Special Article
Outcome of Myocardial Infarction in Veterans Health Administration Patients as Compared with Medicare Patients
N Engl J Med 2000; 343:1934-1941December 28, 2000
- Abstract
Background
Some have the opinion that patients cared for in Veterans Health Administration (VHA) hospitals receive care of poorer quality than those cared for in non-VHA institutions. To assess the quality of care in VHA hospitals, we compared the outcome of acute myocardial infarction among patients in VHA and non-VHA institutions while controlling for potential confounders, including coexisting conditions and severity of illness.
Methods
We studied 2486 veterans discharged from 81 VHA hospitals and 29,249 Medicare patients discharged from 1530 non-VHA hospitals, restricting our samples to men at least 65 years of age who were discharged with confirmed acute myocardial infarction. We compared coexisting conditions, severity of illness, and 30-day and 1-year mortality in the two samples.
Results
VHA patients were significantly more likely than Medicare patients to have a recorded history of hypertension (64.3 percent vs. 57.3 percent), chronic obstructive pulmonary disease or asthma (30.9 percent vs. 23.5 percent), diabetes (34.8 percent vs. 29.0 percent), stroke (20.4 percent vs. 14.2 percent), or dementia (7.2 percent vs. 4.8 percent) (P<0.001 for all comparisons). According to both multivariate logistic regression and an analysis using 2265 matched pairs of VHA and Medicare patients, there were no significant differences in 30-day or 1-year mortality. The matched-pairs analysis found that the difference in mortality at 30 days (the mortality rate among Medicare patients minus the mortality rate among VHA patients), averaged over the 5-year age groups, was –0.8 percent (95 percent confidence interval, –2.8 to 1.3), and the difference in mortality at 1 year was –1.3 percent (95 percent confidence interval, –3.9 to 1.3).
Conclusions
VHA patients had more coexisting conditions than Medicare patients. Nevertheless, we found no significant difference in mortality between VHA and Medicare patients, a result that suggests a similar quality of care for acute myocardial infarction.
Media in This Article
Table 1
Sociodemographic Features of Medicare and Veterans Health Administration (VHA) Patients Admitted for Acute Myocardial Infarction and Characteristics of the Admitting Hospitals.Table 2
Clinical Characteristics of Medicare and Veterans Health Administration (VHA) Patients Admitted for Acute Myocardial Infarction.Article Activity
- Article
In the United States, eligible veterans 65 years of age or older may receive health care funded either by the Veterans Health Administration (VHA) or by the Health Care Financing Administration (HCFA) under Medicare. The VHA is the largest integrated health care system in the United States, with a medical care budget of $17.9 billion in fiscal year 1998.1 It is characterized by a Congressional appropriation of a fixed amount of money (a global budget) and salaried physicians. Of the approximately 26 million veterans, more than 3.4 million used the VHA health care system in fiscal year 1998. Access to VHA services is determined by disability associated with military service or by economic disadvantage.
In contrast to health care provided by the VHA, Medicare coverage for the majority of its 39 million beneficiaries consists of indemnity insurance combined with fee-for-service payments to physicians.2 A patient 65 years of age or older becomes eligible by having worked for at least 10 years in Medicare-covered employment, and a younger patient becomes eligible because of disability (including end-stage renal disease).
Some have the opinion that patients cared for in VHA institutions receive care of poorer quality than those cared for in non-VHA institutions.3 However, valid comparisons between VHA and non-VHA care are difficult to carry out, since VHA patients may have more coexisting conditions and greater severity of illness than patients in non-VHA institutions,4,5 confounding comparisons of outcome as a measure of quality of care. Comparisons between VHA and non-VHA care may also be confounded by differences in the patients' age, sex, and socioeconomic status6 and by unmeasured differences in patients' preferences for site of care. Differences among hospitals in the availability of services and in teaching status may also affect the validity of comparisons.
Given these problems with comparisons, there are few published data to address the relative quality of VHA and non-VHA health care. We are aware of only two studies, conducted at a single VHA hospital, that used clinical data to compare the outcome of care in VHA and non-VHA institutions.5,7 Our goal was to compare the coexisting conditions, severity of illness, and outcome of acute myocardial infarction in VHA and non-VHA hospitals using nationally representative clinical data. We assessed outcome (as defined by Donabedian8) to measure quality. Our first hypothesis was that VHA patients had a greater burden of illness at the time of admission with acute myocardial infarction. Our second hypothesis was that after adjustment for patients' characteristics, mortality rates would be higher among VHA patients than among Medicare patients, reflecting poorer quality of care.
Methods
We created two cohorts retrospectively: one consisted of all fee-for-service Medicare beneficiaries discharged with a diagnosis of acute myocardial infarction from acute care hospitals located in seven states, and the other consisted of a national sample of veterans discharged with a diagnosis of acute myocardial infarction from nonpsychiatric VHA facilities.
Medicare Sample
The Medicare sample was obtained through the Cooperative Cardiovascular Project, which was undertaken by HCFA to improve the quality of care for Medicare patients with acute myocardial infarction.9 As part of the Cooperative Cardiovascular Project, HCFA studied all patients discharged with a principal diagnosis of acute myocardial infarction (code 410 of the International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM],10 excluding a fifth digit of 2, which would indicate acute myocardial infarction in the preceding eight weeks) from all nonfederal acute care hospitals in each state during a specified eight-month period between January 1, 1994, and June 30, 1995. Our cohort is a subgroup of the larger HCFA study, including all patients in the Cooperative Cardiovascular Project who were discharged from hospitals in California, Florida, Massachusetts, New York, Ohio, Pennsylvania, and Texas. These states were selected because they were known to differ in the frequency of use of cardiac procedures, are large and geographically diverse, and served as the basis of a study examining the appropriateness of care after acute myocardial infarction.11,12 Eliminating women, we initially identified 41,754 male Medicare beneficiaries who were 65 years of age or older.
We excluded 12,505 patients from the study. The numbers of excluded patients and the reasons for their exclusion were as follows (some patients met more than one of the exclusion criteria): 4498 patients did not meet the clinical criteria for acute myocardial infarction9 (creatine kinase MB fraction above 0.05; lactate dehydrogenase level exceeding 1.5 times the upper limit of normal, with isoenzyme 1 level higher than isoenzyme 2 level; or the presence of two of the following three conditions: chest pain, a doubling of the creatine kinase level, or detection of a new acute myocardial infarction on an electrocardiogram); 6576 patients were discharged from the hospital to which they were transferred without a diagnosis of ICD-9-CM code 410; 423 patients were discharged alive after a length of stay of less than three days; data were incomplete for 1969 patients who resided outside the United States, whose medical records were unavailable, or who were transferred more than once; 3196 patients were enrolled in a health maintenance organization at the time of the index event, and we could not ascertain the details of their subsequent care; 641 patients were admitted or discharged outside the study period; 187 patients were transferred to hospitals out of the seven study states; 10 patients were hospitalized for more than 180 days; and an incorrect date of death was recorded for 10 patients (e.g., a date of death before admission). After these exclusions, there remained 29,249 male Medicare patients who were at least 65 years of age and who had been discharged from 1530 non-VHA hospitals.
VHA Sample
Since there are many fewer VHA hospitals than non-VHA hospitals in the seven sampled states, we used a national VHA sample. We used the Patient Treatment File, a national centralized data base that records all use of VHA facilities, to identify all male patients with a primary diagnosis of acute myocardial infarction (ICD-9-CM code 410) who were discharged between January 1, 1994, and September 30, 1995. Only patients discharged from nonpsychiatric VHA facilities with a length of stay of at least three days (if discharged alive) and without a fifth digit ICD-9-CM code of 2 were included.13 We initially identified 13,310 VHA patients.
We sampled patients stratified according to the capability of the hospital cardiac service.14-16 Each of the 139 VHA hospitals was classified as one of four types. Noncatheterization hospitals do not perform on-site catheterization, percutaneous transluminal coronary angioplasty, or coronary-artery bypass grafting. The hospitals in the lowest quartile of admissions for acute myocardial infarction were defined as having a low volume, and all other hospitals were defined as having a high volume. Cardiac-catheterization-only hospitals perform on-site catheterization but not revascularization. Cardiac-surgery hospitals perform all the cardiac procedures named above. Within each type of hospital, we randomly included up to 100 patients, generating a stratified national random sample of 5503 patients from 81 VHA hospitals. We reviewed the records of 5193 (94.4 percent) of these patients.
We excluded 2707 patients for one or more reasons: 433 who did not meet the clinical criteria for acute myocardial infarction,9 2029 who were less than 65 years of age, 181 who were discharged to an acute care non-VHA facility, and 64 for whom information was incomplete (missing discharge date or date of birth). After these exclusions, there remained 2486 male veterans who were at least 65 years of age and who had been discharged from 81 VHA hospitals.
Data Sources
We used the Cooperative Cardiovascular Project17 structured review instrument to obtain medical-records data for Medicare patients. The records of transfer patients were linked with the initial admitting hospital. The data were abstracted at two abstraction centers under contract with HCFA.9,18 The overall agreement between abstracters averaged 95 percent.9 Mortality was determined from the Health Insurance Master File. The HCFA Provider of Service File and the American Hospital Association data bases were linked to our sample to obtain structural characteristics of the hospitals, such as availability of cardiac services, teaching affiliation, and number of beds.
Medical-records data for the VHA patients were abstracted by trained nurses using the Cooperative Cardiovascular Project interactive software.19 Overall agreement between abstracters with respect to key variables was 96 percent. Mortality was determined from the inpatient discharge status in the Patient Treatment File as well as from the Veterans Affairs Beneficiary Identification and Record Location Subsystem (BIRLS).20,21 We obtained the characteristics of the VHA hospitals from the American Hospital Association data base, the Department of Veterans Affairs Cardiac Services Directory, and the 1995 version of the Federal Practitioner. For both samples, a hospital was considered to have a university teaching affiliation if it had at least one intern or resident in an accredited allopathic or osteopathic residency training program according to the American Hospital Association data base.
Statistical Analysis
Differences in Coexisting Conditions and Severity of Acute Myocardial Infarction
We calculated the frequency of coexisting conditions and measures of the severity of acute myocardial infarction in both samples.22 Chi-square tests were used to examine differences between the two groups in discrete variables, and t-tests were used to examine differences in continuous variables. For continuous variables, means ±SD were calculated. When appropriate, we also calculated the frequency with which a variable was missing or a test was not performed. We adjusted for multiple comparisons using a Bonferroni adjustment, so that the overall level of significance was 0.05 within each class of comparisons.
Differences in Mortality
In addition to calculating crude 30-day and 1-year rates of mortality from all causes, we estimated differences in mortality by two adjustment methods. First, we calculated the risk-adjusted odds of mortality for Medicare patients relative to VHA patients using logistic regression, the standard method of controlling simultaneously for observed covariates.23 We included in the model sociodemographic features, coexisting conditions, severity of acute myocardial infarction, hospital characteristics (availability of cardiac services and presence or absence of university teaching affiliation), and other admission characteristics known to affect mortality, as well as a binary variable indicating to which cohort (Medicare or VHA) the patient belonged.22
Second, because we might not have accounted for all confounders appropriately, we created a matched sample using a propensity-score approach to compare the survival of VHA and Medicare patients.24 This technique balances patients from each cohort on the basis of observed characteristics to replicate a randomized, controlled trial. To create the propensity scores, we created a logistic-regression model in which the response was the log of the odds of belonging to the VHA cohort. Characteristics of the patient (sociodemographic features, coexisting conditions, and severity of acute myocardial infarction) and the hospital (availability of cardiac services and presence or absence of university affiliation) were included in the model. Once the model was fitted, we stratified the sample according to the cardiac services available in the hospital (noncatheterization services, catheterization only, or cardiac surgery) and five-year age group. Within each of these strata, we matched each VHA patient to the Medicare patient with the closest estimated propensity score. We included in our analyses only the matches that were within 0.60 of the pooled standard error of the estimated propensity score.25 If no match was found, the VHA patient was excluded from the analyses. To measure how well we balanced the two cohorts in terms of observed covariates, we calculated how far apart the two cohorts were in terms of each observed covariate. To achieve this, we measured the average difference in each covariate, expressed as a percentage of the pooled standard deviation of the covariate, before and after matching. For example, if the fraction of VHA patients who were black minus the fraction of Medicare patients who were black, as measured by the percentage of the pooled standard deviation, was 20 percent, the means of the two samples were considered to differ by 2/10 of a standard deviation. Differences larger than 10 percent indicate that the two samples were far apart in terms of the distribution of the covariate and therefore might not be appropriately balanced.26
Using the matched pairs, we then estimated differences in 30-day and 1-year mortality. Paired differences (and their corresponding standard errors) were calculated within each five-year age group and then within each hospital type. We estimated the overall average difference by combining the paired differences among the five-year age groups using precision weights27,28 and constructed a 95 percent confidence interval for the overall average difference. We repeated this across the hospital strata, calculating the precision-weighted average difference in mortality across the three types of hospitals.
Results
Characteristics of the Patients and the Hospitals
Table 1Table 1
Sociodemographic Features of Medicare and Veterans Health Administration (VHA) Patients Admitted for Acute Myocardial Infarction and Characteristics of the Admitting Hospitals. shows the sociodemographic features of the patients and the characteristics of the hospitals. VHA patients were younger, were less likely to be white, and had a longer inpatient stay than Medicare patients. Almost half the VHA patients were initially admitted to a noncatheterization hospital, whereas half the Medicare patients were initially admitted to a cardiac-surgery hospital. More VHA patients than Medicare patients were initially admitted to a university-affiliated hospital.Coexisting Conditions and Severity of Acute Myocardial Infarction
Table 2Table 2
Clinical Characteristics of Medicare and Veterans Health Administration (VHA) Patients Admitted for Acute Myocardial Infarction. shows the clinical characteristics of the patients. VHA patients were significantly more likely than Medicare patients to have a history of various coexisting conditions, such as hypertension, chronic obstructive pulmonary disease or asthma, diabetes, stroke, and dementia.Table 3Table 3
Severity of Coronary Artery Disease and Results of Laboratory Tests at Admission of Medicare and Veterans Health Administration (VHA) Patients for Acute Myocardial Infarction. shows the severity of coronary artery disease on admission. On presentation with acute myocardial infarction, VHA patients were more likely to have ST elevation on the electrocardiogram, but there was no significant difference between the two groups in the number of patients who presented with cardiac arrest, shock, congestive heart failure or pulmonary edema, or tachycardia.Mortality
The unadjusted 30-day mortality rates for VHA and Medicare patients were 17.3 percent and 18.1 percent, respectively (P=0.30) (Table 4Table 4
Logistic-Regression Analysis of Mortality among Medicare Patients as Compared with Veterans Health Administration (VHA) Patients 30 Days and 1 Year after Acute Myocardial Infarction.). At one year, the unadjusted mortality rates were also nearly indistinguishable in the two cohorts: 31.5 percent for VHA patients and 31.8 percent for Medicare patients (P=0.77).Risk-Adjusted Differences in Mortality
Table 4 shows the odds ratios and 95 percent confidence intervals for each covariate used in the logistic model. The estimated odds of 30-day mortality for Medicare patients as compared with VHA patients were 0.94 (95 percent confidence interval, 0.82 to 1.07; receiver-operating-characteristic curve, 0.800). The corresponding estimate at one year was 0.94 (95 percent confidence interval, 0.84 to 1.05; receiver-operating-characteristic curve, 0.799).
Matched Analysis
Using a model with 29 covariates to predict VHA use, we were able to obtain an accuracy of 88 percent (receiver-operating-characteristic curve, 0.88) and to match 2265 (91.1 percent) of the VHA patients to Medicare patients. Before matching, 16 of the 29 covariates had a standardized difference larger than 10 percent, whereas after matching, all standardized differences were less than 5 percent.
Using the matched sample, we observed no statistically significant difference in 30-day or 1-year mortality between Medicare and VHA patients. The difference in mortality at 30 days (mortality among Medicare patients minus mortality among VHA patients) averaged over the 5-year age groups was –0.8 percent (95 percent confidence interval, –2.8 to 1.3), and the difference in mortality at 1 year was –1.3 percent (95 percent confidence interval, –3.9 to 1.3). After averaging among types of hospital, similar results were observed: –0.8 percent for 30-day mortality (95 percent confidence interval, –2.9 to 1.3) and –0.9 percent for 1-year mortality (95 percent confidence interval, –3.6 to 1.7).
Our findings with regard to mortality were not consistent with our prior hypotheses. To try to explain our findings, and because survival is improved by the use of a number of medications after acute myocardial infarction,29 we calculated the crude rates of use of thrombolytic agents at the time of arrival at the hospital and of use of beta-blockers, angiotensin-converting–enzyme inhibitors, aspirin, or combinations of these drugs at the time of discharge. A similar percentage of VHA and Medicare patients underwent thrombolysis at the time of arrival (15.8 percent vs. 16.9 percent, P=0.16). Of the patients who survived to discharge, more VHA patients than Medicare patients were receiving beta-blockers (49.7 percent vs. 41.6 percent, P<0.001), angiotensin-converting–enzyme inhibitors (44.6 percent vs. 32.5 percent, P<0.001), or aspirin (77.2 percent vs. 68.6 percent, P<0.001) at discharge.
Discussion
We conducted a national study using clinical data to compare the coexisting conditions, severity of acute myocardial infarction, and outcome in patients cared for in VHA hospitals and patients cared for under fee-for-service Medicare financing. To minimize potential confounding, we collected comparable data from a uniform clinical cohort, restricted our samples to men 65 years or age or more, and matched the cohorts according to patient and hospital characteristics to carry out risk-adjusted comparisons of mortality.
We found that among elderly men with acute myocardial infarction, those treated at VHA hospitals are more likely to have coexisting conditions, such as chronic obstructive pulmonary disease or asthma, diabetes, hypertension, stroke, and dementia, than those cared for under Medicare financing. Given these base-line differences, the ideal way to answer our question of whether the quality of care is poorer in VHA hospitals would be to randomly assign patients with acute myocardial infarction to either fee-for-service Medicare or VHA care and then to examine their long-term outcome. Given that we could not perform this experiment, we used a propensity-score approach to replicate randomization within our observational data set. Using this technique to match patients on the basis of their propensity to use VHA services, we compared survival among those who were treated within the VHA system and those who were not, within each type of hospital and five-year age group. After this matching technique had been applied, there were no significant differences between the two groups of patients in 30-day or 1-year mortality.
Our findings with regard to mortality were not consistent with our prior hypotheses. The use of thrombolytic agents was similar in both groups, but more VHA patients than Medicare patients were receiving beta-blockers, angiotensin-converting–enzyme inhibitors, or aspirin at discharge. We postulate that the similar outcomes with regard to mortality are at least partly accounted for by the higher rates of use of medications that are known to decrease mortality in the VHA cohort. Of course, none of these unadjusted rates of use account for important differences among patients (in, for example, age or coexisting conditions), hospitals, or indications for or contraindications to treatment. Thus, process of care, as defined by Donabedian,8 in VHA hospitals may be better (or worse), but our data do not allow us to judge that dimension of the quality of health care.
To assess whether our exclusions from the VHA cohort might have biased our mortality findings in favor of the VHA, we determined the one-year mortality rate for the patients who were discharged to an acute care hospital from a VHA facility and were excluded from our sample. Among these 181 patients, one-year mortality was 30 percent, suggesting that the transfer of sicker patients out of VHA hospitals did not explain our findings. Since only 8.9 percent of our patients were transferred from another VHA hospital, it is unlikely that our mortality findings could be accounted for by transfer into VHA hospitals of patients who received care elsewhere. Because there is little variation in the population-based rates of hospitalization for acute myocardial infarction in most areas30 and little disagreement about the appropriateness of hospitalization for this condition, it is unlikely that differences in the threshold for admission for VHA and Medicare patients confounded our findings. Furthermore, the findings in Table 3 do not support the view that VHA hospitals selectively admit patients with less severe disease.
Our findings with regard to mortality are consistent with those of a previous single-institution study that used clinical data to compare outcomes of VHA patients and those treated by the private sector,7 although the authors of that study noted that their power to demonstrate even a 50 percent difference in mortality was only 55 percent. Other comparative studies have used administrative data and either have reported unadjusted mortality rates31 or have not been able to account for a number of possible confounders of their results.32,33
From data-base studies of patients who use both VHA and Medicare services, we know that most users of VHA services are initially hospitalized for acute myocardial infarction under Medicare financing.34 This is because ambulances that are called to assist patients with cardiac symptoms may be required to take them to the nearest emergency department, which may not be a VHA facility. Thus, the findings of this study cannot be generalized to all veterans with acute myocardial infarction, but only to veterans who are cared for in VHA hospitals for this condition.
There are many methodologic challenges to be overcome in carrying out comparisons between different systems of health care, but given the size, scope, and budget of the VHA health care system, the lack of such comparative data is surprising. We have demonstrated that patients cared for in VHA hospitals have a greater burden of illness than patients cared for under Medicare financing. With extensive risk adjustment, we have found no differences in mortality between VHA patients and fee-for-service Medicare patients, suggesting that VHA patients receive care of similar quality for acute myocardial infarction.
Supported by grants from the Department of Veterans Affairs Health Services Research and Development Service (IIR 94-054), the Department of Veterans Affairs Cooperative Studies Program (EPC 97-069), and the Agency for Healthcare Quality and Research (R01-HS08071). Dr. Petersen has received a Research Career Development Award (RCD 95-306) from the Veterans Affairs Health Services Research and Development Service.
The views expressed in this article are solely those of the authors and do not necessarily represent those of the Department of Veterans Affairs.
We are indebted to Margaret Volya, M.Sc., Harvard Medical School, and Caterina Brown, Boston Veterans Affairs Health Care System, for expert SAS programming and data management; and to George E. Thibault, M.D., for advice and support.
Source Information
From the Houston Center for Quality of Care and Utilization Studies, Houston Veterans Affairs Medical Center, and the Section for Health Services Research, Department of Medicine, Baylor College of Medicine, Houston (L.A.P.); the Department of Health Care Policy, Harvard Medical School, Boston (S.-L.T.N., B.J.M.); the Institute for Health Policy, Partners Health Care System, and the Department of Medicine, Massachusetts General Hospital, Boston (J.D.); the Department of Biostatistics, Harvard School of Public Health, Boston (S.-L.T.N.); and the Department of Radiology, Brigham and Women's Hospital, Boston (B.J.M.).
Address reprint requests to Dr. Petersen at Health Services Research and Development (152) (T110), Houston Veterans Affairs Medical Center, 2002 Holcombe Blvd., Houston, TX 77030.
- References
References
1
Iglehart JK . Reform of the Veterans Affairs health care system. N Engl J Med 1996;335:1407-1411
Full Text | Web of Science | Medline2
Iglehart JK . The American health care system: Medicare. N Engl J Med 1999;340:327-332
Full Text | Web of Science | Medline3
Quality of care in the Veterans Affairs health care system: hearing before the Committee on Veterans' Affairs, United States Senate, one hundred fifth Congress, second session: September 22, 1998. Washington, D.C.: Government Printing Office, 1999:62.
4
Kazis LE ,Miller DR ,Clark J , et al. Health-related quality of life in patients served by the Department of Veterans Affairs: results from the Veterans Health Study. Arch Intern Med 1998;158:626-632
CrossRef | Web of Science | Medline5
Gordon HS ,Aron DC ,Fuehrer SM ,Rosenthal GE . Using severity-adjusted mortality to compare performance in a Veterans Affairs (VA) hospital and in private sector hospitals. Am J Med Qual 2000;15:207-211
CrossRef | Web of Science | Medline6
Peabody JW ,Luck J . How far down the managed care road? A comparison of primary care outpatient services in a Veterans Affairs medical center and a capitated multispecialty group practice. Arch Intern Med 1998;158:2291-2299
CrossRef | Web of Science | Medline7
Rosenthal GE ,Larimer DJ ,Owens KE . Treatment of patients with acute myocardial infarction at a Veterans Affairs (VA) hospital and a non-VA hospital. J Gen Intern Med 1994;9:455-458
CrossRef | Web of Science | Medline8
Donabedian A. Explorations in quality assessment and monitoring. Vol. 1. The definition of quality and approaches to its assessment. Ann Arbor, Mich.: Health Administration Press, 1980.
9
Marciniak TA ,Ellerbeck EF ,Radford MJ , et al. Improving the quality of care for Medicare patients with acute myocardial infarction: results from the Cooperative Cardiovascular Project. JAMA 1998;279:1351-1357
CrossRef | Web of Science | Medline10
Public Health Service, Health Care Financing Administration. International classification of diseases, 9th rev., clinical modification: ICD-9-CM. 4th ed. Washington, D.C.: Government Printing Office, 1980. (DHHS publication no. (PHS) 80-1260.)
11
Ayanian JZ ,Landrum MB ,Normand S-LT ,Guadagnoli E ,McNeil BJ . Rating the appropriateness of coronary angiography -- do practicing physicians agree with an expert panel and with each other? N Engl J Med 1998;338:1896-1904
Full Text | Web of Science | Medline12
Landrum MB ,Normand SL . Applying Bayesian ideas to the development of medical guidelines. Stat Med 1999;18:117-137
CrossRef | Web of Science | Medline13
Petersen LA ,Wright SM ,Normand SLT ,Daley J . Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database. J Gen Intern Med 1999;14:555-558
CrossRef | Web of Science | Medline14
Wright SM ,Daley J ,Peterson ED ,Thibault GE . Outcomes of acute myocardial infarction in the Department of Veterans Affairs: does regionalization of health care work? Med Care 1997;35:128-141
CrossRef | Web of Science | Medline15
Every NR ,Larson EB ,Litwin PE , et al. The association between on-site cardiac catheterization facilities and the use of coronary angiography after acute myocardial infarction. N Engl J Med 1993;329:546-551
Full Text | Web of Science | Medline16
Blustein J . High-technology cardiac procedures: the impact of service availability on service use in New York State. JAMA 1993;270:344-349
CrossRef | Web of Science | Medline17
Jencks SF . HCFA's Health Care Quality Improvement Program and the Cooperative Cardiovascular Project. Ann Thorac Surg 1994;58:1858-1862
CrossRef | Web of Science | Medline18
Krumholz HM ,Radford MJ ,Wang Y ,Chen J ,Heiat A ,Marciniak T . National use and effectiveness of beta-blockers for the treatment of elderly patients after acute myocardial infarction: National Cooperative Cardiovascular Project. JAMA 1998;280:623-629[Erratum, JAMA 1999;281:37.]
CrossRef | Web of Science | Medline19
Ellerbeck EF ,Jencks SF ,Radford MJ , et al. Quality of care for Medicare patients wih acute myocardial infarction: a four-state pilot study from the Cooperative Cardiovascular Project. JAMA 1995;273:1509-1514
CrossRef | Web of Science | Medline20
Fleming C ,Fisher ES ,Chang CH ,Bubolz TA ,Malenka DJ . Studying outcomes and hospital utilization in the elderly: the advantages of a merged data base for Medicare and Veterans Affairs hospitals. Med Care 1992;30:377-391
CrossRef | Web of Science | Medline21
Fisher SG ,Weber L ,Goldberg J ,Davis F . Mortality ascertainment in the veteran population: alternatives to the National Death Index. Am J Epidemiol 1995;141:242-250
Web of Science | Medline22
Normand SLT ,Glickman ME ,Sharma RGVRK ,McNeil BJ . Using admission characteristics to predict short-term mortality from myocardial infarction in elderly patients: results from the Cooperative Cardiovascular Project. JAMA 1996;275:1322-1328
CrossRef | Web of Science | Medline23
Iezzoni LI, ed. Risk adjustment for measuring healthcare outcomes. 2nd ed. Chicago: Health Administration Press, 1997.
24
Rosenbaum PR ,Rubin DB . The central role of the propensity score in observational studies for causal effects. Biometrika 1983;70:41-55
CrossRef | Web of Science25
Rosenbaum PR ,Rubin DB . Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat 1985;39:33-38
CrossRef | Web of Science26
Cohen J. Statistical power analysis for the behavioral sciences. Rev. ed. Orlando, Fla.: Academic Press, 1977.
27
DerSimonian R ,Laird N . Meta-analysis in clinical trials. Control Clin Trials 1986;7:177-188
CrossRef | Medline28
Rosenbaum PR ,Rubin DB . Reducing bias in observational studies using subclassification on the propensity score. J Am Stat Assoc 1984;79:516-524
CrossRef | Web of Science29
Chassin MR . Assessing strategies for quality improvement. Health Aff (Millwood) 1997;16:151-161
CrossRef | Web of Science | Medline30
Chassin MR ,Brook RH ,Park RE , et al. Variations in the use of medical and surgical services by the Medicare population. N Engl J Med 1986;314:285-290
Full Text | Web of Science | Medline31
Kress DC ,Kroncke GM ,Chopra PS , et al. Comparison of survival in cardiac surgery at a Veterans Administration hospital and its affiliated university hospital. Arch Surg 1988;123:439-443
Web of Science | Medline32
Stremple JF ,Bross DS ,Davis CL ,McDonald GO . Comparison of postoperative mortality in VA and private hospitals. Ann Surg 1993;217:277-285
CrossRef | Web of Science | Medline33
Ritchie JL ,Maynard C ,Chapko MK ,Every NR ,Martin DC . A comparison of percutaneous transluminal coronary angioplasty in the Department of Veterans Affairs and in the private sector in the state of Washington. Am J Cardiol 1998;81:1094-1099
CrossRef | Web of Science | Medline34
Wright SM ,Petersen LA ,Lamkin RP ,Daley J . Increasing use of Medicare services by veterans with acute myocardial infarction. Med Care 1999;37:529-537
CrossRef | Web of Science | Medline
- Citing Articles (58)
Citing Articles
1
Amal N. Trivedi, Sierra Matula, Isomi Miake-Lye, Peter A. Glassman, Paul Shekelle, Steven Asch. (2011) Systematic Review. Medical Care 49:1, 76-88
CrossRef2
Thad E. Abrams, Mary Vaughan-Sarrazin, Peter J. Kaboli. (2010) Mortality and Revascularization Following Admission for Acute Myocardial Infarction: Implication for Rural Veterans. The Journal of Rural Health 26:4, 310-317
CrossRef3
Nancy L. Keating, Mary Beth Landrum, Elizabeth B. Lamont, Craig C. Earle, Samuel R. Bozeman, Barbara J. McNeil. (2010) End-of-life care for older cancer patients in the Veterans Health Administration versus the private sector. Cancer 116:15, 3732-3739
CrossRef4
Alfredo J. Selim, Dan Berlowitz, Lewis E. Kazis, William Rogers, Steven M. Wright, Shirley X. Qian, James A. Rothendler, Avron Spiro III, Donald Miller, Bernardo J. Selim, Benjamin G. Fincke. (2010) Comparison of Health Outcomes for Male Seniors in the Veterans Health Administration and Medicare Advantage Plans. Health Services Research 45:2, 376-396
CrossRef5
Ruth L. Bush, Ralph G. DePalma, Kamal M.F. Itani, William G. Henderson, Tracy S. Smith, William P. Gunnar. (2009) Outcomes of care of abdominal aortic aneurysm in Veterans Health Administration facilities: results from the National Surgical Quality Improvement Program. The American Journal of Surgery 198:5, S41-S48
CrossRef6
Justin C. Choi, Faisal G. Bakaeen, Joseph Huh, Tam K. Dao, Scott A. LeMaire, Joseph S. Coselli, Danny Chu. (2009) Outcomes of Coronary Surgery at a Veterans Affairs Hospital Versus Other Hospitals. Journal of Surgical Research 156:1, 150-154
CrossRef7
Masoor Kamalesh, Jianzhao Shen. (2009) Diabetes and Peripheral Arterial Disease in Men: Trends in Prevalence, Mortality, and Effect of Concomitant Coronary Disease. Clinical Cardiology 32:8, 442-446
CrossRef8
Kenneth W. Kizer, R. Adams Dudley. (2009) Extreme Makeover: Transformation of the Veterans Health Care System. Annual Review of Public Health 30:1, 313-339
CrossRef9
Ryan Edwards. (2008) Widening health inequalities among U.S. military retirees since 1974. Social Science & Medicine 67:11, 1657-1668
CrossRef10
Masoor Kamalesh, Usha Subramanian, Anahita Ariana, George J. Eckert, Stephen Sawada. (2008) Paradoxical lower postmyocardial infarction mortality among veteran women – does a sex bias exist in the Veterans Affairs medical system?. Canadian Journal of Cardiology 24:9, 691-695
CrossRef11
Ruth L. Bush, Michael A. Kallen, Debra R. Liles, Jeffrey T. Bates, Laura A. Petersen. (2008) Knowledge and Awareness of Peripheral Vascular Disease Are Poor Among Women at Risk for Cardiovascular Disease. Journal of Surgical Research 145:2, 313-319
CrossRef12
Edwin P. Martens, Anthonius de Boer, Wiebe R. Pestman, Svetlana V. Belitser, Bruno H. Ch. Stricker, Olaf H. Klungel. (2008) Comparing treatment effects after adjustment with multivariable Cox proportional hazards regression and propensity score methods. Pharmacoepidemiology and Drug Safety 17:1, 1-8
CrossRef13
Paul R. Rosenbaum. 2007. Propensity Score. .
CrossRef14
S. Keyhani, J. S. Ross, P. Hebert, C. Dellenbaugh, J. D. Penrod, A. L. Siu. (2007) Use of Preventive Care by Elderly Male Veterans Receiving Care Through the Veterans Health Administration, Medicare Fee-for-Service, and Medicare HMO Plans. American Journal of Public Health 97:12, 2179-2185
CrossRef15
D. U. Himmelstein, K. E. Lasser, D. McCormick, D. H. Bor, J. W. Boyd, S. Woolhandler. (2007) Lack of Health Coverage Among US Veterans From 1987 to 2004. American Journal of Public Health 97:12, 2199-2203
CrossRef16
Mary S. Vaughan-Sarrazin, Bonnie Wakefield, Gary E. Rosenthal. (2007) Mortality of Department of Veterans Affairs Patients Undergoing Coronary Revascularization in Private Sector Hospitals. Health Services Research 42:5, 1802-1821
CrossRef17
Alfredo J. Selim, Lewis E. Kazis, William Rogers, Shirley X. Qian, James A. Rothendler, Avron Spiro, Xinhua S. Ren, Donald Miller, Bernardo J. Selim, Benjamin G. Fincke. (2007) Change in health status and mortality as indicators of outcomes: comparison between the Medicare Advantage Program and the Veterans Health Administration. Quality of Life Research 16:7, 1179-1191
CrossRef18
Robert G. Johnson, Catherine M. Wittgen, Matthew M. Hutter, William G. Henderson, Cecilia Mosca, Shukri F. Khuri. (2007) Comparison of Risk-Adjusted 30-Day Postoperative Mortality and Morbidity in Department of Veterans Affairs Hospitals and Selected University Medical Centers: Vascular Surgical Operations in Women. Journal of the American College of Surgeons 204:6, 1137-1146
CrossRef19
Margaret M. Byrne, Kenneth Pietz, LeChauncy Woodard, Laura A. Petersen. (2007) Health care funding levels and patient outcomes: a national study. Health Economics 16:4, 385-393
CrossRef20
Ruth L. Bush, Michael L. Johnson, Nasim Hedayati, William G. Henderson, Peter H. Lin, Alan B. Lumsden. (2007) Performance of endovascular aortic aneurysm repair in high-risk patients: Results from the Veterans Affairs National Surgical Quality Improvement Program. Journal of Vascular Surgery 45:2, 227-235.e1
CrossRef21
Jennifer Hill, Jerome P. Reiter. (2006) Interval estimation for treatment effects using propensity score matching. Statistics in Medicine 25:13, 2230-2256
CrossRef22
Til Stürmer, Manisha Joshi, Robert J. Glynn, Jerry Avorn, Kenneth J. Rothman, Sebastian Schneeweiss. (2006) A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. Journal of Clinical Epidemiology 59:5, 437.e1-437.e24
CrossRef23
Ruth L. Bush, Michael L. Johnson, Tracie C. Collins, William G. Henderson, Shukri F. Khuri, Hong-Jen Yu, Peter H. Lin, Alan B. Lumsden, Carol M. Ashton. (2006) Open Versus Endovascular Abdominal Aortic Aneurysm Repair in VA Hospitals. Journal of the American College of Surgeons 202:4, 577-587
CrossRef24
Alfredo J. Selim, Lewis E. Kazis, William Rogers, Shirley Qian, James A. Rothendler, Austin Lee, Xinhua S. Ren, Samuel C. Haffer, Russ Mardon, Donald Miller, Avron Spiro, Bernardo J. Selim, Benjamin G. Fincke. (2006) Risk-Adjusted Mortality as an Indicator of Outcomes. Medical Care 44:4, 359-365
CrossRef25
Mitchell J. Barnett, Gary Milavetz, Peter J. Kaboli. (2005) β-Blocker Therapy in Veterans with Asthma or Chronic Obstructive Pulmonary Disease. Pharmacotherapy 25:11, 1550-1559
CrossRef26
Jacqueline Goffaux, Gottlieb C. Friesinger, Warren Lambert, Laurie W. Shroyer, Thomas E. Moritz, Martin McCarthy, William G. Henderson, Karl E. Hammermeister. (2005) Biological Age—A Concept Whose Time Has Come: A Preliminary Study. Southern Medical Journal 98:10, 985-993
CrossRef27
Uptal D. Patel, Eric W. Young, Akinlolu O. Ojo, Rodney A. Hayward. (2005) CKD Progression and Mortality Among Older Patients With Diabetes. American Journal of Kidney Diseases 46:3, 406-414
CrossRef28
Masoor Kamalesh, Usha Subramanian, Anahita Ariana, Stephen Sawada, William Tierney. (2005) Similar Decline in Post-Myocardial Infarction Mortality among Subjects with and without Diabetes. The American Journal of the Medical Sciences 329:5, 228-233
CrossRef29
Monica Schaefer, Melissa DeLattre, Xin Gao, Jennifer Stephens, Marc Botteman, Anthony Morreale. (2005) Assessing the cost-effectiveness of COX-2 specific inhibitors for arthritis in the Veterans Health Administration. Current Medical Research and Opinion 21:1, 47-60
CrossRef30
Mary Beth Landrum, Edward Guadagnoli, Rose Zummo, David Chin, Barbara J. McNeil. (2004) Care following Acute Myocardial Infarction in the Veterans Administration Medical Centers: A Comparison with Medicare. Health Services Research 39:6p1, 1773-1792
CrossRef31
Paul A. Heidenreich. (2004) Commentary: Measuring the Quality of the VA Health Care System. Health Services Research 39:6p1, 1793-1798
CrossRef32
L. D. Woodard, N. R. Kressin, L. A. Petersen. (2004) Is Lipid-Lowering Therapy Underused by African Americans at High Risk of Coronary Heart Disease Within the VA Health Care System?. American Journal of Public Health 94:12, 2112-2117
CrossRef33
Frank A. Sloan, Justin G. Trogdon, Lesley H. Curtis, Kevin A. Schulman. (2004) The Effect of Dementia on Outcomes and Process of Care for Medicare Beneficiaries Admitted with Acute Myocardial Infarction. Journal of the American Geriatrics Society 52:2, 173-181
CrossRef34
Carlo Saitto, Carla Ancona, Danilo Fusco, Massimo Arcà, Carlo A. Perucci. (2004) Outcome of Patients With Cardiac Diseases Admitted to Coronary Care Units. Medical Care 42:2, 147-154
CrossRef35
Takahiro HOSHINO, Kazuo SHIGEMASU. (2004) Estimation of Causal Effect and Adjustment of Survey Data using Propensity Scores. Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 31:1, 43-61
CrossRef36
Frank A. Sloan, Justin G. Trogdon, Lesley H. Curtis, Kevin A. Schulman. (2003) Does the Ownership of the Admitting Hospital Make a Difference?. Medical Care 41:10, 1193-1205
CrossRef37
Daniela D’Ippoliti, Francesco Forastiere, Carla Ancona, Nera Agabiti, Danilo Fusco, Paola Michelozzi, Carlo A. Perucci. (2003) Air Pollution and Myocardial Infarction in Rome. Epidemiology 14:5, 528-535
CrossRef38
Gary E. Rosenthal, Peter J. Kaboli, Mitchell J. Barnett. (2003) Differences in Length of Stay in Veterans Health Administration and Other United States Hospitals. Medical Care 41:8, 882-894
CrossRef39
Gary E. Rosenthal, Mary Vaughan Sarrazin, Dwain L. Harper, Susan M. Fuehrer. (2003) Mortality and Length of Stay in a Veterans Administration Hospital and Private Sector Hospitals Serving a Common Market. Journal of General Internal Medicine 18:8, 601-608
CrossRef40
Gary Roselle, Marta L. Render, Linda B. Nugent, Gary N. Nugent. (2003) Estimating Private Sector Professional Fees for VA Providers. Medical Care 41:Supplement, II-23-II-32
CrossRef41
Gary Nugent, Ann Hendricks. (2003) Estimating Private Sector Values for VA Health Care: An Overview. Medical Care 41:Supplement, II-2-II-10
CrossRef42
Gary N. Nugent, Gary Roselle, Linda B. Nugent, Marta L. Render. (2003) Methods to Determine Private Sector Payment for VA Outpatient Services: Institutional Payments to Providers. Medical Care 41:Supplement, II-33-II-42
CrossRef43
Petersen, Laura A., Normand, Sharon-Lise T., Leape, Lucian L., McNeil, Barbara J., . (2003) Regionalization and the Underuse of Angiography in the Veterans Affairs Health Care System as Compared with a Fee-for-Service System. New England Journal of Medicine 348:22, 2209-2217
Full Text44
Saif S. Rathore, Yongfei Wang, Martha J. Radford, Diana L. Ordin, Harlan M. Krumholz. (2003) Quality of Care of Medicare Beneficiaries with Acute Myocardial Infarction: Who Is Included in Quality Improvement Measurement?. Journal of the American Geriatrics Society 51:4, 466-475
CrossRef45
Gary E. Rosenthal, Mary Vaughan Sarrazin, Edward L. Hannan. (2003) In-Hospital Mortality Following Coronary Artery Bypass Graft Surgery in Veterans Health Administration and Private Sector Hospitals. Medical Care 41:4, 522-535
CrossRef46
Laura A. Petersen, Sharon-Lise T. Normand, Benjamin G. Druss, Robert A. Rosenheck. (2003) Process of Care and Outcome after Acute Myocardial Infarction for Patients with Mental Illness in the VA Health Care System: Are There Disparities?. Health Services Research 38:1p1, 41-63
CrossRef47
Gabriel A. Picone, Frank A. Sloan, Shin-Yi Chou, Donald H. Taylor. (2003) Does Higher Hospital Cost Imply Higher Quality of Care?. Review of Economics and Statistics 85:1, 51-62
CrossRef48
Ian A Scott. (2003) Determinants of Quality of In-Hospital Care for Patients with Acute Coronary Syndromes. Disease Management & Health Outcomes 11:12, 801-816
CrossRef49
Ayanian, John Z., Landrum, Mary Beth, Guadagnoli, Edward, Gaccione, Peter, . (2002) Specialty of Ambulatory Care Physicians and Mortality among Elderly Patients after Myocardial Infarction. New England Journal of Medicine 347:21, 1678-1686
Full Text50
Usha Subramanian, Morris Weinberger, George J. Eckert, Gilbert J. L'Italien, Pablo Lapuerta, William Tierney. (2002) Geographic Variation in Health Care Utilization and Outcomes in Veterans with Acute Myocardial Infarction. Journal of General Internal Medicine 17:8, 604-611
CrossRef51
Robert C Kaplan, Susan R Heckbert, Curt D Furberg, Bruce M Psaty. (2002) Predictors of subsequent coronary events, stroke, and death among survivors of first hospitalized myocardial infarction. Journal of Clinical Epidemiology 55:7, 654-664
CrossRef52
Monir Hossain, Steven Wright, Laura A. Petersen. (2002) Comparing performance of multinomial logistic regression and discriminant analysis for monitoring access to care for acute myocardial infarction. Journal of Clinical Epidemiology 55:4, 400-406
CrossRef53
Benjamin G. Druss, Robert A. Rosenheck, Mayur M. Desai, Jonathan B. Perlin. (2002) Quality of Preventive Medical Care for Patients With Mental Disorders. Medical Care 40:2, 129-136
CrossRef54
Laura A. Petersen, Steven M. Wright, Eric D. Peterson, Jennifer Daley. (2002) Impact of Race on Cardiac Care and Outcomes in Veterans With Acute Myocardial Infarction. Medical Care 40:Supplement, I-86-I-96
CrossRef55
Eugene Z. Oddone, Laura A. Petersen, Morris Weinberger, Jay Freedman, Nancy R. Kressin. (2002) Contribution of the Veterans Health Administration in Understanding Racial Disparities in Access and Utilization of Health Care. Medical Care 40:Supplement, I-3-I-13
CrossRef56
Peter J. Kaboli, Mitchell J. Barnett, Susan M. Fuehrer, Gary E. Rosenthal. (2001) Length of Stay as a Source of Bias in Comparing Performance in VA and Private Sector Facilities. Medical Care 39:9, 1014-1024
CrossRef57
(2001) Quality of Care in the Veterans Health Administration. New England Journal of Medicine 344:15, 1168-1170
Full Text58
Fihn, Stephan D.. (2000) Does VA Health Care Measure up?. New England Journal of Medicine 343:26, 1963-1965
Full Text
