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Christensen EW, Pelzl CE, Hemingway J, Wang JJ, Sanmartin MX, Naidich JJ, Rula EY, Sanelli PC. Drivers of Ischemic Stroke Hospital Cost Trends Among Older Adults in the United States. J Am Coll Radiol 2022; 20:411-421. [PMID: 36357310 DOI: 10.1016/j.jacr.2022.09.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 09/08/2022] [Accepted: 09/19/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE The increased use of neuroimaging and innovations in ischemic stroke (IS) treatment have improved outcomes, but the impact on median hospital costs is not well understood. METHODS A retrospective study was conducted using Medicare 5% claims data for 75,525 consecutive index IS hospitalizations for patients aged ≥65 years from 2012 to 2019 (values in 2019 dollars). IS episode cost was calculated in each year for trend analysis and stratified by cost components, including neuroimaging (CT angiography [CTA], CT perfusion [CTP], MRI, and MR angiography [MRA]), treatment (endovascular thrombectomy [EVT] and/or intravenous thrombolysis), and patient sociodemographic factors. Logistic regression was performed to analyze the drivers of high-cost episodes and median regression to assess drivers of median costs. RESULTS The median IS episode cost increased by 4.9% from $9,509 in 2012 to $9,973 in 2019 (P = .0021). Treatment with EVT resulted in the greatest odds of having a high-cost (>$20,000) hospitalization (odds ratio [OR], 71.86; 95% confidence interval [CI], 54.62-94.55), as did intravenous thrombolysis treatment (OR, 3.19; 95% CI, 2.90-3.52). Controlling for other factors, neuroimaging with CTA (OR, 1.72; 95% CI, 1.58-1.87), CTP (OR, 1.32; 95% CI, 1.14-1.52), and/or MRA (OR, 1.26; 95% CI, 1.15-1.38) had greater odds of having high-cost episodes than those without CTA, CTP, and MRA. Length of stay > 4 days (OR, 4.34; 95% CI, 3.99-4.72) and in-hospital mortality (OR, 1.85; 95% CI, 1.63-2.10) were also associated with high-cost episodes. CONCLUSIONS From 2012 to 2019, the median IS episode cost increased by 4.9%, with EVT as the main cost driver. However, the increasing treatment cost trends have been partially offset by decreases in median length of stay and in-hospital mortality.
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Barton P, Sheppard JP, Penaloza-Ramos CM, Jowett S, Ford GA, Lasserson D, Mant J, Mellor RM, Quinn T, Rothwell PM, Sandler D, Sims D, McManus RJ. When has service provision for transient ischaemic attack improved enough? A discrete event simulation economic modelling study. BMJ Open 2017; 7:e018189. [PMID: 29175888 PMCID: PMC5719325 DOI: 10.1136/bmjopen-2017-018189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
OBJECTIVES The aim of this study was to examine the impact of transient ischaemic attack (TIA) service modification in two hospitals on costs and clinical outcomes. DESIGN Discrete event simulation model using data from routine electronic health records from 2011. PARTICIPANTS Patients with suspected TIA were followed from symptom onset to presentation, referral to specialist clinics, treatment and subsequent stroke. INTERVENTIONS Included existing versus previous (less same day clinics) and hypothetical service reconfiguration (7-day service with less availability of clinics per day). OUTCOME MEASURES The primary outcome of the model was the prevalence of major stroke after TIA. Secondary outcomes included service costs (including those of treating subsequent stroke) and time to treatment and attainment of national targets for service provision (proportion of high-risk patients (according to ABCD2 score) seen within 24 hours). RESULTS The estimated costs of previous service provision for 490 patients (aged 74±12 years, 48.9% female and 23.6% high risk) per year at each site were £340 000 and £368 000, respectively. This resulted in 31% of high-risk patients seen within 24 hours of referral (47/150) with a median time from referral to clinic attendance/treatment of 1.15 days (IQR 0.93-2.88). The costs associated with the existing and hypothetical services decreased by £5000 at one site and increased £21 000 at the other site. Target attainment was improved to 79% (118/150). However, the median time to clinic attendance was only reduced to 0.85 days (IQR 0.17-0.99) and thus no appreciable impact on the modelled incidence of major stroke was observed (10.7 per year, 99% CI 10.5 to 10.9 (previous service) vs 10.6 per year, 99% CI 10.4 to 10.8 (existing service)). CONCLUSIONS Reconfiguration of services for TIA is effective at increasing target attainment, but in services which are already working efficiently (treating patients within 1-2 days), it has little estimated impact on clinical outcomes and increased investment may not be worthwhile.
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Affiliation(s)
- Pelham Barton
- Health Economics Unit, University of Birmingham, Birmingham, UK
| | - James P Sheppard
- Nuffield Department of Primary Care Health Sciences, NIHR School for Primary Care Research, University of Oxford, Oxford, UK
| | | | - Sue Jowett
- Health Economics Unit, University of Birmingham, Birmingham, UK
| | - Gary A Ford
- Oxford Academic Health Science Network, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Daniel Lasserson
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jonathan Mant
- Primary Care Unit, University of Cambridge, Cambridge, UK
| | - Ruth M Mellor
- Department of Public Health, NHS Lanarkshire, Bothwell, UK
| | - Tom Quinn
- Centre for Health and Social Care Research, Faculty of Health, Social Care and Education, St George's University of London, Kingston University, London, UK
| | - Peter M Rothwell
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - David Sandler
- Geriatric Medicine, Heart of England NHS Foundation Trust, Birmingham, UK
| | - Don Sims
- Stroke Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Richard J McManus
- Nuffield Department of Primary Care Health Sciences, NIHR School for Primary Care Research, University of Oxford, Oxford, UK
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El-Tawil S, Wardlaw J, Ford I, Mair G, Robinson T, Kalra L, Muir KW. Penumbra and re-canalization acute computed tomography in ischemic stroke evaluation: PRACTISE study protocol. Int J Stroke 2017; 12:671-678. [PMID: 28730951 DOI: 10.1177/1747493017696099] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Rationale Multimodal imaging, including computed tomography angiography and computed tomography perfusion imaging, yields additional information on intracranial vessels and brain perfusion and can differentiate between ischemic core and penumbra which may affect patient selection for intravenous thrombolysis. Hypothesis The use of multimodal imaging will increase the number of patients receiving intravenous thrombolysis and lead to better treatment outcomes. Sample size 400 patients. Methods and design PRACTISE is a prospective, multicenter, randomized, controlled trial in which patients presenting within 4.5 h of symptom onset are randomized to either the current evidence-based imaging (NCCT alone) or additional multimodal computed tomography imaging (NCCT + computed tomography angiography + computed tomography perfusion). Clinical decisions on intravenous recombinant tissue plasminogen activator are documented. Total imaging time in both arms and time to initiation of treatment delivery in those treated with intravenous recombinant tissue plasminogen activator, is recorded. Follow-up will include brain imaging at 24 h to document infarct size, the presence of edema and the presence of intra-cerebral hemorrhage. Clinical evaluations include NIHSS score at baseline, 24 h and day 7 ± 2, and mRS at day 90 to define functional outcomes. Study outcomes The primary outcome is the proportion of patients receiving intravenous recombinant tissue plasminogen activator. Secondary end-points evaluate times to decision-making, comparison of different image processing software and clinical outcomes at three months. Discussion Multimodal computed tomography is a widely available tool for patient selection for revascularization therapy, but it is currently unknown whether the use of additional imaging in all stroke patients is beneficial. The study opened for recruitment in March 2015 and will provide data on the value of multimodal imaging in treatment decisions for acute stroke.
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Affiliation(s)
- Salwa El-Tawil
- 1 Institute of Neuroscience & Psychology, Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK
| | - Joanna Wardlaw
- 2 Division of Neuroimaging Sciences, Western General Hospital, Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Ian Ford
- 3 Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK
| | - Grant Mair
- 2 Division of Neuroimaging Sciences, Western General Hospital, Edinburgh, University of Edinburgh, Edinburgh, UK
| | - Tom Robinson
- 4 Department of Cardiovascular Sciences, Ageing and Stroke Medicine Group, University of Leicester, Leicester, UK
| | - Lalit Kalra
- 5 Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK
| | - Keith W Muir
- 1 Institute of Neuroscience & Psychology, Queen Elizabeth University Hospital, University of Glasgow, Glasgow, UK
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Dietrich M, Walter S, Ragoschke-Schumm A, Helwig S, Levine S, Balucani C, Lesmeister M, Haass A, Liu Y, Lossius HM, Fassbender K. Is prehospital treatment of acute stroke too expensive? An economic evaluation based on the first trial. Cerebrovasc Dis 2014; 38:457-63. [PMID: 25531507 DOI: 10.1159/000371427] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2014] [Accepted: 12/08/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Recently, a strategy for treating stroke directly at the emergency site was developed. It was based on the use of an ambulance equipped with a scanner, a point-of-care laboratory, and telemedicine capabilities (Mobile Stroke Unit). Despite demonstrating a marked reduction in the delay to thrombolysis, this strategy is criticized because of potentially unacceptable costs. METHODS We related the incremental direct costs of prehospital stroke treatment based on data of the first trial on this concept to one year direct cost savings taken from published research results. Key parameters were configuration of emergency medical service personnel, operating distance, and population density. Model parameters were varied to cover 5 different relevant emergency medical service scenarios. Additionally, the effects of operating distance and population density on benefit-cost ratios were analyzed. RESULTS Benefits of the concept of prehospital stroke treatment outweighed its costs with a benefit-cost ratio of 1.96 in the baseline experimental setting. The benefit-cost ratio markedly increased with the reduction of the staff and with higher population density. Maximum benefit-cost ratios between 2.16 and 6.85 were identified at optimum operating distances in a range between 43.01 and 64.88 km (26.88 and 40.55 miles). Our model implies that in different scenarios the Mobile Stroke Unit strategy is cost-efficient starting from an operating distance of 15.98 km (9.99 miles) or from a population density of 79 inhabitants per km2 (202 inhabitants per square mile). CONCLUSION This study indicates that based on a one-year benefit-cost analysis that prehospital treatment of acute stroke is highly cost-effective across a wide range of possible scenarios. It is the highest when the staff size of the Mobile Stroke Unit can be reduced, for example, by the use of telemedical support from hospital experts. Although efficiency is positively related to population density, benefit-cost ratios can be greater than 1 even in rural settings.
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Affiliation(s)
- Martin Dietrich
- Chair of Business Administration and Health Services Management Research, Saarbrücken, Germany
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Burton KR, Perlis N, Aviv RI, Moody AR, Kapral MK, Krahn MD, Laupacis A. Systematic review, critical appraisal, and analysis of the quality of economic evaluations in stroke imaging. Stroke 2014; 45:807-14. [PMID: 24519409 DOI: 10.1161/strokeaha.113.004027] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE This study reviews the quality of economic evaluations of imaging after acute stroke and identifies areas for improvement. METHODS We performed full-text searches of electronic databases that included Medline, Econlit, the National Health Service Economic Evaluation Database, and the Tufts Cost Effectiveness Analysis Registry through July 2012. Search strategy terms included the following: stroke*; cost*; or cost-benefit analysis*; and imag*. Inclusion criteria were empirical studies published in any language that reported the results of economic evaluations of imaging interventions for patients with stroke symptoms. Study quality was assessed by a commonly used checklist (with a score range of 0% to 100%). RESULTS Of 568 unique potential articles identified, 5 were included in the review. Four of 5 articles were explicit in their analysis perspectives, which included healthcare system payers, hospitals, and stroke services. Two studies reported results during a 5-year time horizon, and 3 studies reported lifetime results. All included the modified Rankin Scale score as an outcome measure. The median quality score was 84.4% (range=71.9%-93.5%). Most studies did not consider the possibility that patients could not tolerate contrast media or could incur contrast-induced nephropathy. Three studies compared perfusion computed tomography with unenhanced computed tomography but assumed that outcomes guided by the results of perfusion computed tomography were equivalent to outcomes guided by the results of magnetic resonance imaging or noncontrast computed tomography. CONCLUSIONS Economic evaluations of imaging modalities after acute ischemic stroke were generally of high methodological quality. However, important radiology-specific clinical components were missing from all of these analyses.
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Affiliation(s)
- Kirsteen R Burton
- From the Institute of Health Policy, Management and Evaluation (K.R.B., N.P., M.K.K., M.D.K., A.L.), Departments of Medical Imaging (K.R.B., R.I.A., A.R.M.), Surgery, Division of Urology (N.P.), Institute of Medical Science (R.I.A., A.R.M.), Medicine (M.K.K., M.D.K., A.L.), and Toronto Health Economics and Technology Assessment Collaborative (M.D.K.), University of Toronto, Toronto, ON, Canada; Institute for Clinical and Evaluative Sciences, Toronto, ON, Canada (M.K.K.); and Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada (A.L.)
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Penaloza-Ramos MC, Sheppard JP, Jowett S, Barton P, Mant J, Quinn T, Mellor RM, Sims D, Sandler D, McManus RJ, Carr P, Greenfield S, Helliwell B, Nand C, Phillips N, Scott R, Singh S, Ward M. Cost-Effectiveness of Optimizing Acute Stroke Care Services for Thrombolysis. Stroke 2014; 45:553-62. [DOI: 10.1161/strokeaha.113.003216] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Maria Cristina Penaloza-Ramos
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - James P. Sheppard
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Sue Jowett
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Pelham Barton
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Jonathan Mant
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Tom Quinn
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Ruth M. Mellor
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Don Sims
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - David Sandler
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | - Richard J. McManus
- From the Health Economics Unit (M.C.P.-R., S.J., P.B.) and Primary Care Clinical Sciences (J.P.S., R.M.M.), University of Birmingham, Edgbaston, Birmingham, UK; Department of Primary Care Health Sciences, University of Oxford, Oxford, UK (J.P.S., R.J.M.); Primary Care Unit, University of Cambridge, Cambridge, UK (J.M.); Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK (T.Q.); University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK (D. Sims); and Heart of
| | | | | | | | | | | | | | - Satinder Singh
- Primary Care Clinical Sciences, University of Birmingham
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