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Bowden N, Figueroa JF, Papanicolas I. Bridging borders: Current trends and future directions in comparative health systems research. Health Serv Res 2024. [PMID: 39323263 DOI: 10.1111/1475-6773.14385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2024] Open
Affiliation(s)
- Nicholas Bowden
- Department of Women's and Children's Health, University of Otago, Dunedin, New Zealand
| | - Jose F Figueroa
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Irene Papanicolas
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
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2
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Shen M, Osman K, Blumenthal DM, DeMuth K, Liu Y. Home Heart Hospital Associated With Reduced Hospitalizations and Costs Among High-Cost Patients With Cardiovascular Disease. Clin Cardiol 2024; 47:e24302. [PMID: 38874052 PMCID: PMC11177177 DOI: 10.1002/clc.24302] [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: 02/13/2024] [Revised: 05/22/2024] [Accepted: 05/23/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND There is no widely accepted care model for managing high-need, high-cost (HNHC) patients. We hypothesized that a Home Heart Hospital (H3), which provides longitudinal, hospital-level at-home care, would improve care quality and reduce costs for HNHC patients with cardiovascular disease (CVD). OBJECTIVE To evaluate associations between enrollment in H3, which provides longitudinal, hospital-level at-home care, care quality, and costs for HNHC patients with CVD. METHODS This retrospective within-subject cohort study used insurance claims and electronic health records data to evaluate unadjusted and adjusted annualized hospitalization rates, total costs of care, part A costs, and mortality rates before, during, and following H3. RESULTS Ninety-four patients were enrolled in H3 between February 2019 and October 2021. Patients' mean age was 75 years and 50% were female. Common comorbidities included congestive heart failure (50%), atrial fibrillation (37%), coronary artery disease (44%). Relative to pre-enrollment, enrollment in H3 was associated with significant reductions in annualized hospitalization rates (absolute reduction (AR): 2.4 hospitalizations/year, 95% confidence interval [95% CI]: -0.8, -4.0; p < 0.001; total costs of care (AR: -$56 990, 95% CI: -$105 170, -$8810; p < 0.05; and part A costs (AR: -$78 210, 95% CI: -$114 770, -$41 640; p < 0.001). Annualized post-H3 total costs and part A costs were significantly lower than pre-enrollment costs (total costs of care: -$113 510, 95% CI: -$151 340, -$65 320; p < 0.001; part A costs: -$84 480, 95% CI: -$121 040, -$47 920; p < 0.001). CONCLUSIONS Longitudinal home-based care models hold promise for improving quality and reducing healthcare spending for HNHC patients with CVD.
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Affiliation(s)
- Michael Shen
- Novolink Health (Previously Duxlink Health), A Division of Cardiovascular Associates of America, Sunrise, Florida, USA
| | - Kareem Osman
- University of California Los Angeles David Geffen School of Medicine, Department of Medicine, Los Angeles, California, USA
| | - Daniel M Blumenthal
- Novocardia, A Division of Cardiovascular Associates of America, Celebration, Florida, USA
- Cardiology Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Kaelin DeMuth
- Philadelphia College of Osteopathic Medicine South Georgia, Moultrie, Georgia, USA
| | - Yixiang Liu
- Novolink Health (Previously Duxlink Health), A Division of Cardiovascular Associates of America, Sunrise, Florida, USA
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Luo AL, Ravi A, Arvisais-Anhalt S, Muniyappa AN, Liu X, Wang S. Development and Internal Validation of an Interpretable Machine Learning Model to Predict Readmissions in a United States Healthcare System. INFORMATICS 2023. [DOI: 10.3390/informatics10020033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023] Open
Abstract
(1) One in four hospital readmissions is potentially preventable. Machine learning (ML) models have been developed to predict hospital readmissions and risk-stratify patients, but thus far they have been limited in clinical applicability, timeliness, and generalizability. (2) Methods: Using deidentified clinical data from the University of California, San Francisco (UCSF) between January 2016 and November 2021, we developed and compared four supervised ML models (logistic regression, random forest, gradient boosting, and XGBoost) to predict 30-day readmissions for adults admitted to a UCSF hospital. (3) Results: Of 147,358 inpatient encounters, 20,747 (13.9%) patients were readmitted within 30 days of discharge. The final model selected was XGBoost, which had an area under the receiver operating characteristic curve of 0.783 and an area under the precision-recall curve of 0.434. The most important features by Shapley Additive Explanations were days since last admission, discharge department, and inpatient length of stay. (4) Conclusions: We developed and internally validated a supervised ML model to predict 30-day readmissions in a US-based healthcare system. This model has several advantages including state-of-the-art performance metrics, the use of clinical data, the use of features available within 24 h of discharge, and generalizability to multiple disease states.
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Patel R, Judge A, Johansen A, Marques EMR, Griffin J, Bradshaw M, Drew S, Whale K, Chesser T, Griffin XL, Javaid MK, Ben-Shlomo Y, Gregson CL. Multiple hospital organisational factors are associated with adverse patient outcomes post-hip fracture in England and Wales: the REDUCE record-linkage cohort study. Age Ageing 2022; 51:6679179. [PMID: 36041740 PMCID: PMC9427326 DOI: 10.1093/ageing/afac183] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/23/2022] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVES Despite established standards and guidelines, substantial variation remains in the delivery of hip fracture care across the United Kingdom. We aimed to determine which hospital-level organisational factors predict adverse patient outcomes in the months following hip fracture. METHODS We examined a national record-linkage cohort of 178,757 patients aged ≥60 years who sustained a hip fracture in England and Wales in 2016-19. Patient-level hospital admissions datasets, National Hip Fracture Database and mortality data were linked to metrics from 18 hospital-level organisational-level audits and reports. Multilevel models identified organisational factors, independent of patient case-mix, associated with three patient outcomes: length of hospital stay (LOS), 30-day all-cause mortality and emergency 30-day readmission. RESULTS Across hospitals mean LOS ranged from 12 to 41.9 days, mean 30-day mortality from 3.7 to 10.4% and mean readmission rates from 3.7 to 30.3%, overall means were 21.4 days, 7.3% and 15.3%, respectively. In all, 22 organisational factors were independently associated with LOS; e.g. a hospital's ability to mobilise >90% of patients promptly after surgery predicted a 2-day shorter LOS (95% confidence interval [CI]: 1.2-2.6). Ten organisational factors were independently associated with 30-day mortality; e.g. discussion of patient experience feedback at clinical governance meetings and provision of prompt surgery to >80% of patients were each associated with 10% lower mortality (95%CI: 5-15%). Nine organisational factors were independently associated with readmissions; e.g. readmissions were 17% lower if hospitals reported how soon community therapy would start after discharge (95%CI: 9-24%). CONCLUSIONS Receipt of hip fracture care should be reliable and equitable across the country. We have identified multiple, potentially modifiable, organisational factors associated with important patient outcomes following hip fracture.
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Affiliation(s)
- Rita Patel
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew Judge
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK,Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK,NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, UK
| | - Antony Johansen
- Division of Population Medicine, School of Medicine, Cardiff University and University Hospital of Wales, Cardiff, UK,National Hip Fracture Database, Royal College of Physicians, London, UK
| | - Elsa M R Marques
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK,NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, UK
| | - Jill Griffin
- Clinical & Operations Directorate, Royal Osteoporosis Society, Bath, UK
| | - Marianne Bradshaw
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sarah Drew
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Katie Whale
- Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK,NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, UK
| | - Tim Chesser
- Department of Trauma and Orthopaedics, Southmead Hospital, North Bristol NHS Trust, Bristol, UK
| | - Xavier L Griffin
- Barts Bone and Joint Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK,Royal London Hospital, Barts Health NHS Trust, London, UK
| | - Muhammad K Javaid
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Celia L Gregson
- Address correspondence to: Celia L. Gregson, Musculoskeletal Research Unit, Translational Health Sciences, Bristol Medical School, University of Bristol, Learning and Research Building, Level 1, Southmead Hospital, Bristol, BS10 5NB, UK. Tel: +44 7815102351.
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Grimm F, Johansen A, Knight H, Brine R, Deeny SR. Indirect effect of the COVID-19 pandemic on hospital mortality in patients with hip fracture: a competing risk survival analysis using linked administrative data. BMJ Qual Saf 2022; 32:264-273. [PMID: 35914925 PMCID: PMC10176403 DOI: 10.1136/bmjqs-2022-014896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/20/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND Hip fracture is a leading cause of disability and mortality among older people. During the COVID-19 pandemic, orthopaedic care pathways in the National Health Service in England were restructured to manage pressures on hospital capacity. We examined the indirect consequences of the pandemic for hospital mortality among older patients with hip fracture, admitted from care homes or the community. METHODS Retrospective analysis of linked care home and hospital inpatient data for patients with hip fracture aged 65 years and over admitted to hospitals in England during the first year of the pandemic (1 March 2020 to 28 February 2021) or during the previous year. We performed survival analysis, adjusting for case mix and COVID-19 infection, and considered live discharge as a competing risk. We present cause-specific hazard ratios (HRCS) for the effect of admission year on hospital mortality risk. RESULTS During the first year of the pandemic, there were 55 648 hip fracture admissions: a 5.2% decrease on the previous year. 9.5% of patients had confirmed or suspected COVID-19. Hospital stays were substantially shorter (p<0.05), and there was a higher daily chance of discharge (HRCS 1.40, 95% CI 1.38 to 1.41). Overall hip fracture inpatient mortality increased (7.2% in 2020/2021 vs 6.4% in 2019/2020), but patients without concomitant COVID-19 infection had lower mortality rates compared with the year before (5.3%). Admission during the pandemic was associated with a 11% increase in the daily risk of hospital death for patients with hip fracture (HRCS 1.11, 95% CI 1.05 to 1.16). CONCLUSIONS Although COVID-19 infections led to increases in hospital mortality, overall hospital mortality risk for older patients with hip fracture remained largely stable during the first year of the pandemic.
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Affiliation(s)
| | - Antony Johansen
- University Hospital of Wales and Cardiff University School of Medicine, Cardiff, UK.,National Hip Fracture Database, Royal College of Physicians, London, UK
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Johansen A, Ojeda-Thies C, Poacher AT, Hall AJ, Brent L, Ahern EC, Costa ML. Developing a minimum common dataset for hip fracture audit to help countries set up national audits that can support international comparisons. Bone Joint J 2022; 104-B:721-728. [PMID: 35638208 PMCID: PMC9948447 DOI: 10.1302/0301-620x.104b6.bjj-2022-0080.r1] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
AIMS The aim of this study was to explore current use of the Global Fragility Fracture Network (FFN) Minimum Common Dataset (MCD) within established national hip fracture registries, and to propose a revised MCD to enable international benchmarking for hip fracture care. METHODS We compared all ten established national hip fracture registries: England, Wales, and Northern Ireland; Scotland; Australia and New Zealand; Republic of Ireland; Germany; the Netherlands; Sweden; Norway; Denmark; and Spain. We tabulated all questions included in each registry, and cross-referenced them against the 32 questions of the MCD dataset. Having identified those questions consistently used in the majority of national audits, and which additional fields were used less commonly, we then used consensus methods to establish a revised MCD. RESULTS A total of 215 unique questions were used across the ten registries. Only 72 (34%) were used in more than one national audit, and only 32 (15%) by more than half of audits. Only one registry used all 32 questions from the 2014 MCD, and five questions were only collected by a single registry. Only 21 of the 32 questions in the MCD were used in the majority of national audits. Only three fields (anaesthetic grade, operation, and date/time of surgery) were used by all ten established audits. We presented these findings at the Asia-Pacific FFN meeting, and used an online questionnaire to capture feedback from expert clinicians from different countries. A draft revision of the MCD was then presented to all 95 nations represented at the Global FFN conference in September 2021, with online feedback again used to finalize the revised MCD. CONCLUSION The revised MCD will help aspirant nations establish new registry programmes, facilitate the integration of novel analytic techniques and greater multinational collaboration, and serve as an internationally-accepted standard for monitoring and improving hip fracture services. Cite this article: Bone Joint J 2022;104-B(6):721-728.
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Affiliation(s)
- Antony Johansen
- University Hospital of Wales and School of Medicine, Cardiff University, Cardiff, UK,National Hip Fracture Database, Royal College of Physicians, London, UK
| | | | | | | | - Louise Brent
- National Office of Clinical Audit, Royal College of Surgeons in Ireland, University of Medicine and Health Sciences, Dublin, Ireland
| | | | - Matt L. Costa
- Oxford Trauma and Emergency Care, Nuffield Department of Orthopaedics, Rheumatology & Musculoskeletal Sciences, University of Oxford, Oxford, UK,Correspondence should be sent to Matt L. Costa. E-mail:
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Cram P, Hatfield LA, Bakx P, Banerjee A, Fu C, Gordon M, Heine R, Huang N, Ko D, Lix LM, Novack V, Pasea L, Qiu F, Stukel TA, de Groot CU, Yan L, Landon B. Variation in revascularisation use and outcomes of patients in hospital with acute myocardial infarction across six high income countries: cross sectional cohort study. BMJ 2022; 377:e069164. [PMID: 35508312 PMCID: PMC9066381 DOI: 10.1136/bmj-2021-069164] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To compare treatment and outcomes for patients admitted to hospital with a primary diagnosis of ST elevation or non-ST elevation myocardial infarction (STEMI or NSTEMI) in six high income countries with very different healthcare delivery systems. DESIGN Retrospective cross sectional cohort study. SETTING Patient level administrative data from the United States, Canada (Ontario and Manitoba), England, the Netherlands, Israel, and Taiwan. PARTICIPANTS Adults aged 66 years and older admitted to hospital with STEMI or NSTEMI between 1 January 2011 and 31 December 2017. OUTCOMES MEASURES The three categories of outcomes were coronary revascularisation (percutaneous coronary intervention or coronary artery bypass graft surgery), mortality, and efficiency (hospital length of stay and 30 day readmission). Rates were standardised to the age and sex distribution of the US acute myocardial infarction population in 2017. Outcomes were assessed separately for STEMI and NSTEMI. Performance was evaluated longitudinally (over time) and cross sectionally (between countries). RESULTS The total number of hospital admissions ranged from 19 043 in Israel to 1 064 099 in the US. Large differences were found between countries for all outcomes. For example, the proportion of patients admitted to hospital with STEMI who received percutaneous coronary intervention in hospital during 2017 ranged from 36.9% (England) to 78.6% (Canada; 71.8% in the US); use of percutaneous coronary intervention for STEMI increased in all countries between 2011 and 2017, with particularly large rises in Israel (48.4-65.9%) and Taiwan (49.4-70.2%). The proportion of patients with NSTEMI who underwent coronary artery bypass graft surgery within 90 days of admission during 2017 was lowest in the Netherlands (3.5%) and highest in the US (11.7%). Death within one year of admission for STEMI in 2017 ranged from 18.9% (Netherlands) to 27.8% (US) and 32.3% (Taiwan). Mean hospital length of stay in 2017 for STEMI was lowest in the Netherlands and the US (5.0 and 5.1 days) and highest in Taiwan (8.5 days); 30 day readmission for STEMI was lowest in Taiwan (11.7%) and the US (12.2%) and highest in England (23.1%). CONCLUSIONS In an analysis of myocardial infarction in six high income countries, all countries had areas of high performance, but no country excelled in all three domains. Our findings suggest that countries could learn from each other by using international comparisons of patient level nationally representative data.
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Affiliation(s)
- Peter Cram
- Department of Medicine, University of Texas Medical Branch, Galveston, TX, USA
- ICES, Toronto, ON, Canada
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Laura A Hatfield
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Pieter Bakx
- Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, Netherlands
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
- Department of Cardiology, University College London Hospitals, London, UK
| | - Christina Fu
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | - Michal Gordon
- Clinical Research Center, Soroka University Medical Center, Faculty of Health Sciences, Ben Gurion University of the Negev, Beersheba, Israel
| | - Renaud Heine
- Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, Netherlands
| | - Nicole Huang
- Institute of Hospital and Health Care Administration, National Yang-Ming Chiao Tung University, Taipei, Taiwan
| | - Dennis Ko
- ICES, Toronto, ON, Canada
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Schulich Heart Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Lisa M Lix
- Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- George & Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, MB, Canada
| | - Victor Novack
- Clinical Research Center, Soroka University Medical Center, Faculty of Health Sciences, Ben Gurion University of the Negev, Beersheba, Israel
| | - Laura Pasea
- Institute of Health Informatics, University College London, London, UK
| | | | - Therese A Stukel
- ICES, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Carin Uyl de Groot
- Erasmus School of Health Policy and Management, Erasmus University, Rotterdam, Netherlands
| | - Lin Yan
- Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- George & Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, MB, Canada
| | - Bruce Landon
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
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Asheim A, Nilsen SM, Aam S, Anthun KS, Carlsen F, Janszky I, Vatten LJ, Bjørngaard JH. High ward occupancy, bedspacing, and 60 day mortality for patients with myocardial infarction, stroke, and heart failure. ESC Heart Fail 2022; 9:1884-1890. [PMID: 35345059 PMCID: PMC9065853 DOI: 10.1002/ehf2.13894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 02/14/2022] [Accepted: 03/02/2022] [Indexed: 11/20/2022] Open
Abstract
Aims To study the consequences of crowded wards among patients with cardiovascular disease. Methods and results This is a cohort study among 201 801 patients with 258 807 admissions who were acutely admitted for myocardial infarction (N = 107 895), stroke (N = 87 336), or heart failure (N = 63 576) to any Norwegian hospital between 2008 and 2016. The ward admitting most patients with the given clinical condition was considered a patient's home ward. We compared patients with the same condition admitted when home ward occupancy was different, at the same hospital and during comparable time periods. Occupancy was standardized such that a one‐unit difference corresponded to the interquartile range in occupancy in the given month. One interquartile increase in home ward occupancy was associated with 7% higher odds of admission to an alternate ward [odds ratio (OR) 1.07, 95% confidence interval (CI) 1.09 to 1.11], and length of stay was shorter (−0.10 days, 95% CI −0.18 to −0.09). Patients with heart failure had 15% higher odds of admission to alternate wards (OR 1.15, 95% CI 1.08 to 1.23) and increased mortality [hazard ratio (HR) 1.08, 95% CI 1.03 to 1.15]. We found no apparent effect on mortality for patients with myocardial infarction (HR 0.99, 95% CI 0.94 to 1.05) or stroke (HR 1.00, 95% CI 0.96 to 1.05). Conclusions Patients with heart failure had higher risk of admission to alternate wards when home ward occupancy was high. These patients may be negatively affected by full wards.
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Affiliation(s)
- Andreas Asheim
- Center for Health Care Improvement, St. Olav's Hospital HF, Trondheim University Hospital, Trondheim, Norway.,Department of Mathematical Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Sara Marie Nilsen
- Center for Health Care Improvement, St. Olav's Hospital HF, Trondheim University Hospital, Trondheim, Norway
| | - Stina Aam
- Department of Geriatric Medicine, Clinic of Medicine, St. Olav's Hospital HF, Trondheim University Hospital, Trondheim, Norway.,Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kjartan Sarheim Anthun
- Department of Public Health and Nursing, Norwegian University of Science and Technology, PO Box 8905, Trondheim, 7491, Norway.,Department of Health Research, SINTEF Digital, Trondheim, Norway
| | - Fredrik Carlsen
- Department of Economics, Norwegian University of Science and Technology, Trondheim, Norway
| | - Imre Janszky
- Center for Health Care Improvement, St. Olav's Hospital HF, Trondheim University Hospital, Trondheim, Norway.,Department of Public Health and Nursing, Norwegian University of Science and Technology, PO Box 8905, Trondheim, 7491, Norway
| | - Lars Johan Vatten
- Department of Public Health and Nursing, Norwegian University of Science and Technology, PO Box 8905, Trondheim, 7491, Norway
| | - Johan Håkon Bjørngaard
- Department of Public Health and Nursing, Norwegian University of Science and Technology, PO Box 8905, Trondheim, 7491, Norway.,Faculty of Nursing and Health Sciences, Nord University, Levanger, Norway
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Street A, Smith P. How can we make valid and useful comparisons of different health care systems? Health Serv Res 2021; 56 Suppl 3:1299-1301. [PMID: 34755335 PMCID: PMC8579199 DOI: 10.1111/1475-6773.13883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 09/18/2021] [Accepted: 09/24/2021] [Indexed: 11/28/2022] Open
Affiliation(s)
- Andrew Street
- Department of Health PolicyLondon School of Economics and Political ScienceLondonUK
| | - Peter Smith
- Centre for Health EconomicsUniversity of YorkYorkUK
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Papanicolas I, Figueroa JF. International comparison of patient care trajectories: Insights from the ICCONIC project. Health Serv Res 2021; 56 Suppl 3:1295-1298. [PMID: 34755338 PMCID: PMC8579200 DOI: 10.1111/1475-6773.13887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 11/26/2022] Open
Affiliation(s)
| | - Jose F. Figueroa
- Department of Health Policy and ManagementHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
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Figueroa JF, Horneffer KE, Riley K, Abiona O, Arvin M, Atsma F, Bernal‐Delgado E, Blankart CR, Bowden N, Deeny S, Estupiñán‐Romero F, Gauld R, Hansen TM, Haywood P, Janlov N, Knight H, Lorenzoni L, Marino A, Or Z, Pellet L, Orlander D, Penneau A, Schoenfeld AJ, Shatrov K, Skudal KE, Stafford M, van de Galien O, van Gool K, Wodchis WP, Tanke M, Jha AK, Papanicolas I. A methodology for identifying high-need, high-cost patient personas for international comparisons. Health Serv Res 2021; 56 Suppl 3:1302-1316. [PMID: 34755334 PMCID: PMC8579201 DOI: 10.1111/1475-6773.13890] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE To establish a methodological approach to compare two high-need, high-cost (HNHC) patient personas internationally. DATA SOURCES Linked individual-level administrative data from the inpatient and outpatient sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC) across 11 countries: Australia, Canada, England, France, Germany, the Netherlands, New Zealand, Spain, Sweden, Switzerland, and the United States. STUDY DESIGN We outline a methodological approach to identify HNHC patient types for international comparisons that reflect complex, priority populations defined by the National Academy of Medicine. We define two patient profiles using accessible patient-level datasets linked across different domains of care-hospital care, primary care, outpatient specialty care, post-acute rehabilitative care, long-term care, home-health care, and outpatient drugs. The personas include a frail older adult with a hip fracture with subsequent hip replacement and an older person with complex multimorbidity, including heart failure and diabetes. We demonstrate their comparability by examining the characteristics and clinical diagnoses captured across countries. DATA COLLECTION/EXTRACTION METHODS Data collected by ICCONIC partners. PRINCIPAL FINDINGS Across 11 countries, the identification of HNHC patient personas was feasible to examine variations in healthcare utilization, spending, and patient outcomes. The ability of countries to examine linked, individual-level data varied, with the Netherlands, Canada, and Germany able to comprehensively examine care across all seven domains, whereas other countries such as England, Switzerland, and New Zealand were more limited. All countries were able to identify a hip fracture persona and a heart failure persona. Patient characteristics were reassuringly similar across countries. CONCLUSION Although there are cross-country differences in the availability and structure of data sources, countries had the ability to effectively identify comparable HNHC personas for international study. This work serves as the methodological paper for six accompanying papers examining differences in spending, utilization, and outcomes for these personas across countries.
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Affiliation(s)
- Jose F. Figueroa
- Department of Health Policy and ManagementHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Kathryn E. Horneffer
- Department of Health Policy and ManagementHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Kristen Riley
- Department of Health Policy and ManagementHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Olukorede Abiona
- Centre for Health Economics Research and Evaluation (CHERE)University of TechnologySydneyAustralia
| | - Mina Arvin
- Radboud University Medical Center, Radboud Institute for Health Sciences, Scientific Center for Quality of HealthcareNijmegenThe Netherlands
| | - Femke Atsma
- Radboud University Medical Center, Radboud Institute for Health Sciences, Scientific Center for Quality of HealthcareNijmegenThe Netherlands
| | | | - Carl Rudolf Blankart
- KPM Center for Public ManagementUniversity of BernBernSwitzerland
- Hamburg Center for Health EconomicsUniversität HamburgHamburgGermany
| | - Nicholas Bowden
- Dunedin School of MedicineUniversity of OtagoDunedinNew Zealand
| | | | | | - Robin Gauld
- Otago Business SchoolUniversity of OtagoDunedinNew Zealand
| | | | - Philip Haywood
- Centre for Health Economics Research and Evaluation (CHERE)University of TechnologySydneyAustralia
| | - Nils Janlov
- The Swedish Agency for Health and Care Services AnalysisStockholmSweden
| | | | - Luca Lorenzoni
- Health DivisionOrganisation for Economic Co‐operation and Development (OECD)ParisFrance
| | - Alberto Marino
- Health DivisionOrganisation for Economic Co‐operation and Development (OECD)ParisFrance
- Department of Health PolicyLondon School of EconomicsLondonUK
| | - Zeynep Or
- Institute for Research and Documentation in Health Economics (IRDES)ParisFrance
| | - Leila Pellet
- Institute for Research and Documentation in Health Economics (IRDES)ParisFrance
| | - Duncan Orlander
- Department of Health Policy and ManagementHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Anne Penneau
- Institute for Research and Documentation in Health Economics (IRDES)ParisFrance
| | - Andrew J. Schoenfeld
- Department of Orthopedic SurgeryBrigham and Women's HospitalBostonMassachusettsUSA
| | - Kosta Shatrov
- KPM Center for Public ManagementUniversity of BernBernSwitzerland
| | | | | | | | - Kees van Gool
- Centre for Health Economics Research and Evaluation (CHERE)University of TechnologySydneyAustralia
| | - Walter P. Wodchis
- Institute of Health Policy Management & EvaluationUniversity of TorontoTorontoOntarioCanada
- Institute for Better Health, Trillium Health PartnersMississaugaOntarioCanada
| | - Marit Tanke
- Radboud University Medical Center, Radboud Institute for Health Sciences, Scientific Center for Quality of HealthcareNijmegenThe Netherlands
| | - Ashish K. Jha
- Brown School of Public HealthProvidenceRhode IslandUSA
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