Introduction: A validated clinical decision tool predictive of favorable functional outcomes following endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) remains elusive. We performed a retrospective case series of patients at our regional Comprehensive Stroke Center, over a four-year period, who have undergone EVT to elucidate patient characteristics and factors associated with a favorable functional outcome after EVT. Methods: We reviewed all cases of EVT at our institution between February 2018 and February 2022 in the extended time window from 6–24 h. Demographic, clinical, imaging, and procedure co-variates were included. A favorable clinical outcome was defined as a modified Rankin scale of 0–2. We included patients with M1 or internal carotid artery occlusion treated with EVT within 6–24 h after symptom onset. We used a univariate and multivariate logistic regression analysis to identify patient factors associated with a favorable clinical outcome at 90 days. Results: Our study included evaluation of 121 patients who underwent EVT at our comprehensive stroke center. Our analysis demonstrates that a higher recanalization score based on the modified Thrombolysis In Cerebral Infarction (mTICI) scale (2B-3) was a strong indicator of a favorable outcome (OR 7.33; CI 2.06–26.07; p = 0.0021). Our data also showed that a higher baseline National Institutes of Health Stroke Scale (NIHSS) score (p = 0.0095) and the presence of pre-existing hypertension (p = 0.0035) may also be predictors of an unfavorable outcome (mRS > 2) per our multivariate analysis. Conclusion: Patients without pre-existing hypertension had more favorable outcomes following EVT in the expanded time window. This is consistent with other multicenter data in the expanded time window that demonstrates greater odds of a poor outcome with elevated pre-, peri-, and post-endovascular-treatment blood pressure. Our data also demonstrate that the mTICI score is a strong predictor of favorable outcome, even after controlling for other variables. A lower baseline NIHSS at the time of thrombectomy may also indicate a favorable outcome. Furthermore, the presence of clinical or radiographic mismatch based on the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) and NIHSS per DAWN and DEFUSE-3 criteria did not emerge as a predictor of favorable outcome, which is congruent with recent randomized controlled trials and meta-analyses.

Introduction: A validated clinical decision tool predictive of favorable functional outcomes following endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) remains elusive. We performed a retrospective case series of patients at our regional Comprehensive Stroke Center, over a 4-year period, who have undergone EVT to elucidate patient characteristics and factors associated with a favorable functional outcome after EVT. Methods: We reviewed all cases of EVT at our institution from 2/2018 - 2/2022 in the extended time window from 6 - 24 hours. Demographic, clinical, imaging, and procedure co-variates were included. A favorable clinical outcome was defined as a modified Rankin scale or 0-2. We included patients with M1 or ICA occlusion treated with EVT within 6-24 hours after symptom onset. We used a univariate and multivariate logistic regression analysis to identify patient factors associated with a favorable clinical outcome at 90 days. Results: Our analysis demonstrates that higher recanalization score based on the mTICI scale (2B-3) was a strong indicator of favorable outcome per both our multivariate and univariate analysis (OR 4.11; CI 1.10 - 15.31; p 0.035). Our data also showed signal that the younger age (p 0.013), lower baseline NIHSS (p 0.043), shorter hospital length of stay (LOS) (p 0.030), and absence of pre-existing hypertension (p 0.026) may also be a predictor of favorable outcome per our univariate analysis. Conclusion: Patients without pre-existing hypertension had more favorable outcomes following EVT in the expanded time window. This is consistent with other multicenter data in the expanded time window that demonstrates greater odds of a poor outcome with elevated pre-, peri-, and post- endovascular treatment blood pressure. Our data also demonstrates mTICI score is a strong predictor of favorable outcome even when controlled for other variables. Other factors that may indicate a favorable outcome include younger age, lower baseline NIHSS, and shorter hospital LOS. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement No external funding was received ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Approved by University of Wisconsin SMPH IRB under Protocol ID: 2016-0418 I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data underlying the results are available as part of the article. No additional source data is required. Raw data used in analysis is available upon request.

HomeStrokeVol. 54, No. 5Neuro-Hospitalist—Hospital Capacity Strain Impacting Stroke Care No AccessArticle CommentaryRequest AccessFull TextAboutView Full TextView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toNo AccessArticle CommentaryRequest AccessFull TextNeuro-Hospitalist—Hospital Capacity Strain Impacting Stroke Care Eric E. Adelman and Michelle H. Leppert Eric E. AdelmanEric E. Adelman Correspondence to: Eric E. Adelman, MD, Department of Neurology, University of Wisconsin, 1685 Highland Ave, MFCB Room 7257, Madison, WI 53705. Email E-mail Address: [email protected] https://orcid.org/0000-0002-3559-5580 Department of Neurology, University of Wisconsin School of Medicine and Public Health, Madison (E.E.A.). and Michelle H. LeppertMichelle H. Leppert https://orcid.org/0000-0002-0679-7634 Department of Neurology, University of Colorado School of Medicine, Aurora (M.H.L.). Colorado Cardiovascular Outcomes Research Group, Denver (M.H.L.). Originally published23 Mar 2023https://doi.org/10.1161/STROKEAHA.123.042309Stroke. 2023;54:1390–1391"Neuro-Hospitalist—Hospital Capacity Strain Impacting Stroke Care." Stroke, 54(5), pp. 1390–1391FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.For Sources of Funding and Disclosures, see page 1391.Correspondence to: Eric E. Adelman, MD, Department of Neurology, University of Wisconsin, 1685 Highland Ave, MFCB Room 7257, Madison, WI 53705. Email adelman@neurology.wisc.eduReferences1. Eriksson CO, Stoner RC, Eden KB, Newgard CD, Guise JM. The association between hospital capacity strain and inpatient outcomes in highly developed countries: a systematic review.J Gen Intern Med. 2017; 32:686–696. doi: 10.1007/s11606-016-3936-3CrossrefGoogle Scholar2. Glatter R, Papadakos P. The coming collapse of the U.S. health care system.Time.2023. Accessed February 14, 2023. https://time.com/6246045/collapse-us-health-care-systemGoogle Scholar3. Wisconsin Department of Health Services. COVID-19 hospitalizations and hospital capacity.Accessed February 14, 2023. https://dhs.wisconsin.gov/covid-19/hosp-data.htmGoogle Scholar4. Adeoye O, Nystrom KV, Yavagal DR, Luciano J, Nogueira RG, Zorowitz RD, Khalessi AA, Bushnell C, Barsan WG, Panagos P, et al. Recommendations for the establishment of stroke systems of care: a 2019 update.Stroke. 2019; 50:e187–e210. doi: 10.1161/STR.0000000000000173LinkGoogle Scholar5. Ladwig B. IU Health Bloomington has lost a stroke certification. What that means for patients.The Herald Times. Accessed February 14, 2023. https://www.heraldtimesonline.com/story/news/local/2022/08/26/iu-health-bloomington-hospital-loses-joint-commission-stroke-certification/65417515007Google Scholar6. Darehed D, Norrving B, Stegmayr B, Zingmark K, Blom MC. Patients with acute stroke are less likely to be admitted directly to a stroke unit when hospital beds are scarce: a Swedish multicenter register study.Eur Stroke J. 2017; 2:178–186. doi: 10.1177/2396987317698328CrossrefGoogle Scholar7. Hughes S. AHA letter Re: challenges facing America's Health care workforce as the u.s. enters third year of COVID-19 pandemic.Accessed February 14, 2023. https://www.aha.org/lettercomment/2022-03-01-aha-provides-information-congress-re-challenges-facing-americas-healthGoogle Scholar8. Muoio D. Hospitals forced to delay patient discharges as nursing homes and rehab centers face major staff shortages.Accessed February 14, 2023. https://www.fiercehealthcare.com/hospitals/nursing-homes-snfs-facing-pandemic-labor-challenges-force-hospitals-to-delay-dischargesGoogle Scholar9. Landeiro F, Roberts K, Gray AM, Leal J. Delayed hospital discharges of older patients: a systematic review on prevalence and costs.Gerontologist. 2017; 59:e86–e97. doi: 10.1093/geront/gnx028CrossrefGoogle Scholar10. Arogyaswamy S, Vukovic N, Keniston A, Apgar S, Bowden K, Kantor MA, Diaz M, McBeth L, Burden M. The impact of hospital capacity strain: a qualitative analysis of experience and solutions at 13 academic medical centers.J Gen Intern Med. 2022; 37:1463–1474. doi: 10.1007/s11606-021-07106-8CrossrefGoogle Scholar11. Wisconsin Medicine addresses workforce shortages with innovative programs.Accessed: February 14, 2023. https://www.uwhealth.org/news/wisconsin-medicines-addresses-workforce-shortagesGoogle Scholar eLetters(0) eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate. Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page. Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetails May 2023Vol 54, Issue 5 Advertisement Article Information Metrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/STROKEAHA.123.042309PMID: 36951050 Originally publishedMarch 23, 2023 KeywordsCOVID-19emergencieshospitalnursesPDF download Advertisement Subjects Health Services Ischemic Stroke

We describe a case of 76-year-old woman with glossopharyngeal neuralgia who developed bradycardia and syncope after decreased carbamazepine dosing due to worsening renal function. Telemetry and EKG showed bradycardia and sinus pauses associated with paroxysms of typical glossopharyngeal neuralgia pain. With the addition of gabapentin to carbamazepine, her glossopharyngeal neuralgia pain as well as bradycardia resolved. A pacemaker was placed to prevent bradycardia and syncope. Clinicians should be mindful of the association between glossopharyngeal neuralgia and bradycardia and cardiac syncope so appropriate treatment can be offered in a timely manner to prevent adverse outcomes associated with syncope and cardiac arrest.

The relative mildness of the pandemic 2009 (H1N1) swine influenza virus compared to the 1918 pandemic (H1N1) virus may be due to a variety of possible causes, including the existence of effective immunity in the host, the lessened ability of the virus to bind to target cells or to replicate in them, a diminished secretion of molecules that could cause further complications like pneumonia, etc. A comparison of the hemagglutinin sequences from the pandemic 2009 (H1N1) viruses with that of the 1918 (H1N1) virus reveals a difference in the residues occupying position 200, which has been shown to be involved in receptor binding. In all the pandemic 2009 (H1N1) hemagglutinin sequences available in the NCBI database, position 200 is occupied by serine. In the hemagglutinin of the 1918 (H1N1) virus, position 200 is occupied by proline. A proline-to-serine substitution could introduce a significant structural change in the receptor-binding site of the hemagglutinin, which could reduce the receptor-binding ability of the 2009 (H1N1) virus. It is proposed that this substitution is the cause of the relative avirulence of the 2009 (H1N1) virus compared to the 1918 (H1N1) virus.

Importance:Debate continues about the value of event adjudication in clinical trials and whether independent centralized assessments improve reliability and validity of study results in masked randomized trials compared with local, investigator-assessed end points.Objective:To assess the results of the adjudicated end point process in the Platelet-Oriented Inhibition in New TIA and Minor Ischemic Stroke (POINT) trial by comparing end points assessed by local site investigators with centrally adjudicated end points.Design, Setting, and Participants:This is an ad hoc secondary analysis of a randomized, double-blind clinical trial comparing safety and effectiveness of clopidogrel bisulphate plus aspirin vs placebo plus aspirin. Patients received either 600 mg of clopidogrel bisulphate on day 1, then 75 mg per day through day 90 plus 50 to 325 mg of aspirin per day, or the same range of dosages of placebo plus aspirin. Investigators reported all potential end points; independent masked adjudicators were randomly assigned to review using definitions specified in the study protocol. This was a multicenter study; 269 international sites in 10 countries enrolled from May 28, 2010, to December 19, 2017. The study enrolled 4881 patients 18 years or older with transient ischemic attack or minor acute ischemic stroke within 12 hours of symptom onset and followed for 90 days from randomization; last follow-up was completed in March 2018.Main Outcomes and Measures:Independent adjudicators external to the study and masked to study treatment assignment adjudicated 467 primary and secondary effectiveness outcomes and major and minor bleeding events, including the primary composite end point, which was the risk of a composite of major ischemic events at 90 days, defined as ischemic stroke, myocardial infarction, or death from an ischemic vascular event. The primary safety end point was major hemorrhage. All components of the primary and safety outcomes were adjudicated.Results:In this secondary analysis of an international randomized clinical trial, a total of 269 sites worldwide randomized 4881 patients (median age, 65.0 years; interquartile range, 55-74 years); 55.0% were male. The primary results have been published previously. The hazard ratios for clopidogrel plus aspirin vs placebo plus aspirin for the primary composite end point were 0.75 (95% CI, 0.59-0.95) for adjudicator-assessed events and 0.76 (95% CI, 0.60-0.95) for investigator-assessed events. Agreement between adjudicator and investigator assessments was 90.7%. The hazard ratios for clopidogrel plus aspirin vs placebo plus aspirin for the primary safety end point were 2.32 (95% CI, 1.10-4.87) for adjudicator-assessed events and 2.58 (95% CI, 1.19-5.58) for investigator-assessed events, with an agreement rate of 77.5%.Conclusions and Relevance:Independent end point adjudication did not substantially alter estimates of the primary treatment effectiveness in the POINT trial.Trial Registration:ClinicalTrials.gov identifier: NCT00991029.

Purpose: Previous investigations into concussions' effects on Major League Baseball (MLB) players suggested that concussion negatively impacts traditional measures of batting performance. This study examined whether post-concussion batting performance, as measured by traditional, plate discipline, and batted ball statistics, in MLB players was worse than other post-injury performance. Subjects and methods: MLB players with concussion from 2008 to 2014 were identified. Concussion was defined by placement on the disabled list or missing games due to concussion, post-concussive syndrome, or head trauma. Injuries causing players to be put on the disabled list were matched by age, position, and injury duration to serve as controls. Mixed effects models were used to estimate concussion's influence after adjusting for potential confounders. The primary study outcome measurements were: traditional (eg, average), plate discipline (eg, swing-at-strike rate), and batted ball (eg, ground ball percentage) statistics. Results: There were 85 concussed players and 212 controls included in the analyses. There was no significant difference in performance between concussed players and controls. However, concussed players started at a lower level of performance pre-event than the controls, striking out a 9.2% rate vs 8.2% (P=0.042) with an isolated power of 0.075 vs 0.082 (P=0.035). For concussed players, traditional batting statistics decreased before plate discipline metrics. Conclusion: MLB players' performance was lower after return from concussion, but no more than after return from other injuries. The decreased performance prior to concussion suggests that concussion-related performance declines may not be due exclusively to concussion and perhaps point to risk factors predisposing to concussion.

To facilitate high-quality inpatient care for stroke patients, we built a system within our electronic health record (EHR) to identify stroke patients while they are in the hospital; capture necessary data in the EHR to minimize the burden of manual abstraction for stroke performance measures, decreasing daily time requirement from 2 hours to 15 minutes; generate reports using an automated process; and electronically transmit data to third parties. Provider champions and support from the EHR development team ensured that we balanced the needs of the hospital with those of frontline providers. This work summarizes the development and implementation of our stroke quality system.

Background: Migraine headache has been attributed to specific craniofacial peripheral nerve trigger sites. Some have postulated that hypertrophy of the corrugator muscles causes compression of the supraorbital and supratrochlear nerves, resulting in migraine headache. This study uses morphometric evaluation to determine whether corrugator anatomy differs between patients with migraine headache and control subjects. Methods: A retrospective review identified patients with and without migraine headache who had a recent computed tomographic scan. Morphometric evaluation of the corrugator supercilii muscles was performed in a randomized and blinded fashion on 63 migraine headache and 63 gender-matched control patients using a three-dimensional image-processing program. These images were analyzed to determine whether corrugator size differed between migraine and control patients. Results: There was no difference in mean corrugator volume or thickness between migraine and control patients. The mean corrugator volume was 1.01 ± 0.26 cm3 compared with 1.06 ± 0.27 cm3 in control patients (p = 0.258), and the mean maximum thickness was 5.36 ± 0.86 mm in migraine patients compared with 5.50 ± 0.91 mm in controls (p = 0.359). Similarly, subgroup analysis of 38 patients with frontal migraine and 38 control subjects demonstrated no difference in corrugator size. Further subgroup analysis of nine patients with unilateral frontal migraine showed no difference in corrugator size between the symptomatic side compared with the contralateral side. Conclusions: Muscle hypertrophy itself does not play a major role in triggering migraine headache. Instead, factors such as muscle hyperactivity or peripheral nerve sensitization may be more causative.

HomeCirculation: Cardiovascular Quality and OutcomesVol. 10, No. 9Can Electronic Health Records Make Quality Measurement Fast and Easy? Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBCan Electronic Health Records Make Quality Measurement Fast and Easy? Eric E. Adelman, MD and James F. Burke, MD Eric E. AdelmanEric E. Adelman From the Department of Neurology, University of Wisconsin-Madison (E.E.A.); Stroke Program, University of Michigan, Ann Arbor (J.F.B.); and Department of Neurology, Veterans Affairs Health System, Ann Arbor, MI (J.F.B.). and James F. BurkeJames F. Burke From the Department of Neurology, University of Wisconsin-Madison (E.E.A.); Stroke Program, University of Michigan, Ann Arbor (J.F.B.); and Department of Neurology, Veterans Affairs Health System, Ann Arbor, MI (J.F.B.). Originally published14 Sep 2017https://doi.org/10.1161/CIRCOUTCOMES.117.004180Circulation: Cardiovascular Quality and Outcomes. 2017;10:e004180Electronic health records (EHRs) present key opportunities to improve the efficiency of quality reporting. An underappreciated aspect of quality measurement is the amount of effort that goes into acquiring and reporting quality data. From chart abstraction to formatting the data so it can be shared with payers, accreditation agencies, and clinical staff, health systems spend a tremendous amount of funds on tracking and reporting of metrics. Electronic quality measures (eQMs) have the potential to automate much of this data collection and reporting process. By freeing staff who have extensive familiarity with the metrics from time-consuming chart abstraction, these quality experts can partner with clinical staff to improve patient care.See Article by Bravata et alIn this issue of Circulation: Cardiovascular Quality and Outcomes, Bravata et al1 developed and evaluated a series eQMs abstracted electronically from the medical record for patients with minor stroke and transient ischemic attack (TIA). The authors developed 31 eQMs encompassing 15 domains of care for patients with minor stroke and TIA that are aligned with national guidelines,2 clinical performance measures,3 and joint commission metrics.4 They then evaluated the agreement between these eQMs and the same measures abstracted manually in a random sample of 763 patients from 50 Veterans Health Administration hospitals.The authors found that for 16 of the 31 measures, electronic abstraction compared favorably with manual abstraction both for eligibility determination and for pass rate. The highest concordance was seen in administrative and laboratory data. Not surprisingly, eQMs struggled with data in free-text fields, such as preference-based medication refusal and outside-facility diagnostic testing. As a consequence, electronic abstraction of eligibility for clinically important measures, such as antithrombotic therapy by hospital day 2, performed poorly when compared with manual abstraction because eligibility assessment requires judgments that are typically captured in free-text fields. However, when pass rates (the number of patients who met a measure divided by the number eligible) were evaluated, electronic abstraction was similar to manual abstraction for many measures, likely because eQMs generally performed well enough to evaluate pass rates on measures with high baseline success rates. Strengths of this work include the broad array of measures studied; a focus on eligibility for each of the measures, in addition to simply evaluating pass/fail status; the use of double manual abstraction to ensure accuracy; rigorous testing of the validity of the eQMs; and comparison of performance across sites.As the authors note, although eQMs compared favorably with manual chart abstraction, there was a range of concordance, and some of the metrics with the highest concordance, such as hemoglobin A1c measurement, are not the most clinically valuable. eQM performance was often at its best for measures where the pass rate was high; thus, the ability of eQMs to drive performance improvement in the absence of abstracted measures may be limited. One conceptually appealing approach may be to replace high-performing abstracted measures with eQMS to prevent back sliding while focusing abstraction and resources on the frontiers of quality. The applicability of this work to commercially available EHR products is somewhat uncertain because it was done at Veterans Health Administration facilities using a narrowly disseminated EHR. Even though all Veterans Health Administration facilities use an integrated system, the authors still needed to leverage 6 databases to build the eQMs. In principle, it is likely that these results are reproducible in other systems, but it would require considerable effort.The inclusion of patients with TIA in this study is a potentially important advance for stroke quality measurement. TIA is common and represents a key opportunity to prevent stroke, and the exclusion of patients with TIA from the existing stroke quality paradigm substantially limits its reach. One problem with including patients with TIA with stroke patients for quality metrics is that TIA is a major diagnostic challenge. Interobserver agreement on what constitutes a TIA is limited,5,6 differential use of magnetic resonance imaging can lead to differential classification into stroke,7 and TIA diagnostic codes perform poorly.8 Impressively, the electronic criteria used by Bravata et al to identify patients with TIA was robust when compared with manual chart review: only 1% of EHR-based TIA diagnoses were reclassified to a diagnosis other than stroke or TIA by chart review. If replicated in other studies, this finding identifies a major opportunity to include patients with TIA in selected stroke quality metrics. Another potential virtue of combining TIA and stroke is that it potentially limits the opportunity for gaming of existing quality measurement systems.9 Given the fuzzy clinical boundary between TIA and stroke, facilities currently have the theoretical capacity to differentially assign patients to one group or the other to suit their needs. For example, classifying a transient ambiguous episode that lasts >24 hours as a stroke as opposed to a TIA both increases reimbursement and reduces a facility's adjusted mortality given the low risk of death in this condition.As quality measures (and eQMS in particular) proliferate, we run the risk of being awash in metrics that are easy to generate but have limited clinical utility.10 Institutions will need to choose how to prioritize which quality measures to track and report. Broadly, this requires an understanding of both the marginal clinical utility of individual measures and of the resources necessary to measure them. On both counts, considerable research is needed. For eQMs, a key strategy to increasing their utility is to minimize the burden on clinicians by integrating quality measurement into the typical workflow. This may mean more emphasis on structured documentation rather than free-text entry, so data can be pulled automatically, but these changes should optimally be done in such a way that patient interactions, as well as the narrative flow and informational content of notes is not disrupted.11With the integration of eQMs into EHRs, we now have the theoretical capacity to identify gaps in quality of care while patients are still in the hospital. Rather than reacting to missed opportunities, days to weeks later, EHRs open the door to a world where we can identify suboptimal care and address it in real time. Yet, in spite of this considerable potential, the present value of EHRs for quality measurement is distressingly limited. EHRs have been in use for almost 50 years, and the promise of real time quality monitoring remains almost entirely unfulfilled. If EHRs are to eventually transform care, its essential to understand why this is the case. As Bravata et al1 illustrate, the technology is not the problem. Rather we would speculate that a central factor is that the incentives are not strong enough for hospitals, EHR developers, and the healthcare system at large, to invest the time and energy needed to meaningfully optimize EHR-based quality measurement. To improve the quality of stroke care, it may be more important to get the incentives right than the technology.The stroke quality paradigm of the future should pull reliable data electronically from the EHR and integrate it into reports that are used by frontline staff to monitor and address the needs of their patients. The measures should be clinically meaningful and not require excess documentation from clinical staff. Payers, quality-improvement registries, and accreditation agencies should harmonize the measures they collect and encourage facilities to submit these data directly from the EHR. The work by Bravata et al is an important first step in this direction.DisclosuresNone.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.Correspondence to James F. Burke, MD, Robert Wood Johnson Foundation Clinical Scholars Program, 2800 Plymouth Rd, NCRC B10-G016, Ann Arbor, MI 48109-2800. E-mail [email protected]References1. Bravata DM, Myers LJ, Cheng E, Reeves M, Baye F, Yu Z, Damush T, Miech EJ, Sico J, Phipps M, Zillich A, Johanning J, Chaturvedi S, Austin C, Ferguson J, Maryfield B, Snow K, Ofner S, Graham G, Rhude R, Williams LS, Arling G. Development and validation of electronic quality measures to assess care for patients with transient ischemic attack and minor ischemic stroke.Circ Cardiovasc Qual Outcomes2017; 10:e003157. doi: 10.1161/CIRCOUTCOMES.116.003157.LinkGoogle Scholar2. Kernan WN, Ovbiagele B, Black HR, Bravata DM, Chimowitz MI, Ezekowitz MD, Fang MC, Fisher M, Furie KL, Heck DV, Johnston SC, Kasner SE, Kittner SJ, Mitchell PH, Rich MW, Richardson D, Schwamm LH, Wilson JA; American Heart Association Stroke Council, Council on Cardiovascular and Stroke Nursing, Council on Clinical Cardiology, and Council on Peripheral Vascular Disease. Guidelines for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association.Stroke. 2014; 45:2160–2236. doi: 10.1161/STR.0000000000000024.LinkGoogle Scholar3. Smith EE, Saver JL, Alexander DN, Furie KL, Hopkins LN, Katzan IL, Mackey JS, Miller EL, Schwamm LH, Williams LS; AHA/ASA Stroke Performance Oversight Committee. Clinical performance measures for adults hospitalized with acute ischemic stroke: performance measures for healthcare professionals from the American Heart Association/American Stroke Association.Stroke. 2014; 45:3472–3498. doi: 10.1161/STR.0000000000000045.LinkGoogle Scholar4. The Joint Commission. Primary Stroke Center Certification.https://www.jointcommission.org/certification/primary_stroke_centers.aspx. Accessed August 16, 2017.Google Scholar5. Schrock JW, Glasenapp M, Victor A, Losey T, Cydulka RK. Variables associated with discordance between emergency physician and neurologist diagnoses of transient ischemic attacks in the emergency department.Ann Emerg Med. 2012; 59:19–26. doi: 10.1016/j.annemergmed.2011.03.009.CrossrefMedlineGoogle Scholar6. Castle J, Mlynash M, Lee K, Caulfield AF, Wolford C, Kemp S, Hamilton S, Albers GW, Olivot JM. Agreement regarding diagnosis of transient ischemic attack fairly low among stroke-trained neurologists.Stroke. 2010; 41:1367–1370. doi: 10.1161/STROKEAHA.109.577650.LinkGoogle Scholar7. Burke JF, Kerber KA, Iwashyna TJ, Morgenstern LB. Wide variation and rising utilization of stroke magnetic resonance imaging: data from 11 states.Ann Neurol. 2012; 71:179–185. doi: 10.1002/ana.22698.CrossrefMedlineGoogle Scholar8. Benesch C, Witter DM, Wilder AL, Duncan PW, Samsa GP, Matchar DB. Inaccuracy of the international classification of diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease.Neurology. 1997; 49:660–664.CrossrefMedlineGoogle Scholar9. Mears A, Webley P. Gaming of performance measurement in health care: parallels with tax compliance.J Health Serv Res Policy. 2010; 15:236–242. doi: 10.1258/jhsrp.2010.009074.CrossrefMedlineGoogle Scholar10. Kelly A, Thompson JP, Tuttle D, Benesch C, Holloway RG. Public reporting of quality data for stroke: is it measuring quality?Stroke. 2008; 39:3367–3371. doi: 10.1161/STROKEAHA.108.518738.LinkGoogle Scholar11. Martin SA, Sinsky CA. The map is not the territory: medical records and 21st century practice.Lancet. 2016; 388:2053–2056. doi: 10.1016/S0140-6736(16)00338-X.CrossrefMedlineGoogle Scholar Previous Back to top Next FiguresReferencesRelatedDetailsCited By Baillieu R, Hoang H, Sripipatana A, Nair S, Lin S and Ozkaynak M (2020) Impact of health information technology optimization on clinical quality performance in health centers: A national cross-sectional study, PLOS ONE, 10.1371/journal.pone.0236019, 15:7, (e0236019) September 2017Vol 10, Issue 9 Advertisement Article InformationMetrics © 2017 American Heart Association, Inc.https://doi.org/10.1161/CIRCOUTCOMES.117.004180PMID: 28912203 Originally publishedSeptember 14, 2017 KeywordshumansEditorialsstrokepatient carefinancial managementPDF download Advertisement SubjectsQuality and OutcomesTransient Ischemic Attack (TIA)

Electronic health records (EHRs) present key opportunities to improve the efficiency of quality reporting. An underappreciated aspect of quality measurement is the amount of effort that goes into acquiring and reporting quality data. From chart abstraction to formatting the data so it can be shared with payers, accreditation agencies, and clinical staff, health systems spend a tremendous amount of funds on tracking and reporting of metrics. Electronic quality measures (eQMs) have the potential to automate much of this data collection and reporting process. By freeing staff who have extensive familiarity with the metrics from time-consuming chart abstraction, these quality experts can partner with clinical staff to improve patient care.See Article by Bravata et al In this issue of Circulation: Cardiovascular Quality and Outcomes , Bravata et al1 developed and evaluated a series eQMs abstracted electronically from the medical record for patients with minor stroke and transient ischemic attack (TIA). The authors developed 31 eQMs encompassing 15 domains of care for patients with minor stroke and TIA that are aligned with national guidelines,2 clinical performance measures,3 and joint commission metrics.4 They then evaluated the agreement between these eQMs and the same measures abstracted manually in a random sample of 763 patients from 50 Veterans Health Administration hospitals.The authors found that for 16 of the 31 measures, electronic abstraction compared favorably with manual abstraction both for eligibility …

Stroke is a major comorbidity for CEA/CAS patients (3%-6%) periprocedural. Patients require stringent monitoring post procedure (vital signs & neurological checks) to assess for neurological decline, initiate expedited treatment as necessary for improved patient outcomes. Post assessment auditing demonstrated 37% compliance with documentation of neurological assessments.

Mexican Americans (MAs) have been shown to have worse outcomes after stroke than non-Hispanic Whites (NHWs), but it is unknown if ethnic differences in stroke quality of care may contribute to these worse outcomes. We investigated ethnic differences in the quality of inpatient stroke care between MAs and NHWs within the population-based prospective Brain Attack Surveillance in Corpus Christi (BASIC) Project (February 2009- June 2012). Quality measures for inpatient stroke care, based on the 2008 Joint Commission Primary Stroke Center definitions were assessed from the medical record by a trained abstractor. Two summary measure of overall quality were also created (binary measure of defect-free care and the proportion of measures achieved for which the patient was eligible). 757 individuals were included (480 MAs and 277 NHWs). MAs were younger, more likely to have hypertension and diabetes, and less likely to have atrial fibrillation than NHWs. MAs were less likely than NHWs to receive tPA (RR: 0.72, 95% confidence interval (CI) 0.52, 0.98), and MAs with atrial fibrillation were less likely to receive anticoagulant medications at discharge than NHWs (RR 0.73, 95% CI 0.58, 0.94). There were no ethnic differences in the other individual quality measures, or in the two summary measures assessing overall quality. In conclusion, there were no ethnic differences in the overall quality of stroke care between MAs and NHWs, though ethnic differences were seen in the proportion of patients who received tPA and anticoagulant at discharge for atrial fibrillation.

Introduction: Studies have suggested that women may receive lower quality of care (QOC) than men, although population-based studies are lacking. We investigated sex disparities in QOC in the Brain Attack Surveillance in Corpus Christi Project. Methods: All ischemic stroke patients admitted to one of six Nueces County community hospitals between Feb 2009 and Jun 2012 were prospectively identified. Data regarding compliance with seven performance measures (PMs) were extracted from the medical records. A composite score of QOC representing the number of achieved PMs over all patient-appropriate PMs was calculated. Multivariable models with generalized estimating equations assessed the association between sex and the composite score and between sex and individual PMs. Models were adjusted for hospital clustering, age, and ethnicity, while the model assessing composite score was also adjusted for insurance status, education, pre-stroke functional status (Rankin 0-2), initial NIH stroke scale score, and comorbidity index. Results: Compared to men, women were older (median age 72 vs 65), less likely to have a pre-stroke Rankin 0-2 (69% vs 83%), and less likely to identify as married/living together (38% vs 61%). Results for the association of sex with individual PMs are shown below. Women were less likely to receive DVT prophylaxis at 48 hours, an antithrombotic at 48 hours, and to be discharged on an antithrombotic. Women were less likely to be discharged on a cholesterol medication, although this finding was of borderline significance. Women had a lower composite score (mean difference -0.030, 95% CI -0.057 to -0.003). Conclusions: In this population-based study, women had a lower overall stroke QOC, although absolute differences in most individual PMs were small. Further investigation into the factors contributing to the gender disparity in guideline-concordant stroke therapy should be pursued.

Introduction: Stroke Core Measures are intended to ensure that patients receive high quality, guideline-concordant acute stroke care. Compliance data is collected and reported to the public and to regulatory agencies for benchmarking and for reimbursement. Hypothesis: Core Measures noncompliance within one academic institution will often reflect ambiguous or incomplete documentation instead of true failure to provide medically appropriate care. Methods: We retrospectively reviewed Core Measures data for all ischemic and hemorrhagic stroke patients discharged from the University of Michigan between January 2013 and May 2014. Core Measures data was collected and reported per routine practice and contemporaneously reviewed by the institutional team. For this study, Core Measures failures were cross-referenced with the full medical chart and classified as “true failures” when care was not compliant with the Core Measure standard or “documentation failures” when chart review revealed poor documentation of otherwise appropriate care--for example, where a normal neurological examination was not explicitly linked with a decision to defer assessment for rehabilitation. Determinations of the basis for noncompliance on chart review were made by two different reviewers, with 100% agreement. Results: A total of 40 failures in 872 patients were identified and reviewed. Core Measures failures were documentation failures in 20 patients. Additional details are provided in Table 1. Conclusion: The high number of documentation-based failures in our experience illustrates potential problems in the use of administratively-defined measures as a marker of the quality of clinical care.

Background and Purpose: Poststroke functional outcome is critical to stroke survivors. We sought to determine whether adherence to current stroke performance measures is associated with better functional outcome 90 days after an ischemic stroke. Methods: Utilizing the Brain Attack Surveillance in Corpus Christi cohort, we examined adherence to 7 ischemic stroke performance measures from February 2009 to June 2012. Adherence to the measures was analyzed in aggregate using a binary defect-free score and an opportunity score, representing the proportion of eligible measures met. The opportunity score ranges from 0 to 1, with values closer to 1 implying better adherence. Functional outcome, defined by an activities of daily living and instrumental activities of daily living (ADL/IADL) score (range 1-4, higher scores worse), was ascertained at 90 days poststroke. Tobit regression models were fitted to examine the associations between the performance measures and functional outcome, adjusting for demographic and clinical characteristics, including stroke severity. Results: There were 565 patients with ischemic stroke included in the analysis. The median ADL/IADL score was 2.32 (interquartile range [IQR]: 1.41-3.41). The median opportunity score was 1 (IQR: 0.8-1), and 58.4% of the patients received defect-free care. After adjustment, the opportunity score (P =.67) and defect-free care (P =.92) were not associated with functional outcome. Conclusion: In this population, adherence to a composite of current stroke performance measures was not associated with poststroke functional outcome after adjustment for other factors. Performance measures that are associated with improved functional outcome should be developed and incorporated into stroke quality measures.

Objective:To estimate the ability of bedside information to risk stratify stroke in acute dizziness presentations.Methods:Surveillance methods were used to identify patients with acute dizziness and nystagmus or imbalance, excluding those with benign paroxysmal positional vertigo, medical causes, or moderate to severe neurologic deficits. Stroke was defined as acute infarction or intracerebral hemorrhage on a clinical or research MRI performed within 14 days of dizziness onset. Bedside information comprised history of stroke, the ABCD(2) score (age, blood pressure, clinical features, duration, and diabetes), an ocular motor (OM)-based assessment (head impulse test, nystagmus pattern [central vs other], test of skew), and a general neurologic examination for other CNS features. Multivariable logistic regression was used to determine the association of the bedside information with stroke. Model calibration was assessed using low (<5%), intermediate (5% to <10%), and high (10%) predicted probability risk categories.Results:Acute stroke was identified in 29 of 272 patients (10.7%). Associations with stroke were as follows: ABCD(2) score (continuous) (odds ratio [OR] 1.74; 95% confidence interval [CI] 1.20-2.51), any other CNS features (OR 2.54; 95% CI 1.06-6.08), OM assessment (OR 2.82; 95% CI 0.96-8.30), and prior stroke (OR 0.48; 95% CI 0.05-4.57). No stroke cases were in the model's low-risk probability category (0/86, 0%), whereas 9 were in the moderate-risk category (9/94, 9.6%) and 20 were in the high-risk category (20/92, 21.7%).Conclusion:In acute dizziness presentations, the combination of ABCD(2) score, general neurologic examination, and a specialized OM examination has the capacity to risk-stratify acute stroke on MRI.