Jonathan B. Perlin

Quality of preventive medical care for patients with mental disorders

Background/Objectives. This study compares quality of preventive services between persons with and without mental/substance use disorders for a national sample of medical outpatients. Research Design. Cross‐sectional study. Subjects. A total of 113,505 veterans with chronic conditions and at least three general medical visits to Veterans Health Administration medical providers during 1998 to 1999. Measures. Chart‐derived rates of eight preventive services: two measures of immunization, four measures of cancer screening, and two of tobacco screening and counseling. Multivariable‐generalized estimating equations compared rates of each preventive service among veterans with psychiatric disorders, substance use disorders, both, and neither, adjusting for demographic, health status, and facility‐level characteristics. Results. On average, persons in the sample obtained 64% of the eight preventive procedures for which they were eligible. Overall rates of currency with preventive services were 58% for patients with combined psychiatric/substance use disorders, 60% and 65% for those with psychiatric and substance use disorders alone, and 66% for those with neither psychiatric nor substance use disorders. Each difference remained statistically significant in multivariable models. Conclusions. In this sample of patients in active medical treatment, rates of preventive services were higher than rates reported for population‐based, private‐sector samples. Despite these high‐baseline rates, persons with psychiatric disorders, particularly with comorbid substance use, were at risk for lower rate of receipt of preventive services.

Effect of the implementation of an enterprise-wide Electronic Health Record on productivity in the Veterans Health Administration

Since 1995, the Veterans Health Administration (VHA) has had an ongoing process of systems improvement that has led to dramatic improvement in the quality of care delivered. A major component of the redesign of the VHA has been the creation of a fully developed enterprise-wide Electronic Health Record (EHR). VHAs Health Information Technology was developed in a collaborative fashion between local clinical champions and central software engineers. Successful national EHR implementation was achieved by 1999, since when the VHA has been able to increase its productivity by nearly 6 per cent per year.

Risk factors for intermediate-term survival after coronary artery bypass grafting.

BACKGROUNDnRisk factors for short-term mortality after coronary artery bypass grafting are well established, but little is known about risk factors for intermediate-term mortality.nnnMETHODSnWe analyzed the outcomes of 11,815 patients undergoing coronary artery bypass grafting in one of the 43 cardiac surgery programs of the Department of Veteran Affairs. Risk factors for intermediate- and short-term mortality were determined using Cox proportional hazards regression models. Effects of risk factors during these two periods were explicitly compared.nnnRESULTSnWe found important differences in mortality risk-factor sets between the intermediate- and short-term periods after coronary artery bypass grafting. The majority of predictors of intermediate-term mortality were noncardiac-related variables, whereas the majority of predictors of short-term mortality were cardiac-related variables. Impaired functional status, chronic obstructive pulmonary disease, and renal dysfunction had greater effects in the intermediate-term period. Previous heart operation, angina class III or IV, previous myocardial infarction, and preoperative use of an intraaortic balloon pump had greater effects in the short-term period.nnnCONCLUSIONSnThe risk factors for intermediate-term mortality identified in this study can augment preoperative risk assessment and counseling of patients. Clinicians should be aware of the importance of noncardiac-related variables as predictors of mortality in the intermediate-term period after coronary artery bypass grafting.

Organizational predictors of adherence to ambulatory care screening guidelines

Objective. The purpose of this study was to identify hospital organizational characteristics consistently associated with adherence to multiple clinical practice guidelines (CPGs). We examined the relationship between organizational and patient population characteristics and adherence to three screening CPGs implemented throughout the Veterans Health Administration (VHA). Materials and methods. The study included 114 acute care facilities. Three sources of data were used: 1998 American Hospital Association data, VHA External Peer Review Program data for 1998 and 1999, and the 1999 Veterans Satisfaction Survey. Organizational characteristics likely to affect adherence with the CPGs were classified into five conceptual domains (clinical emphasis, operational capacity, patient population, professionalism, and urbanicity). Organizational characteristics were ranked, based on their standardized beta coefficients in bivariate logistic regressions predicting the likelihood of adherence. Within-domain multivariable logistic analyses assessed the robustness of individual predictors of CPG adherence, controlling for other organizational factors within the same domain. Results. Overall, 46 of 48 relationships in the bivariate logistic analyses were significant, and 43 of these remained significant in the within-domain multivariate analyses. The relative rankings of the variables as predictors of CPG adherence within conceptual domains were also quite consistent. Conclusions. Strong evidence was found for the importance of specific organizational factors, including mission, capacity, professionalism, and patient population characteristics that influence CPG adherence in a large multiinstitutional sample involving multiple provider practices. Research and programs to improve adherence to CPGs and other quality improvement activities in hospitals should incorporate these organizational factors.

Physician Process and Patient Outcome Measures for Diabetes Care: Relationships to Organizational Characteristics

Background:Optimal diabetes management relies on providers adhering to evidence-based practice guidelines in the processes of care delivery and patients adhering to self-management recommendations to maximize patient outcomes. Purpose:To explore: (1) the degree to which providers adhere to the guidelines; (2) the extent of glycemic, lipid, and blood pressure control in patients with diabetes; and (3) the roles of organizational and patient population characteristics in affecting both provider adherence and patient outcome measures for diabetes. Design:Secondary data analysis of provider adherence and patient outcome measures from chart reviews, along with surveys of facility quality managers. Sample:We sampled 109 Veterans Affairs medical centers (VAMCs). Results:Analyses indicated that provider adherence to diabetes guidelines (ie, hemoglobin A1c, foot, eye, renal, and lipid screens) and patient outcome measures (ie, glycemic, lipid, and hypertension control plus nonsmoking status) are comparable or better in VAMCs than reported elsewhere. VAMCs with higher levels of provider adherence to diabetes guidelines had distinguishing organizational characteristics, including more frequent feedback on diabetes quality of care, designation of a guideline champion, timely implementation of quality-of-care changes, and greater acceptance of guideline applicability. VAMCs with better patient outcome measures for diabetes had more effective communication between physicians and nurses, used educational programs and Grand Rounds presentations to implement the diabetes guidelines, and had an overall patient population that was older and with a smaller percentage of black patients. Conclusions:Healthcare organizations can adopt many of the identified organizational characteristics to enhance the delivery of care in their settings.

Quality of ambulatory care for women and men in the Veterans Affairs Health Care System.

AbstractBACKGROUND: Gender differences in inpatient quality of care are well known. However, whether men and women receive equivalent ambulatory care is less well understood.n OBJECTIVE: To study gender differences in quality of care for patients receiving primary care in the Veterans Affairs (VA) Health Care System.n DESIGN: Cross-sectional samples of VA enrollees during fiscal years 1999 to 2000.n PARTICIPANTS: Samples of 6,442 to 86,405 men and women treated at VA facilities for whom at least 1 of 9 quality measures was available.n MEASUREMENTS: Appropriate general preventive services (pneumococcal vaccination, influenza vaccination, colorectal cancer screening), and specific services for diabetes (annual hemoglobin A1c [HbA1c] testing, good glycemic control, annual diabetic eye exam), hypertension (good blood pressure control), or prior myocardial infarction (use of β-blockers or aspirin).n RESULTS: In adjusted analyses, there were no substantial gender differences in rates of appropriate care. For women compared with men, the adjusted relative risk for appropriate care ranged from 0.96 for blood pressure control (95% confidence interval: 0.93 to 0.99; P=.02) to 1.05 for HbA1c≤8.0% (95% confidence interval: 1.03 to 1.07; P<.01). Analyses stratified by age demonstrated equivalent care between men and women in 9 of the 14 subgroups evaluated.n CONCLUSIONS: In this large national health care system that predominantly serves men, the quality of ambulatory care is equivalent for women and men on numerous measures.

Receipt of nutrition and exercise counseling among medical outpatients with psychiatric and substance use disorders

OBJECTIVE: Mentally ill persons represent a population that is potentially vulnerable to receiving a poorer quality of medical care. This study examines the relationship between mental disorders and the likelihood of receiving recommended nutrition and exercise counseling.DESIGN: Cross-sectional study combining chart-review data and administrative database records.SETTING: One hundred forty-seven Veterans Affairs (VA) medical centers nationwide.PATIENTS/PARTICIPANTS: The sample included 90,240 patients with obesity and/or hypertension who had ≥3 medical outpatient visits in the previous year.MEASUREMENTS AND MAIN RESULTS: The outcomes of interest were chart-documented receipt of nutrition counseling and receipt of exercise counseling in the past 2 years. This chart information was merged with VA inpatient and outpatient administrative databases, which were used to identify persons with diagnosed mental disorders. Most patients received nutrition counseling (90.4%), exercise counseling (88.5%), and counseling for both (85.7%) in the past 2 years. The rates of counseling differed significantly but modestly by mental health status. The lowest rates were found among patients dually diagnosed with comorbid psychiatric and substance use disorders; however, the magnitude of the disparities was small, ranging from 2% to 4% across outcomes. These results were unchanged after controlling for demographics, health status, and facility characteristics using multivariable generalized estimating equation modeling.CONCLUSIONS: Among patients engaged in active medical treatment, rates of nutrition and exercise counseling were high at VA medical centers, and the diagnosis of mental illness was not a substantial barrier to such counseling. More work is needed to determine whether these findings generalize to non-VA settings and to understand the potential role that integrated systems such as the VA can play in reducing disparities for vulnerable populations.

Variation in mortality risk factors with time after coronary artery bypass graft operation.

BACKGROUNDnDifferences in mortality risk factor sets during different time periods (eg, short-term versus intermediate-term) after coronary artery bypass grafting have been reported. However, little is known about the time-varying effects of mortality risk factors after the operation.nnnMETHODSnWe analyzed 11,815 veterans who had coronary artery bypass grafting at any of the 43 Veterans Affairs cardiac surgery centers from October 1997 to September 1999. Time-varying effects of 14 mortality risk factors during the 210 days after coronary artery bypass grafting were evaluated using Cox B-spline regression, which provides an estimate of risk for each variable for each day after operation.nnnRESULTSnEight variables showed significant time-varying effects after operation. The effect of prior heart operation was very high immediately after operation, but disappeared within 1 week. Three other cardiac variables (prior myocardial infarction, preoperative intraaortic balloon pump, and Canadian Cardiovascular Society anginal class III or IV) also conferred the highest risk on the day of operation and decreased thereafter. In contrast, the four time-varying noncardiac risk variables (age, impaired functional status, chronic obstructive pulmonary disease, and renal dysfunction) showed little or no association with mortality immediately after operation, but had increasing impact during the several months after operation.nnnCONCLUSIONSnA sizable number of mortality risk factors have time-varying effects after coronary artery bypass grafting. Several cardiac risk factors have peak impact immediately after operation but dissipate thereafter. Several noncardiac risk factors confer little risk immediately after operation, but these risks increase during several months. This information may help clinicians focus management strategies for patients during the 7 months after operation.

Improving the Outcomes of Metabolic Conditions: Managing Momentum To Overcome Clinical Inertia

Hypertension, dyslipidemia, and diabetes are highly prevalent, and often concurrent, conditions: 50 million Americans have hypertension (1), 38 million have high-risk cholesterol levels (2), and 20.8 million have diabetes (3). The direct (medical services) and indirect (disability and premature death) costs of treating diabetes alone exceed

Effectiveness of a nationally implemented smoking cessation guideline on provider and patient practices

130 billion per year (4). Amputations, renal failure, visual loss, stroke, heart attack, and premature death reduce the length of life of patients and the quality of life for them and their families. In the last decade or so, several remarkable clinical trials have shown that better control of glycemia, blood pressure, and low-density lipoprotein (LDL) cholesterol level leads to better outcomes (1-3). We now know that surveillance for nephropathy, neuropathy, and retinopathy enables early identification and treatment of diabetes-related complications (5). Guidelines have incorporated the new evidence very quickly. National public education programs and professional societies have disseminated these evidence-based recommendations to the public and to professionals. The new evidence likewise influenced national voluntary consensus standards for performance measurement, which are widely used for accreditation (6) and quality improvement (7). Has this unprecedented momentum created by publicizing evidence and measuring outcomes resulted in translation of evidence into practice? And if not, why? Two studies in this issue (8, 9) provide us with a progress report from both the public health and managed health care plan perspectives. Saaddine and colleagues (8) evaluate changes in the quality of diabetes care from the 1990s to the early 2000s. They measured care by comparing patient-level findings on nationally representative, federally sponsored surveys to standardized national consensus measures for diabetes care. The news is mixed. Encouragingly, the number of individuals with hemoglobin A1c levels between 6% and 8% increased by about 13% to 47%, the proportion of individuals with LDL cholesterol levels less than 3.4 mmol/L (<130 mg/dL) increased by 22% to 64%, and the frequency of aspirin use increased by 13% to 45%. However, mean hemoglobin A1c remained unchanged, as did the percentage (about 68%) of individuals whose blood pressure was less than 140/90 mm Hg. Important process measures, such as foot screening and dilated eye examinations, did not increase. Although better-educated individuals with health insurance generally fared better, these socioeconomic factors did not consistently predict better intermediate outcomes, such as blood pressure control or reduced LDL cholesterol level. The study has weaknesses and strengths. We should be cautious about comparing responses on cross-sectional surveys that were performed years apart, especially with an intervening change in the definition of diabetes. On the other hand, the National Health and Nutrition Examination Survey used a sampling strategy that assures a study sample representative of the U.S. population. Extrapolation of the findings to the U.S. population suggests that millions of Americans with diabetes are benefiting from improved glycemic and cholesterol level control. Unfortunately, care remains poor, not merely suboptimal, for a substantial minority of patients: About 20% have hemoglobin A1c greater than 9% (with 14% having hemoglobin A1c > 10%), 33% have uncontrolled blood pressure (>140/90 mm Hg), and 40% have poor LDL cholesterol level control (>3.4 mmol/L [>130mg/dL]). Less than 50% of patients were taking aspirin, an inexpensive and reasonably safe, yet effective, medication to reduce the risk for coronary heart disease. The main message of Saaddine and colleagues study is that millions of Americans remain at high risk for the complications of diabetes despite the new evidence and campaigns to educate the public and the medical profession. The term clinical inertia refers to the failure of providers to alter therapy in the face of clear indications for changes (10). Rodondi and colleagues (9) used automated data from a large health maintenance organization to evaluate predictors of medication changes for patients with and without diabetes. The authors defined a single poor glycemic control threshold (hemoglobin A1c > 8%) and varying poor LDL cholesterol level and blood pressure control thresholds on the basis of co-existing conditions, such as diabetes or cardiovascular or renal disease. The baseline prevalence of poor control was 28% for hypertension and 42% for dyslipidemia and glycemic control. The authors defined appropriate care as either an indicated change in treatment or a subsequent measurement that was within the range of adequate control. Most patients with poor control of risk factors70% for hemoglobin A1c, 59% for LDL cholesterol level, 71% for systolic blood pressure, and 82% for diastolic blood pressurewere managed appropriately. Indeed, 70% of the treatment changes occurred within 2 months. The results are especially encouraging for glycemic control since the threshold that defined the need for action was a hemoglobin A1c less than 8%. However, the authors excluded insulin-requiring persons with poor hemoglobin A1c control, which limits the generalizability of this finding. These 2 articles show that diabetes care in the United States is getting better but still falls far short of reasonable goals. The performance of the Veterans Health Administration (VHA) in diabetes care has improved substantially in the past decade so that it is similar to and generally exceeds commercial health care plans (11) and fee-for-service Medicare (12). Moreover, ongoing measurements show that the VHAs performance continues to improve (13). Both the public health and managed care sectors can learn from the VHA experience in systematizing care for more than 1 million veterans with diabetes and overcoming clinical inertia that characterized care as late as 19992000 (14). The VHA developed a national infrastructure to support the delivery of evidence-based care. Key elements included assignment of patients to an identified primary care provider, dissemination of guidelines through pocket cards and internal educational broadcasts, implementation of electronic medical records, and quarterly performance assessment. Each VHA network and medical center director had a performance contract that included fulfillment of reasonable target goals for each accountability measure. Facility managers could implement computerized clinical reminders, academic detailing, and feedback to clinicians but could not offer financial incentives. Cross-sectional analyses demonstrated that most of the variation in outcomes was between VHA medical centers rather than between individual physicians in a medical center (15). Indeed, some facilities far exceed the VHA-wide average rate of lowering of hemoglobin A1c levels over a 2-year period (16). Since all VHA medical centers operate under the same policies and use the same electronic health records, why does facility performance still vary? One evolving area of inquiry suggests the importance of organizational factors. Medical centers with better performance had more frequent internal feedback to clinicians, identified frontline clinicians to lead (champions), and were more likely to accept the guidelines as applicable to their practice (17). These observations suggest that while a health care system may initiate momentum for change, clinicians are essential change agents for local quality improvement efforts. Momentum is now building nationally to improve individual physicians access to high-quality medical information systems, which was a key factor in the success of the VHA. The American Health Information Community has been chartered to support the Presidents goal of electronic health records for most Americans within 10 years (18). However, negative trials of diabetes quality improvement interventions in large health care systems with electronic health records (19) underscore the need for continued research to better understand the inter-relationshipsamong patient, provider, and health care systemthat contribute to clinical inertia. Although generalizable solutions are not yet within our reach, the studies in this issue clearly document that physicians must hold themselves to a higher standard than simply maintaining the status quo. The success of the VHA demonstrates that continued managerial momentum can lead to sustained improvement even in disadvantaged populations. We, therefore, offer a modest but achievable proposal for every health care professional, every practice, and every private and public health care system. First, review your own data and processes of care for diabetes. Second, use the principles of evidence-based medicine to identify the highest-priority goals and treatment strategies (20). Third, develop actionable plans to increase the proportion of clinical encounters in which clinicians take appropriate action. Fourth, systematically track progress toward achieving treatment goals. Fifth, give feedback to those who are making patient care decisions (9). We must recognize the deadly consequences of clinical inertia and commit ourselves to the task of overcoming it in our own practices. If we succeed, we will improve the prospect of healthier lives for tens of millions of Americans.