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Palo Alto, CA, United States

Heidenreich P.,Stanford University | Heidenreich P.,Palo Alto Medical Center
Heart Failure Clinics | Year: 2015

There is substantial opportunity to reduce health care costs through prevention of heart failure. Team-based management of medical homes and large populations will be important for the success of any prevention interventions. Clinical trials of treatment are needed to show that heart failure is reduced by treatment. A team-based approach to treatment of asymptomatic left ventricular systolic dysfunction (LVSD) can work well with the availability of electronic medical records and a population approach to health. Attention should be given to optimizing risk factor reduction and preventive treatment with angiotensin-converting enzyme inhibitors/angiotensin receptor blockers and β-blockers if LVSD is present. © 2015.

Anderson J.L.,Intermountain Medical Center | Heidenreich P.A.,Palo Alto Medical Center | Barnett P.G.,Palo Alto Medical Center | Creager M.A.,Brigham and Womens Hospital | And 13 more authors.
Circulation | Year: 2014

Traditionally, resource utilization and value considerations have been explicitly excluded from practice guidelines and performance measures formulations, although they often are implicitly considered. This document challenges this historical policy. With accelerating healthcare costs and the desire to achieve the best value (health benefit for every dollar spent), there is growing recognition of the need for more explicit and transparent assessment of the value of health care. Thus, from a societal policy perspective, a critical healthcare goal should be to achieve the best possible health outcomes with finite healthcare resources. Consideration of cost/resource utilization as an outcome presents special challenges. Frequently, the scientific evidence base is inadequate to accurately assess cost-benefit. Also, costs may vary widely by practice setting, locality, and nationality, and over time. Moreover, individuals bear the burden of adverse health outcomes, yet costs typically are shared by society (eg, by families, employers, government, premium payers, fellow employees, taxpayers). Finally, attitudes differ among stakeholders about the extent to which cost should influence treatment decisions for individual patients and who should bear these costs. Consequently, resource utilization debates often become highly politicized, and significant conflicts of interest among individuals impaneled to formulate resource-based guidelines may be difficult to avoid. A transparent and consistent approach to considering value is needed when making healthcare decisions. This must begin with an understanding of key economic concepts, including allocation of resources to produce more health care of various types, methods for assessing the monetary value of these resources, and the perspective used for making this assessment of the value of healthcare expenditures (ie, societal perspective, individual patient costs, hospital costs, and payer costs). Methodological challenges include limitations in the robustness and quality of value evidence, regional variations in costs, and outdated (temporally dynamic) and biased data. Despite these challenges, the writing committee agreed that progress has been made in these areas and that the need for greater transparency and utility in addressing resource issues has become acute enough that the time has come to include cost-effectiveness/value assessments and recommendations in practice guidelines and performance measures. The writing committee chose to emphasize the nomenclatures of "value" and "resource utilization" over "cost." Given evidence and resource limitations, the writing committee also recognized the need to selectively target guidelines and performance measures for initial resource use evaluation. A plan for performing a thorough, independent literature search and a consistent method for assessing the quality and potential for bias of identified articles should be prospectively designated. The evidence base then should be synthesized to provide an overall value classification together with a supporting level of evidence, which should be reported alongside but separate from the scientific class and level/quality of evidence. The proposed level of value (LOV) categories, outlined in Section 5 of this paper, are high value (H), intermediate value (I), and low value (L), augmented as appropriate with uncertain value (U) and value not assessed (NA). For example, high value might be set at <$50 000 and low value at >$150 000 per quality of life-year added, indexed to gross domestic product (GDP) or as otherwise determined by agreed-on societal norms. The value category (ie, H, I, L, U) would be supplemented by a level/quality of evidence paralleling those for scientific level of evidence (ie, A, B, and C) and based on the robustness of the database supporting the value category. These value assessments would also inform development of performance measures. Class I recommendations determined to be of low value would not be recommended as performance measures. Because the value of a given care practice will change if the cost or benefit of the practice changes, timely review and updates of guidelines will be even more important when value determinations are included in the guidelines. This report stresses that the value category should be only one of several considerations in medical decision making and resource allocation. Providers and society may be willing to pay more for the only effective treatment for a rare disease (eg, congenital versus adult cardiac care). As noted, given differing methodologies, quality of evidence, and temporal and geographic dynamics of resource and value assessments, the value level of a recommendation should be given separately and not averaged together with the level/quality of evidence from clinical trial results as a single metric. It is anticipated that these will usually be concordant, but in some cases, discordance may be noted (eg, an intervention is shown to provide a small incremental health care benefit but at a high cost in resources). Defining how medical decision making should be affected in specific instances by such discordance between value and guideline recommendations is controversial, but highlighting these instances explicitly and transparently will further inform appropriate discussion and policy making. © 2014 American Heart Association, Inc.

Hernandez A.F.,Duke University | Fonarow G.C.,University of California at Los Angeles | Liang L.,Duke University | Heidenreich P.A.,Palo Alto Medical Center | And 2 more authors.
Circulation | Year: 2011

BACKGROUND-: Process and outcome measures are often used to quantify quality of care in hospitals. Whether these quality measures correlate with one another and the degree to which hospital provider rankings shift on the basis of the performance metric is uncertain. METHODS AND RESULTS-: Heart failure patients > 65 years of age hospitalized in the Get With the Guidelines-Heart Failure registry of the American Heart Association were linked to Medicare claims from 2005 to 2006. Hospitals were ranked by (1) composite adherence scores for 5 heart failure process measures, (2) composite adherence scores for emerging quality measures, (3) risk-adjusted 30-day death after admission, and (4) risk-adjusted 30-day readmission after discharge. Hierarchical models using shrinkage estimates were performed to adjust for case mix and hospital volume. There were 19 483 patients hospitalized from 2005 to 2006 from 153 hospitals. The overall median composite adherence rate to heart process measures was 85.8% (25th, 75th percentiles 77.5, 91.4). Median 30-day risk-adjusted mortality was 9.0% (7.9, 10.4). Median risk-adjusted 30-day readmission was 22.9% (22.1, 23.5). The weighted κ for remaining within the top 20th percentile or bottom 20th percentile was ≤0.15 and the Spearman correlation overall was ≤0.21 between the different measures of quality of care. The average shift in ranks was 33 positions (13, 68) when criteria were changed from 30-day mortality to readmission and 51 positions (22, 76) when ranking metric changed from 30-day mortality to composite process adherence. CONCLUSIONS-: Agreement between different methods of ranking hospital-based quality of care and 30-day mortality or readmission rankings was poor. Profiling quality of care will require multidimensional ranking methods and/or additional measures. Copyright © 2011 American Heart Association.

Hernandez A.F.,Duke University | Greiner M.A.,Duke University | Fonarow G.C.,University of California at Los Angeles | Hammill B.G.,Duke University | And 4 more authors.
JAMA - Journal of the American Medical Association | Year: 2010

Context: Readmission after hospitalization for heart failure is common. Early outpatient follow-up after hospitalization has been proposed as a means of reducing readmission rates. However, there are limited data describing patterns of follow-up after heart failure hospitalization and its association with readmission rates. Objective: To examine associations between outpatient follow-up within 7 days after discharge from a heart failure hospitalization and readmission within 30 days. Design, Setting, and Patients: Observational analysis of patients 65 years or older with heart failure and discharged to home from hospitals participating in the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure and the Get With the Guidelines-Heart Failure quality improvement program from January 1, 2003, through December 31, 2006. Main Outcome Measure: All-cause readmission within 30 days after discharge. Results: The study population included 30 136 patients from 225 hospitals. Median length of stay was 4 days (interquartile range, 2-6) and 21.3% of patients were readmitted within 30 days. At the hospital level, the median percentage of patients who had early follow-up after discharge from the index hospitalization was 38.3% (interquartile range, 32.4%-44.5%). Compared with patients whose index admission was in a hospital in the lowest quartile of early follow-up (30-day readmission rate, 23.3%), the rates of 30-day readmission were 20.5% among patients in the second quartile (risk-adjusted hazard ratio [HR], 0.85;95%confidence interval [CI], 0.78-0.93), 20.5% among patients in the third quartile (risk-adjusted HR, 0.87; 95% CI, 0.78-0.96), and 20.9% among patients in the fourth quartile (risk-adjusted HR, 0.91; 95% CI, 0.83-1.00). Conclusions: Among patients who are hospitalized for heart failure, substantial variation exists in hospital-level rates of early outpatient follow-up after discharge. Patients who are discharged from hospitals that have higher early follow-up rates have a lower risk of 30-day readmission. Trial Registration: clinicaltrials.gov Identifier: NCT00344513. ©2010 American Medical Association. All rights reserved.

Rosen A.C.,Stanford University | Rosen A.C.,Palo Alto Medical Center | Sugiura L.,Stanford University | Kramer J.H.,The Medical Memory | And 4 more authors.
Journal of Alzheimer's Disease | Year: 2011

A randomized pilot experiment examined the neural substrates of response to cognitive training in participants with mild cognitive impairment (MCI). Participants performed exercises previously demonstrated to improve verbal memory and an active control group performed other computer activities. An auditory-verbal fMRI task was conducted before and after the two-month training program. Verbal memory scores improved significantly and left hippocampal activation increased significantly in the experimental group (gains in 5 of 6 participants) relative to the control group (reductions in all 6 participants). Results suggest that the hippocampus in MCI may retain sufficient neuroplasticity to benefit from cognitive training. © 2011 IOS Press and the authors. All rights reserved.

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