Steven M. Asch

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

Increasing Prevalence of HCC and Cirrhosis in Patients With Chronic Hepatitis C Virus Infection

BACKGROUND & AIMS Patients with hepatitis C virus (HCV) infection are at risk for developing costly and morbid complications, although the actual prevalence of these complications is unknown. We examined time trends in the prevalence of cirrhosis and its related complications, such as hepatic decompensation and hepatocellular carcinoma (HCC). METHODS We calculated the annual prevalence of cirrhosis, decompensated cirrhosis, and HCC in a national sample of veterans diagnosed with HCV between 1996 and 2006. Patients with HCV who had at least one physician visit in a given calendar year were included in the analysis of prevalence for that year. We used direct standardization to adjust the prevalence of cirrhosis and related complications for increasing age of the cohort as well as sex and changes in clinical characteristics. RESULTS In this cohort, the number of individuals with HCV increased from 17,261 in 1996 to 106,242 in 2006. The prevalence of cirrhosis increased from 9% in 1996 to 18.5% in 2006. The prevalence of patients with decompensated cirrhosis doubled, from 5% in 1996 to 11% in 2006, whereas the prevalence of HCC increased approximately 20-fold (0.07% in 1996 to 1.3% in 2006). After adjustment, the time trend in the prevalence of cirrhosis (and its complications) was lower than the crude trend, although it still increased significantly. CONCLUSIONS The prevalence of cirrhosis and HCC in HCV-infected patients has increased significantly over the past 10 years. An aging cohort of patients with HCV could partly explain our findings. Clinicians and health care systems should develop strategies to provide timely and effective care to this high-risk population of patients.

Measuring Pain as the 5th Vital Sign Does Not Improve Quality of Pain Management

AbstractBACKGROUND: To improve pain management, the Veterans Health Administration launched the “Pain as the 5th Vital Sign” initiative in 1999, requiring a pain intensity rating (0 to 10) at all clinical encounters. OBJECTIVE: To measure the initiative’s impact on the quality of pain management. DESIGN: We retrospectively reviewed medical records at a single medical center to compare providers’ pain management before and after implementing the initiative and performed a subgroup analysis of patients reporting substantial pain (≥4) during a postimplementation visit. PARTICIPANTS: Unique patient visits selected from all 15 primary care providers of a general medicine outpatient clinic. MEASUREMENTS: We used 7 process indicators of quality pain management, based on appropriately evaluating and treating pain, to assess 300 randomly selected visits before and 300 visits after implementing the pain initiative. RESULTS: The quality of pain care was unchanged between visits before and after the pain initiative (P>.05 for all comparisons): subjective provider assessment (49.3% before, 48.7% after), pain exam (26.3%, 26.0%), orders to assess pain (11.7%, 8.3%), new analgesic (8.7%, 11.0%), change in existing analgesics (6.7%, 4.3%), other pain treatment (11.7%, 13.7%), or follow-up plans (10.0%, 8.7%). Patients (n=79) who reported substantial pain often did not receive recommended care: 22% had no attention to pain documented in the medical record, 27% had no further assessment documented, and 52% received no new therapy for pain at that visit. CONCLUSIONS: Routinely measuring pain by the 5th vital sign did not increase the quality of pain management. Patients with substantial pain documented by the 5th vital sign often had inadequate pain management.

Effect of Emergency Department Crowding on Outcomes of Admitted Patients

STUDY OBJECTIVE Emergency department (ED) crowding is a prevalent health delivery problem and may adversely affect the outcomes of patients requiring admission. We assess the association of ED crowding with subsequent outcomes in a general population of hospitalized patients. METHODS We performed a retrospective cohort analysis of patients admitted in 2007 through the EDs of nonfederal, acute care hospitals in California. The primary outcome was inpatient mortality. Secondary outcomes included hospital length of stay and costs. ED crowding was established by the proxy measure of ambulance diversion hours on the day of admission. To control for hospital-level confounders of ambulance diversion, we defined periods of high ED crowding as those days within the top quartile of diversion hours for a specific facility. Hierarchic regression models controlled for demographics, time variables, patient comorbidities, primary diagnosis, and hospital fixed effects. We used bootstrap sampling to estimate excess outcomes attributable to ED crowding. RESULTS We studied 995,379 ED visits resulting in admission to 187 hospitals. Patients who were admitted on days with high ED crowding experienced 5% greater odds of inpatient death (95% confidence interval [CI] 2% to 8%), 0.8% longer hospital length of stay (95% CI 0.5% to 1%), and 1% increased costs per admission (95% CI 0.7% to 2%). Excess outcomes attributable to periods of high ED crowding included 300 inpatient deaths (95% CI 200 to 500 inpatient deaths), 6,200 hospital days (95% CI 2,800 to 8,900 hospital days), and

Developing a Clinical Performance Measure

17 million (95% CI

Exploring Barriers and Facilitators to the Use of Computerized Clinical Reminders

11 to

Underdiagnosis of Depression in HIV: Who Are We Missing?

23 million) in costs. CONCLUSION Periods of high ED crowding were associated with increased inpatient mortality and modest increases in length of stay and costs for admitted patients.

Associations of Symptoms and Health-Related Quality of Life: Findings from a National Study of Persons with HIV Infection

BACKGROUND Clinical performance measurement is an increasingly important way for public and private purchasers alike to compare the value of health services provided by competing health delivery systems. The widespread use of performance measures has increased the demand for development of new measures that cover previously unevaluated aspects of care. METHODS Four steps required to develop a clinical performance measure that is suitable for making comparisons among health delivery systems are discussed: (1) choosing clinical areas to measure, (2) selecting performance indicators within each area, (3) designing specifications for consistent implementation of a measure, and (4) evaluating the scientific strength of a measure. RESULTS The application of these steps to developing measures of quality for hypertension is provided, with an emphasis on a measure of adequacy of control of blood pressure. CONCLUSIONS Developing useful clinical performance measures requires careful attention to methodologic issues. Following the steps outlined in this paper should enhance the quality of future measurement development.

How Well Do Clinicians Estimate Patients' Adherence to Combination Antiretroviral Therapy?

OBJECTIVE Evidence-based practices in preventive care and chronic disease management are inconsistently implemented. Computerized clinical reminders (CRs) can improve compliance with these practices in outpatient settings. However, since clinician adherence to CR recommendations is quite variable and declines over time, we conducted observations to determine barriers and facilitators to the effective use of CRs. DESIGN We conducted an observational study of nurses and providers interacting with CRs in outpatient primary care clinics for two days in each of four geographically distributed Veterans Administration (VA) medical centers. MEASUREMENTS Three observers recorded interactions of 35 nurses and 55 physicians and mid-level practitioners with the CRs, which function as part of an electronic medical record. Field notes were typed, coded in a spreadsheet, and then sorted into logical categories. We then integrated findings across observations into meaningful patterns and abstracted the data into themes, such as recurrent strategies. Several of these themes translated directly to barriers and facilitators to effective CR use. RESULTS Optimally using the CR system for its intended purpose was impeded by (1) lack of coordination between nurses and providers; (2) using the reminders while not with the patient, impairing data acquisition and/or implementation of recommended actions; (3) workload; (4) lack of CR flexibility; and (5) poor interface usability. Facilitators included (1) limiting the number of reminders at a site; (2) strategic location of the computer workstations; (3) integration of reminders into workflow; and (4) the ability to document system problems and receive prompt administrator feedback. CONCLUSION We identified barriers that might explain some of the variability in the use of CRs. Although these barriers may be difficult to overcome, some strategies may increase user acceptance and therefore the effectiveness of the CRs. These include explicitly assigning responsibility for each CR to nurses or providers, improving visibility of positive results from CRs in the electronic medical record, creating a feedback mechanism about CR use, and limiting the overall number of CRs.

Problems in Recruiting Community‐based Physicians for Health Services Research

AbstractOBJECTIVE: To determine the sociodemographic and service delivery correlates of depression underdiagnosis in HIV. DESIGN: Cross-sectional survey. PATIENTS/PARTICIPANTS: National probability sample of HIV-infected persons in care in the contiguous United States who have available medical record data. MEASUREMENTS AND MAIN RESULTS: We interviewed patients using the Composite International Diagnostic Interview (CIDI) survey from the Mental Health Supplement. Patients also provided information regarding demographics, socioeconomic status, and HIV disease severity. We extracted patient medical record data between July 1995 and December 1997, and we defined depression underdiagnosis as a diagnosis of major depressive disorder based on the CIDI and no recorded depression diagnosis by their principal health care provider in their medical records between July 1995 and December 1997. Of the 1,140 HIV Cost and Services Utilization Study patients with medical record data who completed the CIDI, 448 (37%) had CIDI-defined major depression, and of these, 203 (45%) did not have a diagnosis of depression documented in their medical record. Multiple logistic regression analysis revealed that patients who had less than a high school education (P<.05) were less likely to have their depression documented in the medical record compared to those with at least a college education. Patients with Medicare insurance coverage compared to those with private health insurance (P<.01) and those with ≥3 outpatient visits (P<.05) compared to <3 visits were less likely to have their depression diagnosis missed by providers. CONCLUSIONS: Our results suggest that providers should be more attentive to diagnosing comorbid depression in HIV-infected patients.