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Chuzi S, Lindenauer PK, Faridi K, Priya A, Pekow PS, D'Aunno T, Mazor KM, Stefan MS, Spatz ES, Gilstrap L, Werner RM, Lagu T. Variation in Risk-Standardized Acute Admission Rates Among Patients With Heart Failure in Accountable Care Organizations: Implications for Quality Measurement. J Am Heart Assoc 2023; 12:e029758. [PMID: 37345796 PMCID: PMC10356066 DOI: 10.1161/jaha.122.029758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 05/10/2023] [Indexed: 06/23/2023]
Abstract
Background Accountable care organizations (ACOs) aim to improve health care quality and reduce costs, including among patients with heart failure (HF). However, variation across ACOs in admission rates for patients with HF and associated factors are not well described. Methods and Results We identified Medicare fee-for-service beneficiaries with HF who were assigned to a Medicare Shared Savings Program ACO in 2017 and survived ≥30 days into 2018. We calculated risk-standardized acute admission rates across ACOs, assigned ACOs to 1 of 3 performance categories, and examined associations between ACO characteristics and performance categories. Among 1 232 222 beneficiaries with HF, 283 795 (mean age, 81 years; 54% women; 86% White; 78% urban) were assigned to 1 of 467 Medicare Shared Savings Program ACOs. Across ACOs, the median risk-standardized acute admission rate was 87 admissions per 100 people, ranging from 61 (minimum) to 109 (maximum) admissions per 100 beneficiaries. Compared to the overall average, 13% of ACOs performed better on risk-standardized acute admission rates, 72% were no different, and 14% performed worse. Most ACOs with better performance had fewer Black beneficiaries and were not hospital affiliated. Most ACOs that performed worse than average were large, located in the Northeast, had a hospital affiliation, and had a lower proportion of primary care providers. Conclusions Admissions are common among beneficiaries with HF in ACOs, and there is variation in risk-standardized acute admission rates across ACOs. ACO performance was associated with certain ACO characteristics. Future studies should attempt to elucidate the relationship between ACO structure and characteristics and admission risk.
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Affiliation(s)
- Sarah Chuzi
- Division of Cardiology, Department of MedicineNorthwestern University Feinberg School of MedicineChicagoILUSA
| | - Peter K. Lindenauer
- Department of Healthcare Delivery and Population SciencesUniversity of Massachusetts Chan Medical School–BaystateSpringfieldMAUSA
| | - Kamal Faridi
- Department of Healthcare Delivery and Population SciencesUniversity of Massachusetts Chan Medical School–BaystateSpringfieldMAUSA
| | - Aruna Priya
- Department of Healthcare Delivery and Population SciencesUniversity of Massachusetts Chan Medical School–BaystateSpringfieldMAUSA
| | - Penelope S. Pekow
- Department of Healthcare Delivery and Population SciencesUniversity of Massachusetts Chan Medical School–BaystateSpringfieldMAUSA
| | - Thomas D'Aunno
- Wagner Graduate School of Public Service at New York UniversityNew YorkNYUSA
| | - Kathleen M. Mazor
- Division of Health Systems Science, Department of MedicineUniversity of Massachusetts Chan Medical SchoolWorcesterMAUSA
| | - Mihaela S. Stefan
- Department of MedicineUniversity of Massachusetts Chan Medical SchoolSpringfieldMAUSA
| | - Erica S. Spatz
- Section of Cardiovascular MedicineYale School of MedicineNew HavenCTUSA
- Department of EpidemiologyYale School of Public HealthNew HavenCTUSA
- Yale Center for Outcomes Research and EvaluationNew HavenCTUSA
| | - Lauren Gilstrap
- Heart and Vascular Center, Dartmouth Hitchcock Medical CenterThe Dartmouth Institute, Geisel School of Medicine at DartmouthLebanonNHUSA
| | - Rachel M. Werner
- Leonard Davis Institute of Health Economics and Perelman School of MedicineUniversity of Pennsylvania; Corporal Michael J. Crescenz VA Medical CenterPhiladelphiaPAUSA
| | - Tara Lagu
- Institute for Public Health and Medicine, Northwestern University Feinberg School of MedicineChicagoILUSA
- Division of Hospital Medicine, Department of MedicineNorthwestern University Feinberg School of MedicineChicagoILUSA
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Meekers E, Mullens W. Spot Urinary Sodium Measurements: the Future Direction of the Treatment and Follow-up of Patients with Heart Failure. Curr Heart Fail Rep 2023; 20:88-100. [PMID: 36807114 DOI: 10.1007/s11897-023-00591-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/16/2022] [Indexed: 02/23/2023]
Abstract
PURPOSE OF REVIEW Heart failure is characterized by episodes of congestion with need for hospitalization. The current metrics lack the accuracy to predict and prevent episodes of congestion and to guide diuretic titration to reach euvolemia in case of decompensation. This article aims to provide answers to the role of urinary sodium measurements in acute and chronic heart failure. RECENT FINDINGS In acute heart failure, urinary sodium concentrations at the moment of admission and after diuretic administration are correlated with short- and long-term outcome. As this is a reflection of the degree of sodium retention, it can be used as a guide in the diuretic titration. In chronic heart failure, it might be used to predict and consequently prevent episodes of decompensation. Urinary sodium measurements hold great promises to be a novel diagnostic and therapeutic parameter in patients with acute and chronic heart failure. However, more research is needed.
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Affiliation(s)
- Evelyne Meekers
- Hasselt University, Universiteitslaan 1, 3500, Hasselt, Belgium.
- Ziekenhuis Oost-Limburg, Schiepse Bos 6, 3600, Genk, Belgium.
| | - Wilfried Mullens
- Hasselt University, Universiteitslaan 1, 3500, Hasselt, Belgium
- Ziekenhuis Oost-Limburg, Schiepse Bos 6, 3600, Genk, Belgium
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Di Tanna GL, Angell B, Urbich M, Lindgren P, Gaziano TA, Globe G, Stollenwerk B. A Proposal of a Cost-Effectiveness Modeling Approach for Heart Failure Treatment Assessment: Considering the Short- and Long-Term Impact of Hospitalization on Event Rates. PHARMACOECONOMICS 2022; 40:1095-1105. [PMID: 35960435 DOI: 10.1007/s40273-022-01174-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/05/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND The rate of events such as recurrent heart failure (HF) hospitalization and death are known to dramatically increase directly after HF hospitalization. Furthermore, the number of HF hospitalizations is associated with irreversible long-term disease progression, which is in turn associated with increased event rates. However, cost-effectiveness models of HF treatments commonly fail to capture both the short- and long-term association between HF hospitalization and events. OBJECTIVE The aim of this study was to provide a decision-analytic model that reflects the short- and long-term association between HF hospitalization and event rates. Furthermore, we assess the impact of omitting these associations. METHODS We developed a life-time Markov cohort model to evaluate HF treatments, and modeled the short-term impact of HF hospitalization on event rates via a sequence of tunnel states, with transition probabilities following a parametric survival curve. The corresponding long-term impact was modeled via hazard ratios per HF hospitalization. We obtained baseline event rates and utilities from published literature. Subsequently, we assessed, for a hypothetical HF treatment, how omitting the modeled associations (through a simple two-state model) affects incremental quality-adjusted life-years (QALYs). RESULTS We developed a model that incorporates both short- and long-term impacts of HF hospitalizations. Based on an assumed treatment effect of a 20% risk reduction for HF hospitalization (and associated reductions in all-cause mortality of 15%), omitting the short-term, the long-term, or both associations resulted in a 5%, 1%, and 22% decrease in QALYs gained, respectively. CONCLUSION For both modeling components, i.e., the short- and long-term implications of HF hospitalization, the impact on incremental outcomes associated with treatment was substantial. Considering these aspects as proposed within this modeling approach better reflects the natural course of this progressive condition and will enhance the evaluation of future HF treatments.
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Affiliation(s)
- Gian Luca Di Tanna
- University of New South Wales, Sydney, NSW, Australia.
- The George Institute for Global Health, Level 5, 1 King St, Newtown, NSW, 2042, Australia.
| | - Blake Angell
- The George Institute for Global Health, Level 5, 1 King St, Newtown, NSW, 2042, Australia
| | | | - Peter Lindgren
- Karolinska Institutet, Stockholm, Sweden
- The Swedish Institute for Health Economics, Lund, Sweden
| | - Thomas A Gaziano
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Gary Globe
- Cerevel Therapeutics, Cambridge, MA, USA
| | - Björn Stollenwerk
- Amgen (Europe) GmbH, Economic Modeling Center of Excellence, Rotkreuz, Switzerland
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Masterson Creber RM, Daniels B, Munjal K, Reading Turchioe M, Shafran Topaz L, Goytia C, Díaz I, Goyal P, Weiner M, Yu J, Khullar D, Slotwiner D, Ramasubbu K, Kaushal R. Using Mobile Integrated Health and telehealth to support transitions of care among patients with heart failure (MIGHTy-Heart): protocol for a pragmatic randomised controlled trial. BMJ Open 2022; 12:e054956. [PMID: 35273051 PMCID: PMC8915277 DOI: 10.1136/bmjopen-2021-054956] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 12/16/2021] [Indexed: 11/14/2022] Open
Abstract
INTRODUCTION Nearly one-quarter of patients discharged from the hospital with heart failure (HF) are readmitted within 30 days, placing a significant burden on patients, families and health systems. The objective of the 'Using Mobile Integrated Health and Telehealth to support transitions of care among patients with Heart failure' (MIGHTy-Heart) study is to compare the effectiveness of two postdischarge interventions on healthcare utilisation, patient-reported outcomes and healthcare quality among patients with HF. METHODS AND ANALYSIS The MIGHTy-Heart study is a pragmatic comparative effectiveness trial comparing two interventions demonstrated to improve the hospital to home transition for patients with HF: mobile integrated health (MIH) and transitions of care coordinators (TOCC). The MIH intervention bundles home visits from a community paramedic (CP) with telehealth video visits by emergency medicine physicians to support the management of acute symptoms and postdischarge care coordination. The TOCC intervention consists of follow-up phone calls from a registered nurse within 48-72 hours of discharge to assess a patient's clinical status, identify unmet clinical and social needs and reinforce patient education (eg, medication adherence and lifestyle changes). MIGHTy-Heart is enrolling and randomising (1:1) 2100 patients with HF who are discharged to home following a hospitalisation in two New York City (NY, USA) academic health systems. The coprimary study outcomes are all-cause 30-day hospital readmissions and quality of life measured with the Kansas City Cardiomyopathy Questionnaire 30 days after hospital discharge. The secondary endpoints are days at home, preventable emergency department visits, unplanned hospital admissions and patient-reported symptoms. Data sources for the study outcomes include patient surveys, electronic health records and claims submitted to Medicare and Medicaid. ETHICS AND DISSEMINATION All participants provide written or verbal informed consent prior to randomisation in English, Spanish, French, Mandarin or Russian. Study findings are being disseminated to scientific audiences through peer-reviewed publications and presentations at national and international conferences. This study has been approved by: Biomedical Research Alliance of New York (BRANY #20-08-329-380), Weill Cornell Medicine Institutional Review Board (20-08022605) and Mt. Sinai Institutional Review Board (20-01901). TRIAL REGISTRATION NUMBER Clinicaltrials.gov, NCT04662541.
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Affiliation(s)
| | - Brock Daniels
- Emergency Medicine, NewYork-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York, USA
| | - Kevin Munjal
- Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Leah Shafran Topaz
- Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Crispin Goytia
- Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Iván Díaz
- Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Parag Goyal
- Medicine, Weill Cornell Medicine, New York, New York, USA
| | - Mark Weiner
- Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Jiani Yu
- Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - Dhruv Khullar
- Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
| | - David Slotwiner
- Medicine, Weill Cornell Medical College, New York, New York, USA
- Medicine, NewYork-Presbyterian Queens, Flushing, New York, USA
| | - Kumudha Ramasubbu
- Cardiology, NewYork-Presbyterian Brooklyn Methodist Hospital, Brooklyn, New York, USA
| | - Rainu Kaushal
- Population Health Sciences, Weill Cornell Medicine, New York, New York, USA
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5
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Flynn MJ, Kronebusch BJ, Sikkink LA, Swanson KM, Niccum KJ, Crane SJ, Aoun B, Takahashi PY. Impact of the Registered Nurse Clinical Liaison Role in Ambulatory Care on Transitions of Care: A Retrospective Cohort Study. Prof Case Manag 2022; 27:58-66. [PMID: 35099419 DOI: 10.1097/ncm.0000000000000538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE OF STUDY To determine the relationship between engagement with the novel register nurse care liaison (RNCL) and enrollment in care management compared with usual care in hospitalized patients. PRIMARY PRACTICE SETTING Patients in the hospital from January 1, 2019, to September 30, 2019, who would be eligible for care management. METHODOLOGY AND SAMPLE This was a retrospective cohort study. The authors compared a group of 419 patients who utilized the services of the RNCL at any time during their hospital stay with the RNCL to a propensity matched control group of 833 patients, which consisted of patients who were hospitalized during the same time as the RNCL intervention group. Our primary outcome was enrollment in care management programs. Our secondary outcome was 30-day readmissions, emergency department (ED) use, and office visits. The authors compared baseline characteristics and outcomes across groups using Wilcoxon-Mann-Whitney and χ2 tests and performed an adjusted analysis using conditional logistic regression models controlling for patient education and previous health care utilization. RESULTS The authors matched 419 patients who had engaged an RNCL to 833 patients in the usual care group; this comprised the analytic cohort for this study. The authors found 67.1% of patients enrolled in a care management program with RNCL compared with only 15.3% in usual care (p < .0001). The authors found higher rates of enrollment in all programs of care management. After the full adjustment, the odds ratio for enrollment in any program was 13.7 (95% confidence interval: 9.3, 20.2) for RNCL compared with usual care. There was no difference between groups with 30-day hospitalization or ED visit. CONCLUSION In this matched study of 419 patients with RNCL engagement, the authors found significantly higher enrollment in all care management programs. IMPLICATIONS FOR CASE MANAGEMENT PRACTICE These findings encourage further study of this care model. This could help enhance enrollment in care management programs, increase relationships between inpatient practice and ambulatory practice, as well as increase communication across the continuum of care.
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Affiliation(s)
- Mollie J Flynn
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Beckie J Kronebusch
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Laura A Sikkink
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Kristi M Swanson
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Kelly J Niccum
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Sarah J Crane
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Bernard Aoun
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
| | - Paul Y Takahashi
- Mollie J. Flynn, BSN, RN , is a bachelor's prepared registered nurse at Mayo Clinic in Rochester. She serves as the sole nurse clinical liaison for the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Beckie J. Kronebusch, MS, APRN, CNS , is a master's prepared clinical nurse specialist. She currently works at Mayo Clinic Health System in La Crosse, Wisconsin
- Laura A. Sikkink, MSN, RN , is a master's prepared registered nurse. She is an ambulatory nurse manager, who manages the care coordination groups at the Mayo Clinic Rochester/Kasson primary care clinic in Rochester, Minnesota
- Kristi M. Swanson, MS , is a master's prepared principal health services analyst. She currently works for Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery at Mayo Clinic in Rochester, Minnesota
- Kelly J. Niccum, CCRP, PMP , is a project manager for the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery in Rochester, Minnesota
- Sarah J. Crane, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
- Bernard Aoun, MD , is a consultant in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic. He is an instructor of medicine and is board certified in Geriatrics
- Paul Y. Takahashi, MD , is a consultant and section head in Community Internal Medicine at the Mayo Clinic Rochester/Kasson primary care clinic
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6
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Riester MR, Bosco E, Silva JBB, Bardenheier BH, Goyal P, O’Neil ET, van Aalst R, Chit A, Gravenstein S, Zullo AR. Causes and timing of 30-day rehospitalization from skilled nursing facilities after a hospital admission for pneumonia or sepsis. PLoS One 2022; 17:e0260664. [PMID: 35051181 PMCID: PMC8775208 DOI: 10.1371/journal.pone.0260664] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 11/12/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Pneumonia and sepsis are among the most common causes of hospitalization in the United States and often result in discharges to a skilled nursing facility (SNF) for rehabilitation. We described the timing and most common causes of 30-day unplanned hospital readmission following an index hospitalization for pneumonia or sepsis. METHODS AND FINDINGS This national retrospective cohort study included adults ≥65 years who were hospitalized for pneumonia or sepsis and were discharged to a SNF between July 1, 2012 and July 4, 2015. We quantified the ten most common 30-day unplanned readmission diagnoses and estimated the daily risk of first unplanned rehospitalization for four causes of readmission (circulatory, infectious, respiratory, and genitourinary). The index hospitalization was pneumonia for 92,153 SNF stays and sepsis for 452,254 SNF stays. Of these SNF stays, 20.9% and 25.9%, respectively, resulted in a 30-day unplanned readmission. Overall, septicemia was the single most common readmission diagnosis for residents with an index hospitalization for pneumonia (16.7% of 30-day readmissions) and sepsis (22.4% of 30-day readmissions). The mean time to unplanned readmission was approximately 14 days overall. Respiratory causes displayed the highest daily risk of rehospitalization following index hospitalizations for pneumonia, while circulatory and infectious causes had the highest daily risk of rehospitalization following index hospitalizations for sepsis. The day of highest risk for readmission occurred within two weeks of the index hospitalization discharge, but the readmission risk persisted across the 30-day follow-up. CONCLUSION Among older adults discharged to SNFs following a hospitalization for pneumonia or sepsis, hospital readmissions for infectious, circulatory, respiratory, and genitourinary causes occurred frequently throughout the 30-day post-discharge period. Our data suggests further study is needed, perhaps on the value of closer monitoring in SNFs post-hospital discharge and improved communication between hospitals and SNFs, to reduce the risk of potentially preventable hospital readmissions.
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Affiliation(s)
- Melissa R. Riester
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
| | - Elliott Bosco
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
| | - Joe B. B. Silva
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
| | - Barbara H. Bardenheier
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, United States of America
| | - Parag Goyal
- Division of Cardiology and Division of General Internal Medicine, Department of Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Emily T. O’Neil
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
| | - Robertus van Aalst
- Sanofi Pasteur, Swiftwater, PA, United States of America
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Ayman Chit
- Sanofi Pasteur, Swiftwater, PA, United States of America
- Leslie Dan School of Pharmacy, University of Toronto, Ontario, Canada
| | - Stefan Gravenstein
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
- Department of Medicine, Warren Alpert Medical School, Brown University, Providence, RI, United States of America
- Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, United States of America
| | - Andrew R. Zullo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, United States of America
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, United States of America
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, United States of America
- Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, United States of America
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Garfein J, Cholack G, Krallman R, Feldeisen D, Montgomery D, Kline-Rogers E, Eagle K, Rubenfire M, Bumpus S. Cardiac Transitional Care Effectiveness: Does Overall Comorbidity Burden Matter? Am J Med 2021; 134:1506-1513. [PMID: 34273282 PMCID: PMC8688268 DOI: 10.1016/j.amjmed.2021.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Cardiovascular disease is the most common cause of mortality and hospitalization in the United States. Transitional care initiatives can improve outcomes for cardiac patients, but it is unclear whether patients with different baseline comorbidity burden benefit equally. We evaluated the effectiveness of the Bridging the Discharge Gap Effectively (BRIDGE) program, a nurse-practitioner-led transitional care clinic, in mitigating adverse clinical outcomes in cardiac patients with varying Charlson comorbidity index (CCI). METHODS We studied patients referred to BRIDGE between 2008 and 2017 postdischarge for a cardiac condition. Using proportional hazards regression models, we evaluated associations between attendance at BRIDGE and hospital readmission, emergency department (ED) visit, and a composite outcome consisting of readmission, ED visit, or mortality, and assessed interaction between BRIDGE attendance and CCI. RESULTS Of 4559 patients, 3256 (71.4%) attended BRIDGE. In patients with low CCI, attendance at BRIDGE was inversely associated with hospital readmission (adjusted hazard ratio = 0.82, 95% confidence interval [CI]: 0.69, 0.97, P = .02) and the composite endpoint (adjusted hazard ratio = 0.84, 95% CI: 0.72, 0.98, P = .02). Associations of BRIDGE attendance with both readmission and ED visit were significantly weaker in patients with high CCI (adjusted P, interaction = .007 and .03, respectively). Overall, BRIDGE attendance was associated with an 11% lower hazard of developing the composite endpoint (95% CI: 2%, 19%, P = .01). CONCLUSIONS Attendance at a transitional care clinic is inversely associated with risk of readmission and a composite endpoint in cardiac patients with low CCI. Future research should investigate modified transitional care programs in patients with varying comorbidity burden.
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Affiliation(s)
| | - George Cholack
- Michigan Medicine, Ann Arbor; Oakland University William Beaumont School of Medicine, Rochester, Mich
| | | | | | | | | | | | | | - Sherry Bumpus
- Michigan Medicine, Ann Arbor; Eastern Michigan University, School of Nursing, Ypsilanti.
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Bhardwaj V, Spaulding EM, Marvel FA, LaFave S, Yu J, Mota D, Lorigiano TJ, Huynh PP, Shan R, Yesantharao PS, Lee MA, Yang WE, Demo R, Ding J, Wang J, Xun H, Shah L, Weng D, Wongvibulsin S, Carter J, Sheidy J, McLin R, Flowers J, Majmudar M, Elgin E, Vilarino V, Lumelsky D, Leung C, Allen JK, Martin SS, Padula WV. Cost-effectiveness of a Digital Health Intervention for Acute Myocardial Infarction Recovery. Med Care 2021; 59:1023-1030. [PMID: 34534188 PMCID: PMC8516712 DOI: 10.1097/mlr.0000000000001636] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Acute myocardial infarction (AMI) is a common cause of hospital admissions, readmissions, and mortality worldwide. Digital health interventions (DHIs) that promote self-management, adherence to guideline-directed therapy, and cardiovascular risk reduction may improve health outcomes in this population. The "Corrie" DHI consists of a smartphone application, smartwatch, and wireless blood pressure monitor to support medication tracking, education, vital signs monitoring, and care coordination. We aimed to assess the cost-effectiveness of this DHI plus standard of care in reducing 30-day readmissions among AMI patients in comparison to standard of care alone. METHODS A Markov model was used to explore cost-effectiveness from the hospital perspective. The time horizon of the analysis was 1 year, with 30-day cycles, using inflation-adjusted cost data with no discount rate. Currencies were quantified in US dollars, and effectiveness was measured in quality-adjusted life-years (QALYs). The results were interpreted as an incremental cost-effectiveness ratio at a threshold of $100,000 per QALY. Univariate sensitivity and multivariate probabilistic sensitivity analyses tested model uncertainty. RESULTS The DHI reduced costs and increased QALYs on average, dominating standard of care in 99.7% of simulations in the probabilistic analysis. Based on the assumption that the DHI costs $2750 per patient, use of the DHI leads to a cost-savings of $7274 per patient compared with standard of care alone. CONCLUSIONS Our results demonstrate that this DHI is cost-saving through the reduction of risk for all-cause readmission following AMI. DHIs that promote improved adherence with guideline-based health care can reduce hospital readmissions and associated costs.
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Affiliation(s)
- Vinayak Bhardwaj
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, US
| | - Erin M. Spaulding
- Johns Hopkins University School of Nursing, Baltimore, MD, US
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Francoise A. Marvel
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Sarah LaFave
- Johns Hopkins University School of Nursing, Baltimore, MD, US
| | - Jeffrey Yu
- Johns Hopkins Health System, Baltimore, MD, US
- Dept. of Pharmaceutical & Health Economics, School of Pharmacy, University of Southern California, Los Angeles, CA, US
| | - Daniel Mota
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, US
- Dimock Center, Baltimore, MD, US
| | | | - Pauline P. Huynh
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Rongzi Shan
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Pooja S. Yesantharao
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Matthias A. Lee
- Johns Hopkins University Whiting School of Engineering, Baltimore, MD, US
| | - William E. Yang
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Ryan Demo
- Johns Hopkins University Whiting School of Engineering, Baltimore, MD, US
| | - Jie Ding
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, US
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Jane Wang
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Helen Xun
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Lochan Shah
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Daniel Weng
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Shannon Wongvibulsin
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | | | | | | | | | - Maulik Majmudar
- Massachusetts General Hospital, Boston, MA, US
- Harvard Medical School, Boston, MA, US
| | | | - Valerie Vilarino
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University Krieger School of Arts and Sciences, Baltimore, MD, US
| | - David Lumelsky
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University Krieger School of Arts and Sciences, Baltimore, MD, US
| | | | - Jerilyn K. Allen
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, US
- Johns Hopkins University School of Nursing, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
| | - Seth S. Martin
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, US
- Digital Health Innovation Laboratory, Ciccarone Center for the Prevention of Cardiovascular Disease, Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University School of Medicine, Baltimore, MD, US
- Johns Hopkins University Whiting School of Engineering, Baltimore, MD, US
| | - William V. Padula
- Dept. of Pharmaceutical & Health Economics, School of Pharmacy, University of Southern California, Los Angeles, CA, US
- Leonard D. Schaeffer Center for Health Economics & Policy, University of Southern California, Los Angeles, CA
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9
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Kundi H, Coskun N, Yesiltepe M. Association of entirely claims-based frailty indices with long-term outcomes in patients with acute myocardial infarction, heart failure, or pneumonia: a nationwide cohort study in Turkey. THE LANCET REGIONAL HEALTH. EUROPE 2021; 10:100183. [PMID: 34806063 PMCID: PMC8589716 DOI: 10.1016/j.lanepe.2021.100183] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
BACKGROUND Several countries have increasingly focused on improving care for acute myocardial infarction (AMI), heart failure (HF), and pneumonia to reduce their readmissions and mortality rates. Frailty is becoming increasingly important to accurately predict healthcare utilization for the aging population. The preferred method for the measurement of frailty remains unclear, and current risk-adjustment models do not account for frailty. We sought to compare commonly used frailty indices in terms of the ability to predict clinical adverse outcomes in AMI, HF, and pneumonia patients. METHODS A nationwide cohort study included AMI, HF, and pneumonia with 65 years and older patients in the Turkey between January 1 and December 31, 2018. The primary predictor of interest was frailty. We used two claims-based frailty indices (Johns Hopkins Claims-Based Frailty Index and Hospital Frailty Risk Score) to assess frailty. The main outcome was all-cause long-term mortality up to 3 years. Time to death was calculated as the time period between the date of first admission and the date of death. Patients were censored as of September 30, 2020, which marked the end of the follow-up period. FINDINGS Of the 200,948 patients, 35,096 (17.5%) had AMI, 62,403 (31.1%) had HF, and 103,449 (51.5%) had pneumonia. Johns Hopkins Claims-Based Frailty Index (c-statistics for long-term mortality: 0.68 in AMI, 0.61 in HF, 0.64 in pneumonia) was better compared to Hospital Frailty Risk Score (c-statistics for long-term mortality: AMI=0.62, HF=0.58, pneumonia=0.62) (DeLong p<0.001 in all). INTERPRETATION Readmission and mortality rates after AMI, HF, and pneumonia gradually increases with increasing frailty score. While the Hospital Frailty Risk Score had a better discrimination for predicting readmissions, Johns Hopkins Claims-Based Frailty Index had a better discrimination for predicting mortality. These findings should be taken into account for a better evaluation of hospital performance. FUNDING This study was supported by funding from The Scientific and Technological Research Council of Turkey (grant 120S422, HK).
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Affiliation(s)
- Harun Kundi
- Department of Cardiology, Ankara City Hospital, Ankara, Turkey
- Department of Digital Hospital and Analytical Management Unit, Ankara City Hospital, Ankara, Turkey
| | - Nazim Coskun
- Department of Digital Hospital and Analytical Management Unit, Ankara City Hospital, Ankara, Turkey
- Department of Nuclear Medicine, Ankara City Hospital, Ankara, Turkey
| | - Metin Yesiltepe
- Department of Digital Hospital and Analytical Management Unit, Ankara City Hospital, Ankara, Turkey
- Department of Pharmacology, Ankara City Hospital, Ankara, Turkey
- Department of Pharmacology, Physiology & Neuroscience, New Jersey Medical School, Rutgers The State University of New Jersey, NJ, USA
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Maggioni AP, Dondi L, Andreotti F, Ronconi G, Calabria S, Piccinni C, Pedrini A, Esposito I, Martini N. Prevalence, prescriptions, outcomes and costs of type 2 diabetes patients with or without prior coronary artery disease or stroke: a longitudinal 5-year claims-data analysis of over 7 million inhabitants. Ther Adv Chronic Dis 2021; 12:20406223211026390. [PMID: 34221306 PMCID: PMC8221674 DOI: 10.1177/20406223211026390] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 06/01/2021] [Indexed: 01/07/2023] Open
Abstract
AIMS To analyze the prevalence, comorbidities, outcomes and costs of type 2 diabetes mellitus (T2DM) patients with and without coronary artery disease (CAD) or stroke in a population of over 7 million inhabitants. METHODS T2DM patients were identified in 2015 (accrual period) from the Ricerca e Salute (ReS) database linking administrative records to demographics. Based on 2013-2015 information, four cohorts were considered: #1 with CAD and/or stroke; #2 without CAD and/or stroke; #3 with chronic CAD but no myocardial infarction or stroke; #4 with chronic CAD undergoing percutaneous coronary interventions (PCI). Hospitalizations, drugs and other outpatient care were assessed from 2015 to 2017. RESULTS The prevalence of T2DM was 6% (441,085/7,365,954). CAD and/or stroke in the previous 3 years affected 7.5% of T2DM patients (33,153); this cohort was generally older, of male sex, with more comorbidities, prescriptions, and hospital admissions (50.5% versus 13.4% during the first follow-up year) compared to cohort #2. Yearly costs were over three-fold for cohort #1 versus #2, main drivers being hospitalizations in the former and drugs in the latter. Two-year cardiovascular events were recorded significantly more commonly in cohort #4 compared to the other cohorts. Guideline-recommended lipid-lowering therapy was <80% in all but cohort #4. CONCLUSIONS The present analysis points to three areas of potential improvement in T2DM management: (a) guideline-recommended treatment patterns of T2DM patients; (b) three-fold recurrences and costs in T2DM patients with, compared to those without, prior cardiovascular events; (c) high event rates associated with chronic CAD and PCI, warranting specific studies aimed at improved prevention.
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Affiliation(s)
- Aldo Pietro Maggioni
- Fondazione Ricerca e Salute (ReS), Rome, Italy ANMCO Research Center, Fondazione per il Tuo cuore – HCF onlus, Via La Marmora 34, Florence, 50121, Italy
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11
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Benge C, Pouliot J, Muldowney JAS. Evaluation of a Clinical Pharmacist Specialist Transition of Care Pathway to Manage Heart Failure Readmissions During a Provider Shortage. J Pharm Pract 2021; 35:929-939. [PMID: 34060365 DOI: 10.1177/08971900211017484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Evidence supports scheduling early follow-up after heart failure (HF) hospitalization with a provider capable of managing hypervolemia. Often this service is provided by cardiologists or specialty nurse practitioners. Continuity or "familiar" providers may be better positioned to identify decompensating HF in patients who have advanced HF and/or multiple complicating medical problems. The objective of this study was to evaluate whether a clinical pharmacy specialist (CPS) service, covering the role of a "familiar" provider in an advanced HF specialty clinic (AHFC) during a staffing shortage, may prevent readmission metrics from worsening. METHODS We evaluated the entire, eligible concurrent cohorts, representing 175 AHFC-CPS and 273 control patient-admissions, respectively. Study- and disease-specific predictors for readmission were assessed. A matched cohort of 202 patient-admissions (101 AHFC-CPS:101 NO-CPS) were evaluated. RESULTS Subjects were predominantly white, elderly males. While overall "clinic [performance] profiling" outcomes for readmissions (p = 0.43) and mortality (p = 0.66) did not statistically differ between the AHFC-CPS and NO-CPS groups, an imbalance in severity of illness persisted. A survival curve and analysis were constructed, and the hazard ratio for all-cause mortality was 0.69 (p = 0.033). CONCLUSIONS This retrospective project supports the premise that AHFC-CPS intervention may be a suitable alternative to maintain the volume status for AHFC patients during a staffing short-fall. More work needs to be done to determine intervention effect size, predictors for readmission, specifically in advanced cardiovascular disease, and to evaluate CPS opportunities in the provision of independent HF care, particularly for patients with advanced HF.
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Affiliation(s)
- Cassandra Benge
- 20106VA Tennessee Valley Healthcare System, Nashville, TN, USA
| | - Jonathon Pouliot
- 5707Lipscomb University College of Pharmacy and Health Sciences, Nashville, TN, USA
| | - James A S Muldowney
- 20106VA Tennessee Valley Healthcare System, Nashville, TN, USA.,Vanderbilt University Medical Center, Nashville, TN, USA
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12
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Rijpkema CJ, Verweij L, Jepma P, Latour CHM, Peters RJG, Scholte Op Reimer WJM, Buurman BM. The course of readmission in frail older cardiac patients. J Adv Nurs 2021; 77:2807-2818. [PMID: 33739473 PMCID: PMC8251632 DOI: 10.1111/jan.14828] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 02/02/2021] [Accepted: 02/28/2021] [Indexed: 12/14/2022]
Abstract
AIM The aim of this study is to explore patients' and (in)formal caregivers' perspectives on their role(s) and contributing factors in the course of unplanned hospital readmission of older cardiac patients in the Cardiac Care Bridge (CCB) program. DESIGN This study is a qualitative multiple case study alongside the CCB randomized trial, based on grounded theory principles. METHODS Five cases within the intervention group, with an unplanned hospital readmission within six months after randomization, were selected. In each case, semi-structured interviews were held with patients (n = 4), informal caregivers (n = 5), physical therapists (n = 4), and community nurses (n = 5) between April and June 2019. Patients' medical records were collected to reconstruct care processes before the readmission. Thematic analysis and the six-step analysis of Strauss & Corbin have been used. RESULTS Three main themes emerged. Patients experienced acute episodes of physical deterioration before unplanned hospital readmission. The involvement of (in)formal caregivers in adequate observation of patients' health status is vital to prevent rehospitalization (theme 1). Patients and (in)formal caregivers' perception of care needs did not always match, which resulted in hampering care support (theme 2). CCB caregivers experienced difficulties in providing care in some cases, resulting in limited care provision in addition to the existing care services (theme 3). CONCLUSION Early detection of deteriorating health status that leads to readmission was often lacking, due to the acuteness of the deterioration. Empowerment of patients and their informal caregivers in the recognition of early signs of deterioration and adequate collaboration between caregivers could support early detection. Patients' care needs and expectations should be prioritized to stimulate participation. IMPACT (In)formal caregivers may be able to prevent unplanned hospital readmission of older cardiac patients by ensuring: (1) early detection of health deterioration, (2) empowerment of patient and informal caregivers, and (3) clear understanding of patients' care needs and expectations.
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Affiliation(s)
- Corinne J. Rijpkema
- Department of Internal MedicineSection of Geriatric MedicineAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Lotte Verweij
- Department of CardiologyAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Center of Expertise Urban VitalityFaculty of HealthAmsterdam University of Applied ScienceAmsterdamThe Netherlands
| | - Patricia Jepma
- Department of CardiologyAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Center of Expertise Urban VitalityFaculty of HealthAmsterdam University of Applied ScienceAmsterdamThe Netherlands
| | - Corine H. M. Latour
- Center of Expertise Urban VitalityFaculty of HealthAmsterdam University of Applied ScienceAmsterdamThe Netherlands
| | - Ron J. G. Peters
- Department of CardiologyAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Wilma J. M. Scholte Op Reimer
- Department of CardiologyAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Research Group Chronic DiseasesUniversity of Applied Sciences UtrechtUtrechtThe Netherlands
| | - Bianca M. Buurman
- Department of Internal MedicineSection of Geriatric MedicineAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Center of Expertise Urban VitalityFaculty of HealthAmsterdam University of Applied ScienceAmsterdamThe Netherlands
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13
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Correction of iron deficiency in hospitalized heart failure patients does not improve patient outcomes. Ann Hematol 2020; 100:661-666. [PMID: 33169197 DOI: 10.1007/s00277-020-04338-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 11/03/2020] [Indexed: 10/23/2022]
Abstract
Heart failure (HF) has an estimated prevalence of 1-2% in the world's population and up to 10% of patients age 65 and above. Iron deficiency (ID) in HF has been shown to be an independent contributor of increased mortality and poorer quality of life and has been associated with increased rates of hospitalization. Estimates are varied, but it is believed that as many as 30-83% of HF patients have ID, often without overt anemia, therefore making diagnosis more difficult. Well-established large studies have shown intravenous iron (IVFe) supplementation in HF patients is superior to an oral route, though these guidelines were developed for the chronic HF patients in the outpatient setting. For patients who are frequently hospitalized for HF, their inpatient stays may present an opportunity to diagnose ID. We previously showed that ID is underdiagnosed in the inpatient setting. To date, limited studies investigate long-term outcomes in hospitalized HF patients diagnosed with ID who are treated with IVFe compared to those who are not. In this retrospective analysis, we assessed 1-year readmission rates and mortality outcomes in patients who were diagnosed with ID while admitted for HF and subsequently received IVFe versus those who did not on their initial admission. These data suggest that there is no significant reduction in readmissions for HF or mortality between those patients who received IVFe and those who did not.
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Schjødt I, Liljeroos M, Larsen P, Johnsen SP, Strömberg A, Løgstrup BB. Risk factors for hospital readmission in adult patients with heart failure with reduced ejection fraction: a systematic review. JBI Evid Synth 2020; 18:1641-1700. [PMID: 32898362 DOI: 10.11124/jbisrir-d-19-00203] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Abstract
OBJECTIVE The objective of this review was to identify and synthesize evidence on risk factors associated with hospital readmission within the first year after heart failure hospitalization among patients with heart failure with reduced left ventricular ejection fraction. INTRODUCTION Heart failure is associated with a high risk of hospital readmission. Readmissions are associated with higher mortality and health care costs. It is a high health care priority to identify vulnerable patients with heart failure who may potentially benefit from targeted personalized care interventions aiming to reduce readmissions. INCLUSION CRITERIA This review considered studies including adult patients who had heart failure with a reduced left ventricular ejection fraction ≤ 40% who were discharged after a heart failure hospitalization. The authors included studies with experimental and observational designs evaluating risk factors for i) all-cause hospital readmission, ii) heart failure hospital readmission, and iii) composite outcomes within seven, 15, 30, 60, 90, 180, and 365 days after hospital discharge. Composite outcomes included end points where all-cause readmission and/or heart failure readmission were part of a defined end point (i.e. all-cause readmission or mortality; heart failure readmission or mortality; cardiovascular readmission; cardiovascular readmission or mortality; and readmission, mortality, or cardiac transplant). Studies reporting all-cause readmission and/or heart failure readmission as a primary outcome, secondary outcome, or part of a composite outcome were included. METHODS PubMed, Embase, CINAHL, Cochrane CENTRAL, PsycINFO, OpenGrey, MedNar, DART-Europe, ProQuest Dissertations and Theses, and the Grey Literature Report in Public Health were searched to find both published and unpublished studies in English, Swedish, Norwegian, or Danish from 2000 to June 2018. Study selection, critical appraisal, data extraction, and data synthesis followed the JBI approach for systematic reviews. Statistical pooling was not possible due to clinical and methodological heterogeneity of the studies included and the lack of risk factors reported more than once. A narrative summary of the findings was performed. RESULTS Fifty-two studies, including one randomized controlled trial and 51 cohort studies with a total of 128,186 participants, were included. Risk factors for readmission were reported for 30-day outcome in 16 studies, 60-day in three studies, 90-day in 15 studies, 180-day in 12 studies, and 365-day outcome in 15 studies. Based on multivariable analyses from 43 cohort studies and results from one randomized controlled trial, the authors identified several factors associated with higher risk of all-cause readmission, heart failure readmission, and composite outcomes (e.g. readmission or death) within 30, 60, 90, 180, and 365 days after discharge for a heart failure hospitalization. CONCLUSIONS This review provides a comprehensive overview of factors associated with a clinical outcome after a heart failure hospitalization in patients with heart failure with left ventricular ejection fraction ≤ 40%. Owing to the heterogeneity of variables investigated and the lack of comparability of findings, the clinical impact of the identified risk factors remains uncertain. This review highlights research gaps and the need for a standardized way to define and measure all-cause readmission, heart failure readmission, and composite end points in clinical research to improve study quality and enable comparison of findings between studies.
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Affiliation(s)
- Inge Schjødt
- 1Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark 2Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden 3Centre for Clinical Research Sörmland, Uppsala University, Eskilstuna, Sweden 4Health Sciences Research Center, University College Lillebælt, Odense, Denmark 5Danish Center for Clinical Health Services Research, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark 6Department of Cardiology, Linköping University Hospital, Linköping, Sweden 7Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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Cowper PA, Knight JD, Davidson-Ray L, Peterson ED, Wang TY, Mark DB. Acute and 1-Year Hospitalization Costs for Acute Myocardial Infarction Treated With Percutaneous Coronary Intervention: Results From the TRANSLATE-ACS Registry. J Am Heart Assoc 2020; 8:e011322. [PMID: 30975005 PMCID: PMC6507213 DOI: 10.1161/jaha.118.011322] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Background Hospitalization for acute myocardial infarction (MI) in the United States is both common and expensive, but those features alone provide little insight into cost‐saving opportunities. Methods and Results To understand the cost drivers during hospitalization for acute MI and in the following year, we prospectively studied 11 969 patients with acute MI undergoing percutaneous coronary intervention at 233 US hospitals (2010–2013) from the TRANSLATE‐ACS (Treatment With ADP Receptor Inhibitors: Longitudinal Assessment of Treatment Patterns and Events After Acute Coronary Syndrome) registry. Baseline costs were collected in a random subset (n=4619 patients, 54% ST‐segment–elevation MI [STEMI]), while follow‐up costs out to 1 year were collected for all patients. The mean index length of stay was 3.1 days (for both STEMI and non‐STEMI) and mean intensive care unit length of stay was 1.2 days (1.4 days for STEMI and 1.0 days for non‐STEMI). Index hospital costs averaged $18 931 ($19 327 for STEMI, $18 465 for non‐STEMI), with 45% catheterization laboratory–related and 20% attributable to postprocedure hospital stay. Patient factors, including severity of illness and extent of coronary disease, and hospital characteristics, including for profit status and geographic region, identified significant variations in cost. Intensive care was used for 53% of non‐STEMI and increased costs by $3282. Postdischarge 1‐year costs averaged $8037, and 48% of patients were rehospitalized (half within 2 months and 57% with a cardiovascular diagnosis). Conclusions While much of the cost of patients with acute MI treated with percutaneous coronary intervention is probably not modifiable by the care team, cost reductions are still possible through quality‐preserving practice efficiencies, such as need‐based use rather than routine use of intensive care unit for patients with stable non‐STEMI. Clinical Trial Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT00097591. See Editorial Weintraub
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Affiliation(s)
- Patricia A Cowper
- 1 The Duke Clinical Research Institute Duke University Medical Center Durham NC
| | - J David Knight
- 1 The Duke Clinical Research Institute Duke University Medical Center Durham NC
| | - Linda Davidson-Ray
- 1 The Duke Clinical Research Institute Duke University Medical Center Durham NC
| | - Eric D Peterson
- 1 The Duke Clinical Research Institute Duke University Medical Center Durham NC
| | - Tracy Y Wang
- 1 The Duke Clinical Research Institute Duke University Medical Center Durham NC
| | - Daniel B Mark
- 1 The Duke Clinical Research Institute Duke University Medical Center Durham NC
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16
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Kundi H, Wadhera RK, Strom JB, Valsdottir LR, Shen C, Kazi DS, Yeh RW. Association of Frailty With 30-Day Outcomes for Acute Myocardial Infarction, Heart Failure, and Pneumonia Among Elderly Adults. JAMA Cardiol 2020; 4:1084-1091. [PMID: 31553402 DOI: 10.1001/jamacardio.2019.3511] [Citation(s) in RCA: 109] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Importance The addition of a claims-based frailty metric to traditional comorbidity-based risk-adjustment models for acute myocardial infarction (AMI), heart failure (HF), and pneumonia improves the prediction of 30-day mortality and readmission. This may have important implications for hospitals that tend to care for frail populations and participate in Centers for Medicare & Medicaid Services value-based payment programs, which use these risk-adjusted metrics to determine reimbursement. Objective To determine whether the addition of frailty measures to traditional comorbidity-based risk-adjustment models improved prediction of outcomes for patients with AMI, HF, and pneumonia. Design, Setting, and Participants A nationwide cohort study included Medicare fee-for-service beneficiaries 65 years and older in the United States between January 1 and December 1, 2016. Analysis began August 2018. Main Outcomes and Measures Rates of mortality within 30 days of admission and 30 days of discharge, as well as 30-day readmission rates by frailty group. We evaluated the incremental effect of adding the Hospital Frailty Risk Score (HFRS) to current comorbidity-based risk-adjustment models for 30-day outcomes across all conditions. Results For 785 127 participants, there were 166 200 hospitalizations [21.2%] for AMI, 348 619 [44.4%] for HF, and 270 308 [34.4%] for pneumonia. The mean (SD) age at the time of hospitalization was 79.2 (8.9) years; 656 315 (83.6%) were white and 402 639 (51.3%) were women. The mean (SD) HFRS was 7.3 (7.4) for patients with AMI, 10.8 (8.3) for patients with HF, and 8.2 (5.7) for patients with pneumonia. Among patients hospitalized for AMI, an HFRS more than 15 (compared with an HFRS <5) was associated with a higher risk of 30-day postadmission mortality (adjusted odds ratio [aOR], 3.6; 95% CI, 3.4-3.8), 30-day postdischarge mortality (aOR, 4.0; 95% CI, 3.7-4.3), and 30-day readmission (aOR, 3.0; 95% CI, 2.9-3.1) after multivariable adjustment for age, sex, race, and comorbidities. Similar patterns were observed for patients hospitalized with HF (30-day postadmission mortality: aOR, 3.5; 95% CI, 3.4-3.7; 30-day postdischarge mortality: aOR, 3.5; 95% CI, 3.3-3.6; and 30-day readmission: aOR, 2.9; 95% CI, 2.8-3.0) and among patients with pneumonia (30-day postadmission mortality: aOR, 2.5; 95% CI, 2.3-2.6; 30-day postdischarge mortality: aOR, 3.0; 95% CI, 2.9-3.2; and 30-day readmission: aOR, 2.8; 95% CI, 2.7-2.9). The addition of HFRS to traditional comorbidity-based risk-prediction models improved discrimination to predict outcomes for all 3 conditions. Conclusions and Relevance Among Medicare fee-for-service beneficiaries, frailty as measured by the HFRS was associated with mortality and readmissions among patients hospitalized for AMI, HF, or pneumonia. The addition of HFRS to traditional comorbidity-based risk-prediction models improved the prediction of outcomes for all 3 conditions.
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Affiliation(s)
- Harun Kundi
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Rishi K Wadhera
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Division of Cardiology, Department of Medicine; Brigham and Women's Hospital, Boston, Massachusetts
| | - Jordan B Strom
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Linda R Valsdottir
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Changyu Shen
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Dhruv S Kazi
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Robert W Yeh
- Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine; Beth Israel Deaconess Medical Center, Boston, Massachusetts
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17
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Kaneko H, Itoh H, Yotsumoto H, Kiriyama H, Kamon T, Fujiu K, Morita K, Michihata N, Jo T, Morita H, Yasunaga H, Komuro I. Characteristics and Outcomes of Super-Elderly Patients (Aged ≥90 Years) Hospitalized for Heart Failure - Analysis of a Nationwide Inpatient Database. Circ Rep 2020; 2:393-399. [PMID: 33693260 PMCID: PMC7819647 DOI: 10.1253/circrep.cr-20-0053] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Background:
Although the aged population is increasing in developed countries, clinical evidence on super-elderly heart failure (HF) patients is scarce. This study determined the characteristics and outcomes of Japanese hospitalized super-elderly HF patients (aged ≥90 years) using a nationwide inpatient database. Methods and Results:
A comprehensive analysis was performed of 447,818 HF patients in the Diagnosis Procedure Combination database who were hospitalized and discharged between January 2010 and March 2018. Among the study population, 243,028 patients (54.3%) were aged ≥80 years and 64,628 patients (14.4%) were aged ≥90 years. The percentage of elderly patients increased over time. Elderly patients were more likely to be female and had a higher New York Heart Association functional class at admission. Invasive and advanced procedures were rarely performed, whereas infectious complications were more common in patients with older age. Length of hospital stay and in-hospital mortality increased with age. Multivariable logistic regression analysis fitted with a generalized estimating equation showed higher in-hospital mortality in patients aged ≥80 and ≥90 years (odds ratios 1.99 and 3.23, respectively) compared with those aged <80 years. Conclusions:
The number of hospitalized super-elderly HF patients has increased, and these patients are associated with worse clinical outcomes. The results of this study may be useful in establishing an optimal management strategy for super-elderly HF patients in the era of HF pandemic.
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Affiliation(s)
- Hidehiro Kaneko
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan.,Department of Advanced Cardiology, The University of Tokyo Tokyo Japan
| | - Hidetaka Itoh
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan
| | - Haruki Yotsumoto
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan
| | - Hiroyuki Kiriyama
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan
| | - Tatsuya Kamon
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan
| | - Katsuhito Fujiu
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan.,Department of Advanced Cardiology, The University of Tokyo Tokyo Japan
| | - Kojiro Morita
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo Tokyo Japan.,Department of Health Services Research, Faculty of Medicine, University of Tsukuba Tsukuba Japan
| | - Nobuaki Michihata
- Department of Health Services Research, The University of Tokyo Tokyo Japan
| | - Taisuke Jo
- Department of Health Services Research, The University of Tokyo Tokyo Japan
| | - Hiroyuki Morita
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan
| | - Hideo Yasunaga
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo Tokyo Japan
| | - Issei Komuro
- Department of Cardiovascular Medicine, The University of Tokyo Tokyo Japan
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18
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Roshanghalb A, Mazzali C, Lettieri E. Composite Outcomes of Mortality and Readmission in Patients with Heart Failure: Retrospective Review of Administrative Datasets. J Multidiscip Healthc 2020; 13:539-547. [PMID: 32612362 PMCID: PMC7322138 DOI: 10.2147/jmdh.s255206] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 05/22/2020] [Indexed: 12/22/2022] Open
Abstract
Background Controlling the quality of care through readmissions and mortality for patients with heart failure (HF) is a national priority for healthcare regulators in developed countries. In this longitudinal cohort study, using administrative data such as hospital discharge forms (HDFs), emergency departments (EDs) accesses, and vital statistics, we test new covariates for predicting mortality and readmissions of patients hospitalized for HF and discuss the use of combined outcome as an alternative. Methods Logistic models, with a stepwise selection method, were estimated on 70% of the sample and validated on the remaining 30% to evaluate 30-day mortality, 30-day readmissions, and the combined outcome. We followed an extraction method for any-cause mortality and unplanned readmission within 30 days after incident HF hospitalization. Data on patient admission and previous history were extracted by HDFs and ED dataset. Results Our principal findings demonstrate that the model’s discriminant ability is consistent with literature both for mortality (AUC=0.738, CI (0.729–0.748)) and readmissions (AUC=0.578, CI (0.562–0.594)). Additionally, the discriminant ability of the composite outcome model is satisfactory (AUC=0.675, CI (0.666–0.684)). Conclusion Hospitalization characteristics and patient history introduced in the logistic models do not improve their discriminant ability. The composite outcome prediction is led more by mortality than readmission, without improvements for the comprehension of the readmission phenomenon.
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Affiliation(s)
- Afsaneh Roshanghalb
- Department of Management, Economics & Industrial Engineering, Politecnico di Milano, Milan, Italy
| | | | - Emanuele Lettieri
- Department of Management, Economics & Industrial Engineering, Politecnico di Milano, Milan, Italy
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19
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Bucholz EM, Toomey SL, Butala NM, Chien AT, Yeh RW, Schuster MA. Suitability of elderly adult hospital readmission rates for profiling readmissions in younger adult and pediatric populations. Health Serv Res 2020; 55:277-287. [PMID: 32037552 DOI: 10.1111/1475-6773.13269] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
OBJECTIVE To determine the correlation between hospital 30-day risk-standardized readmission rates (RSRRs) in elderly adults and those in nonelderly adults and children. DATA SOURCES/STUDY SETTING US hospitals (n = 1760 hospitals admitting adult patients and 235 hospitals admitting both adult and pediatric patients) in the 2013-2014 Nationwide Readmissions Database. STUDY DESIGN Cross-sectional analysis comparing 30-day RSRRs for elderly adult (≥65 years), middle-aged adult (40-64 years), young adult (18-39 years), and pediatric (1-17 years) patients. PRINCIPAL FINDINGS Hospital elderly adult RSRRs were strongly correlated with middle-aged adult RSRRs (Pearson R2 .69 [95% confidence interval (CI) 0.66-0.71]), moderately correlated with young adult RSRRs (Pearson R2 .44 [95% CI 0.40-0.47]), and weakly correlated with pediatric RSRRs (Pearson R2 .28 [95% CI 0.17-0.38]). Nearly identical findings were observed with measures of interquartile agreement and Kappa statistics. This stepwise relationship between age and strength of correlation was consistent across every hospital characteristic. CONCLUSIONS Hospital readmission rates in elderly adults, which are currently used for public reporting and hospital comparisons, may reflect broader hospital readmission performance in middle-aged and young adult populations; however, they are not reflective of hospital performance in pediatric populations.
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Affiliation(s)
- Emily M Bucholz
- Department of Cardiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Sara L Toomey
- Harvard Medical School, Boston, Massachusetts.,Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts
| | - Neel M Butala
- Harvard Medical School, Boston, Massachusetts.,Department of Cardiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Alyna T Chien
- Harvard Medical School, Boston, Massachusetts.,Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts
| | - Robert W Yeh
- Department of Cardiology, Beth Israel Deaconess Hospital, Boston, Massachusetts
| | - Mark A Schuster
- Harvard Medical School, Boston, Massachusetts.,Division of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts.,Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California
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20
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Khot UN, Johnson MJ, Wiggins NB, Lowry AM, Rajeswaran J, Kapadia S, Menon V, Ellis SG, Goepfarth P, Blackstone EH. Long-Term Time-Varying Risk of Readmission After Acute Myocardial Infarction. J Am Heart Assoc 2019; 7:e009650. [PMID: 30375246 PMCID: PMC6404216 DOI: 10.1161/jaha.118.009650] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Background Readmission after myocardial infarction (MI) is a publicly reported quality metric with hospital reimbursement linked to readmission rates. We describe the timing and pattern of readmission by cause within the first year after MI in consecutive patients, regardless of revascularization strategy, payer status, or age. Methods and Results We identified patients discharged after an MI from April 2008 to June 2012. Readmission within 12 months was the primary end point. Readmissions were classified into 4 groups: MI related, other cardiovascular, noncardiovascular, and planned. A total of 3069 patients were discharged after an MI (average age, 65±13 years; and 1941 [63%] men). A total of 655 patients (21.3%) were readmitted at least once (897 total readmissions). A total of 147 patients (4.8%) were readmitted ≥2 times, accounting for 389 readmissions (43%). The instantaneous risk of all‐cause readmission was highest (15 readmissions/100 patients per month; 95% confidence interval, 12–19 readmissions/100 patients per month) immediately after discharge, decreased by almost half (8.1 readmissions/100 patients per month; 95% confidence interval, 7.2–9.0 readmissions/100 patients per month) within 15 days, and was substantially lower and relatively constant (1.4 readmissions/100 patients per month; 95% confidence interval, 1.2–1.6 readmissions/100 patients per month) out to 1 year. Cardiovascular causes of readmission were more common early after discharge. Conclusions Most patients with MI are never readmitted, whereas a small minority (≈5%) account for nearly half of 1‐year readmissions. The readmission pattern after MI is characterized by an early peak (first 15 days) of cardiovascular readmissions, followed by a middle period (months 1–4) of noncardiovascular readmissions, and ending with a low‐risk period (>4 months) during which the risk appears independent of cause. See Editorial by Levy and Allen
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Affiliation(s)
- Umesh N Khot
- 1 Department of Cardiology Heart and Vascular Institute Center for Healthcare Delivery Innovation Cleveland OH
| | - Michael J Johnson
- 1 Department of Cardiology Heart and Vascular Institute Center for Healthcare Delivery Innovation Cleveland OH
| | - Newton B Wiggins
- 1 Department of Cardiology Heart and Vascular Institute Center for Healthcare Delivery Innovation Cleveland OH
| | - Ashley M Lowry
- 2 Department of Quantitative Health Sciences Research Institute Cleveland OH
| | | | - Samir Kapadia
- 3 Department of Cardiology Heart and Vascular Institute Cleveland OH
| | - Venu Menon
- 3 Department of Cardiology Heart and Vascular Institute Cleveland OH
| | - Stephen G Ellis
- 3 Department of Cardiology Heart and Vascular Institute Cleveland OH
| | - Pamela Goepfarth
- 3 Department of Cardiology Heart and Vascular Institute Cleveland OH
| | - Eugene H Blackstone
- 2 Department of Quantitative Health Sciences Research Institute Cleveland OH.,3 Department of Cardiology Heart and Vascular Institute Cleveland OH
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21
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Singh GM, Becquart N, Cruz M, Acevedo A, Mozaffarian D, Naumova EN. Spatiotemporal and Demographic Trends and Disparities in Cardiovascular Disease Among Older Adults in the United States Based on 181 Million Hospitalization Records. J Am Heart Assoc 2019; 8:e012727. [PMID: 31658854 PMCID: PMC6898811 DOI: 10.1161/jaha.119.012727] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Background The US population is aging, with concurrent increases in cardiovascular disease (CVD) burdens; however, spatiotemporal and demographic trends in CVD incidence in the US elderly have not been investigated in detail. This study aims to characterize trends from 1991 to 2014 in CVD hospitalizations among US Medicare beneficiaries, aged 65+ years, by single year of age/sex/race/state using records from the US Centers for Medicare & Medicaid, covering 98% of older Americans. Methods and Results We abstracted 181 202 758 US Centers for Medicare & Medicaid hospitalization records indicating CVD in any of 10 diagnosis codes; tabulated total cases of CVD by sex, age, race, state, and calendar year (1991–2014); and normalized hospitalization counts to standardize over data batches. Stratum‐specific hospitalization rates were calculated using US Centers for Medicare & Medicaid records and US Census population counts; a cubic polynomial function was fit to year‐specific distributions of rates by single year of age. Nationwide, CVD‐related hospitalization rates increased from 1991 to 2014. Differences between hospitalization rates at age 65 and 66 years, representing magnitude of healthcare deferral until Medicare onset, increased by 7.49 per 100 people 1991 to 2006 overall, and were largest among blacks and Native Americans. Rates of CVD hospitalizations were consistently highest in the Midwest/Deep South. Evidence of misclassification of race/ethnicity in US Centers for Medicare & Medicaid hospitalization records in the 1990s was noted. Conclusions Trends in CVD‐related hospitalization rates among older Americans highlight the essential need for targeted policies to reduce CVD burdens, to improve reporting of race/ethnicity in large administrative databases, and to enhance access to affordable healthcare.
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Affiliation(s)
| | - Ninon Becquart
- Tufts Friedman School of Nutrition Science & Policy Boston MA
| | - Melissa Cruz
- Tufts Friedman School of Nutrition Science & Policy Boston MA
| | - Andrea Acevedo
- Department of Community Health Tufts University Medford MA
| | | | - Elena N Naumova
- Tufts Friedman School of Nutrition Science & Policy Boston MA
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22
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Chang BP. Can hospitalization be hazardous to your health? A nosocomial based stress model for hospitalization. Gen Hosp Psychiatry 2019; 60:83-89. [PMID: 31376645 PMCID: PMC6791742 DOI: 10.1016/j.genhosppsych.2019.07.014] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 07/17/2019] [Accepted: 07/25/2019] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Hospitalization places patients at elevated risk for the development of "nosocomial" or hospital acquired complications, ranging from multidrug resistant infections to delirium and physical deconditioning. Adverse nosocomial psychological effects of hospitalization may also exist. This paper introduces a nosocomial based stress model, conceptualizing hospitalization as a unique period of biopsychosocial vulnerability, due to physiologic effects of acute illness and psychosocial variables of the hospital experience. METHOD A research synthesis and narrative review was performed to evaluate evidence supporting this model, integrating existing knowledge of the psychological and physiological effects of acute life threatening events, with known sequelae associated with hospitalization. RESULT Psychosocial factors during hospitalization may act as independent predictors of recovery following hospitalization, moderating variables impacting ongoing physiologic changes due to acute illness, and/or dynamic bidirectional elements, influencing medical and psychological outcomes in the near and long-term setting. CONCLUSION The Nosocomial Stress model provides a novel framework to understanding the biopsychosocial interactions between the psychological and physiologic processes associated with illness and hospitalization. Based on this model, a research agenda is proposed to assess the contributions of acute illness, the hospital experience, and their interactions on the recovery of patients following hospitalization.
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Affiliation(s)
- Bernard P Chang
- Department of Emergency Medicine, Columbia University Medical Center, New York, NY, United States of America.
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23
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Schjødt I, Johnsen SP, Strömberg A, Kristensen NR, Løgstrup BB. Socioeconomic Factors and Clinical Outcomes Among Patients With Heart Failure in a Universal Health Care System. JACC-HEART FAILURE 2019; 7:746-755. [DOI: 10.1016/j.jchf.2019.06.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 06/04/2019] [Accepted: 06/04/2019] [Indexed: 12/28/2022]
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24
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Levy AE, Allen LA. When a Short-Term Outlook Is the Best Long-Term Strategy: Time-Varying Risk of Readmission After Acute Myocardial Infarction. J Am Heart Assoc 2019; 7:e010864. [PMID: 30373449 PMCID: PMC6404190 DOI: 10.1161/jaha.118.010864] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
See Article by Khot et al
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Affiliation(s)
- Andrew E Levy
- 1 Division of Cardiology Department of Medicine University of Colorado School of Medicine Aurora CO
| | - Larry A Allen
- 1 Division of Cardiology Department of Medicine University of Colorado School of Medicine Aurora CO
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25
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Komuro I, Kaneko H, Morita H, Isobe M, Nakayama H, Minematsu K, Yamaguchi T, Yazaki Y. Nationwide Actions Against Heart Failure Pandemic in Japan - What Should We Do From Academia? Circ J 2019; 83:1819-1821. [PMID: 31391350 DOI: 10.1253/circj.cj-19-0562] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Heart failure pandemic is rapidly approaching in Japan, requiring nationwide actions. In particular, the Japanese Circulation Society and related societies launched the Stroke and Cardiovascular Disease Control Act, which was passed by the National Diet, as the first ever legislative policy measure against stroke and cardiovascular disease. In association with this, actions against heart failure pandemic from the scientific field are also important. Because heart failure pandemic is a critical problem not only in Japan but also in many developed countries, we believe the nationwide approach, as summarized here, will greatly contribute to the development of cardiovascular medicine, particularly the management and treatment of heart failure worldwide.
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Affiliation(s)
- Issei Komuro
- Department of Cardiovascular Medicine, The University of Tokyo Graduate School of Medicine.,The Japanese Circulation Society.,The Japan Heart Foundation
| | - Hidehiro Kaneko
- Department of Cardiovascular Medicine, The University of Tokyo Graduate School of Medicine.,Department of Advanced Cardiology, The University of Tokyo Graduate School of Medicine
| | - Hiroyuki Morita
- Department of Cardiovascular Medicine, The University of Tokyo Graduate School of Medicine
| | - Mitsuaki Isobe
- The Japanese Circulation Society.,Sakakibara Heart Institute
| | | | - Kazuo Minematsu
- The Japan Stroke Association.,National Cerebral and Cardiovascular Center
| | - Takenori Yamaguchi
- The Japan Stroke Association.,National Cerebral and Cardiovascular Center
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26
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Khera R, Wang Y, Nasir K, Lin Z, Krumholz HM. Evaluation of 30-Day Hospital Readmission and Mortality Rates Using Regression-Discontinuity Framework. J Am Coll Cardiol 2019; 74:219-234. [DOI: 10.1016/j.jacc.2019.04.060] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 03/28/2019] [Accepted: 04/16/2019] [Indexed: 11/24/2022]
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27
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Tsutsui H. Heart Failure Practice in Japan: Successful at Present, but Challenging in the Future. J Card Fail 2019; 25:145-146. [DOI: 10.1016/j.cardfail.2019.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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28
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Roubinian NH, Murphy EL, Mark DG, Triulzi DJ, Carson JL, Lee C, Kipnis P, Kleinman S, Liu VX, Escobar GJ. Long-Term Outcomes Among Patients Discharged From the Hospital With Moderate Anemia: A Retrospective Cohort Study. Ann Intern Med 2019; 170:81-89. [PMID: 30557414 PMCID: PMC6639156 DOI: 10.7326/m17-3253] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Randomized clinical trial findings support decreased red blood cell (RBC) transfusion and short-term tolerance of in-hospital anemia. However, long-term outcomes related to changes in transfusion practice have not been described. OBJECTIVE To describe the prevalence of anemia at and after hospital discharge and associated morbidity and mortality events. DESIGN Retrospective cohort study. SETTING Integrated health care delivery system with 21 hospitals serving 4 million members. PARTICIPANTS 445 371 surviving adults who had 801 261 hospitalizations between January 2010 and December 2014. MEASUREMENTS Hemoglobin levels and RBC transfusion, rehospitalization, and mortality events within 6 months of hospital discharge. Generalized estimating equations were used to examine trends over time, accounting for correlated observations and patient-level covariates. RESULTS From 2010 to 2014, the prevalence of moderate anemia (hemoglobin levels between 7 and 10 g/dL) at hospital discharge increased from 20% to 25% (P < 0.001) and RBC transfusion declined by 28% (39.8 to 28.5 RBC units per 1000 patients; P < 0.001). The proportion of patients whose moderate anemia had resolved within 6 months of hospital discharge decreased from 42% to 34% (P < 0.001), and RBC transfusion and rehospitalization within 6 months of hospital discharge decreased from 19% to 17% and 37% to 33%, respectively (P < 0.001 for both). During this period, the adjusted 6-month mortality rate decreased from 16.1% to 15.6% (P = 0.004) in patients with moderate anemia, in parallel with that of all others. LIMITATION Possible unmeasured confounding. CONCLUSION Anemia after hospitalization increased in parallel with decreased RBC transfusion. This increase was not accompanied by a rise in subsequent RBC use, rehospitalization, or mortality within 6 months of hospital discharge. Longitudinal analyses support the safety of practice recommendations to limit RBC transfusion and tolerate anemia during and after hospitalization. PRIMARY FUNDING SOURCE National Heart, Lung, and Blood Institute.
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Affiliation(s)
- Nareg H Roubinian
- Kaiser Permanente Northern California, Oakland, and Blood Systems Research Institute and University of California, San Francisco, San Francisco, California (N.H.R.)
| | - Edward L Murphy
- Blood Systems Research Institute and University of California, San Francisco, San Francisco, California (E.L.M.)
| | - Dustin G Mark
- Kaiser Permanente Northern California, Oakland, California (D.G.M., C.L., P.K., V.X.L., G.J.E.)
| | - Darrell J Triulzi
- Institute for Transfusion Medicine, Pittsburgh, Pennsylvania (D.J.T.)
| | - Jeffrey L Carson
- Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey (J.L.C.)
| | - Catherine Lee
- Kaiser Permanente Northern California, Oakland, California (D.G.M., C.L., P.K., V.X.L., G.J.E.)
| | - Patricia Kipnis
- Kaiser Permanente Northern California, Oakland, California (D.G.M., C.L., P.K., V.X.L., G.J.E.)
| | - Steven Kleinman
- University of British Columbia, Victoria, British Columbia, Canada (S.K.)
| | - Vincent X Liu
- Kaiser Permanente Northern California, Oakland, California (D.G.M., C.L., P.K., V.X.L., G.J.E.)
| | - Gabriel J Escobar
- Kaiser Permanente Northern California, Oakland, California (D.G.M., C.L., P.K., V.X.L., G.J.E.)
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Iyngkaran P, Liew D, Neil C, Driscoll A, Marwick TH, Hare DL. Moving From Heart Failure Guidelines to Clinical Practice: Gaps Contributing to Readmissions in Patients With Multiple Comorbidities and Older Age. CLINICAL MEDICINE INSIGHTS-CARDIOLOGY 2018; 12:1179546818809358. [PMID: 30618487 PMCID: PMC6299336 DOI: 10.1177/1179546818809358] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2017] [Accepted: 09/14/2018] [Indexed: 12/20/2022]
Abstract
This feature article for the thematic series on congestive heart failure (CHF) readmissions aims to outline important gaps in guidelines for patients with multiple comorbidities and the elderly. Congestive heart failure diagnosis manifests as a 3-phase journey between the hospital and community, during acute, chronic stable, and end-of-life (palliative) phases. This journey requires in variable intensities a combination of multidisciplinary care within tertiary hospital or ambulatory care from hospital outpatients or primary health services, within the general community. Management goals are uniform, ie, to achieve the lowest New York Heart Association class possible, with improvement in ejection fraction, by delivering gold standard therapies within a CHF program. Comorbidities are an important common denominator that influences outcomes. Comorbidities include diabetes mellitus, chronic obstructive airways disease, chronic renal impairment, hypertension, obesity, sleep apnea, and advancing age. Geriatric care includes the latter as well as syndromes such as frailty, falls, incontinence, and confusion. Many systems still fail to comprehensively achieve all aspects of such programs. This review explores these factors.
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Affiliation(s)
- Pupalan Iyngkaran
- Northern Territory Medical Program, Flinders University, Darwin, NT, Australia
- Pupalan Iyngkaran, Yellow Building 4 Cnr University Drive North & University Drive West Charles Darwin University, Casuarina, NT 0815, Australia.
| | - Danny Liew
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Christopher Neil
- Department of Medicine—Western Precinct, The University of Melbourne, Melbourne, VIC, Australia
| | - Andrea Driscoll
- School of Nursing and Midwifery, Deakin University, Geelong, VIC, Australia
- Austin Health, Melbourne, VIC, Australia
| | | | - David L Hare
- Cardiovascular Research, The University of Melbourne, Melbourne, VIC, Australia
- Heart Failure Services, Austin Health, Melbourne, VIC, Australia
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30
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Niedziela JT, Parma Z, Pawlowski T, Rozentryt P, Gasior M, Wojakowski W. Secular trends in first-time hospitalization for heart failure with following one-year readmission and mortality rates in the 3.8 million adult population of Silesia, Poland between 2010 and 2016. The SILCARD database. Int J Cardiol 2018; 271:146-151. [DOI: 10.1016/j.ijcard.2018.05.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 04/22/2018] [Accepted: 05/08/2018] [Indexed: 10/28/2022]
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31
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Verweij L, Jepma P, Buurman BM, Latour CHM, Engelbert RHH, Ter Riet G, Karapinar-Çarkit F, Daliri S, Peters RJG, Scholte Op Reimer WJM. The cardiac care bridge program: design of a randomized trial of nurse-coordinated transitional care in older hospitalized cardiac patients at high risk of readmission and mortality. BMC Health Serv Res 2018; 18:508. [PMID: 29954403 PMCID: PMC6025727 DOI: 10.1186/s12913-018-3301-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Accepted: 06/15/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND After hospitalization for cardiac disease, older patients are at high risk of readmission and death. Although geriatric conditions increase this risk, treatment of older cardiac patients is limited to the management of cardiac diseases. The aim of this study is to investigate if unplanned hospital readmission and mortality can be reduced by the Cardiac Care Bridge transitional care program (CCB program) that integrates case management, disease management and home-based cardiac rehabilitation. METHODS In a randomized trial on patient level, 500 eligible patients ≥ 70 years and at high risk of readmission and mortality will be enrolled in six hospitals in the Netherlands. Included patients will receive a Comprehensive Geriatric Assessment (CGA) at admission. Randomization with stratified blocks will be used with pre-stratification by study site and cognitive status based on the Mini-Mental State Examination (15-23 vs ≥ 24). Patients enrolled in the intervention group will receive a CGA-based integrated care plan, a face-to-face handover with the community care registered nurse (CCRN) before discharge and four home visits post-discharge. The CCRNs collaborate with physical therapists, who will perform home-based cardiac rehabilitation and with a pharmacist who advices the CCRNs in medication management The control group will receive care as usual. The primary outcome is the incidence of first all-cause unplanned readmission or mortality within 6 months post-randomization. Secondary outcomes at three, six and 12 months after randomization are physical functioning, functional capacity, depression, anxiety, medication adherence, health-related quality of life, healthcare utilization and care giver burden. DISCUSSION This study will provide new knowledge on the effectiveness of the integration of geriatric and cardiac care. TRIAL REGISTRATION NTR6316 . Date of registration: April 6, 2017.
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Affiliation(s)
- L Verweij
- ACHIEVE Center of Applied Research, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands. .,Department of Cardiology, Academic Medical Center, Amsterdam, the Netherlands.
| | - P Jepma
- ACHIEVE Center of Applied Research, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands.,Department of Cardiology, Academic Medical Center, Amsterdam, the Netherlands
| | - B M Buurman
- ACHIEVE Center of Applied Research, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands.,Department of Internal Medicine, Section of Geriatric Medicine, Academic Medical Center, Amsterdam, the Netherlands
| | - C H M Latour
- ACHIEVE Center of Applied Research, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands
| | - R H H Engelbert
- ACHIEVE Center of Applied Research, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands.,Department of Rehabilitation, Academic Medical Center, Amsterdam, the Netherlands
| | - G Ter Riet
- Department of General Practice, Academic Medical Center, Amsterdam, the Netherlands
| | - F Karapinar-Çarkit
- Department of Clinical Pharmacy, OLVG hospital, Amsterdam, the Netherlands
| | - S Daliri
- Department of Cardiology, Academic Medical Center, Amsterdam, the Netherlands.,Department of Clinical Pharmacy, OLVG hospital, Amsterdam, the Netherlands
| | - R J G Peters
- Department of Cardiology, Academic Medical Center, Amsterdam, the Netherlands
| | - W J M Scholte Op Reimer
- ACHIEVE Center of Applied Research, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands.,Department of Cardiology, Academic Medical Center, Amsterdam, the Netherlands
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32
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Butala NM, Kramer DB, Shen C, Strom JB, Kennedy KF, Wang Y, Valsdottir LR, Wasfy JH, Yeh RW. Applicability of Publicly Reported Hospital Readmission Measures to Unreported Conditions and Other Patient Populations: A Cross-sectional All-Payer Study. Ann Intern Med 2018; 168:631-639. [PMID: 29582086 DOI: 10.7326/m17-1492] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Readmission rates after hospitalizations for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among Medicare beneficiaries are used to assess quality and determine reimbursement. Whether these measures reflect readmission rates for other conditions or insurance groups is unknown. OBJECTIVE To investigate whether hospital-level 30-day readmission measures for publicly reported conditions (HF, AMI, and pneumonia) among Medicare patients reflect those for Medicare patients hospitalized for unreported conditions or non-Medicare patients hospitalized with HF, AMI, or pneumonia. DESIGN Cross-sectional. SETTING Population-based. PARTICIPANTS Hospitals in the all-payer Nationwide Readmissions Database in 2013 and 2014. MEASUREMENTS Hospital-level 30-day all-cause risk-standardized excess readmission ratios (ERRs) were compared for 3 groups of patients: Medicare beneficiaries admitted for HF, AMI, or pneumonia (Medicare reported group); Medicare beneficiaries admitted for other conditions (Medicare unreported group); and non-Medicare beneficiaries admitted for HF, AMI, or pneumonia (non-Medicare group). RESULTS Within-hospital differences in ERRs varied widely among groups. Medicare reported ratios differed from Medicare unreported ratios by more than 0.1 for 29% of hospitals and from non-Medicare ratios by more than 0.1 for 46% of hospitals. Among hospitals with higher readmission ratios, ERRs for the Medicare reported group tended to overestimate ERRs for the non-Medicare group but underestimate those for the Medicare unreported group. LIMITATION Medicare groups and risk adjustment differed slightly from those used by the Centers for Medicare & Medicaid Services. CONCLUSION Hospital ERRs, as estimated by Medicare to determine financial penalties, have poor agreement with corresponding measures for populations and conditions not tied to financial penalties. Current publicly reported measures may not be good surrogates for overall hospital quality related to 30-day readmissions. PRIMARY FUNDING SOURCE Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology.
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Affiliation(s)
- Neel M Butala
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts (N.M.B., J.H.W.)
| | - Daniel B Kramer
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (D.B.K., C.S., J.B.S., L.R.V., R.W.Y.)
| | - Changyu Shen
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (D.B.K., C.S., J.B.S., L.R.V., R.W.Y.)
| | - Jordan B Strom
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (D.B.K., C.S., J.B.S., L.R.V., R.W.Y.)
| | - Kevin F Kennedy
- Saint Luke's Mid America Heart Institute/University of Missouri-Kansas City, Kansas City, Missouri (K.F.K.)
| | - Yun Wang
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Y.W.)
| | - Linda R Valsdottir
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (D.B.K., C.S., J.B.S., L.R.V., R.W.Y.)
| | - Jason H Wasfy
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts (N.M.B., J.H.W.)
| | - Robert W Yeh
- Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts (D.B.K., C.S., J.B.S., L.R.V., R.W.Y.)
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Lindenauer PK, Dharmarajan K, Qin L, Lin Z, Gershon AS, Krumholz HM. Risk Trajectories of Readmission and Death in the First Year after Hospitalization for Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 2018; 197:1009-1017. [PMID: 29206052 PMCID: PMC5909167 DOI: 10.1164/rccm.201709-1852oc] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 12/01/2017] [Indexed: 11/16/2022] Open
Abstract
RATIONALE Characterization of the dynamic nature of posthospital risk in chronic obstructive pulmonary disease (COPD) is needed to provide counseling and plan clinical services. OBJECTIVES To analyze risk of readmission and death after discharge for COPD among Medicare beneficiaries aged 65 years and older and to determine the association between ventilator support and risk trajectory. METHODS We computed daily absolute risks of hospital readmission and death for 1 year after discharge for COPD, stratified by ventilator support. We determined the time required for risks to decline by 50% from maximum daily values after discharge and for daily risks to plateau. We compared risks with those found in the general elderly population. MEASUREMENTS AND MAIN RESULTS Among 2,340,637 hospitalizations, the readmission rate at 1 year was 64.2%, including 63.5%, 66.0%, and 64.1% among those receiving invasive, noninvasive, and no ventilation, respectively. Among 1,283,069 hospitalizations, mortality at 1 year was 26.2%, including 45.7%, 41.8%, and 24.4% among those same respective groups. Daily risk of readmission declined by 50% within 28, 39, and 43 days and plateaued at 46, 54, and 61 days among those receiving invasive, noninvasive, and no ventilation, respectively. Risk of death declined by 50% by 3, 4, and 17 days and plateaued by 21, 18, and 24 days in the same respective groups. Risks of hospitalization and death were significantly higher after discharge for COPD than among the general Medicare population. CONCLUSIONS Discharge from the hospital is associated with prolonged risks of readmission and death that vary with need for ventilator support. Interventions limited to the first month after discharge may be insufficient to improve longitudinal outcomes.
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Affiliation(s)
- Peter K. Lindenauer
- Institute for Healthcare Delivery and Population Science and
- Department of Medicine, University of Massachusetts Medical School–Baystate, Springfield, Massachusetts
- Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Kumar Dharmarajan
- Clover Health, Jersey City, New Jersey
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, New Haven, Connecticut
| | - Li Qin
- Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, New Haven, Connecticut
| | - Zhenqiu Lin
- Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, New Haven, Connecticut
| | - Andrea S. Gershon
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
- University of Toronto, Toronto, Ontario, Canada
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada; and
| | - Harlan M. Krumholz
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
- Center for Outcomes Research and Evaluation, Yale–New Haven Hospital, New Haven, Connecticut
- Department of Health Policy and Management, Yale University School of Public Health, New Haven, Connecticut
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Nguyen JT, Vakil K, Adabag S, Westanmo A, Madlon-Kay R, Ishani A, Garcia S, McFalls EO. Hospital Readmission Rates Following AMI: Potential Interventions to Improve Efficiency. South Med J 2018; 111:93-97. [PMID: 29394425 DOI: 10.14423/smj.0000000000000768] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
OBJECTIVES Quality of care utilization measures for patients admitted to the hospital with an acute myocardial infarction (AMI) include length of stay (LOS) and 30-day readmission rates. Our aim was to test whether efforts resulting in reduced LOS in patients diagnosed as having AMI would result in a higher risk of readmission within 30 days of hospital discharge and whether specific interventions could be targeted to reduce readmissions. METHODS Using data supplied by the Veterans Affairs Inpatient Evaluation Center, we analyzed both the readmissions within 30 days of an AMI and LOS and determined the timing of readmissions and associated diagnoses. RESULTS During 2013-2015, 35 (13.3%) of 263 patients with AMI were readmitted within 30 days of discharge compared with 19 (13.4%) of 142 patients during 2016 (not significant). During the same time, LOS was <3 days in most patients. From 2013 to 2015, the initial hospital time was 6 ± 6 days, whereas time out of the hospital before readmission was 11 ± 8 days; these times did not differ from 2016. Initial therapeutic decisions were based on coronary anatomy in >90% of patients with a decision to proceed with revascularization in most patients. Diagnoses during readmission to the hospital were also similar during early and later time periods and most frequently were a result of either coronary artery bypass grafting-related complications from the initial hospitalization or elective coronary artery bypass grafting. Acute coronary syndrome-related diagnoses and recurrent noncardiac causes of chest pain also were common diagnoses during both time periods and did not involve extensive workup during the readmission. CONCLUSIONS Readmissions for patients with AMI were stable during a 4-year period, at a time that efforts to reduce LOS were emphasized. Because a significant proportion of readmissions involved noncardiac sources of chest pain, improved communication between the emergency department and in-patient cardiology services at the time of triage may be a feasible way to improve efficiency of utilization.
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Affiliation(s)
- Jennifer T Nguyen
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Kairav Vakil
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Selcuk Adabag
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Anders Westanmo
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Richard Madlon-Kay
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Areef Ishani
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Santiago Garcia
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
| | - Edward O McFalls
- From Cardiology, Veterans Affairs Medical Center, Minneapolis, Minnesota
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Lagu T, Pekow PS, Stefan MS, Shieh MS, Pack QR, Kashef MA, Atreya AR, Valania G, Slawsky MT, Lindenauer PK. Derivation and Validation of an In-Hospital Mortality Prediction Model Suitable for Profiling Hospital Performance in Heart Failure. J Am Heart Assoc 2018; 7:JAHA.116.005256. [PMID: 29437604 PMCID: PMC5850175 DOI: 10.1161/jaha.116.005256] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
BACKGROUND Comparing heart failure (HF) outcomes across hospitals requires adequate risk adjustment. We aimed to develop and validate a model that can be used to compare quality of HF care across hospitals. METHODS AND RESULTS We included patients with HF aged ≥18 years admitted to one of 433 hospitals that participated in the Premier Inc Data Warehouse. This model (Premier) contained patient demographics, comorbidities, and acute conditions present on admission, derived from administrative and billing records. In a separate data set derived from electronic health records, we validated the Premier model by comparing hospital risk-standardized mortality rates calculated with the Premier model to those calculated with a validated clinical model containing laboratory data (LAPS [Laboratory-Based Acute Physiology Score]). Among the 200 832 admissions in the Premier Inc Data Warehouse, inpatient mortality was 4.0%. The model showed acceptable discrimination in the warehouse data (C statistic 0.75; 95% confidence interval, 0.74-0.76). In the validation data set, both the Premier model and the LAPS models showed acceptable discrimination (C statistic: Premier: 0.76 [95% confidence interval, 0.74-0.77]; LAPS: 0.78 [95% confidence interval, 0.76-0.80]). Risk-standardized mortality rates for both models ranged from 2% to 7%. A linear regression equation describing the association between Premier- and LAPS-specific mortality rates revealed a regression line with a slope of 0.71 (SE: 0.07). The correlation coefficient of the standardized mortality rates from the 2 models was 0.82. CONCLUSIONS Compared with a validated model derived from clinical data, an HF mortality model derived from administrative data showed highly correlated risk-standardized mortality rate estimates, suggesting it could be used to identify high- and low-performing hospitals for HF care.
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Affiliation(s)
- Tara Lagu
- Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA .,University of Massachusetts Medical School-Baystate, Springfield, MA.,Department of Medicine, Baystate Medical Center, Springfield, MA
| | - Penelope S Pekow
- Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.,School of Public Health and Health Sciences, University of Massachusetts-Amherst, Amherst, MA
| | - Mihaela S Stefan
- Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.,University of Massachusetts Medical School-Baystate, Springfield, MA.,Department of Medicine, Baystate Medical Center, Springfield, MA
| | - Meng-Shiou Shieh
- Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA
| | - Quinn R Pack
- Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.,University of Massachusetts Medical School-Baystate, Springfield, MA.,Division of Cardiology, Baystate Medical Center, Springfield, MA
| | - Mohammad Amin Kashef
- University of Massachusetts Medical School-Baystate, Springfield, MA.,Division of Cardiology, Baystate Medical Center, Springfield, MA
| | - Auras R Atreya
- University of Massachusetts Medical School-Baystate, Springfield, MA.,Division of Cardiology, Baystate Medical Center, Springfield, MA.,Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI
| | - Gregory Valania
- University of Massachusetts Medical School-Baystate, Springfield, MA.,Division of Cardiology, Baystate Medical Center, Springfield, MA
| | - Mara T Slawsky
- University of Massachusetts Medical School-Baystate, Springfield, MA.,Division of Cardiology, Baystate Medical Center, Springfield, MA
| | - Peter K Lindenauer
- Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School-Baystate, Springfield, MA.,University of Massachusetts Medical School-Baystate, Springfield, MA.,Department of Medicine, Baystate Medical Center, Springfield, MA
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36
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Khera R, Jain S, Pandey A, Agusala V, Kumbhani DJ, Das SR, Berry JD, de Lemos JA, Girotra S. Comparison of Readmission Rates After Acute Myocardial Infarction in 3 Patient Age Groups (18 to 44, 45 to 64, and ≥65 Years) in the United States. Am J Cardiol 2017; 120:1761-1767. [PMID: 28865892 PMCID: PMC5825232 DOI: 10.1016/j.amjcard.2017.07.081] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Revised: 07/19/2017] [Accepted: 07/24/2017] [Indexed: 11/24/2022]
Abstract
Postacute myocardial infarction (AMI) readmissions are common among Medicare beneficiaries (≥65 years) and are associated with significant resource utilization. However, patterns of AMI readmissions for younger age groups in the United States are not known. In the Nationwide Readmissions Database, a nationally representative all-payer database of inpatient hospitalizations, we identified 212,171 index AMI hospitalizations in January to November 2013, weighted to represent 478,247 hospitalizations nationally (mean age 66.9 years, 38% women, 29% low income). This included 26,516 cases in the 18 to 44 age group, 183,703 in the 45 to 64 age group, and 268,027 in the ≥65 age group. The overall 30-day readmission rate was 14.5% and varied across age groups (9.7% [18 to 44], 11.2% [45 to 64], and 17.3% [≥65]). The cumulative cost of 30-day readmissions was $1.1 billion, of which $365 million was spent on those <65 years of age. In multivariable hierarchical models, the risk of readmission was higher in women and in low-income patients, but the effect varied by age (p value for age-gender and age-income interactions <0.05) and was more prominent in the younger age groups. Further, patients in all age groups continue to have a high hospitalization burden beyond the typical 30-day readmission period, with an overall 24% post-AMI 90-day readmission rate. In conclusion, readmissions in young and middle-aged AMI survivors pose a substantial burden on patients and on U.S. health-care resources. Women and low-income patients with AMI, particularly those in younger age groups, are more frequently readmitted, and readmissions continue to burden the health-care system beyond the typical 30-day window. Future investigations would need to be targeted toward a better understanding and improvement of the rehospitalization burden for vulnerable patient groups.
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Affiliation(s)
- Rohan Khera
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas.
| | - Snigdha Jain
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Ambarish Pandey
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Vijay Agusala
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Dharam J Kumbhani
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Sandeep R Das
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Jarett D Berry
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - James A de Lemos
- Division of Cardiology, UT Southwestern Medical Center, Dallas, Texas
| | - Saket Girotra
- Division of Cardiology, Department of Internal Medicine, University of Iowa, Iowa City, Iowa
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37
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Real-World Data on Heart Failure Readmission Reduction. J Am Coll Cardiol 2017; 69:2366-2368. [DOI: 10.1016/j.jacc.2017.03.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 03/10/2017] [Indexed: 11/22/2022]
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