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Original Investigation |

Influence of a Performance-Improvement Initiative on Quality of Care for Patients Hospitalized With Heart Failure:  Results of the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) FREE

Gregg C. Fonarow, MD; William T. Abraham, MD; Nancy M. Albert, RN, PhD; Wendy Gattis Stough, PharmD; Mihai Gheorghiade, MD; Barry H. Greenberg, MD; Christopher M. O’Connor, MD; Karen Pieper, MS; Jie Lena Sun, MS; Clyde W. Yancy, MD; James B. Young, MD; OPTIMIZE-HF Investigators and Hospitals
[+] Author Affiliations

Author Affiliations: Departments of Medicine, University of California–Los Angeles Medical Center (Dr Fonarow), Duke University Medical Center, Durham, North Carolina (Dr Gattis Stough), University of California–San Diego Medical Center (Dr Greenberg), and The University of Texas Southwestern Medical Center, Dallas (Dr Yancy); Divisions of Cardiology, The Ohio State University, Columbus (Dr Abraham), Feinberg School of Medicine, Northwestern University, Chicago, Illinois (Dr Gheorghiade), and Duke University Medical Center/Duke Clinical Research Institute, Durham (Dr O’Connor); George M. and Linda H. Kaufman Center for Heart Failure (Dr Albert) and Department of Cardiovascular Medicine, Heart Failure Section (Dr Young), Cleveland Clinic Foundation, Cleveland, Ohio; Department of Clinical Research, Campbell University School of Pharmacy, Research Triangle Park, North Carolina (Dr Gattis Stough); and Duke Clinical Research Institute, Durham (Mss Pieper and Sun). Dr Yancy is now with Baylor Heart and Vascular Institute, Baylor University Medical Center, Dallas.


Arch Intern Med. 2007;167(14):1493-1502. doi:10.1001/archinte.167.14.1493.
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Published online

Background  Despite evidence-based national guidelines for optimal treatment of heart failure (HF), the quality of care remains inadequate. We sought to evaluate the effect of a national hospital-based initiative on quality of care in patients hospitalized with HF.

Methods  Two hundred fifty-nine US hospitals participating in the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) submitted data on 48 612 patients with HF from March 1, 2003, through December 31, 2004. Admission, hospital, discharge care, and outcomes data were collected using a Web-based registry that provided real-time feedback on performance measures benchmarked to other hospitals. Process-of-care improvement tools, including evidence-based best-practice algorithms and customizable admission and discharge sets, were provided.

Results  Provision of complete discharge instructions and smoking-cessation counseling increased significantly (from 46.8%-66.5% and 48.2%-75.6%, respectively; < .001 for both). Left ventricular function assessment started at a high rate (89.3%) and improved to 92.1% (< .001). Angiotensin-converting enzyme inhibitors were prescribed at discharge to 75.8% of eligible patients, which did not improve during the 2-year study. There were trends for reduction of in-hospital mortality, postdischarge death, and combined postdischarge death and rehospitalization and a significant reduction in mean length of stay. Use of preprinted admission order sets and/or discharge checklists increased from 35.6% to 54.1% and was associated with an increase in the use of evidence-based therapies and lower risk-adjusted in-hospital mortality.

Conclusions  Participation in OPTIMIZE-HF was associated with an increase in use of evidence-based therapy, adherence to performance measures, and shorter lengths of stay in patients hospitalized with HF. Increased use of process-of-care improvement tools was associated with further improvements in quality of care.

Trial Registration  clinicaltrials.gov Identifier NCT00344513.

Figures in this Article

The burden of heart failure (HF) has grown into a major public health problem, with increasingly higher rates of mortality and hospitalization. More than 5 million individuals in the United States have HF, and HF is the primary or secondary cause for almost 3.6 million hospitalizations each year.1,2 Measuring quality is an important aspect of tracking and improving medical care.36 Accordingly, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) and the American College of Cardiology and American Heart Association (ACC/AHA) have constructed sets of performance measures that serve as quantifiable, evidence-based quality indicators.4,6 These are processes of care for which the evidence of benefit is so strong that failure to adhere to them reduces the likelihood of optimal patient outcomes.4,5 Current JCAHO performance measures for adults hospitalized with HF include complete discharge instructions, left ventricular function assessment, use of an angiotensin-converting enzyme inhibitor (ACEI) or an angiotensin receptor blocker (ARB) in patients with left ventricular systolic dysfunction, and smoking cessation counseling.6 Although β-blocker use at hospital discharge in stable patients is recommended in the ACC/AHA guidelines,2 it is not a JCAHO or ACC/AHA inpatient HF performance measure. Several state and national initiatives have been undertaken to improve the quality of care for patients with cardiovascular disease. These programs use a variety of mechanisms, including national tracking and reporting of quality indicators obtained through Medicare claims and random reviews of patient medical records,7 providing feedback to practitioners of quality indicator adherence through local peer-review organizations,8 requiring accredited hospitals to submit performance measure data,5 and providing performance-improvement tools designed to enhance adherence to national treatment guidelines and performance measures such as admission and discharge order sets that incorporate evidence-based processes of care.9

The Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) is the largest national hospital-based initiative to improve quality of HF care undertaken to date and the only program designed to capture 60- to 90-day postdischarge outcomes in a prespecified cohort of patients. Building on features of previous programs, the aim of OPTIMIZE-HF was to increase adherence to evidence-based guideline recommendations and performance measures for hospitalized patients with HF specifically through a Web-based patient registry that facilitated feedback on performance data, providing specific process-of-care improvement (PrCI) tools and promoting in-hospital initiation of recommended therapies.

STUDY DESIGN

OPTIMIZE-HF was designed to evaluate and enhance the quality of care given to patients hospitalized with HF. Details of the study design have been described previously.10,11 The overall program comprised 2 major components: a comprehensive Web-based registry and a process-of-care intervention arm.

PATIENT POPULATION

From March 1, 2003, through December 31, 2004, eligible adult patients hospitalized with HF at 259 participating hospital centers in the United States were enrolled in the OPTIMIZE-HF prospective registry. Hospital teams used case-ascertainment methods identical to those of the JCAHO. Patients qualified for enrollment if they were hospitalized for episodes of new or worsening HF as the primary cause of admission or if significant HF symptoms developed during hospitalization for another primary diagnosis, with HF being the primary discharge diagnosis. Patients were enrolled irrespective of their ventricular function, including systolic dysfunction documented by a left ventricular ejection fraction (LVEF) of less than 40%, HF symptoms in the setting of preserved left ventricular systolic function (diastolic dysfunction HF), or HF without left ventricular function measurement.10

Data were collected on pertinent patient characteristics at admission and discharge, as well as on adherence to OPTIMIZE-HF performance and quality measures. Admission staff, medical staff, or both recorded race/ethnicity, usually as the patient was registered. Previous studies of patients hospitalized with HF have suggested differences in characteristics and outcomes based on race/ethnicity. The performance measures consisted of the 4 JCAHO HF core measures. The following additional quality measures were also assessed: use of an ACEI or an ARB, use of any β-blocker at hospital discharge (which is not a JCAHO or ACC/AHA inpatient HF performance measure), evidence-based use of a β-blocker (ie, bisoprolol fumarate, carvedilol, or metoprolol succinate), aldosterone antagonist use, statin use in appropriate patients, and anticoagulation for atrial fibrillation (Table 1). Eligibility to receive ACEIs, ARBs, aldosterone antagonists, and β-blockers was defined by HF due to left ventricular systolic dysfunction, indicated by an LVEF of less than 40% or by a qualitative report in the absence of documented contraindications or intolerance to the therapeutic agent.10 Eligibility for statin therapy was defined as known coronary artery disease, peripheral vascular disease, cerebrovascular disease, and/or diabetes mellitus. All measures were applied to eligible patients who had no documented contraindications or intolerance. Data were reported on a confidential Web-based information system that allowed participating hospitals to review their performance data in real time, benchmarked to aggregate data from similar national and regional hospitals. The registry coordinating center was Outcome Sciences, Inc, Cambridge, Massachusetts.

Table Graphic Jump LocationTable 1. Performance and Quality of Care Measures Assessed in OPTIMIZE-HF

A prespecified patient subgroup (10.0%) was followed up for 60 to 90 days after discharge for the collection of outcomes data.10 Sites had the option of participating in the follow-up data collection, and the protocol was approved by each participating center's institutional review board or through use of a central institutional review board. Written informed consent was obtained before enrollment from patients who participated in the follow-up data collection.

The OPTIMIZE-HF PrCI program focused on helping hospitals improve institutional systems for treating HF has been previously described.10 The program relied on a hospital tool kit, benchmarked quality-of-care reports, and structured educational/collaborative opportunities. As part of an enhanced treatment and discharge plan, OPTIMIZE-HF provided evidence-based best-practices algorithms, critical pathways, standardized orders, discharge checklists, pocket cards, medical chart stickers, and a variety of other elements to assist hospitals inimproving HF management (OPTIMIZE-HF tools can be found at http://www.optimize-hf.org). The tools were designed by the OPTIMIZE-HF steering committee to be consistent with national guidelines and the most current scientific evidence. Use of the PrCI tools was encouraged but not mandatory; hospitals could adopt or modify tools at their choosing. A Web-based management tool provided hospitals real-time quality-of-care reports and benchmark comparisons of institutions regionally and nationally. The investigators and study coordinators attended a 1-day workshop at study initiation detailing quality improvement processes, use of collected data to provide feedback, and the OPTIMIZE-HF tool kit. Hospital teams were encouraged to participate in quarterly educational and collaborative Web-based seminars.

STUDY ANALYSES

The planned primary analyses of OPTIMIZE-HF were the change in the percentage of eligible patients with HF who received an ACEI or an ARB and β-blockers on discharge, the change in the rates of adherence to JCAHO core HF performance measures reported, and the change in additional quality measures during the 2-year study period. Secondary analyses included in-hospital outcomes (mortality and length of stay) for the entire study population, postdischarge mortality and rehospitalization rates for the 60- to 90-day follow-up subset, and the influence of PrCI tools on guideline-recommended therapies, performance measures, and short-term outcomes.10

ANALYSIS COHORT AND STATISTICAL ANALYSIS

Data were extracted directly from the registry as entered by the participating hospitals and analyzed across the entire database at the end of the registry period.10 All statistical analyses were performed independently at the Duke Clinical Research Institute. SAS statistical software (version 8.2; SAS Institute Inc, Cary, North Carolina) was used for all statistical analyses.

The data were reported as the number and frequency of eligible patients treated at the time of hospital discharge and as the percentages of eligible patients treated over time. Patients with a documented medication contraindication or intolerance were excluded from therapy analyses. Use of the PrCI tools was defined by a preprinted order set or a discharge checklist documented in the medical record. Patient characteristics and evidence-based treatments were compared using the Pearson χ2 test for categorical variables and the Wilcoxon rank sum test for continuous variables. The Cochran-Armitage test was used to evaluate changes over time, with P < .05 indicating significance. Multivariable models of in-hospital death, length of hospital stay, postdischarge mortality, and combined postdischarge death and rehospitalization were developed to be used for consistent covariate adjustment across all studies. The types of models were logistic for in-hospital mortality, general linear modeling for length of stay, Cox proportional hazards for postdischarge mortality, and logistic for postdischarge mortality and rehospitalization (date of rehospitalization was not available for survival modeling). The model-development process was similar for all 4 outcomes and used stepwise and backward variable selection methods. The linearity assumption for continuous measures was evaluated using restricted cubic spline transformations. When needed, appropriate transformations such as piecewise linear splines were applied. A P value of .05 was used both for entry and to remain in the model. The potential covariates were preselected with 45 for in-hospital mortality, 39 for length of stay, 19 for postdischarge mortality, and 70 for postdischarge mortality and rehospitalization (available at http://www.optimize-hf.org). Generalized estimating equations were used to account for the correlation of data within the same hospital in the adjusted models. There was greater than 99% power to detect a 25% change in in-hospital and postdischarge clinical outcomes over time. To compare the effect of admission order set use on in-hospital mortality with no admission order set use, there was 80% power to detect a treatment difference of 25% or greater. There was 66% power to detect a treatment difference of 25% or greater regarding use of an order set or discharge checklist on the combined outcome of 60- to 90-day mortality and rehospitalization.

CLINICAL CHARACTERISTICS OF PATIENTS HOSPITALIZED FOR HF

OPTIMIZE-HF enrolled a total of 48 612 patients hospitalized for HF at 259 academic and community hospitals of varying size from all regions of the United States (Table 2). The mean patient age was 73.1 years; 51.6% of the patients were female and 74.1% were white (Table 3). Heart failure etiology was ischemic in 45.7% of enrolled patients and the mean LVEF was 39.0%. Of those undergoing assessment, 48.8% had documented left ventricular systolic dysfunction and 51.2% had HF with preserved systolic function. The follow-up cohort included 5791 patients, whose characteristics were similar to those of the overall registry (Table 3).

Table Graphic Jump LocationTable 2. Participating Hospital Characteristics
Table Graphic Jump LocationTable 3. Patient Characteristics and Comorbidities a

Adherence to recommended HF therapies increased as follows: for an ACEI, from 50.0% of eligible patients (7272 of 14 528) before admission to 75.3% of eligible patients (10 940 of 14 528) at discharge, a net change of 25.3% (P < .001); for an ACEI or an ARB, from 57.9% (8386 of 14 493) before admission to 82.6% (11 976 of 14 493) at discharge (P < .001), a net increase of 24.7%; and for β-blockers, from 59.9% (9382 of 15 675) before admission to 83.1% (13 032 of 15 675) at discharge (P < .001), a net increase of 23.2%.

PRIMARY ANALYSES

The use of ACEIs in eligible patients at discharge did not increase over time from the first quarter of 2003 to the last quarter of 2004. Use of an ACEI or an ARB in eligible patients showed a slight decrease, from 84.0% in the first quarter of 2003 to 81.8% in the fourth quarter of 2004. In contrast, use of β-blockers increased substantially over the same period, from 76.3% to 86.4% (P < .001). Figure 1 and Figure 2 show the change in each of the 4 JCAHO performance measures and the change in quality measures during the 8 calendar quarters of OPTIMIZE-HF. The issuance of complete discharge instructions (from 46.8%-66.5%) and smoking-cessation counseling (from 48.2%-75.6%) increased significantly over time (P < .001 for both). Left ventricular function assessment started at a high rate and increased slightly but significantly (P < .001). Use of an ACEI at discharge remained unchanged during the entire study period (P = .18). An examination of time trends in additional OPTIMIZE-HF quality measures during the study period showed that the use of those β-blockers specifically proved to improve survival in randomized clinical trials (bisoprolol, carvedilol, and metoprolol) increased from 56.0% in the first quarter of 2003 to 68.3% in the last quarter of 2004 (P < .001). Aldosterone antagonists were used in 18.0% of patients, and use increased significantly over time; statins were given to 39.2% of patients, with use increasing over time; and anticoagulation therapy was prescribed for atrial fibrillation in 51.0% of eligible patients, with improved use over time.

Place holder to copy figure label and caption
Figure 1.

Change in performance measures over time. Q indicates quarter. Other abbreviations are defined in Table 1. *Values are number of patients for whom therapy was applied/eligible patients. †P value from Cochran-Armitage test for changes over time.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Change in other quality measures over time. AA indicates aldosterone antagonist; ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; BB, β-blocker; EB BB, evidence-based β-blocker; and Q, quarter. *Values are number of patients for whom therapy was applied/eligible patients. †P value from Cochran-Armitage test for changes over time.

Graphic Jump Location
SECONDARY ANALYSES

There were 1834 in-hospital deaths reported in the OPTIMIZE-HF registry of 48 612 enrolled patients (3.8%). The median length of stay was 4.0 days (25th-75th interquartile range, 3.0-7.0 days) and mean length of stay was 6.4 days (SD, 85.2 days). Mean length of stay improved significantly during the registry, from 7.5 to 6.2 days (P < .001). After multivariable risk adjustment and taking into account hospital clustering, this remained significant (P < .001). During the program, in-hospital mortality rates improved slightly, from 3.5% to 3.4%, but the difference did not reach statistical significance (P = .06). After risk adjustment and taking into account hospital clustering, a similar trend was still seen (P = .07).

During the 60- to 90-day period after hospital discharge, the follow-up cohort experienced 481 deaths (8.6% of the 5610 patients available at follow-up), occurring a median of 42.0 days (25th-75th interquartile range, 24.0-66.0 days) after discharge. Rehospitalization within the follow-up period occurred in 1715 patients (29.6%). The combined end point of mortality and rehospitalization was met in 36.2% of patients. During the program, unadjusted postdischarge mortality showed a trend toward improvement, from 9.9% to 6.3%, but the change did not reach statistical significance (P = .09). The combination postdischarge mortality and rehospitalization also showed a trend toward improvement, from 38.0% to 30.2% (P = .18). When adjusted outcomes also accounting for hospital clustering were examined by calendar time in the OPTIMIZE-HF registry, postdischarge death trended toward improvement, but the change was not significant (P = .74), and the change in postdischarge death and rehospitalization also did not reach significance (P = .78).

Use of PrCI tools was reported during hospitalization in 45.3% (22 017 of 48 612) of patients (23.0% admission order sets and 36.0% discharge checklists) and progressed steadily over the OPTIMIZE-HF registry duration, from 35.6% in the first quarter of 2003 to 54.1% in the last quarter of 2004 (P < .001). Use of recommended HF treatment was associated with the use of PrCI tools (Figure 3). Use of PrCI tools was associated with substantial improvements in clinical outcomes. In-hospital mortality was 2.5% in those with admission order set use vs 4.1% in those without (P < .001). Even after adjustment for other predictive variables and the propensity score and after taking hospital clustering into account, risk-adjusted in-hospital mortality was significantly lower in patients with use of an OPTIMIZE-HF admission order set than in those without (odds ratio, 0.71 [95% confidence interval, 0.53-0.95]; P = .02). Postdischarge 60- to 90-day death and rehospitalization rates were lower with than without the use of PrCI tools (34.8% vs38.2%; P = .02). The risk- and propensity-score–adjusted postdischarge mortality or rehospitalization rates were favorably influenced but did not reach significance (odds ratio, 0.93 [95% confidence interval, 0.81-1.06]; P = .27).

Place holder to copy figure label and caption
Figure 3.

Process-of-care improvement (PrCI) tools effect on the Joint Commission on Accreditation of Healthcare Organizations measures. Other abbreviations are defined in Table 1.

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A well-documented treatment gap exists for many patients with HF: despite compelling scientific evidence and readily accessible national guidelines, life-prolonging agents remain underused. By virtue of its design, combining a comprehensive patient registry with a performance-improvement program and capturing postdischarge patient outcomes, OPTIMIZE-HF has contributed to the current understanding of patients hospitalized with HF and has provided a new model of care for clinical management of HF in the hospital setting. OPTIMIZE-HF has shown that evidence-based, guideline-recommended HF therapies can be initiated in most real-world patients hospitalized with HF and that significant improvements in care can be achieved over time.

Angiotensin-converting enzyme inhibitors and β-blockers have been shown to significantly improve survival in patients with systolic HF.1216 Furthermore, in-hospital initiation of these and other evidence-based cardiovascular medication therapies has been demonstrated to increase their continued long-term use after hospital discharge, thereby improving clinical outcomes.1720 Nevertheless, many patients hospitalized for HF are not discharged receiving these guideline-recommended, life-prolonging agents, and they are not receiving other ACC/AHA guideline or JCAHO-recommended measures for promoting optimal outcomes.4,5,21 Several hospital-based, quality-of-care improvement initiatives have been reported involving the treatment of patients with cardiovascular disease.8,9,17,19

The JCAHO performed an uncontrolled quality-of-care improvement project that examined the change in recognized performance measures over time for several diseases, including HF.5 A total of 1864 accredited hospitals were required to submit data relating to their performance on the JCAHO core HF measures during a 2-year period (2002-2004). Participating hospitals received comparative feedback data on a quarterly basis; otherwise, no specific behavior-modification techniques or performance-enhancement incentives were used. During the 2-year study, all 4 core HF performance measures improved significantly. Discharge instructions increased from 29% to 55%, an absolute change of 26%; left ventricular function assessment improved by 7% (81% to 88%); and increases of 4% (73% to 77%) and 33% (39% to 72%) were seen in the use of ACEIs for left ventricular systolic dysfunction and smoking-cessation counseling, respectively. Those hospitals with the poorest baseline performance showed the greatest degree of improvement.5 In a Centers for Medicaid and Medicare Services Quality Improvement Organization program, determination of LVEF and discharge ACEI use were evaluated in up to 800 patients per state who were hospitalized with HF during the 1998-1999 to the 2000-2001 periods. The median state use of LVEF determination was 66% and increased to 70% (a 4% absolute improvement), whereas use of ACEIs for systolic HF at hospital discharge was 72% and decreased to 68% (a 4% absolute decrease).7

OPTIMIZE-HF has extended the general findings of previous quality-of-care improvement programs specifically for patients hospitalized with HF. The use of an ACEI or an ARB at hospital discharge was 82.6% and did not change over time. Other performance initiatives have also had little effect on treatment rates for ACEIs or ARBs, and further studies are necessary to better understand persistent barriers to their use and to further improve use of these agents in eligible patients. Although prescription of β-blockers is not a current JCAHO or ACC/AHA inpatient performance measure for HF, there was a notable influence on the prescription rate for β-blockers at discharge, with an absolute increase of 10% (from 76.3%-86.4%) during the 2-year program (P < .001). The use of specific β-blockers that have been proved to reduce mortality in randomized clinical trials increased even more, by 12% (56.0%-68.3%; P <.001). The 86.4% treatment rate at discharge for β-blockers is quite remarkable, equaling or exceeding the treatment rates achieved in dedicated specialty programs for HF management or in highly select patients enrolled in randomized clinical trials. For comparison, the β-blocker treatment rate at the time of hospital discharge in ideal candidates in the Enhanced Feedback for Effective Cardiac Treatment study was only 42%.21 A national initiative to improve the use of β-blockers in patients undergoing coronary artery bypass graft produced only a 3.7% absolute change in treatment rates during a 2-year period.22 Similarly, the performance measures of complete discharge instructions and smoking-cessation counseling increased significantly during OPTIMIZE-HF (both < .001). Use of PrCI tools increased from 35.6% to 54.1% by the end of the study. Use of PrCI tools was positively associated with an increase in the rate of adherence to all JCAHO HF performance measures (Figure 3). Of particular note, use of PrCI tools was also independently associated with reduced in-hospital mortality.

Analyses of the OPTIMIZE-HF results may be influenced by several limitations. Registry data relied on self-reporting by hospitals as opposed to abstraction from medical records by independent operators and had no method for separate verification of complete case ascertainment. However, the overall results were compatible with those seen in the Cardiovascular Cooperative Project and the Medicare Quality Improvement Program, which previously used medical chart abstractions for data collection,7,8 and were identical to the processes now being used by JCAHO and the Centers for Medicaid and Medicare Services for hospital comparisons.5 Given the overall large number of patients observed, some differences, although statistically significant, may not be clinically relevant. OPTIMIZE-HF was not a randomized clinical trial with a concurrent control group, and the improvements in performance measures may have been influenced by secular trends and concurrent factors other than participation in the study. However, OPTIMIZE-HF was associated with substantial improvements in therapies that were not part of any other concurrent local or regional performance-improvement initiative for HF, making external influence less likely. Furthermore, those quality-of-care improvement initiatives that did use concurrent controls, such as the Cardiovascular Cooperative Project and ACC-sponsored Guidelines Applied in Practice, resulted in changes consistent with those found in OPTIMIZE-HF. Although it was shown that the use of PrCI tools was independently associated with improved quality of care, its exact role relative to OPTIMIZE-HF participation cannot be ascertained. We assessed the use of order sets and discharge checklists only and thus cannot determine the role, if any, of other tool kit components. Also, despite multivariable and propensity score adjustment, we cannot exclude that residual measured and unmeasured confounding account for these observations. The findings are consistent with those of the Guidelines Applied in Practice study, in which PrCI tools similar to those used in OPTIMIZE-HF (but for patients with acute myocardial infarction) were associated with significant increases in performance measures as well as reduced in-hospital and postdischarge mortality.23

In conclusion, OPTIMIZE-HF is the largest national hospital-based program dedicated to quality-of-care improvement for patients hospitalized with HF in the United States. Hospitals participating in OPTIMIZE-HF demonstrated an increase in adherence to national guideline-recommended therapies over time. There were trends for reduction in in-hospital mortality, postdischarge death, and the combination of postdischarge death and rehospitalization and a significant reduction in mean length of stay. The use of PrCI tools was positively associated with increased adherence to JCAHO core performance measures and improvements in in-hospital mortality rates. The results of OPTIMIZE-HF and other health care–improvement programs demonstrate that the quality of care provided to patients with cardiovascular disease can be enhanced by the use of patient data submission and performance feedback, concentrating on specific processes of care proven to improve outcomes.

Correspondence: Gregg C. Fonarow, MD, Ahmanson-UCLA Cardiomyopathy Center, UCLA Medical Center, 10833 LeConte Ave, Room 47-123 CHS, Los Angeles, CA 90095-1679 (gfonarow@mednet.ucla.edu).

Accepted for Publication: February 24, 2007.

Author Contributions: Dr Fonarow had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All of the authors approved of the final manuscript before submission. Study concept and design: Fonarow, Abraham, Albert, Gattis Stough, Gheorghiade, Greenberg, and Young. Acquisition of data: Fonarow, Abraham, Albert, Greenberg, and O’Connor. Analysis and interpretation of data: Fonarow, Albert, Gattis Stough, Greenberg, O’Connor, Pieper, Sun, Yancy, and Young. Drafting of the manuscript: Fonarow, O’Connor, and Sun. Critical revision of the manuscript for important intellectual content: Fonarow, Abraham, Albert, Gattis Stough, Gheorghiade, Greenberg, O’Connor, Pieper, Sun, Yancy, and Young. Statistical analysis: Fonarow, Pieper, and Sun. Obtained funding: Fonarow. Administrative, technical, and material support: Gattis Stough and Gheorghiade. Study supervision: Fonarow, Greenberg, and Yancy.

Financial Disclosure: Dr Fonarow has received research grants from Amgen, Biosite Inc, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Medtronic Inc, Merck & Co, Pfizer, Sanofi-Aventis, Scios Inc, and the National Institutes of Health (NIH); has been on the speakers' bureau or has received honoraria in the past 5 years from Amgen, AstraZeneca, Biosite Inc, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Kos, Medtronic Inc, Merck & Co, NitroMed, Pfizer, Sanofi-Aventis, Schering-Plough, Scios Inc, St Jude Medical, Takeda, and Wyeth; has been a consultant for Biosite Inc, Bristol-Myers Squibb, Boston Scientific/Guidant, GlaxoSmithKline, Medtronic Inc, Merck & Co, NitroMed, Orqis Medical, Pfizer, Sanofi-Aventis, Schering-Plough, Scios Inc, and Wyeth; and reports editorial board involvement with American Heart Journal, Circulation, Journal of Cardiac Failure, Journal of the American College of Cardiology, and Reviews of Cardiovascular Medicine. Dr Abraham has received research grants from Amgen, Biotronik, CHF Solutions, GlaxoSmithKline, Heart Failure Society of America, Medtronic Inc, Myogen, NIH, Orqis Medical, Otsuka Maryland Research Institute, Paracor, and Scios Inc; has been a consultant or on the speakers' bureau for Amgen, AstraZeneca, Boehringer-Ingelheim, CHF Solutions, GlaxoSmithKline, Guidant, Medtronic Inc, Merck & Co, Pfizer, ResMed, Respironics, Scios Inc, and St Jude Medical; is on the advisory board of CardioKine, CardioKinetix Inc, CHF Solutions, Department of Veterans Affairs Cooperative Studies Program, Inovise, NIH, and Savacor Inc; has received honoraria from AstraZeneca, Boehringer-Ingelheim, GlaxoSmithKline, Guidant, Medtronic Inc, Merck & Co, Pfizer, ResMed, Respironics, Scios Inc, and St Jude Medical; and reports editorial board involvement with Congestive Heart Failure, Current Cardiology Reviews, Current Heart Failure Reports, Expert Review of Cardiovascular Therapy, Journal Watch Cardiology, PACE–Pacing and Clinical Electrophysiology, The American Heart Hospital Journal, and The Journal of Heart Failure. Dr Albert is a consultant for GlaxoSmithKline and Medtronic Inc; is on the speakers' bureau for GlaxoSmithKline, Medtronic Inc, NitroMed, and Scios Inc; is employed by the Cleveland Clinic Foundation; and reports editorial board involvement with Progress in Cardiovascular Nursing (senior editor), Journal of Cardiovascular Nursing, and Critical Care Nurse. Dr Gattis Stough has received research grants from Actelion, GlaxoSmithKline, Medtronic Inc, Otsuka, and Pfizer; is a consultant or on the speakers' bureau for Abbott, AstraZeneca, GlaxoSmithKline, Medtronic Inc, Novacardia, Otsuka, Protein Design Labs, RenaMed, Sigma Tau, and Scios Inc; and has received honoraria from Abbott, AstraZeneca, GlaxoSmithKline, Medtronic Inc, and Pfizer. Dr Gheorghiade has received research grants from NIH, Otsuka, Sigma Tau, Merck & Co, and Scios Inc; has been a consultant for Debbio Pharm, Errekappa Terapeutici, GlaxoSmithKline, Protein Design Labs, and Medtronic Inc; has received honoraria from Abbott, AstraZeneca, GlaxoSmithKline, Medtronic Inc, Otsuka, Protein Design Lab, Scios Inc, and Sigma Tau; and reports editorial board involvement with Acute Cardiac Care Journal (associate editor), American Heart Journal, American Journal of Therapeutics (associate editor), Archives for Chest Disease (associate editor), Current Cardiology Reviews, Expert Review of Cardiovascular Therapy, Heart Disease: A Journal of Cardiovascular Medicine, Heart Failure Reviews, Heart International, Journal of Cardiac Failure, Journal of the American College of Cardiology,Italian Heart Journal, The American Journal of Cardiology, The Journal of Heart Disease, and The Journal of Heart Failure. Dr Greenberg has received research grant support from Amgen, Cardiodynamics, GlaxoSmithKline, Millennium, Novacardia, Otsuka, Pfizer, Sanofi-Aventis, and Titan; is on the speakers' bureau or is a consultant for Amgen, AstraZeneca, GlaxoSmithKline, Guidant Corp, Medtronic Inc, Merck & Co, NitroMed, Pfizer, Remon Medical Technologies, and Scios Inc; is an advisory board member for CHF Solutions, GlaxoSmithKline, and NitroMed; has received honoraria from AstraZeneca, GlaxoSmithKline, Medtronic Inc, Merck & Co, NitroMed, Novartis, Pfizer, and Scios Inc; and reports editorial board involvement with Congestive Heart Failure and Journal of the American College of Cardiology. Dr O’Connor has received research grant support from NIH; is on the speakers' bureau and/or is a consultant for Amgen, AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Guidant, Medtronic Inc, Merck, NitroMed, Novartis, Otsuka, Pfizer, and Scios Inc; and has received honoraria from GlaxoSmithKline, Pfizer, and Otsuka. Mss Pieper and Sun are employees of Duke Clinical Research Institute (DCRI). Dr Yancy has received research grants from Cardiodynamics, GlaxoSmithKline, Scios Inc, Medtronic Inc, and NitroMed; is a consultant or on the speakers' bureau for AstraZeneca, Cardiodynamics, GlaxoSmithKline, Medtronic Inc, NitroMed, Novartis, and Scios Inc; is on the advisory board for CHF Solutions, the Food and Drug Administration cardiovascular device panel, and NIH; has received honoraria from AstraZeneca, Cardiodynamics, GlaxoSmithKline, Medtronic Inc, Novartis, and Scios Inc; and reports editorial board involvement with Circulation (guest editor), Congestive Heart Failure, Current Heart Failure Reports, Journal of Acute Cardiac Care, Journal of Urban Cardiology, and The American Heart Journal. Dr Young has received research grants from Abbott, Acorn, Amgen, Artesion Therapeutics, AstraZeneca, Biosite Inc, GlaxoSmithKline, Guidant, Medtronic Inc, MicroMed, NIH, Scios Inc, Vasogen, and World Heart; is a consultant for Abbott, Acorn, Amgen, Biomax Canada, Biosite Inc, Boehringer-Ingelheim, Bristol-Myers Squibb, Cotherix, Edwards Lifescience, GlaxoSmithKline, Guidant, Medtronic Inc, MicroMed, Novartis, Paracor, Proctor & Gamble, Protemix, Scios Inc, Sunshine, Thoratec, Transworld Medical Corporation, Vasogen, Viacor, and World Heart; and reports editorial board involvement with Journal of Heart and Lung Transplantation, Evidence-Based Medicine, Journal of the American College of Cardiology, American Heart Journal, Cleveland Clinic Journal of Medicine, Cardiology Today, Graft, TheHeart.org, Transplantation and Immunology Letter, and American Society of Transplantation Newsletter.

Funding/Support: This study was supported by GlaxoSmithKline.

Group Information: A list of the OPTIMIZE-HF hospitals and investigators was published in JAMA. 2007;297(1):68-69.

Role of the Sponsor: GlaxoSmithKline was involved in the design and conduct of the OPTIMIZE-HF registry and funded data collection and management through Outcome Sciences, Inc, and data management and statistical analyses through DCRI. The sponsor was not involved in the management, analysis, or interpretation of data or the preparation of the manuscript. GlaxoSmithKline reviewed the manuscript before submission.

Additional Contributions: Accel Health provided administrative and material support.

American Heart Association, Heart Disease and Stroke Statistics: 2007 Update.  Dallas, TX American Heart Association2007;
Hunt  SAAbraham  WTChin  MH  et al. Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure, ACC/AHA 2005 Guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. American College of Cardiology Web site. 2005;http://www.acc.org/qualityandscience/clinical/guidelines/failure/update/index.pdf. Accessed February 4, 2007
Jha  AKLi  ZOrav  EJEpstein  AM Care in US hospitals: the Hospital Quality Alliance program. N Engl J Med 2005;353 (3) 265- 274
PubMed Link to Article
Bonow  ROBennett  SCasey  DE  Jr  et al. Writing Committee to Develop Heart Failure Clinical Performance Measures, ACC/AHA clinical performance measures for adults with chronic heart failure: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Heart Failure Clinical Performance Measures) endorsed by the Heart Failure Society of America. J Am Coll Cardiol 2005;46 (6) 1144- 1178
PubMed Link to Article
Williams  SCSchmaltz  SPMorton  DJKoss  RGLoeb  JM Quality of care in U.S. hospitals as reflected by standardized measures, 2002-2004. N Engl J Med 2005;353 (3) 255- 264
PubMed Link to Article
Joint Commission on Accreditation of Healthcare Organizations, Specification Manual for National Implementation of Hospital Core Measures.  Oakbrook Terrace, IL JCAHO2004;
Jencks  SFHuff  EDCuerdon  T Change in the quality of care delivered to Medicare beneficiaries: 1998-1999 to 2000-2001. JAMA 2003;289 (3) 305- 312
PubMed Link to Article
Marciniak  TAEllerbeck  EFRadford  MJ  et al.  Improving the quality of care for Medicare patients with acute myocardial infarction: results from the Cooperative Cardiovascular Project. JAMA 1998;279 (17) 1351- 1357
PubMed Link to Article
Mehta  RHMontoye  CKGallogly  M  et al. GAP Steering Committee of the American College of Cardiology, Improving quality of care for acute myocardial infarction: the Guidelines Applied in Practice (GAP) Initiative. JAMA 2002;287 (10) 1269- 1276
PubMed Link to Article
Fonarow  GCAbraham  WTAlbert  NM  et al.  Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF): rationale and design. Am Heart J 2004;148 (1) 43- 51
PubMed Link to Article
Gheorghiade  MAbraham  WTAlbert  NM  et al. OPTIMIZE-HF Investigators and Coordinators, Systolic blood pressure at admission, clinical characteristics, and outcomes in patients hospitalized with acute heart failure. JAMA 2006;296 (18) 2217- 2226
PubMed Link to Article
CONSENSUS Trial Study Group, Effects of enalapril on mortality in severe congestive heart failure: results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). N Engl J Med 1987;316 (23) 1429- 1435
PubMed Link to Article
SOLVD Investigators, Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med 1991;325 (5) 293- 302
PubMed Link to Article
CIBIS-II Investigators, The Cardiac Insufficiency Bisoprolol Study II (CIBIS-II): a randomised trial. Lancet 1999;353 (9146) 9- 13
PubMed Link to Article
MERIT-HF Investigators, Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF). Lancet 1999;353 (9169) 2001- 2007
PubMed Link to Article
Packer  MCoats  AJFowler  MB  et al. Carvedilol Prospective Randomized Cumulative Survival Study Group, Effect of carvedilol on survival in severe chronic heart failure. N Engl J Med 2001;344 (22) 1651- 1658
PubMed Link to Article
Fonarow  GCGawlinski  AMoughrabi  STillisch  JH Improved treatment of coronary heart disease by implementation of a Cardiac Hospitalization Atherosclerosis Management Program (CHAMP). Am J Cardiol 2001;87 (7) 819- 822
PubMed Link to Article
Gattis  WAO’Connor  CMGallup  DSHasselblad  VGheorghiade  M Predischarge initiation of carvedilol in patients hospitalized for decompensated heart failure: results of the Initiation Management Predischarge: Process for Assessment of Carvedilol Therapy in Heart Failure (IMPACT-HF) trial. J Am Coll Cardiol 2004;43 (9) 1534- 1541
PubMed Link to Article
Pearson  TAHorne  BDMaycock  CA  et al.  An institutional heart failure discharge medication program reduces future cardiovascular readmissions and mortality: an analysis of 19,083 heart failure patients [abstract 3918]. Circulation 2001;104 (17) ((suppl II)) II-838
Lappé  JMMuhlestein  JBLappé  DL  et al.  Improvements in 1-year cardiovascular clinical outcomes associated with a hospital-based discharge medication program. Ann Intern Med 2004;141 (6) 446- 453
PubMed Link to Article
Lee  DSTu  JVJuurlink  DN  et al.  Risk-treatment mismatch in the pharmacotherapy of heart failure. JAMA 2005;294 (10) 1240- 1247
PubMed Link to Article
Ferguson  TB  JrPeterson  EDCoombs  LP  et al. Society of Thoracic Surgeons and the National Cardiac Database, Use of continuous quality improvement to increase use of process measures in patients undergoing coronary artery bypass graft surgery: a randomized controlled trial. JAMA 2003;290 (1) 49- 56
PubMed Link to Article
Eagle  KAMontoye  CKRiba  AL  et al. American College of Cardiology Foundation (Bethesda, Maryland) Guidelines Applied in Practice Steering Committee, Guideline-based standardized care is associated with substantially lower mortality in Medicare patients with acute myocardial infarction: the American College of Cardiology's Guidelines Applied in Practice (GAP) Projects in Michigan. J Am Coll Cardiol 2005;46 (7) 1242- 1248
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Change in performance measures over time. Q indicates quarter. Other abbreviations are defined in Table 1. *Values are number of patients for whom therapy was applied/eligible patients. †P value from Cochran-Armitage test for changes over time.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Change in other quality measures over time. AA indicates aldosterone antagonist; ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; BB, β-blocker; EB BB, evidence-based β-blocker; and Q, quarter. *Values are number of patients for whom therapy was applied/eligible patients. †P value from Cochran-Armitage test for changes over time.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Process-of-care improvement (PrCI) tools effect on the Joint Commission on Accreditation of Healthcare Organizations measures. Other abbreviations are defined in Table 1.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Performance and Quality of Care Measures Assessed in OPTIMIZE-HF
Table Graphic Jump LocationTable 2. Participating Hospital Characteristics
Table Graphic Jump LocationTable 3. Patient Characteristics and Comorbidities a

References

American Heart Association, Heart Disease and Stroke Statistics: 2007 Update.  Dallas, TX American Heart Association2007;
Hunt  SAAbraham  WTChin  MH  et al. Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure, ACC/AHA 2005 Guideline update for the diagnosis and management of chronic heart failure in the adult: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. American College of Cardiology Web site. 2005;http://www.acc.org/qualityandscience/clinical/guidelines/failure/update/index.pdf. Accessed February 4, 2007
Jha  AKLi  ZOrav  EJEpstein  AM Care in US hospitals: the Hospital Quality Alliance program. N Engl J Med 2005;353 (3) 265- 274
PubMed Link to Article
Bonow  ROBennett  SCasey  DE  Jr  et al. Writing Committee to Develop Heart Failure Clinical Performance Measures, ACC/AHA clinical performance measures for adults with chronic heart failure: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Heart Failure Clinical Performance Measures) endorsed by the Heart Failure Society of America. J Am Coll Cardiol 2005;46 (6) 1144- 1178
PubMed Link to Article
Williams  SCSchmaltz  SPMorton  DJKoss  RGLoeb  JM Quality of care in U.S. hospitals as reflected by standardized measures, 2002-2004. N Engl J Med 2005;353 (3) 255- 264
PubMed Link to Article
Joint Commission on Accreditation of Healthcare Organizations, Specification Manual for National Implementation of Hospital Core Measures.  Oakbrook Terrace, IL JCAHO2004;
Jencks  SFHuff  EDCuerdon  T Change in the quality of care delivered to Medicare beneficiaries: 1998-1999 to 2000-2001. JAMA 2003;289 (3) 305- 312
PubMed Link to Article
Marciniak  TAEllerbeck  EFRadford  MJ  et al.  Improving the quality of care for Medicare patients with acute myocardial infarction: results from the Cooperative Cardiovascular Project. JAMA 1998;279 (17) 1351- 1357
PubMed Link to Article
Mehta  RHMontoye  CKGallogly  M  et al. GAP Steering Committee of the American College of Cardiology, Improving quality of care for acute myocardial infarction: the Guidelines Applied in Practice (GAP) Initiative. JAMA 2002;287 (10) 1269- 1276
PubMed Link to Article
Fonarow  GCAbraham  WTAlbert  NM  et al.  Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF): rationale and design. Am Heart J 2004;148 (1) 43- 51
PubMed Link to Article
Gheorghiade  MAbraham  WTAlbert  NM  et al. OPTIMIZE-HF Investigators and Coordinators, Systolic blood pressure at admission, clinical characteristics, and outcomes in patients hospitalized with acute heart failure. JAMA 2006;296 (18) 2217- 2226
PubMed Link to Article
CONSENSUS Trial Study Group, Effects of enalapril on mortality in severe congestive heart failure: results of the Cooperative North Scandinavian Enalapril Survival Study (CONSENSUS). N Engl J Med 1987;316 (23) 1429- 1435
PubMed Link to Article
SOLVD Investigators, Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med 1991;325 (5) 293- 302
PubMed Link to Article
CIBIS-II Investigators, The Cardiac Insufficiency Bisoprolol Study II (CIBIS-II): a randomised trial. Lancet 1999;353 (9146) 9- 13
PubMed Link to Article
MERIT-HF Investigators, Effect of metoprolol CR/XL in chronic heart failure: Metoprolol CR/XL Randomised Intervention Trial in Congestive Heart Failure (MERIT-HF). Lancet 1999;353 (9169) 2001- 2007
PubMed Link to Article
Packer  MCoats  AJFowler  MB  et al. Carvedilol Prospective Randomized Cumulative Survival Study Group, Effect of carvedilol on survival in severe chronic heart failure. N Engl J Med 2001;344 (22) 1651- 1658
PubMed Link to Article
Fonarow  GCGawlinski  AMoughrabi  STillisch  JH Improved treatment of coronary heart disease by implementation of a Cardiac Hospitalization Atherosclerosis Management Program (CHAMP). Am J Cardiol 2001;87 (7) 819- 822
PubMed Link to Article
Gattis  WAO’Connor  CMGallup  DSHasselblad  VGheorghiade  M Predischarge initiation of carvedilol in patients hospitalized for decompensated heart failure: results of the Initiation Management Predischarge: Process for Assessment of Carvedilol Therapy in Heart Failure (IMPACT-HF) trial. J Am Coll Cardiol 2004;43 (9) 1534- 1541
PubMed Link to Article
Pearson  TAHorne  BDMaycock  CA  et al.  An institutional heart failure discharge medication program reduces future cardiovascular readmissions and mortality: an analysis of 19,083 heart failure patients [abstract 3918]. Circulation 2001;104 (17) ((suppl II)) II-838
Lappé  JMMuhlestein  JBLappé  DL  et al.  Improvements in 1-year cardiovascular clinical outcomes associated with a hospital-based discharge medication program. Ann Intern Med 2004;141 (6) 446- 453
PubMed Link to Article
Lee  DSTu  JVJuurlink  DN  et al.  Risk-treatment mismatch in the pharmacotherapy of heart failure. JAMA 2005;294 (10) 1240- 1247
PubMed Link to Article
Ferguson  TB  JrPeterson  EDCoombs  LP  et al. Society of Thoracic Surgeons and the National Cardiac Database, Use of continuous quality improvement to increase use of process measures in patients undergoing coronary artery bypass graft surgery: a randomized controlled trial. JAMA 2003;290 (1) 49- 56
PubMed Link to Article
Eagle  KAMontoye  CKRiba  AL  et al. American College of Cardiology Foundation (Bethesda, Maryland) Guidelines Applied in Practice Steering Committee, Guideline-based standardized care is associated with substantially lower mortality in Medicare patients with acute myocardial infarction: the American College of Cardiology's Guidelines Applied in Practice (GAP) Projects in Michigan. J Am Coll Cardiol 2005;46 (7) 1242- 1248
PubMed Link to Article

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