Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Circ Cardiovasc Qual Outcomes. Author manuscript; available in PMC 2011 January 1.
Published in final edited form as:
PMCID: PMC2818545

Costs of Inpatient Care Among Medicare Beneficiaries With Heart Failure, 2001–2004



Inpatient care is the primary driver of costs for patients with heart failure. It is unclear whether recent advances in heart failure care have reduced the costs to Medicare for the care of inpatients with heart failure.

Methods and Results

In a retrospective cohort study of 1363977 elderly Medicare beneficiaries hospitalized with heart failure between January 1, 2001, and December 31, 2004, we examined costs to Medicare for all inpatient care, inpatient cardiovascular care, and inpatient heart failure care and the adjusted relationships between patient characteristics and costs. Among 1363977 Medicare beneficiaries with an index heart failure hospitalization, 901885 (66%) had a subsequent inpatient claim during the following year. Noncardiovascular costs accounted for 57% of total inpatient costs, and costs associated with heart failure hospitalizations accounted for 15% of total inpatient costs. No significant changes occurred in total, cardiovascular, and heart failure inpatient costs over time.


The costs of inpatient care for patients with heart failure are high, but most subsequent inpatient costs are due to noncardiovascular and non-heart failure admissions. Further research is needed to identify predictors of costs, so that patients can be stratified according to risk, and to evaluate strategies that target primary cost drivers for patients with heart failure.

Keywords: Health Care Costs, Heart Failure, Hospitalization, Medicare


Approximately 4.7 million people in the United States have heart failure, and approximately 550000 new cases are diagnosed annually.1 The 5-year mortality rate among patients with heart failure is close to 50%. The impact of heart failure is greater among elderly patients. Almost 75% of patients with heart failure are older than 65 years, and 80% of hospitalizations for heart failure occur among elderly patients.2,3 Moreover, 65% of elderly persons have 2 or more chronic conditions.4 Consequently, even elderly patients with a primary diagnosis of heart failure upon hospital admission are likely to be treated for other illnesses during the hospital stay or to be readmitted to the hospital for a different cause related to the initial admission. Nevertheless, the primary diagnosis remains the trigger for the allocation of Medicare payments to hospitals.

Treatment options for heart failure have advanced significantly during the past 15 years. A number of therapies that reduce heart failure hospitalizations have been tested in clinical trials, including angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers, β-blockers, and biventricular pacemakers.58 Because it can take years for the results of clinical trials to be adopted by practitioners in the community, reductions in clinical events in the general heart failure population may not be seen for some years after the dissemination of clinical trial results.

We designed a retrospective study of Medicare claims to examine inpatient claims for patients with heart failure. Given the burden of comorbid conditions in elderly patients with heart failure, we hypothesized that non–heart failure and noncardiac hospital admissions would account for a large proportion of inpatient costs. We undertook the study to develop a clearer picture of the inpatient costs of heart failure and to identify the distribution of those costs.


Study Population

From the Centers for Medicare & Medicaid Services (CMS), we obtained inpatient claims and the corresponding denominator files for all Medicare beneficiaries discharged between January 1, 2000, and December 31, 2005. The inpatient files include claims submitted for facility costs covered under Medicare Part A and contain beneficiary, physician, and hospital identifiers, admission and discharge dates, and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis and procedure codes. The denominator files include information about program eligibility and enrollment, birth dates, death dates, sex, and race/ethnicity as reported by Medicare beneficiaries at the time of enrollment. For this analysis, we used the race category “black” and combined all others as “nonblack.”9

We included all beneficiaries with a primary diagnosis of heart failure (ICD-9-CM codes 428.x, 428.2x, 428.3x, 428.4x, 402.x1, and 404.x1) on a single inpatient claim and considered the earliest such hospitalization on or after January 1, 2001, to be the index event.10 Excluding beneficiaries with an index hospitalization in 2000 enhanced the comparability of the annual cohorts by ensuring that all cohorts had at least 1 year without a heart failure hospitalization before the index admission, which was considered a marker of disease stability. In order to avoid double-counting costs, we did not select patients in multiple years. We limited the analysis to beneficiaries living in the United States who were aged 65 years or older on the index date, were discharged alive from the index admission, and were eligible for Medicare during the previous 12 months.


We calculated the total inpatient costs to Medicare by summing the payment amounts and the per diem adjustments for all inpatient stays within 1 year of the index discharge date or until death, whichever occurred first. We adjusted all costs to 2001 US dollars. We used the same formula to calculate the costs of cardiovascular hospitalizations (diagnosis related groups [DRGs] 104–112, 115–118, 121–145, 479, 514–518, 525–527, 535, 536, 547–558 [see Table 1]), heart failure hospitalizations (DRG 127), and costs associated with therapeutic device implantations (DRG 115, 116, 514, 515, 525, 535, 536). We considered the year following the index discharge date to be relevant, given the high 1-year mortality rate among Medicare beneficiaries hospitalized with heart failure and the current focus of health care policy makers on 30-day and 1-year costs.

Table 1
Diagnosis Related Groups Used to Define Cardiovascular Hospitalizations


We extracted beneficiaries’ demographic characteristics from the denominator files. We reserved data from 2000 for identifying baseline comorbid conditions and covariates for beneficiaries whose index admission occurred during 2001. Consistent with the current approach for case-mix adjustment at CMS, we used Hierarchical Condition Categories (HCCs) to define the comorbid conditions.11,12 Specifically, we looked for evidence of cardiorespiratory failure and shock (HCC 79), valvular and rheumatic heart disease (HCC 86), hypertension (HCCs 89 and 91), stroke (HCCs 95 and 96), renal failure (HCC 131), chronic obstructive pulmonary disease (HCC 108), pneumonia (HCCs 111–113), diabetes mellitus (HCCs 15–20 and 120), dementia and major psychiatric disorders (HCCs 49, 50, and 54–56), peripheral vascular disease (HCCs 104 and 105), metastatic cancer (HCCs 7 and 8), chronic liver disease (HCCs 25–27), specified heart arrhythmias (HCC 92), and other heart rhythm and conduction disorders (HCC 93). We also searched for evidence of ischemic disease, which we defined as a history of percutaneous transluminal coronary angioplasty (ICD-9-CM codes 360.1, 360.2, and 360.5), coronary artery bypass graft surgery (ICD-9-CM code 361.x), receipt of an implantable cardioverter-defibrillator (ICD-9-CM codes 379.4, 379.5, 379.6, 379.7, and 379.8), acute myocardial infarction (HCC 81), unstable angina and other acute ischemic heart disease (HCC 82), or chronic atherosclerosis (HCCs 83 and 84). In addition, we calculated the length of stay for the index hospitalization and total Medicare payments for hospitalizations in the 365 days before the index date. We report all Medicare payment amounts in 2001 US dollars.

Statistical Analysis

We present the baseline characteristics of the study population, displaying categorical variables as frequencies and continuous variables as means with SDs. We describe mean readmissions within 1 year of the index heart failure hospitalization in the overall cohort and among patients with at least 1 readmission. Transfers to or from another hospital did not count as readmissions for the purpose of counting hospitalizations, even though these claims were used to calculate total costs to Medicare.

We present descriptive statistics of inpatient costs at 1 year and show the distribution of inpatient costs by DRG within 30 days and 1 year of the index hospitalization. To examine the unadjusted relationships between covariates and total costs, we used generalized linear models with a log link and Poisson distribution and with adjustment for clustering of similar patients within hospitals. When exponentiated, the cost ratios estimate the proportional increase in costs attributable to the variable. We used the same approach to examine adjusted relationships and included age (per 5 years), sex, race, length of stay for the index hospitalization > 7 days, procedures and comorbid conditions, inpatient costs for the previous year (with no inpatient costs in the previous year as the reference and tertiles of cost for patients with prior costs), geographic region (with the southern United States as the reference), and the year the of index hospitalization (with 2001 as the reference year) in the multivariable models.


From January 1, 2001, through December 31, 2004, 1363977 Medicare beneficiaries had an index heart failure hospitalization. The mean length of stay was 5.4 days per stay (Table 2). The mean age of the patients was 80 years, 58.3% were women, and 89.7% were nonblack. The most common cardiovascular comorbid conditions were history of ischemic heart disease (59.2%), hypertension (59.2%), and chronic obstructive pulmonary disease (33.9%). The most common noncardiovascular comorbid conditions were diabetes mellitus (36.8%), renal failure (18.5%), and dementia or major psychiatric disorders (13.5%). Five percent of the patients had undergone percutaneous transluminal coronary angioplasty, 3.6% had undergone coronary artery bypass graft surgery, and 2.4% had received an implantable cardioverter-defibrillator. The mean cost for inpatient care in the year before the index hospitalization was $9337. The mean number of admissions in the year before the index hospitalization was 1.2.

Table 2
Baseline Characteristics of the Study Population

Of the 1363977 patients in the study population, 901885 (66.1%) had a subsequent inpatient claim within 1 year. These patients included 243351/362943 (67.0%) in 2001, 222885/337213 (66.1%) in 2002, 222383/337691 (65.9%), in 2003, and 213266/326130 (65.4%) in 2004. Overall, the mean number of readmissions within 1 year was 1.5 (SD, 1.7) for all causes, 0.6 (SD, 1.1) for cardiovascular readmissions, and 0.3 (SD 0.8) for heart failure readmissions. Among patients with at least 1 readmission, the mean increased to 2.3 (SD, 1.7) for all causes, 1.0 (SD, 1.2) for cardiovascular readmissions, and 0.5 (SD, 0.9) for heart failure.

Costs associated with noncardiovascular hospitalizations accounted for 57% of total inpatient costs, and costs associated with heart failure hospitalizations accounted for 15% of total inpatient costs. As shown in Table 3, the mean 1-year cost during the 4-year period was $1866 for heart failure causes, $5497 for cardiovascular causes (including heart failure), and $12719 for all-cause admissions. During the 4 years of the study, we observed a modest decline in mean 1-year inpatient costs for heart failure from $1985 in 2001 to $1797 in 2004 (P < .001; Table 3). However, we observed a slight increase in mean all-cause inpatient costs of $209 per patient during the same period (P < .001), with an increase in mean cardiovascular inpatient costs of $129 (P < .001).

Table 3
Inpatient Costs to Medicare at 1 Year*

Among DRGs reported on subsequent Medicare claims following an index heart failure admission, heart failure was the costliest and accounted for 13% of total 30-day costs and 15% of total 1-year costs (Table 4). Other high-cost DRGs at both 30 days and 1 year were related to rehabilitation, mechanical ventilation for respiratory failure, implantation of cardiac valves, and renal failure. Inpatient costs associated with therapeutic device implantations accounted for 3.9% of total 30-day costs and 2.7% of total 1-year costs (data not shown).

Table 4
Ten Most Costly Diagnosis Related Groups Within 30 Days and 1 Year of Index Hospitalization

Several patient characteristics predicted 1-year inpatient costs after an index heart failure admission (Table 5). Predictors associated with higher costs included having inpatient costs in the prior year, receiving care in the northeastern United States, renal failure, valvular heart disease, black race, and diabetes mellitus. Predictors associated with lower costs included greater age, dementia, and metastatic cancer. After adjustment for age, sex, race/ethnicity, baseline comorbid conditions, length of the index hospitalization, geographic region, and having inpatient costs in the previous year, the index year was not a significant predictor of all-cause inpatient costs at 1 year.

Table 5
Multivariable Model of All-Cause Costs to Medicare at 1 Year


In this large cohort study of Medicare beneficiaries followed after an index heart failure admission, inpatient costs continue to be high, with over 25% of patients incurring costs of more than $16000 at 1 year. Although the index event was a heart failure admission, subsequent costs were primarily for noncardiovascular events. Even among cardiovascular expenditures, admissions for heart failure represented a minority of costs. However, among all DRGs reported on subsequent Medicare claims, heart failure remains the single costliest, accounting for 15% of total 1-year inpatient costs.

Our findings are consistent with findings from randomized clinical trials. The 3164 participants in the treatment and placebo arms of the Assessment of Treatment With Lisinopril and Survival (ATLAS) had a total of 8216 hospital admissions; heart failure hospitalizations contributed only 2775 (33%) to the total number of admissions.5 Similarly, in the Cardiac Insufficiency Bisoprolol Study II (CIBIS-II), the proportion of participants in the treatment arm who were admitted for worsening heart failure symptoms (n = 159 [12%]) was similar to the proportion in the placebo arm (n = 232 [18%]).6 The all-cause hospital admission rate in the treatment arm was 33% (440/1327).

Diabetes mellitus, hypertension, and chronic obstructive pulmonary disease are among the most prevalent comorbid conditions among elderly patients with heart failure. For example, in a meta-analysis of 6 β-blocker trials, including CIBIS-II, Haas et al13 found that 24.6% of patients had diabetes mellitus. The same high prevalence of these comorbid conditions was seen in the current study, in which comorbid conditions were significant predictors of higher total inpatient costs.

Our finding that the majority of inpatient costs in a cohort of patients with heart failure were for non-heart failure diagnoses has important therapeutic implications. Therapies like ACE inhibitors and spironolactone that target the underlying pathology of heart failure and are beneficial for other coexisting conditions may have a greater impact on overall morbidity and cost. ACE inhibitors, for example, are known to improve outcomes not only for patients with heart failure, but also for patients with hypertension, diabetes mellitus, renal dysfunction, and coronary artery disease.1420 In ATLAS, treatment with an ACE inhibitor reduced hospitalizations for heart failure (1576 vs 1199, low-dose vs high-dose; P = .002), reduced hospitalizations by an additional 90 admissions when all cardiovascular hospitalizations were considered (2923 vs 2456, low-dose vs high-dose; P = .05), and reduced hospitalizations by another 111 admissions when all hospitalizations were considered (4397 vs 3819, low-dose vs high-dose; P = .02).5

In contrast with ACE inhibitors, the effects of aldosterone are primarily directed at pathological issues related specifically to cardiomyopathy, particularly at low doses used in clinical trials.21 Thus, in the Randomized Aldactone Evaluation Study (RALES), spironolactone reduced heart failure hospitalizations by 250 (663 vs 413, placebo vs spironolactone; P < .001) but did not provide further reductions in hospitalizations for cardiovascular events (753 vs 515, placebo vs spironolactone; P < .001) or noncardiovascular hospitalizations (377 vs 361, placebo vs spironolactone).22 Although the cost savings associated with both treatments were similar ($875 vs $713, lisinopril vs spironolactone), the actual cost saving was likely greater for lisinopril given the significant difference in cost for the therapy ($0.92 vs $0.48 per day of therapy, lisinopril vs spironolactone).23,24


This analysis has some limitations. First, we used ICD-9-CM diagnosis codes to identify heart failure admissions. Although other studies have shown that a single inpatient diagnosis of heart failure has high specificity,25 medical chart review is likely to be more sensitive.2628 Our analysis did not take into account coding changes that may have occurred during the period of the study. This may have payment implications using the CMS-HCC method. Second, although a non-heart failure diagnosis may have been the reason for a subsequent admission, heart failure may have contributed to the event. For example, in 23% of rehabilitation claims, heart failure was noted as the second diagnosis. We did not assign costs to clinical events, but rather summed Medicare payments that were reflected in administrative data. Third, the analysis is limited to Medicare beneficiaries aged 65 or older with fee-for-service coverage, so the results may not be generalizable to all patients with heart failure. However, the findings do reflect the experience of a substantial number of relevant patients. Fourth, the costs reported are for inpatient care paid by Medicare during the study period. This analysis does not take into account changes in reimbursement during the study period or the potential that coding practices changed over time because of the payment implications of the CMS-HCC method.12 Out-of-pocket costs, outpatient care costs, and those paid through supplemental insurance are not included. For Medicare beneficiaries who continue to work for an employer with 100 or more employees, Medicare is the secondary insurer. Only costs to Medicare and not costs of total inpatient care for these patients were included in this analysis. In addition, there is no way to explore how medication use contributed to the findings we observed. Finally, claims are not filed during periods of managed care enrollment, so the analysis underestimates costs to the extent that fee-for-service beneficiaries switched to managed care and were readmitted.


Given the findings of this study that the majority of inpatient costs incurred in the care of patients with heart failure are for non-heart failure admissions, treatment strategies need to target outcomes beyond heart failure to have a significant impact on health care costs. The movement within clinical trials to focus on heart failure end points may provide positive results for the study but could mislead policy makers into believing that overall health care costs will be reduced through the implementation of a treatment or care strategy.


What Is Known

  • H eart failure places a heavy burden on health care resources in the United States.
  • Patients with heart failure also tend to have a large number of comorbid conditions.
  • In clinical trials, a large proportion of hospitalizations are for non-heart failure–related diagnoses.

What This Article Adds

  • Total inpatient costs for Medicare beneficiaries discharged after a heart failure admission average $12,719 per year.
  • Inpatient costs associated with heart failure hospitalizations account for 15% of total inpatient costs.


We thank Damon M. Seils, MA, of Duke University and Sue Russell, MFA, of Thomas Jefferson University for editorial assistance and manuscript preparation. Mr Seils and Ms Russell did not receive compensation for their assistance apart from their employment at the institutions where the study was conducted.

Funding/Support: This study was supported by grants U01HL066461 from the National Heart, Lung, and Blood Institute and R01AG026038 from the National Institute on Aging.


Disclaimer: The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute, the National Institute on Aging, or the National Institutes of Health.

Financial Disclosures: Dr Whellan reported receiving grants or funding from Abbott, Duke Clinical Research Institute, GE Medical, Johnson & Johnson, Medtronic, National Heart, Lung, and Blood Institute, and Schering-Plough. Dr Schulman reported receiving research support from Actelion Pharmaceuticals, Allergan, Amgen, Astellas Pharma, Bristol-Myers Squibb, The Duke Endowment, Genentech, Inspire Pharmaceuticals, Johnson & Johnson, Kureha Corporation, LifeMasters Supported SelfCare, Medtronic, Merck & Co, Nabi Biopharmaceuticals, National Patient Advocate Foundation, North Carolina Biotechnology Center, NovaCardia, Novartis, OSI Eyetech, Pfizer, Sanofi-Aventis, Scios, Tengion, Theravance, Thomson Healthcare, and Vertex Pharmaceuticals; receiving personal income for consulting from McKinsey & Company and the National Pharmaceutical Council; having equity in Alnylam Pharmaceuticals; having equity in and serving on the board of directors of Cancer Consultants, Inc; and having equity in and serving on the executive board of Faculty Connection, LLC. Dr Schulman has made available online a detailed listing of financial disclosures ( Dr Curtis reported receiving research support from Allergan, Eli Lilly and Company, GlaxoSmithKline, Medtronic, Merck & Co, Johnson & Johnson (Ortho Biotech), Novartis, OSI Eyetech, and Sanofi-Aventis. Dr Curtis has made available online a detailed listing of financial disclosures ( No other disclosures were reported.


1. Thom T, Haase N, Rosamond W, Howard VJ, Rumsfeld J, Manolio T, Zheng ZJ, Flegal K, O’Donnell C, Kittner S, Lloyd-Jones D, Goff DC, Jr, Hong Y, Adams R, Friday G, Furie K, Gorelick P, Kissela B, Marler J, Meigs J, Roger V, Sidney S, Sorlie P, Steinberger J, Wasserthiel-Smoller S, Wilson M, Wolf P. American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics--2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2006;113:e85–e151. Erratum in: Circulation 2006; 113:e696. [PubMed]
2. Ammar KA, Jacobsen SJ, Mahoney DW, Kors JA, Redfield MM, Burnett JC, Jr, Rodeheffer RJ. Prevalence and prognostic significance of heart failure stages: application of the American College of Cardiology/American Heart Association heart failure staging criteria in the community. Circulation. 2007;115:1563–1570. [PubMed]
3. Haldeman GA, Croft JB, Giles WH, Rashidee A. Hospitalization of patients with heart failure: National Hospital Discharge Survey, 1985 to 1995. Am Heart J. 1999;137:352–360. [PubMed]
4. Wolff JL, Starfield B, Anderson G, Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med. 2002;162:2269–2276. [PubMed]
5. Packer M, Poole-Wilson PA, Armstrong PW, Cleland JG, Horowitz JD, Massie BM, Rydén L, Thygesen K, Uretsky BF. Comparative effects of low and high doses of the angiotensin-converting enzyme inhibitor, lisinopril, on morbidity and mortality in chronic heart failure. ATLAS Study Group. Circulation. 1999;100:2312–2318. [PubMed]
6. CIBIS II Investigators and Committees. The Cardiac Insufficiency Bisoprolol Study II (CIBIS-II): a randomised trial. Lancet. 1999;353:9–13. [PubMed]
7. Bristow MR, Saxon LA, Boehmer J, Krueger S, Kass DA, De Marco T, Carson P, DiCarlo L, DeMets D, White BG, DeVries DW, Feldman AM. Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure (COMPANION) Investigators. Cardiac-resynchronization therapy with or without an implantable defibrillator in advanced chronic heart failure. N Engl J Med. 2004;350:2140–2150. [PubMed]
8. Pfeffer MA, Swedberg K, Granger CB, Held P, McMurray JJ, Michelson EL, Olofsson B, Ostergren J, Yusuf S, Pocock S. CHARM Investigators and Committees. Effects of candesartan on mortality and morbidity in patients with chronic heart failure: the CHARM-Overall programme. Lancet. 2003;362:759–766. [PubMed]
9. Arday SL, Arday DR, Monroe S, Zhang J. HCFA’s racial and ethnic data: current accuracy and recent improvements. Health Care Financ Rev. 2000;21:107–116. [PubMed]
10. Curtis LH, Greiner MA, Hammill BG, Kramer JM, Whellan DJ, Schulman KA, Hernandez AF. Acute and long-term outcomes of heart failure in elderly persons, 2001–2005. Arch Intern Med. 2008;168:2481–2488. [PMC free article] [PubMed]
11. Krumholz HM, Wang Y, Mattera JA, Wang Y, Han LF, Ingber MJ, Roman S, Normand SL. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with heart failure. Circulation. 2006;113:1693–1701. [PubMed]
12. Pope GC, Kautter J, Ellis RP, Ash AS, Ayanian JZ, Lezzoni LI, Ingber MJ, Levy JM, Robst J. Risk adjustment of Medicare capitation payments using the CMS-HCC model. Health Care Financ Rev. 2004;25:119–141. [PubMed]
13. Haas SJ, Vos T, Gilbert RE, Krum H. Are beta-blockers as efficacious in patients with diabetes mellitus as in patients without diabetes mellitus who have chronic heart failure? A meta-analysis of large-scale clinical trials. Am Heart J. 2003;146:848–853. [PubMed]
14. Briggs A, Mihaylova B, Sculpher M, Hall A, Wolstenholme J, Simoons M, Deckers J, Ferrari R, Remme WJ, Bertrand M, Fox K. EUROPA Trial Investigators. Cost effectiveness of perindopril in reducing cardiovascular events in patients with stable coronary artery disease using data from the EUROPA study. Heart. 2007;93:1081–1086. [PMC free article] [PubMed]
15. Ruggenenti P, Fassi A, Ilieva AP, Bruno S, Iliev IP, Brusegan V, Rubis N, Gherardi G, Arnoldi F, Ganeva M, Ene-Iordache B, Gaspari F, Perna A, Bossi A, Trevisan R, Dodesini AR, Remuzzi G. Bergamo Nephrologic Diabetes Complications Trial (BENEDICT) Investigators. Preventing microalbuminuria in type 2 diabetes. N Engl J Med. 2004;351:1941–1951. [PubMed]
16. Yusuf S, Sleight P, Pogue J, Bosch J, Davies R, Dagenais G. Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients. The Heart Outcomes Prevention Evaluation Study Investigators. N Engl J Med. 2000;342:145–153. Erratum in: N Engl J Med, 2000; 342:1376. [PubMed]
17. Agodoa LY, Appel L, Bakris GL, Beck G, Bourgoignie J, Briggs JP, Charleston J, Cheek D, Cleveland W, Douglas JG, Douglas M, Dowie D, Faulkner M, Gabriel A, Gassman J, Greene T, Hall Y, Hebert L, Hiremath L, Jamerson K, Johnson CJ, Kopple J, Kusek J, Lash J, Lea J, Lewis JB, Lipkowitz M, Massry S, Middleton J, Miller ER, 3rd, Norris K, O’Connor D, Ojo A, Phillips RA, Pogue V, Rahman M, Randall OS, Rostand S, Schulman G, Smith W, Thornley-Brown D, Tisher CC, Toto RD, Wright JT, Jr, Xu S. African American Study of Kidney Disease and Hypertension (AASK) Study Group. Effect of ramipril vs amlodipine on renal outcomes in hypertensive nephrosclerosis: a randomized controlled trial. JAMA. 2001;285:2719–2728. [PubMed]
18. Wing LM, Reid CM, Ryan P, Beilin LJ, Brown MA, Jennings GL, Johnston CI, McNeil JJ, Macdonald GJ, Marley JE, Morgan TO, West MJ. Second Australian National Blood Pressure Study Group. A comparison of outcomes with angiotensin-converting enzyme inhibitors and diuretics for hypertension in the elderly. N Engl J Med. 2003;348:583–592. [PubMed]
19. Effects of ramipril on cardiovascular and microvascular outcomes in people with diabetes mellitus: results of the HOPE study and MICRO-HOPE substudy. Heart Outcomes Prevention Evaluation Study Investigators. Lancet. 2000;355:253–259. Erratum in: Lancet. 2000; 356:860. [PubMed]
20. Fox KM. EURopean trial On reduction of cardiac events with Perindopril in stable coronary Artery disease Investigators. Efficacy of perindopril in reduction of cardiovascular events among patients with stable coronary artery disease: randomised, double-blind, placebo-controlled, multicentre trial (the EUROPA study) Lancet. 2003;362:782–788. [PubMed]
21. Swedberg K, Eneroth P, Kjekshus J, Wilhelmsen L. Hormones regulating cardiovascular function in patients with severe congestive heart failure and their relation to mortality. CONSENSUS Trial Study Group. Circulation. 1990;82:1730–1736. [PubMed]
22. Pitt B, Zannad F, Remme WJ, Cody R, Castaigne A, Perez A, Palensky J, Wittes J. The effect of spironolactone on morbidity and mortality in patients with severe heart failure. Randomized Aldactone Evaluation Study Investigators. N Engl J Med. 1999;341:709–717. [PubMed]
23. Schwartz JS, Wang YR, Cleland JG, Gao L, Weiner M, Poole-Wilson PA. ATLAS Study Group. High- versus low-dose angiotensin converting enzyme inhibitor therapy in the treatment of heart failure: an economic analysis of the Assessment of Treatment with Lisinopril and Survival (ATLAS) trial. Am J Manag Care. 2003;9:417–424. [PubMed]
24. Glick HA, Orzol SM, Tooley JF, Remme WJ, Sasayama S, Pitt B. Economic evaluation of the randomized aldactone evaluation study (RALES): treatment of patients with severe heart failure. Cardiovasc Drugs Ther. 2002;16:53–59. [PubMed]
25. Goff DC, Jr, Pandey DK, Chan FA, Ortiz C, Nichaman MZ. Congestive heart failure in the United States: is there more than meets the I(CD code)? The Corpus Christi Heart Project. Arch Intern Med. 2000;160:197–202. [PubMed]
26. Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, Mark DB. Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research. Ann Intern Med. 1993;119:844–850. [PubMed]
27. Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF. Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care. 2005;43:480–485. [PubMed]
28. Lee DS, Donovan L, Austin PC, Gong Y, Liu PP, Rouleau JL, Tu JV. Comparison of coding of heart failure and comorbidities in administrative and clinical data for use in outcomes research. Med Care. 2005;43:182–188. [PubMed]