Angina symptom burden associated with depression status among veterans with ischemic heart disease.

BACKGROUND: Angina and depression are common in ischemic heart disease (IHD), but their association remains understudied. PURPOSE: This study was conducted in order to evaluate the association of 1 year change in depression with change in patient-reported outcomes of stable angina. METHODS: Five hundred sixty-nine stable angina patients completed the Seattle Angina Questionnaire and Patient Health Questionnaire (PHQ) at baseline and 1 year. Participants were divided into four groups: not depressed, new onset of depression at 1 year, remitted at 1 year, and persistently depressed. Associations between depression and angina symptoms were evaluated using regression models. RESULTS: Compared to those not depressed, newly depressed participants reported more angina (ß = -11.7, p < 0.001) and physical limitations (ß = -11.8, p < 0.001) and lower treatment satisfaction (ß = -15.03, p < 0.001) and quality of life (ß = -15.4, p < 0.001). Persistently depressed participants reported physical limitations (ß = -7.4, p < 0.05), lower treatment satisfaction (ß = -10.1, p < 0.001), and poorer quality of life (ß = -10.03, p < 0.001). CONCLUSIONS: Changes in depression scores and angina outcomes were significantly associated.

Predicting risk of hospitalization or death among patients receiving primary care in the Veterans Health Administration.

BACKGROUND: Statistical models that identify patients at elevated risk of death or hospitalization have focused on population subsets, such as those with a specific clinical condition or hospitalized patients. Most models have limitations for clinical use. Our objective was to develop models that identified high-risk primary care patients. METHODS: Using the Primary Care Management Module in the Veterans Health Administration (VHA)'s Corporate Data Warehouse, we identified all patients who were enrolled and assigned to a VHA primary care provider on October 1, 2010. The outcome variable was the occurrence of hospitalization or death during the subsequent 90 days and 1 year. We extracted predictors from 6 categories: sociodemographics, medical conditions, vital signs, prior year use of health services, medications, and laboratory tests and then constructed multinomial logistic regression models to predict outcomes for over 4.6 million patients. RESULTS: In the predicted 95th risk percentiles, observed 90-day event rates were 19.6%, 6.2%, and 22.6%, respectively, for hospitalization, death, and either hospitalization or death, compared with population averages of 2.7%, 0.7%, and 3.4%, respectively; 1-year event rates were 42.3%, 19.4%, and 51.3%, respectively, compared with population averages of 8.2%, 2.6%, and 10.8%, respectively. The C-statistics for 90-day outcomes were 0.83, 0.86, and 0.81, respectively, for hospitalization, death, and either hospitalization or death and were 0.81, 0.85, and 0.79, respectively, for 1-year outcomes. CONCLUSIONS: Prediction models using electronic clinical data accurately identified patients with elevated risk for hospitalization or death. This information can enhance the coordination of care for patients with complex clinical conditions.

Predicting risk of hospitalization or death among patients with heart failure in the veterans health administration.

Patients with heart failure (HF) are at high risk of hospitalization or death. The objective of this study was to develop prediction models to identify patients with HF at highest risk for hospitalization or death. Using clinical and administrative databases, we identified 198,460 patients who received care from the Veterans Health Administration and had ≥1 primary or secondary diagnosis of HF that occurred within 1 year before June 1, 2009. We then tracked their outcomes of hospitalization and death during the subsequent 30 days and 1 year. Predictor variables chosen from 6 clinically relevant categories of sociodemographics, medical conditions, vital signs, use of health services, laboratory tests, and medications were used in multinomial regression models to predict outcomes of hospitalization and death. In patients who were in the ≥95th predicted risk percentile, observed event rates of hospitalization or death within 30 days and 1 year were 27% and 80% respectively, compared to population averages of 5% and 31%, respectively. The c-statistics for the 30-day outcomes were 0.82, 0.80, and 0.80 for hospitalization, death, and hospitalization or death, respectively, and 0.82, 0.76, and 0.77, respectively, for 1-year outcomes. In conclusion, prediction models using electronic health records can accurately identify patients who are at highest risk for hospitalization or death. This information can be used to assist care managers in selecting patients for interventions to decrease their risk of hospitalization or death.

Evaluation of a weight management program for veterans.

INTRODUCTION: To improve the health of overweight and obese veterans, the Department of Veterans Affairs (VA) developed the MOVE! Weight Management Program for Veterans. The aim of this evaluation was to assess its reach and effectiveness. METHODS: We extracted data on program involvement, demographics, medical conditions, and outcomes from VA administrative databases in 4 Western states. Eligibility criteria for MOVE! were being younger than 70 years and having a body mass index (BMI, in kg/m(2)) of at least 30.0, or 25.0 to 29.9 with an obesity-related condition. To evaluate reach, we estimated the percentage of eligible veterans who participated in the program and their representativeness. To evaluate effectiveness, we estimated changes in weight and BMI using multivariable linear regression. RESULTS: Less than 5% of eligible veterans participated, of whom half had only a single encounter. Likelihood of participation was greater in women, those with a higher BMI, and those with more primary care visits, sleep apnea, or a mental health condition. Likelihood of participation was lower among those who were younger than 55 (vs 55-64), widowed, current smokers, and residing farther from the medical center (≥30 vs <30 miles). At 6- and 12-month follow-up, participants lost an average of 1.3 lb (95% confidence interval [CI], -2.6 to -0.02 lb) and 0.9 lb (95% CI, -2.0 to 0.1 lb) more than nonparticipants, after covariate adjustment. More intensive treatment (≥6 encounters) was associated with greater weight loss at 12 months (-3.7 lb; 95% CI, -5.1 to -2.3 lb). CONCLUSION: Few eligible patients participated in the program during the study period, and overall estimates of effectiveness were low.

Collaborative care intervention for stable ischemic heart disease.

BACKGROUND: Accumulating evidence suggests that collaborative models of care enhance communication among primary care providers, improving quality of care and outcomes for patients with chronic conditions. We sought to determine whether a multifaceted intervention that used a collaborative care model and was directed through primary care providers would improve symptoms of angina, self-perceived health, and concordance with practice guidelines for managing chronic stable angina. METHODS: We conducted a prospective trial, cluster randomized by provider, involving patients with symptomatic ischemic heart disease recruited from primary care clinics at 4 academically affiliated Department of Veterans Affairs health care systems. Primary end points were changes over 12 months in symptoms on the Seattle Angina Questionnaire, self-perceived health, and concordance with practice guidelines. RESULTS: In total, 183 primary care providers and 703 patients participated in the study. Providers accepted and implemented 91.6% of 701 recommendations made by collaborative care teams. Almost half were related to medications, including adjustments to ß-blockers, long-acting nitrates, and statins. The intervention did not significantly improve symptoms of angina or self-perceived health, although end points favored collaborative care for 10 of 13 prespecified measures. While concordance with practice guidelines improved 4.5% more among patients receiving collaborative care than among those receiving usual care (P < .01), this was mainly because of increased use of diagnostic testing rather than increased use of recommended medications. CONCLUSION: A collaborative care intervention was well accepted by primary care providers and modestly improved receipt of guideline-concordant care but not symptoms or self-perceived health in patients with stable angina.

Regional variation in health status among chronic obstructive pulmonary disease patients.

BACKGROUND: Little is known about geographic differences in health status among patients with chronic obstructive pulmonary disease (COPD). OBJECTIVES: The aim of this study was to examine regional variations in self-reported health status of COPD patients at 7 Veterans Affairs clinics. METHODS: The Ambulatory Care Quality Improvement Project was a multicenter, randomized trial conducted from 1997 to 2000 that evaluated a quality improvement intervention in the primary care setting. Four thousand and nine participants with COPD (age ≥45 years) completed the Seattle Obstructive Lung Disease Questionnaire (SOLDQ) and 2,991 also completed the Medical Outcomes Study 36-item short form (SF-36). The unadjusted maximal difference in health status scores is reported as the ratio of the highest and lowest site prevalence. We report the maximal site difference in mean health status scores after adjusting for demographics, comorbidities, utilization, medication use and clinic factors. RESULTS: Subjects were predominantly older (66.5 ± 9.2 years) Caucasian (83.2%) men (97.9%). After adjustment, the maximal site difference for each health status score was significant (p < 0.01) but larger for the SOLDQ (physical 11.2, emotional 9.7, coping skills 7.6) than for the SF-36 (physical component summary 4.7, mental component summary 2.6). Most of the health status variation was explained by individual or clinic level factors, not clinic site. CONCLUSIONS: Our models explained <30% of variation in health status measures; therefore, future studies should consider additional predictors of health status such as physical performance, social determinants of health, COPD treatment and environmental factors. Despite its limitations, this study suggests a need to consider regional differences in health status when comparing COPD health outcomes in diverse geographic areas.

Strategies from a nationwide health information technology implementation: the VA CART story.

The VA Cardiovascular Assessment, Reporting, and Tracking (CART) system is a customized electronic medical record system which provides standardized report generation for cardiac catheterization procedures, serves as a national data repository, and is the centerpiece of a national quality improvement program. Like many health information technology projects, CART implementation did not proceed without some barriers and resistance. We describe the nationwide implementation of CART at the 77 VA hospitals which perform cardiac catheterizations in three phases: (1) strategic collaborations; (2) installation; and (3) adoption. Throughout implementation, success required a careful balance of technical, clinical, and organizational factors. We offer strategies developed through CART implementation which are broadly applicable to technology projects aimed at improving the quality, reliability, and efficiency of health care.

Declining mortality following acute myocardial infarction in the Department of Veterans Affairs Health Care System.

BACKGROUND: Mortality from acute myocardial infarction (AMI) is declining worldwide. We sought to determine if mortality in the Veterans Health Administration (VHA) has also been declining. METHODS: We calculated 30-day mortality rates between 2004 and 2006 using data from the VHA External Peer Review Program (EPRP), which entails detailed abstraction of records of all patients with AMI. To compare trends within VHA with other systems of care, we estimated relative mortality rates between 2000 and 2005 for all males 65 years and older with a primary diagnosis of AMI using administrative data from the VHA Patient Treatment File and the Medicare Provider Analysis and Review (MedPAR) files. RESULTS: Using EPRP data on 11,609 patients, we observed a statistically significant decline in adjusted 30-day mortality following AMI in VHA from 16.3% in 2004 to 13.9% in 2006, a relative decrease of 15% and a decrease in the odds of dying of 10% per year (p = .011). Similar declines were found for in-hospital and 90-day mortality.Based on administrative data on 27,494 VHA patients age 65 years and older and 789,400 Medicare patients, 30-day mortality following AMI declined from 16.0% during 2000-2001 to 15.7% during 2004-June 2005 in VHA and from 16.7% to 15.5% in private sector hospitals. After adjusting for patient characteristics and hospital effects, the overall relative odds of death were similar for VHA and Medicare (odds ratio 1.02, 95% C.I. 0.96-1.08). CONCLUSION: Mortality following AMI within VHA has declined significantly since 2003 at a rate that parallels that in Medicare-funded hospitals.

Cause of death in Washington state veterans hospitalized with acute coronary syndromes in the veterans health administration.

BACKGROUND: In the United States, relatively little is known about cause of death in individuals who die prior to or after hospital discharge for acute coronary syndromes (ACS). The purpose of this report was to compare baseline patient characteristics according to whether the underlying cause of death was cardiac or non-cardiac. METHODS: We linked cause of death information from Washington State death records to the Department of Veterans Affairs (VA) External Peer Review Program ACS registry. From 524 individuals who were hospitalized for ACS in veterans hospitals located in Washington State or Oregon, we identified 136 individuals who according to VA death records died during the years 2003 to 2005. Of these, 117 (86%) were found in Washington State death records. Sociodemographic variables, as well as underlying and secondary causes of death, were obtained from Washington State death records provided by the Washington State Department of Health. Clinical variables, including medical histories, presentation on admission, and in-hospital death were extracted from the VA ACS registry. RESULTS: Somewhat surprisingly, only 52% of veterans died of cardiac causes when only the underlying cause of death was used. However, when secondary causes of death were added to the definition, the proportion that died of cardiac causes increased to 81%. Patient characteristics were similar in the two groups, although small numbers limited the ability to detect statistically significant differences. CONCLUSION: These preliminary findings suggest that it is important to consider secondary causes as well as the underlying one when classifying deaths as cardiac or non-cardiac.

Depression, posttraumatic stress disorder, and mortality.

OBJECTIVE: To determine whether a history of depression and/or posttraumatic stress disorder (PTSD) is associated with all-cause mortality in primary care patients over an average of 2 years. METHODS: Patients from seven Department of Veterans Affairs medical centers completed mailed questionnaires. Depression and PTSD status were determined from patient self-report of a prior diagnosis and/or electronic administrative data. Date of death was ascertained from Veterans Health Information Systems and Technology Architecture and the Department of Veterans Affairs' Beneficiary Identification and Records Locator System. RESULTS: Among 35,715 primary care patients, those with a history of depression without a history of PTSD (n = 6876) were at increased risk of death over an average of 2 years compared with patients with neither depression nor PTSD after adjustment for demographic variables, health behaviors, and medical comorbidity (hazard ratio (HR) = 1.17; 95% Confidence Interval (CI) = 1.06-1.28). However, patients with a history of PTSD without a history of depression (n = 748) were not at increased risk of death compared with patients with neither depression nor PTSD (HR = 0.84; 95% CI = 0.63-1.13). Patients with a history of both (n = 3762) were at increased risk of death after adjustment for demographic factors, although not after additional adjustment for health behaviors and medical comorbidity (HR = 0.90; 95% CI = 0.78-1.04). CONCLUSIONS: In a large sample of veterans, a prior diagnosis of depression, but not PTSD, was associated with an increased risk of death over an average of 2 years after adjusting for age, demographic variables, health behaviors, and medical comorbidity.

A refill adherence algorithm for multiple short intervals to estimate refill compliance (ReComp).

BACKGROUND: There are many measures of refill adherence available, but few have been designed or validated for use with repeated measures designs and short observation periods. OBJECTIVE: To design a refill-based adherence algorithm suitable for short observation periods, and compare it to 2 reference measures. METHODS: A single composite algorithm incorporating information on both medication gaps and oversupply was created. Electronic Veterans Affairs pharmacy data, clinical data, and laboratory data from routine clinical care were used to compare the new measure, ReComp, with standard reference measures of medication gaps (MEDOUT) and adherence or oversupply (MEDSUM) in 3 different repeated measures medication adherence-response analyses. These analyses examined the change in low density lipoprotein (LDL) with simvastatin use, blood pressure with antihypertensive use, and heart rate with beta-blocker use for 30- and 90-day intervals. Measures were compared by regression based correlations (R2 values) and graphical comparisons of average medication adherence-response curves. RESULTS: In each analysis, ReComp yielded a significantly higher R2 value and more expected adherence-response curve regardless of the length of the observation interval. For the 30-day intervals, the highest correlations were observed in the LDL-simvastatin analysis (ReComp R2 = 0.231; [95% CI, 0.222-0.239]; MEDSUM R2 = 0.054; [95% CI, 0.049-0.059]; MEDOUT R2 = 0.053; [95% CI, 0.048-0.058]). CONCLUSIONS: ReComp is better suited to shorter observation intervals with repeated measures than previously used measures.

Inhaled corticosteroids and risk of lung cancer among patients with chronic obstructive pulmonary disease.

RATIONALE AND OBJECTIVES: Lung cancer is a frequent cause of death among patients with chronic obstructive pulmonary disease (COPD). We examined whether the use of inhaled corticosteroids among patients with COPD was associated with a decreased risk of lung cancer. METHODS: We performed a cohort study of United States veterans enrolled in primary care clinics between December 1996 and May 2001. Participants had received treatment for, had an International Classification of Disease, 9th edition, diagnosis of, or a self-reported diagnosis of COPD. Patients with a history of lung cancer were excluded. To be exposed, patients must have been at least 80% adherent to inhaled corticosteroids. We used Cox regression models to estimate the risk of cancer and adjust for potential confounding factors. FINDINGS: We identified 10,474 patients with a median follow-up of 3.8 years. In comparison to nonusers of inhaled corticosteroids, adjusting for age, smoking status, smoking intensity, previous history of non-lung cancer malignancy, coexisting illnesses, and bronchodilator use, there was a dose-dependent decreased risk of lung cancer associated with inhaled corticosteroids (ICS dose < 1,200 mug/d: adjusted HR, 1.3; 95% confidence interval, 0.67-1.90; ICS dose >or= 1,200 microg/d: adjusted HR, 0.39; 95% confidence interval, 0.16-0.96). Changes in cohort definitions had minimal effects on the estimated risk. Analyses examining confounding by indication suggest biases in the opposite direction of the described effects. INTERPRETATION: Results suggest that inhaled corticosteroids may have a potential role in lung cancer prevention among patients with COPD. These initial findings require confirmation in separate and larger cohorts.

Depression diagnosis and antidepressant treatment among depressed VA primary care patients.

This study examined the extent to which 3559 VA primary care patients with depression symptomatology received depression diagnoses and/or antidepressant prescriptions. Symptomatology was classified as mild (13%), moderate (42%) or severe (45%) based on SCL-20 scores. Diagnosis and treatment was related to depression severity and other patient characteristics. Overall, 44% were neither diagnosed nor treated. Only 22% of those neither diagnosed nor treated for depression received treatment for other psychopathology. Depression treatment performance measures dependent on diagnoses and antidepressant prescriptions from administrative databases exclude undiagnosed patients with significant, treatable, symptomatology.

Treatment delay associated with alternative medicine use among veterans with head and neck cancer.

BACKGROUND: Use of complementary and alternative medicine (CAM) is increasing in the United States. This study investigates whether the use of alternative medicine is associated with a delay of treatment in head and neck cancer. METHODS: This study used the records obtained from a large trial involving ambulatory care US veterans. Subjects completed a CAM utilization questionnaire. The primary outcome variable was the time duration from cancer diagnosis to the time of cancer treatment. RESULTS: Of veterans with head and neck cancer, 51% reported using some form of CAM, whereas 23% reported using a therapy classified as alternative medicine. Patients who used alternative medicine significantly delayed cancer treatment by 22 days compared with those who did not use alternative medicine (p = .05, 95% confidence interval [CI] = 0-44 days). CONCLUSIONS: CAM use is common in veterans with head and neck cancer. Use of alternative medicine was associated with a significant delay in cancer treatment.

Differences in health care utilization at the end of life among patients with chronic obstructive pulmonary disease and patients with lung cancer.

BACKGROUND: We sought to examine health care resource utilization in the last 6 months of life among patients who died with chronic obstructive pulmonary disease (COPD) compared with those who died with lung cancer and to examine geographic variations in care. METHODS: We performed a retrospective cohort study of patients diagnosed as having COPD or lung cancer, who were seen in 1 of 7 Veteran Affairs medical centers primary care clinics and who died during the study period. Our outcome of interest was health care resource utilization in the last 6 months of life. RESULTS: In the last 6 months of life, patients with COPD were more likely to visit their primary care providers but had fewer hospital admissions compared with patients with lung cancer. Patients with COPD had twice the odds of being admitted to an intensive care unit (ICU), 5 times the odds of remaining there 2 weeks or longer, and received fewer opiates and benzodiazepine prescriptions compared with patients with lung cancer. There were geographic variations in the use of ICUs for patients with COPD but not for those with lung cancer. Total health care costs were $4000 higher for patients with COPD because of ICU utilization. CONCLUSIONS: In the last 6 months of life, patients with COPD were more likely to have had a primary care visit and been admitted to an ICU but less likely to receive palliative medications compared with patients with lung cancer. We found significant geographic variability in ICU utilization but only for patients with COPD.

Predicting mortality and healthcare utilization with a single question.

OBJECTIVE: We compared single- and multi-item measures of general self-rated health (GSRH) to predict mortality and clinical events a large population of veteran patients. DATA SOURCE/STUDY SETTING: We analyzed prospective cohort data collected from 21,732 patients as part of the Veterans Affairs Ambulatory Care Quality Improvement Project (ACQUIP), a randomized controlled trial investigating quality-of-care interventions. STUDY DESIGN: We created an age-adjusted, logistic regression model for each predictor and outcome combination, and estimated the odds of events by response category of the GSRH question and compared the discriminative ability of the predictors by developing receiver operator characteristic curves and comparing the associated area under the curve (AUC)/c-statistic for the single- and multi-item measures. DATA COLLECTION/EXTRACTION METHODS: All patients were sent a baseline assessment that included a multi-item measure of general health, the 36-item Medical Outcomes Study Short Form (SF-36), and an inventory of comorbid conditions. We compared the predictive and discriminative ability of the GSRH to the SF-36 physical component score (PCS), the mental component score (MCS), and the Seattle index of comorbidity (SIC). The GSRH is an item included in the SF-36, with the wording: "In general, would you say your health is: Excellent, Very Good, Good, Fair, Poor?" PRINCIPAL FINDINGS: The GSRH, PCS, and SIC had comparable AUC for predicting mortality (AUC 0.74, 0.73, and 0.73, respectively); hospitalization (AUC 0.63, 0.64, and 0.60, respectively); and high outpatient use (AUC 0.61, 0.61, and 0.60, respectively). The MCS had statistically poorer discriminatory performance for mortality and hospitalization than any other other predictors (p<.001). CONCLUSIONS: The GSRH response categories can be used to stratify patients with varying risks for adverse outcomes. Patients reporting "poor" health are at significantly greater odds of dying or requiring health care resources compared with their peers. The GSRH, collectable at the point of care, is comparable with longer instruments.

The performance of administrative and self-reported measures for risk adjustment of Veterans Affairs expenditures.

OBJECTIVE: To evaluate the performance of different prospective risk adjustment models of outpatient, inpatient, and total expenditures of veterans who regularly use Veterans Affairs (VA) primary care. DATA SOURCES: We utilized administrative, survey and expenditure data on 14,449 VA patients enrolled in a randomized trial that gave providers regular patient health assessments. STUDY DESIGN: This cohort study compared five administrative data-based, two self-report risk adjusters, and base year expenditures in prospective models. DATA EXTRACTION METHODS: VA outpatient care and nonacute inpatient care expenditures were based on unit expenditures and utilization, while VA expenditures for acute inpatient care were calculated from a Medicare-based inpatient cost function. Risk adjusters for this sample were constructed from diagnosis, medication and self-report data collected during a clinical trial. Model performance was compared using adjusted R2 and predictive ratios. PRINCIPAL FINDINGS: In all expenditure models, administrative-based measures performed better than self-reported measures, which performed better than age and gender. The Diagnosis Cost Groups (DCG) model explained total expenditure variation (R2=7.2 percent) better than other models. Prior outpatient expenditures predicted outpatient expenditures best by far (R2=42 percent). Models with multiple measures improved overall prediction, reduced over-prediction of low expenditure quintiles, and reduced under-prediction in the highest quintile of expenditures. CONCLUSIONS: Prediction of VA total expenditures was poor because expenditure variation reflected utilization variation, but not patient severity. Base year expenditures were the best predictor of outpatient expenditures and nearly the best for total expenditures. Models that combined two or more risk adjusters predicted expenditures better than single-measure models, but are more difficult and expensive to apply.

Functional status and patient satisfaction: a comparison of ischemic heart disease, obstructive lung disease, and diabetes mellitus.

OBJECTIVE: To determine the extent to which chronic illness and disease severity affect patient satisfaction with their primary care provider in general internal medicine clinics. DESIGN: Cross-sectional mailed questionnaire study. SETTING: Primary care clinics at 7 Veterans Affairs medical centers. PATIENTS/PARTICIPANTS: Of 62,487 patients participating in the Ambulatory Care Quality Improvement Project, 35,383 (57%) returned an initial screening questionnaire and were subsequently sent a satisfaction questionnaire. Patients (N=21,689; 61%) who returned the Seattle Outpatient Satisfaction Survey (SOSQ) were included in the final analysis, representing 34% of the original sample. MEASUREMENTS AND MAIN RESULTS: The organizational score of the SOSQ measures satisfaction with health care services in the internal medicine clinic, and the humanistic scale measures patient satisfaction with the communication skills and humanistic qualities of the primary care physician. For ischemic heart disease (IHD), chronic obstructive pulmonary disease (COPD), and diabetes, patient ability to cope with their disease was more strongly associated with patient satisfaction than disease severity. Among IHD patients, improvement in ability to cope emotionally with their angina was associated with higher SOSQ organizational scores (standardized beta=0.18; P<.001) but self-reported physical limitation due to angina was not (beta=0.01; P=.65). Similarly, in COPD, improved ability to cope with dyspnea was associated with greater organizational scores (beta=0.11; P<.001) but physical function was not (beta=-0.03; P=.27). For diabetes, increased education was associated with improved organizational scores (beta=0.31; P<.001) but improvement in symptom burden was not (beta=0.03; P=.14). Similar results were seen with prediction of SOSQ humanistic scores. CONCLUSIONS: Patient education and ability to cope with chronic conditions are more strongly associated with satisfaction with their primary care provider than disease severity. Further improvements in patient education and self-management may lead to improved satisfaction and quality of care.

Provider response to computer-based care suggestions for chronic heart failure.

OBJECTIVES: We sought to assess the responses of providers to recommendations generated by a computer-management system for chronic heart failure (CHF). METHODS: This study is an analysis of primary care providers' responses to evidence-based computer-generated suggestions regarding patients with CHF at one center of a randomized trial. The trial randomized primary care providers from 2 VA Medical Centers to receive care suggestions regarding patients with CHF, with or without inclusion of patient symptom data obtained from pre-visit questionnaires. At one center, providers were asked to respond to the suggestions with hand-written comments and a numerical agreement scale. RESULTS: Providers responded to 774 care suggestions (62% of the 1246 delivered). They agreed with 41%, had major disagreements with 12%, and had minor disagreements with 22%. For 7% of the care suggestions, providers asked to not see it again for that patient. The most common reasons for major or minor disagreements were a belief that the suggestion was wrong or unnecessary (45%) or would not be tolerated by the patient (32%). External barriers to implementation of guidelines, lack of guideline awareness, or disagreement with guidelines were uncommon reasons cited by providers in this study. CONCLUSIONS: Providers agreed with less than half of computer-generated care suggestions from evidence-based CHF guidelines, most often because the suggestions were felt to be inapplicable to their patients or unlikely to be tolerated.