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Sico JJ, Hu X, Myers LJ, Levine D, Bravata DM, Arling GW. Real-world analysis of two ischaemic stroke and TIA systolic blood pressure goals on 12-month mortality and recurrent vascular events. Stroke Vasc Neurol 2024:svn-2023-002759. [PMID: 38191185 DOI: 10.1136/svn-2023-002759] [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: 08/02/2023] [Accepted: 12/12/2023] [Indexed: 01/10/2024] Open
Abstract
INTRODUCTION Whether obtaining the more intensive goal systolic blood pressure (SBP) of <130 mm Hg, rather than a less intensive SBP goal of <140 mm Hg poststroke/transient ischaemic attack (TIA) is associated with incremental mortality and recurrent vascular event benefit is largely unexplored using real-world data. Lowering SBP excessively may result in poorer outcomes. METHODS This is a retrospective cohort study of 26 368 Veterans presenting to a Veterans Administration Medical Center (VAMC) with a stroke/TIA between October 2015 and July 2018. Patients were excluded from the study if they had missing or extreme BP values, receiving dialysis or palliative care, left against medical advice had a cancer diagnosis, were cared for in a VAMC enrolled in a stroke/TIA quality improvement initiative, died or had a cerebrovascular or cardiovascular event within 90 days after their index stroke/TIA. The analytical sample included 12 337 patients. Average SBP during 90 days after discharge was assessed in categories (≤105 mm Hg, 106-115 mm Hg, 116-130 mm Hg, 131-140 mm Hg and >140 mm Hg). Separate multivariable Cox proportional hazard regressions were used to examine the relationship between average SBP groups and time to: (1) mortality and (2) any recurrent vascular event, from 90 days to up to 365 days after discharge from the index emergency department visit or inpatient admission. RESULTS Compared with those with SBP>140 mm Hg, patients with SBP between 116 and 130 mm Hg had a significantly lower risk of recurrent stroke/TIA (HR 0.77, 95% CI 0.60 to 0.99) but not cardiovascular events. Patients with SBP lower than 105 mm Hg, compared with those with >140 mm Hg demonstrated a statistically significant higher risk of death (HR 2.07, 95% CI 1.43 to 3.00), but no statistical differences were found in other SBP groups. DISCUSSION Data support a more intensive SBP goal to prevent recurrent cerebrovascular events among stroke/TIA patients by 90 days poststroke/TIA compared with less intensive goal. Very low SBPs were associated with increased mortality risk.
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Affiliation(s)
- Jason J Sico
- Internal Medicine and Neurology, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Neurology, Veterans Affairs Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Xin Hu
- Yale School of Public Health, New Haven, Connecticut, USA
| | - Laura J Myers
- VA Health Services Research and Development (HSR&D) Center for Healthcare Informatics and Communication and the HSR&D Stroke Quality Enhancement Research Initiative (QUERI), Indianapolis, Indiana, USA
- Richard L. Roudebush VA Medical Center, Indianapolis, Indiana, USA
| | - Deborah Levine
- Departments of Medicine and Neurology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Dawn M Bravata
- Health Services Research and Development (HSR&D) Center for Healthcare Informatics and Communication and the HSR&D Stroke Quality Enhancement Research Initiative (QUERI); Richard L. Roudebush VA Medical Center, Indianapolis, Indiana, USA
| | - Greg W Arling
- Department of Veterans Affairs (VA), Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, Indiana, USA
- Department of Nursing, Purdue University, West Lafayette, Indiana, USA
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Cadilhac DA, Bravata DM, Bettger JP, Mikulik R, Norrving B, Uvere EO, Owolabi M, Ranta A, Kilkenny MF. Stroke Learning Health Systems: A Topical Narrative Review With Case Examples. Stroke 2023; 54:1148-1159. [PMID: 36715006 PMCID: PMC10050099 DOI: 10.1161/strokeaha.122.036216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
To our knowledge, the adoption of Learning Health System (LHS) concepts or approaches for improving stroke care, patient outcomes, and value have not previously been summarized. This topical review provides a summary of the published evidence about LHSs applied to stroke, and case examples applied to different aspects of stroke care from high and low-to-middle income countries. Our attempt to systematically identify the relevant literature and obtain real-world examples demonstrated the dissemination gaps, the lack of learning and action for many of the related LHS concepts across the continuum of care but also elucidated the opportunity for continued dialogue on how to study and scale LHS advances. In the field of stroke, we found only a few published examples of LHSs and health systems globally implementing some selected LHS concepts, but the term is not common. A major barrier to identifying relevant LHS examples in stroke may be the lack of an agreed taxonomy or terminology for classification. We acknowledge that health service delivery settings that leverage many of the LHS concepts do so operationally and the lessons learned are not shared in peer-reviewed literature. It is likely that this topical review will further stimulate the stroke community to disseminate related activities and use keywords such as learning health system so that the evidence base can be more readily identified.
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Affiliation(s)
- Dominique A Cadilhac
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia (D.A.C., M.F.K.)
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia (D.A.C., M.F.K.)
| | - Dawn M Bravata
- Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Indianapolis, IN (D.M.B.)
- Departments of Medicine and Neurology, Indiana University School of Medicine, Indianapolis (D.M.B.)
- Regenstrief Institute, Indianapolis, IN (D.M.B.)
| | - Janet Prvu Bettger
- Department of Health and Rehabilitation Sciences, Temple University College of Public Health, Philadelphia, PA (J.P.B.)
| | - Robert Mikulik
- International Clinical Research Centre, Neurology Department, St. Ann's University Hospital and Masaryk University, Brno, Czech Republic (R.M.)
- Health Management Institute, Czech Republic (R.M.)
| | - Bo Norrving
- Lund University, Department of Clinical Sciences Lund, Neurology, Skåne University Hospital, Sweden (B.N.)
| | - Ezinne O Uvere
- Department of Medicine, College of Medicine, University of Ibadan, Nigeria (E.O.U., M.O.)
| | - Mayowa Owolabi
- Department of Medicine, College of Medicine, University of Ibadan, Nigeria (E.O.U., M.O.)
| | - Annemarei Ranta
- Department of Medicine, University of Otago, Wellington, New Zealand (A.R.)
| | - Monique F Kilkenny
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia (D.A.C., M.F.K.)
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia (D.A.C., M.F.K.)
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Ouellet GM, O’Leary JR, Leggett CG, Skinner J, Tinetti ME, Cohen AB. Benefits and harms of oral anticoagulants for atrial fibrillation in nursing home residents with advanced dementia. J Am Geriatr Soc 2023; 71:561-568. [PMID: 36310367 PMCID: PMC9957933 DOI: 10.1111/jgs.18108] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/04/2022] [Accepted: 10/10/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Approximately 20% of older persons with dementia have atrial fibrillation (AF). Nearly all have stroke risks that exceed the guideline-recommended threshold for anticoagulation. Although individuals with dementia develop profound impairments and die from the disease, little evidence exists to guide anticoagulant discontinuation, and almost one-third of nursing home residents with advanced dementia and AF remain anticoagulated in the last 6 months of life. We aimed to quantify the benefits and harms of anticoagulation in this population. METHODS Using Minimum Data Set and Medicare claims, we conducted a retrospective cohort study with 14,877 long-stay nursing home residents aged ≥66 between 2013 and 2018 who had advanced dementia and AF. We excluded individuals with venous thromboembolism and valvular heart disease. We measured anticoagulant exposure quarterly, using Medicare Part D claims. The primary outcome was all-cause mortality; secondary outcomes were ischemic stroke and serious bleeding. We performed survival analyses with multivariable adjustment and inverse probability of treatment (IPT) weighting. RESULTS In the study sample, 72.0% were female, 82.7% were aged ≥80 years, and 13.5% were nonwhite. Mean CHA2 DS2 VASC score was 6.19 ± 1.58. In multivariable survival analysis, anticoagulation was associated with decreased risk of death (HR 0.71, 95% CI 0.67-0.75) and increased bleeding risk (HR 1.15, 95% CI 1.02-1.29); the association with stroke risk was not significant (HR 1.08, 95% CI 0.80-1.46). Results were similar in models with IPT weighting. While >50% of patients in both groups died within a year, median weighted survival was 76 days longer for anticoagulated individuals. CONCLUSION Persons with advanced dementia and AF derive clinically modest life prolongation from anticoagulation, at the cost of elevated risk of bleeding. The relevance of this benefit is unclear in a group with high dementia-related mortality and for whom the primary goal is often comfort.
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Affiliation(s)
- Gregory M. Ouellet
- Section of Geriatrics, Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | - John R. O’Leary
- Section of Geriatrics, Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
| | - Christopher G. Leggett
- The Dartmouth Institute for Health Policy & Clinical Practice, Dartmouth College, Hanover, NH
| | - Jonathan Skinner
- The Dartmouth Institute for Health Policy & Clinical Practice, Dartmouth College, Hanover, NH
| | - Mary E. Tinetti
- Section of Geriatrics, Yale School of Medicine, New Haven, CT
| | - Andrew B. Cohen
- Section of Geriatrics, Yale School of Medicine, New Haven, CT
- VA Connecticut Healthcare System, West Haven, CT
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Chen A, Chen DO. Simulation of a machine learning enabled learning health system for risk prediction using synthetic patient data. Sci Rep 2022; 12:17917. [PMID: 36289292 PMCID: PMC9606301 DOI: 10.1038/s41598-022-23011-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 10/21/2022] [Indexed: 01/20/2023] Open
Abstract
When enabled by machine learning (ML), Learning Health Systems (LHS) hold promise for improving the effectiveness of healthcare delivery to patients. One major barrier to LHS research and development is the lack of access to EHR patient data. To overcome this challenge, this study demonstrated the feasibility of developing a simulated ML-enabled LHS using synthetic patient data. The ML-enabled LHS was initialized using a dataset of 30,000 synthetic Synthea patients and a risk prediction XGBoost base model for lung cancer. 4 additional datasets of 30,000 patients were generated and added to the previous updated dataset sequentially to simulate addition of new patients, resulting in datasets of 60,000, 90,000, 120,000 and 150,000 patients. New XGBoost models were built in each instance, and performance improved with data size increase, attaining 0.936 recall and 0.962 AUC (area under curve) in the 150,000 patients dataset. The effectiveness of the new ML-enabled LHS process was verified by implementing XGBoost models for stroke risk prediction on the same Synthea patient populations. By making the ML code and synthetic patient data publicly available for testing and training, this first synthetic LHS process paves the way for more researchers to start developing LHS with real patient data.
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Affiliation(s)
- Anjun Chen
- LHS Technology Forum Initiative, Learning Health Community, 748 Matadero Ave, Palo Alto, CA, 94306, USA.
| | - Drake O Chen
- LHS Technology Forum Initiative, Learning Health Community, 748 Matadero Ave, Palo Alto, CA, 94306, USA
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Myers LJ, Perkins AJ, Zhang Y, Bravata DM. Identifying transient ischemic attack (TIA) patients at high-risk of adverse outcomes: development and validation of an approach using electronic health record data. BMC Neurol 2022; 22:256. [PMID: 35820867 PMCID: PMC9275263 DOI: 10.1186/s12883-022-02776-1] [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: 10/19/2021] [Accepted: 06/20/2022] [Indexed: 11/24/2022] Open
Abstract
Background Risk-stratification tools that have been developed to identify transient ischemic attack (TIA) patients at risk of recurrent vascular events typically include factors which are not readily available in electronic health record systems. Our objective was to evaluate two TIA risk stratification approaches using electronic health record data. Methods Patients with TIA who were cared for in Department of Veterans Affairs hospitals (October 2015—September 2018) were included. The six outcomes were mortality, recurrent ischemic stroke, and the combined endpoint of stroke or death at 90-days and 1-year post-index TIA event. The cohort was split into development and validation samples. We examined the risk stratification of two scores constructed using electronic health record data. The Clinical Assessment Needs (CAN) score is a validated measure of risk of hospitalization or death. The PREVENT score was developed specifically for TIA risk stratification. Results A total of N = 5250 TIA patients were included in the derivation sample and N = 4248 in the validation sample. The PREVENT score had higher c-statistics than the CAN score across all outcomes in both samples. Within the validation sample the c-statistics for the PREVENT score were: 0.847 for 90-day mortality, 0.814 for 1-year mortality, 0.665 for 90-day stroke, and 0.653 for 1-year stroke, 0.699 for 90-day stroke or death, and 0.744 for 1-year stroke or death. The PREVENT score classified patients into categories with extreme nadir and zenith outcome rates. The observed 1-year mortality rate among validation patients was 7.1%; the PREVENT score lowest decile of patients had 0% mortality and the highest decile group had 30.4% mortality. Conclusions The PREVENT score had strong c-statistics for the mortality outcomes and classified patients into distinct risk categories. Learning healthcare systems could implement TIA risk stratification tools within electronic health records to support ongoing quality improvement. Registration ClinicalTrials.gov Identifier: NCT02769338.
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Affiliation(s)
- Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA. .,VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA. .,Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. .,Regenstrief Institute, Indianapolis, IN, USA.
| | - Anthony J Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA.,Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Ying Zhang
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA.,Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA
| | - Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, USA.,VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN, USA.,Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.,Regenstrief Institute, Indianapolis, IN, USA.,Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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Bravata DM, Miech EJ, Myers LJ, Perkins AJ, Zhang Y, Rattray NA, Baird SA, Penney LS, Austin C, Damush TM. The Perils of a "My Work Here is Done" perspective: a mixed methods evaluation of sustainment of an evidence-based intervention for transient ischemic attack. BMC Health Serv Res 2022; 22:857. [PMID: 35787273 PMCID: PMC9254423 DOI: 10.1186/s12913-022-08207-8] [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] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/16/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND To evaluate quality improvement sustainment for Transient Ischemic Attack (TIA) and identify factors influencing sustainment, which is a challenge for Learning Healthcare Systems. METHODS Mixed methods were used to assess changes in care quality across periods (baseline, implementation, sustainment) and identify factors promoting or hindering sustainment of care quality. PREVENT was a stepped-wedge trial at six US Department of Veterans Affairs implementation sites and 36 control sites (August 2015-September 2019). Quality of care was measured by the without-fail rate: proportion of TIA patients who received all of the care for which they were eligible among brain imaging, carotid artery imaging, neurology consultation, hypertension control, anticoagulation for atrial fibrillation, antithrombotics, and high/moderate potency statins. Key informant interviews were used to identify factors associated with sustainment. RESULTS The without-fail rate at PREVENT sites improved from 36.7% (baseline, 58/158) to 54.0% (implementation, 95/176) and settled at 48.3% (sustainment, 56/116). At control sites, the without-fail rate improved from 38.6% (baseline, 345/893) to 41.8% (implementation, 363/869) and remained at 43.0% (sustainment, 293/681). After adjustment, no statistically significant difference in sustainment quality between intervention and control sites was identified. Among PREVENT facilities, the without-fail rate improved ≥2% at 3 sites, declined ≥2% at two sites, and remained unchanged at one site during sustainment. Factors promoting sustainment were planning, motivation to sustain, integration of processes into routine practice, leadership engagement, and establishing systems for reflecting and evaluating on performance data. The only factor that was sufficient for improving quality of care during sustainment was the presence of a champion with plans for sustainment. Challenges during sustainment included competing demands, low volume, and potential problems with medical coding impairing use of performance data. Four factors were sufficient for declining quality of care during sustainment: low motivation, champion inactivity, no reflecting and evaluating on performance data, and absence of leadership engagement. CONCLUSIONS Although the intervention improved care quality during implementation; performance during sustainment was heterogeneous across intervention sites and not different from control sites. Learning Healthcare Systems seeking to sustain evidence-based practices should embed processes within routine care and establish systems for reviewing and reflecting upon performance. TRIAL REGISTRATION Clinicaltrials.gov ( NCT02769338 ).
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Affiliation(s)
- Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA.
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA.
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Regenstrief Institute, Indianapolis, IN, USA.
| | - Edward J Miech
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Anthony J Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- Department of Biostatistics, Indiana University School of Medicine, IN, Indianapolis, USA
| | - Ying Zhang
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- Department of Biostatistics, College of Public Health, University of Nebraska Medical Center, Omaha, NE, USA
| | - Nicholas A Rattray
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
| | - Sean A Baird
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - Lauren S Penney
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Elizabeth Dole Center of Excellence for Veteran and Caregiver Research, South Texas Veterans Health Care System, San Antonio, TX, USA
- Department of Medicine, University of Texas Health San Antonio, San Antonio, TX, USA
| | - Curt Austin
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
| | - Teresa M Damush
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Indianapolis, IN, USA
- VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, HSR&D Mail Code 11H, 1481 West 10th Street, Indianapolis, IN, 46202, USA
- Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Indianapolis, IN, USA
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Arling G, Perkins A, Myers LJ, Sico JJ, Bravata DM. Blood Pressure Trajectories and Outcomes for Veterans Presenting at VA Medical Centers with a Stroke or Transient Ischemic Attack. Am J Med 2022; 135:889-896.e1. [PMID: 35292287 DOI: 10.1016/j.amjmed.2022.02.012] [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] [Received: 11/02/2021] [Revised: 01/31/2022] [Accepted: 02/10/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Blood pressure control has been shown to reduce risk of vascular events and mortality after an ischemic stroke or transient ischemic attack (TIA). Yet, questions remain about effectiveness, timing, and targeted blood pressure reduction. METHODS We analyzed data from a retrospective cohort of 18,837 veterans cared for 12 months prior and up to 12 months after an emergency department visit or inpatient admission for stroke or TIA. Latent class growth analysis was used to classify patients into systolic blood pressure trajectories. With Cox proportional hazard models, we examined relationships between blood pressure trajectories, intensification of antihypertensive medication, and stroke (fatal or non-fatal) and all-cause mortality in 12 months following the index event. RESULTS The cohort was classified into 4 systolic blood pressure trajectories: 19% with a low systolic blood pressure trajectory (mean systolic blood pressure = 116 mm Hg); 65% with a medium systolic blood pressure trajectory (mean systolic blood pressure = 136 mm Hg); 15% with a high systolic blood pressure trajectory (mean systolic blood pressure = 158 mm Hg), and 1% with a very high trajectory (mean systolic blood pressure = 183 mm Hg). After the stroke or TIA, individuals in the high and very high systolic blood pressure trajectories experienced a substantial decrease in systolic blood pressure that coincided with intensification of antihypertensive medication. Patients with very low and very high systolic blood pressure trajectories had a significantly greater (P < .05) hazard of mortality, while medication intensification was related significantly (P < .05) to lower hazard of mortality. CONCLUSIONS These findings point to the importance of monitoring blood pressure over multiple time points and of instituting enhanced hypertension management after stroke or TIA, particularly for individuals with high or very high blood pressure trajectories.
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Affiliation(s)
- Greg Arling
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; School of Nursing, Purdue University, West Lafayette, Indianapolis, IN.
| | - Anthony Perkins
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; Biostatistics, Indiana University School of Medicine, Indianapolis, IN
| | - Laura J Myers
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN; Health Services Research, Regenstrief Institute, Indianapolis, IN
| | - Jason J Sico
- Neurology Service, VA Connecticut Healthcare System, West Haven, Conn; Department of Neurology, Yale School of Medicine, New Haven, Conn
| | - Dawn M Bravata
- Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D) Precision Monitoring to Transform Care (PRISM) Quality Enhancement Research Initiative (QUERI), Washington, DC; VA HSR&D Center for Health Information and Communication (CHIC), Richard L. Roudebush VA Medical Center, Indianapolis, IN; Department of Internal Medicine, Indiana University School of Medicine, Indianapolis, IN; Health Services Research, Regenstrief Institute, Indianapolis, IN; Medicine Service, Richard L. Roudebush VA Medical Center, Indianapolis, IN
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Miech EJ, Perkins AJ, Zhang Y, Myers LJ, Sico JJ, Daggy J, Bravata DM. Pairing regression and configurational analysis in health services research: modelling outcomes in an observational cohort using a split-sample design. BMJ Open 2022; 12:e061469. [PMID: 35672067 PMCID: PMC9174826 DOI: 10.1136/bmjopen-2022-061469] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/12/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Configurational methods are increasingly being used in health services research. OBJECTIVES To use configurational analysis and logistic regression within a single data set to compare results from the two methods. DESIGN Secondary analysis of an observational cohort; a split-sample design involved randomly dividing patients into training and validation samples. PARTICIPANTS AND SETTING Patients who had a transient ischaemic attack (TIA) in US Department of Veterans Affairs hospitals. MEASURES The patient outcome was the combined endpoint of all-cause mortality or recurrent ischaemic stroke within 1 year post-TIA. The quality-of-care outcome was the without-fail rate (proportion of patients who received all processes for which they were eligible, among seven processes). RESULTS For the recurrent stroke or death outcome, configurational analysis yielded a three-pathway model identifying a set of (validation sample) patients where the prevalence was 15.0% (83/552), substantially higher than the overall sample prevalence of 11.0% (relative difference, 36%). The configurational model had a sensitivity (coverage) of 84.7% and specificity of 40.6%. The logistic regression model identified six factors associated with the combined endpoint (c-statistic, 0.632; sensitivity, 63.3%; specificity, 63.1%). None of these factors were elements of the configurational model. For the quality outcome, configurational analysis yielded a single-pathway model identifying a set of (validation sample) patients where the without-fail rate was 64.3% (231/359), nearly twice the overall sample prevalence (33.7%). The configurational model had a sensitivity (coverage) of 77.3% and specificity of 78.2%. The logistic regression model identified seven factors associated with the without-fail rate (c-statistic, 0.822; sensitivity, 80.3%; specificity, 84.2%). Two of these factors were also identified in the configurational analysis. CONCLUSIONS Configurational analysis and logistic regression represent different methods that can enhance our understanding of a data set when paired together. Configurational models optimise sensitivity with relatively few conditions. Logistic regression models discriminate cases from controls and provided inferential relationships between outcomes and independent variables.
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Affiliation(s)
- Edward J Miech
- Quality Enhancement Research Initiative (QUERI) and Health Services Research and Development (HSR&D), Roudebush VA Medical Center, Indianapolis, Indiana, USA
- Center for Health Services Research, Regenstrief Institute Inc, Indianapolis, Indiana, USA
| | - Anthony J Perkins
- Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ying Zhang
- Department of Biostatistics, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Laura J Myers
- Quality Enhancement Research Initiative (QUERI) and Health Services Research and Development (HSR&D), Roudebush VA Medical Center, Indianapolis, Indiana, USA
- Center for Health Services Research, Regenstrief Institute Inc, Indianapolis, Indiana, USA
| | - Jason J Sico
- Neurology Service, VA Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Joanne Daggy
- Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Dawn M Bravata
- Quality Enhancement Research Initiative (QUERI) and Health Services Research and Development (HSR&D), Roudebush VA Medical Center, Indianapolis, Indiana, USA
- Center for Health Services Research, Regenstrief Institute Inc, Indianapolis, Indiana, USA
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Tsang JY, Peek N, Buchan I, van der Veer SN, Brown B. OUP accepted manuscript. J Am Med Inform Assoc 2022; 29:1106-1119. [PMID: 35271724 PMCID: PMC9093027 DOI: 10.1093/jamia/ocac031] [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: 11/23/2021] [Revised: 02/08/2021] [Accepted: 02/24/2022] [Indexed: 11/26/2022] Open
Abstract
Objectives (1) Systematically review the literature on computerized audit and feedback (e-A&F) systems in healthcare. (2) Compare features of current systems against e-A&F best practices. (3) Generate hypotheses on how e-A&F systems may impact patient care and outcomes. Methods We searched MEDLINE (Ovid), EMBASE (Ovid), and CINAHL (Ebsco) databases to December 31, 2020. Two reviewers independently performed selection, extraction, and quality appraisal (Mixed Methods Appraisal Tool). System features were compared with 18 best practices derived from Clinical Performance Feedback Intervention Theory. We then used realist concepts to generate hypotheses on mechanisms of e-A&F impact. Results are reported in accordance with the PRISMA statement. Results Our search yielded 4301 unique articles. We included 88 studies evaluating 65 e-A&F systems, spanning a diverse range of clinical areas, including medical, surgical, general practice, etc. Systems adopted a median of 8 best practices (interquartile range 6–10), with 32 systems providing near real-time feedback data and 20 systems incorporating action planning. High-confidence hypotheses suggested that favorable e-A&F systems prompted specific actions, particularly enabled by timely and role-specific feedback (including patient lists and individual performance data) and embedded action plans, in order to improve system usage, care quality, and patient outcomes. Conclusions e-A&F systems continue to be developed for many clinical applications. Yet, several systems still lack basic features recommended by best practice, such as timely feedback and action planning. Systems should focus on actionability, by providing real-time data for feedback that is specific to user roles, with embedded action plans. Protocol Registration PROSPERO CRD42016048695.
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Affiliation(s)
- Jung Yin Tsang
- Corresponding Author: Jung Yin Tsang, Centre for Primary Care and Health Services Research, University of Manchester, 6th Floor Williamson Building, Oxford Road, Manchester M13 9PL, UK;
| | - Niels Peek
- Centre for Health Informatics, Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- NIHR Greater Manchester Patient Safety Translational Research Centre (GMPSTRC), University of Manchester, Manchester, UK
- NIHR Applied Research Collaboration Greater Manchester, University of Manchester, Manchester, UK
| | - Iain Buchan
- Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Sabine N van der Veer
- Centre for Health Informatics, Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Benjamin Brown
- Centre for Health Informatics, Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
- Centre for Primary Care and Health Services Research, University of Manchester, Manchester, UK
- NIHR Greater Manchester Patient Safety Translational Research Centre (GMPSTRC), University of Manchester, Manchester, UK
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Ingvar M, Blom MC, Winsnes C, Robinson G, Vanfleteren L, Huff S. On the Annotation of Health Care Pathways to Allow the Application of Care-Plans That Generate Data for Multiple Purposes. Front Digit Health 2021; 3:688218. [PMID: 34713160 PMCID: PMC8521921 DOI: 10.3389/fdgth.2021.688218] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 07/28/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: Procedural interoperability in health care requires information support and monitoring of a common work practice. Our aim was to devise an information model for a complete annotation of actions in clinical pathways that allow use of multiple plans concomitantly as several partial processes underlie any composite clinical process. Materials and Methods: The development of the information model was based on the integration of a defined protocol for clinical interoperability in the care of patients with chronic obstructive pulmonary disease and an observational study protocol for cohort characterization at the group level. In the clinical process patient reported outcome measures were included. Results: The clinical protocol and the observation study protocol were developed on the clinical level and a single plan definition was developed by merging of the protocols. The information model and a common data model that had been developed for care pathways was successfully implemented and data for the medical records and the observational study could be extracted independently. The interprofessional process support improved the communication between the stakeholders (health care professionals, clinical scientists and providers). Discussion: We successfully merged the processes and had a functionally successful pilot demonstrating a seamless appearance for the health care professionals, while at the same time it was possible to generate data that could serve quality registries and clinical research. The adopted data model was initially tested and hereby published to the public domain. Conclusion: The use of a patient centered information model and data annotation focused on the care pathway simplifies the annotation of data for different purposes and supports sharing of knowledge along the patient care path.
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Affiliation(s)
- Martin Ingvar
- Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
- Department of Clinical Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | | | | | - Greg Robinson
- International Consortium for Health Outcomes Measurement, Boston, MA, United States
| | - Lowie Vanfleteren
- University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Stan Huff
- Department of Biomedical Informatics, Intermountain Health Care, University of Utah, Salt Lake City, UT, United States
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Samanta D, Landes SJ. Implementation Science to Improve Quality of Neurological Care. Pediatr Neurol 2021; 121:67-74. [PMID: 34153816 PMCID: PMC8842973 DOI: 10.1016/j.pediatrneurol.2021.05.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 05/05/2021] [Accepted: 05/10/2021] [Indexed: 01/12/2023]
Abstract
Neurological disorders are the leading cause of disability and the second leading cause of death globally. To challenge this enormous disease burden, scientists are pursuing innovative solutions to maintain and improve the quality of neurological care. Despite the availability of many effective evidence-based practices, many patients with neurological disorders cannot access these (or receive them inefficiently after a long delay) and may be exposed to unnecessary, expensive, and potentially harmful treatments. To promote the systematic uptake of evidence-based practices into the real world, a new scientific study of methods has been developed: implementation science. In implementation science research, transdisciplinary research teams systematically (using theory, model, and framework) assess local barriers to facilitate the adoption of evidence-based practices and examine potential solutions using implementation strategies (interventions that help adoption of intended practices) targeting multiple levels in the health care system, including patient, provider, clinic, facility, organization, or broader community and policy environment. The success of these strategies (implementation outcomes) is measured by the extent and quality of the implementation. Implementation studies can be either observational or interventional but are distinct from traditional efficacy or effectiveness studies. Traditional neuroscience research and clinical trials, conducted in controlled settings, focus on discovering new insights with little consideration of translating those insights into the everyday practice of a resource-constrained and dynamic health care system. Thus, neurologists should become familiar with implementation science to reduce the knowledge-practice gap, maximize health care value, and improve management of brain disorders affecting public health.
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Affiliation(s)
- Debopam Samanta
- Neurology Division, Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
| | - Sara J Landes
- Department of Psychiatry & Central Arkansas Veterans Healthcare System, University of Arkansas for Medical Sciences, Behavioral Health QUERI, Little Rock, Arkansas
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12
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Acceptability of a complex team-based quality improvement intervention for transient ischemic attack: a mixed-methods study. BMC Health Serv Res 2021; 21:453. [PMID: 33980224 PMCID: PMC8117601 DOI: 10.1186/s12913-021-06318-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 03/25/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurologic Symptoms (PREVENT) program was a complex quality improvement (QI) intervention targeting transient ischemic attack (TIA) evidence-based care. The aim of this study was to evaluate program acceptability among the QI teams and factors associated with degrees of acceptability. METHODS QI teams from six Veterans Administration facilities participated in active implementation for a one-year period. We employed a mixed methods study to evaluate program acceptability. Multiple data sources were collected over implementation phases and triangulated for this evaluation. First, we conducted 30 onsite, semi-structured interviews during active implementation with 35 participants at 6 months; 27 interviews with 28 participants at 12 months; and 19 participants during program sustainment. Second, we conducted debriefing meetings after onsite visits and monthly virtual collaborative calls. All interviews and debriefings were audiotaped, transcribed, and de-identified. De-identified files were qualitatively coded and analyzed for common themes and acceptability patterns. We conducted mixed-methods matrix analyses comparing acceptability by satisfaction ratings and by the Theoretical Framework of Acceptability (TFA). RESULTS Overall, the QI teams reported the PREVENT program was acceptable. The clinical champions reported high acceptability of the PREVENT program. At pre-implementation phase, reviewing quality data, team brainstorming solutions and development of action plans were rated as most useful during the team kickoff meetings. Program acceptability perceptions varied over time across active implementation and after teams accomplished actions plans and moved into sustainment. We observed team acceptability growth over a year of active implementation in concert with the QI team's self-efficacy to improve quality of care. Guided by the TFA, the QI teams' acceptability was represented by the respective seven components of the multifaceted acceptability construct. CONCLUSIONS Program acceptability varied by time, by champion role on QI team, by team self-efficacy, and by perceived effectiveness to improve quality of care aligned with the TFA. A complex quality improvement program that fostered flexibility in local adaptation and supported users with access to data, resources, and implementation strategies was deemed acceptable and appropriate by front-line clinicians implementing practice changes in a large, national healthcare organization. TRIAL REGISTRATION clinicaltrials.gov : NCT02769338 .
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Affiliation(s)
- Monique F Kilkenny
- Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia (M.F.K.).,The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia (M.F.K.)
| | - Dawn M Bravata
- Precision Monitoring to Transform Care Quality Enhancement Research Initiative, Health Services Research and Development, Department of Veterans Affairs, Indianapolis, IN (D.M.B.).,Health Services Research and Development Center for Health Information and Communication, Richard L. Roudebush VA Medical Center, Department of Veterans Affairs, Indianapolis, IN (D.M.B.).,Medicine Service, Richard L. Roudebush VA Medical Center, Indianapolis, IN (D.M.B.).,Departments of Medicine and of Neurology, Indiana University School of Medicine, Indianapolis (D.M.B.).,William M. Tierney Center for Health Services Research, Regenstrief Institute, Indianapolis, IN (D.M.B.)
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Vahidy FS. A Learning Health Care System-Based Approach for Improving Quality of Care Among Patients With Transient Ischemic Attack. JAMA Netw Open 2020; 3:e2016123. [PMID: 32897370 DOI: 10.1001/jamanetworkopen.2020.16123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Farhaan S Vahidy
- Center for Outcomes Research, Houston Methodist Research Institute, Houston, Texas
- Houston Methodist Neurological Institute, Houston Methodist, Houston, Texas
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