larger integrated delivery system and continue to rely on traditional information systems (4). An exception is the Veterans Health Administration (VHA). As the largest delivery system in the United States, the VHA has been recognized as a leader in developing a more coordinated system of care. Beginning in the early 1990s, VHA leadership instituted both a sophisticated electronic medical record system and a quality measurement approach that holds regional managers accountable for several processes in preventive care and in the management of common chronic conditions (5, 6). Other changes include a system-wide commitment to quality improvement principles and a partnership between researchers and managers for quality improvement (7). As Jha and colleagues (8) have shown, since these changes have been implemented, VHA performance has outpaced that of Medicare in the specific areas targeted. Nevertheless, whether this improvement has extended beyond the relatively narrow scope of the performance measures is unknown. Beyond that study, the data comparing VHA care with other systems of care are sparse and mixed. For example, patients hospitalized at VHA hospitals were more likely than Medicare patients to receive angiotensin-converting enzyme inhibitors and thrombolysis after myocardial infarction (9). On the other hand, VHA patients were less likely to receive angiography when indicated and had higher mortality rates after coronary artery bypass grafting than patients in community hospitals (10, 11). Kerr and colleagues found that care for diabetes was better in almost every dimension in the VHA system than in commercial managed care (12). More extensive comparisons, especially of outpatient care, are lacking. To address these issues, a more comprehensive assessment of quality is needed. Using a broad measure of quality of care that is based on medical record review and was developed outside the VHA, we compared the quality of outpatient and inpatient care among 2 samples: 1) a national sample of patients drawn from 12 communities and 2) VHA patients from 26 facilities in 12 health care systems located in the southwestern and midwestern United States (13). We analyzed performance in the years after the institution of routine performance measurement and the electronic medical record. Using the extensive set of quality indicators included in the measurement system, we compared the overall quality of care delivered in the VHA system and in the United States, as well as the quality of acute, chronic, and preventive care across 26 conditions. In addition, we evaluated whether VHA performance was better in the specific areas targeted by the VHA quality management system. Methods Development of Quality Indicators For this study, we used quality indicators from RANDs Quality Assessment Tools system, which is described in more detail elsewhere (14-17). The indicators included in the Quality Assessment Tools system are process quality measures, are more readily actionable than outcomes measures, require less risk adjustment, and follow the structure of national guidelines (18, 19). After reviewing established national guidelines and the medical literature, we chose a subset of quality indicators from the Quality Assessment Tools system that represented the spectrum of outpatient and inpatient care (that is, screening, diagnosis, treatment, and follow-up) for acute and chronic conditions and preventive care processes representing the leading causes of morbidity, death, and health care use among older male patients. The Appendix Table lists the full indicator set, which was determined by four 9-member, multispecialty expert panels. These panels assessed the validity of the proposed indicators using the RAND/University of California, Los Angelesmodified Delphi method. The experts rated the indicators on a 9-point scale (1 = not valid; 9 = very valid), and we accepted indicators that had a median validity score of 7 or higher. This method of selecting indicators is reliable and has been shown to have content, construct, and predictive validity (20-23). Of the 439 indicators in the Quality Assessment Tools system, we included 348 indicators across 26 conditions in our study and excluded 91 indicators that were unrelated to the target population (for example, those related to prenatal care and cesarean sections). Of the 348 indicators, 21 were indicators of overuse (for example, patients with moderate to severe asthma should not receive -blocker medications) and 327 were indicators of underuse (for example, patients who have been hospitalized for heart failure should have follow-up contact within 4 weeks of discharge). Appendix Table. Comparison of Performance of the Veterans Health Administration Sample and the National Sample by Indicator Two physicians independently classified each indicator according to the type of care delivered; the function of the indicated care (screening, diagnosis, treatment, and follow-up); and whether the indicator was supported by a randomized, controlled trial, another type of controlled trial, or other evidence. Type of care was classified as acute (for example, in patients presenting with dysuria, presence or absence of fever and flank pain should be elicited), chronic (for example, patients with type 2 diabetes mellitus in whom dietary therapy has failed should receive oral hypoglycemic therapy), or preventive (for example, all patients should be screened for problem drinking). In addition, we further classified the indicators into 3 mutually exclusive categories according to whether they corresponded to the VHA performance indicators that were in use in fiscal year 1999. Twenty-six indicators closely matched the VHA indicators, 152 involved conditions that were targeted by the VHA indicators but were not among the 26 matches, and 170 did not match the VHA measures or conditions. We performed a similar process to produce a list of 15 indicators that matched contemporaneous Health Plan Employer Data and Information Set (HEDIS) performance measures (24). Table 1 shows the conditions targeted by the indicators, and Table 2 gives an example indicator for each of the conditions or types of care for which condition- or type-specific comparisons were possible. Table 1. Conditions and Number of Indicators Used in Comparisons Table 2. Example Indicators of Quality of Care Identifying Participants Patients were drawn from 2 ongoing quality-of-care studies: a study of VHA patients and a random sample of adults from 12 communities (13). The VHA patients were drawn from 26 clinical sites in 12 health care systems located in 2 Veterans Integrated Service Networks in the midwestern and southwestern United States. These networks closely match the overall Veterans Affairs system with regard to medical record review and survey-based quality measures (25, 26). We selected patients who had had at least 2 outpatient visits in each of the 2 years between 1 October 1997 and 30 September 1999. A total of 106576 patients met these criteria. We randomly sampled 689, oversampling for chronic obstructive pulmonary disease (COPD), hypertension, and diabetes, and were able to locate records for 664 patients (a record location rate of 96%). Because of resource constraints, we reviewed a random subset of 621 of these records. Since this sample contained only 20 women and 4 patients younger than 35 years of age, we further restricted the sample to men older than 35 years of age. Thus, we included 596 VHA patients in the analysis. All of these patients had complete medical records. The methods we used to obtain the national sample have been described elsewhere (13) and are summarized here. As part of a nationwide study, residents of 12 large metropolitan areas (Boston, Massachusetts; Cleveland, Ohio; Greenville, South Carolina; Indianapolis, Indiana; Lansing, Michigan; Little Rock, Arkansas; Miami, Florida; Newark, New Jersey; Orange County, California; Phoenix, Arizona; Seattle, Washington; and Syracuse, New York) were contacted by using random-digit dialing and were asked to complete a telephone survey (27). To ensure comparability with the VHA sample, we included only men older than 35 years of age. Between October 1998 and August 2000, we telephoned 4086 of these participants and asked for permission to obtain copies of their medical records from all providers (both individual and institutional) that they had visited within the past 2 years. We received verbal consent from 3138 participants (77% of those contacted by telephone). We mailed consent forms and received written permission from 2351 participants (75% of those who had given verbal permission). We received at least 1 medical record for 2075 participants (88% of those who had returned consent forms). We excluded participants who had not had at least 2 medical visits in the past 2 years to further ensure comparability with the VHA sample. Thus, our final national sample included 992 persons. The rolling abstraction period (October 1996 to August 2000) substantially overlapped the VHA sampling period. The average overlap was 70%, and all records had at least 1 year of overlap. Seven hundred eight (71%) of the 992 persons in the national sample had complete medical records. On the basis of data from the original telephone survey, we det

Predicting the Appropriate Use of Carotid Endarterectomy, Upper Gastrointestinal Endoscopy, and Coronary Angiography

BACKGROUND AND METHODS In a nationally representative population 65 years of age or older, we have demonstrated that about one quarter of coronary angiographies and upper gastrointestinal endoscopies and two thirds of carotid endarterectomies were performed for reasons that were less than medically appropriate. In this paper we examine whether specific characteristics of patients (age, sex, and race), physicians (age, board-certification status, and experience with the procedure), or hospitals (teaching status, profit-making status, and size) predict whether a procedure will be performed appropriately. RESULTS In general, we found that little of the variability in the appropriateness of care (4 percent or less) could be explained on the basis of standard, easily obtainable data about the patient, the physician, or the hospital. For all three procedures, however, performance in a teaching hospital increased the likelihood that the reasons would be medically appropriate (P = 0.09 for angiography, P = 0.30 for endoscopy, and P less than 0.01 for endarterectomy). In addition, angiographies were more often performed for appropriate reasons in older or more affluent patients (P less than 0.01 for both). Being treated by a surgeon who performed a high rather than a low number of procedures decreased the likelihood of an appropriate endarterectomy by one third, from 40 to 28 percent (P less than 0.01). CONCLUSIONS Appropriateness of care cannot be closely predicted from many easily determined characteristics of patients, physicians, or hospitals. Thus, for the present, if appropriateness is to be improved it will have to be assessed directly at the level of each patient, hospital, and physician.

Lack of Progress in Labor as a Reason for Cesarean

Objective To estimate the prevalence of lack of progress in labor as a reason for cesarean delivery and to compare published diagnostic criteria with the labor characteristics of women with this diagnosis. Methods We reviewed medical records and did a postpartum telephone survey to collect data from 733 women who delivered full-term, nonbreech infants by unplanned cesarean between March 1993 and February 1994. These were a subset of 2447 births sampled at delivery from 30 hospitals in Los Angeles County and Iowa. We measured the proportion of unplanned cesareans done for lack of progress in labor, the cervical dilatation at the time of cesarean, length of the second stage, and slope of the active phase among the women. We estimated the proportion of these cesareans that conformed to the ACOG criteria for the diagnosis of lack of progress. Results Lack of progress was a reason for 68% of unplanned, vertex cesareans. At least 16% of the subjects who had cesareans for lack of progress were in the latent phase of labor according to ACOG criteria. The second stage was not prolonged in 36% of the women who delivered at 10 cm. Conclusion Lack of progress in labor is a dominant reason for cesarean delivery. Many cesareans are done during the latent phase of labor, and in the second stage of labor when it is not prolonged. These practices do not conform to published diagnostic criteria for lack of progress.

Can a Chronic Care Model Collaborative Reduce Heart Disease Risk in Patients with Diabetes

BackgroundThere is a need to identify effective practical interventions to decrease cardiovascular disease risk in patients with diabetes.ObjectiveWe examine the impact of participation in a collaborative implementing the chronic care model (CCM) on the reduction of cardiovascular disease risk in patients with diabetes.DesignControlled pre- and postintervention study.Patients/ParticipantsPersons with diabetes receiving care at 13 health care organizations exposed to the CCM collaborative and controls receiving care in nonexposed sites.Measurements and Main ResultsTen-year risk of cardiovascular disease; determined using a modified United Kingdom Prospective Diabetes Study risk engine score. A total number of 613 patients from CCM intervention sites and 557 patients from usual care control sites met the inclusion criteria. The baseline mean 10-year risk of cardiovascular disease was 31% for both the intervention group and the control group. Participants in both groups had improved blood pressure, lipid levels, and HbA1c levels during the observation period. Random intercept hierarchical regression models showed that the intervention group had a 2.1% (95% CI −3.7%, −0.5%) greater reduction in predicted risk for future cardiovascular events when compared to the control group. This would result in a reduced risk of one cardiovascular disease event for every 48 patients exposed to the intervention.ConclusionsOver a 1-year interval, this collaborative intervention using the CCM lowered the cardiovascular disease risk factors of patients with diabetes who were cared for in the participating organization’s settings. Further work could enhance the impact of this promising multifactorial intervention on cardiovascular disease risk reduction.

Does the Collaborative Model Improve Care for Chronic Heart Failure

Background:Organizationally based, disease-targeted collaborative quality improvement efforts are widely applied but have not been subject to rigorous evaluation. We evaluated the effects of the Institute of Healthcare Improvements Breakthrough Series (IHI BTS) on quality of care for chronic heart failure (CHF). Research Design:We conducted a quasi-experiment in 4 organizations participating in the IHI BTS for CHF in 1999–2000 and 4 comparable control organizations. We reviewed a total of 489 medical records obtained from the sites and used a computerized data collection tool to measure performance on 23 predefined quality indicators. We then compared differences in indicator performance between the baseline and postintervention periods for participating and nonparticipating organizations. Results:Participating and control patients did not differ significantly with regard to measured clinical factors at baseline. After adjusting for age, gender, number of chronic conditions, and clustering by site, participating sites showed greater improvement than control sites for 11 of the 21 indicators, including use of lipid-lowering and angiotensin converting enzyme inhibition therapy. When all indicators were combined into a single overall process score, participating sites improved more than controls (17% versus 1%, P < 0.0001). The improvement was greatest for measures of education and counseling (24% versus −1%, P < 0.0001). Conclusions:Organizational participation in a common disease-targeted collaborative provider interaction improved a wide range of processes of care for CHF, including both medical therapeutics and education and counseling. Our data support the use of programs like the IHI BTS in improving the processes of care for patients with chronic diseases.

The quality of pharmacologic care for adults in the United States.

Background:Despite rising annual expenditures for prescription drugs, little systematic information is available concerning the quality of pharmacologic care for adults in the United States. We evaluated how frequently appropriate pharmacologic care is ordered in a national sample of U.S. residents. Methods:The RAND/UCLA Modified Delphi process was used to select quality-of-care indicators for adults across 30 chronic and acute conditions and preventive care. One hundred thirty-three pharmacologic quality-of-care indicators were identified. We interviewed a random sample of adults living in 12 metropolitan areas in the United States by telephone and received consent to obtain copies of their medical records for the most recent 2-year period. We abstracted patient medical records and evaluated 4 domains of the prescribing process that encompassed the entire pharmacologic care experience: appropriate medication prescribing (underuse), avoidance of inappropriate medications (overuse), medication monitoring, and medication education and documentation. A total of 3457 participants were eligible for at least 1 quality indicator, and 10,739 eligible events were evaluated. We constructed aggregate scores and studied whether patient, insurance, and community factors impact quality. Results:Participants received 61.9% of recommended pharmacologic care overall (95% confidence interval 60.3–63.5%). Performance was lowest in education and documentation (46.2%); medication monitoring (54.7%) and underuse of appropriate medications (62.6%) performance were higher. Performance was best for avoiding inappropriate medications (83.5%). Patient race and health services utilization were associated with modest quality differences, while insurance status was not. Conclusions:Significant deficits in the quality of pharmacologic care were seen for adults in the United States, with large shortfalls associated with underuse of appropriate medications. Strategies to measure and improve pharmacologic care quality ought to be considered, especially as we initiate a prescription drug benefit for seniors.

Evaluation of a Quality Improvement Collaborative in Asthma Care: Does it Improve Processes and Outcomes of Care?

PURPOSE We wanted to examine whether a collaborative to improve asthma care influences process and outcomes of care in asthmatic adults. METHOD We undertook a preintervention-postintervention evaluation of 185 patients in 6 intervention clinics and 3 matched control sites that participated in the Institute for Healthcare Improvement Breakthrough Series (BTS) Collaborative for asthma care. The intervention consisted of 3, 2-day educational sessions for teams dispatched by participating sites, which were followed by 3 action periods during the course of a year. RESULTS Overall process of asthma care improved significantly in the intervention compared with the control group (change of 10% vs 1%, P = .003). Patients in the intervention group were more likely to attend educational sessions (20% vs 5%, P = .03). Having a written action plan, setting goals, monitoring peak flow rates, and using long-term asthma medications increased between 2% and 19% (not significant), but asthma-related knowledge was unchanged for the 2 groups. Patients in the BTS Collaborative were significantly more likely to be satisfied with clinician and lay educator communication (62% vs 39%, P = .02). Health-related quality of life, asthma-specific quality of life, number of bed days caused by asthma-related illness, and acute care service use were not significantly different between the 2 groups. CONCLUSIONS The intervention was associated with improved process-of-care measures that have been linked with better outcomes. Patients benefited through increased satisfaction with communication. Follow-up of patients who participated in the intervention may have been too brief to be able to detect significant improvement in health-related outcomes.

The Relationship Between Multimorbidity and Patients’ Ratings of Communication

BACKGROUNDThe growing interest in pay-for-performance and other quality improvement programs has generated concerns about potential performance measurement penalties for providers who care for more complex patients, such as patients with more chronic conditions. Few data are available on how multimorbidity affects common performance metrics.OBJECTIVETo examine the relationship between multimorbidity and patients’ ratings of communication, a common performance metric.DESIGNCross-sectional studySETTINGNationally representative sample of U.S. residentsPARTICIPANTSA total of 15,709 noninstitutionalized adults living in the United States participated in a telephone interview.MEASUREMENTSWe used 2 different measures of multimorbidity: 1) “individual conditions” approach disregards similarities/concordance among chronic conditions and 2) “condition-groups” approach considers similarities/concordance among conditions. We used a composite measure of patients’ ratings of patient–physician communication.RESULTSA higher number of individual conditions is associated with lower ratings of communication, although the magnitude of the relationship is small (adjusted average communication scores: 0 conditions, 12.20; 1–2 conditions, 12.06; 3+ conditions, 11.90; scale range 5 = worst, 15 = best). This relationship remains statistically significant when concordant relationships among conditions are considered (0 condition groups 12.19; 1–2 condition groups 12.03; 3+ condition groups 11.94).CONCLUSIONSIn our nationally representative sample, patients with more chronic conditions gave their doctors modestly lower patient–doctor communication scores than their healthier counterparts. Accounting for concordance among conditions does not widen the difference in communication scores. Concerns about performance measurement penalty related to patient complexity cannot be entirely addressed by adjusting for multimorbidity. Future studies should focus on other aspects of clinical complexity (e.g., severity, specific combinations of conditions).

THE URGE TO MERGE : LINKING VITAL STATISTICS RECORDS AND MEDICAID CLAIMS

This paper describes a procedure used to link Medicaid claims data to California vital statistics records for very low birthweight infants. The linkage involved about 53,000 infants born from 1980 to 1987 and 1.46 million claims for delivery/birth-related hospital admissions during the same period. Because the two data files did not share a unique identifier, record linkage required combining evidence across several linking variables: delivery hospital, delivery/birth date or hospitalization period, names, mothers age, and zip code. To combine the various pieces of evidence, we used record linkage theory to compute scores that measure the likelihood of a match, i.e., that two records correspond to the same delivery. These scores appropriately weight the various pieces of evidence for or against a match. Implementation required dealing with large amounts of missing data in one of the files, errors and variations in reported names, and the need to minimize the number of incorrect links.The approach applies to a wide range of linkage problems. The ability to combine existing datasets to form new datasets containing analysis variables from each facilitates analyses that would otherwise be impossible, or prohibitively expensive.