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Abouleish AE, Pomerantz P, Peterson MD, Cannesson M, Akeju O, Miller TR, Rathmell JP, Cole DJ. Closing the Chasm: Understanding and Addressing the Anesthesia Workforce Supply and Demand Imbalance. Anesthesiology 2024; 141:238-249. [PMID: 38884582 DOI: 10.1097/aln.0000000000005052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
The imbalance in anesthesia workforce supply and demand has been exacerbated post-COVID due to a surge in demand for anesthesia care, especially in non-operating room anesthetizing sites, at a faster rate than the increase in anesthesia clinicians. The consequences of this imbalance or labor shortage compromise healthcare facilities, adversely affect the cost of care, worsen anesthesia workforce burnout, disrupt procedural and surgical schedules, and threaten academic missions and the ability to educate future anesthesiologists. In developing possible solutions, one must examine emerging trends that are affecting the anesthesia workforce, new technologies that will transform anesthesia care and the workforce, and financial considerations, including governmental payment policies. Possible practice solutions to this imbalance will require both short- and long-term multifactorial approaches that include increasing training positions and retention policies, improving capacity through innovations, leveraging technology, and addressing financial constraints.
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Affiliation(s)
- Amr E Abouleish
- Department of Anesthesiology, University of Texas Medical Branch, Galveston, Texas
| | - Paul Pomerantz
- American Society of Anesthesiologists, Chicago, Illinois
| | | | - Maxime Cannesson
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Oluwaseun Akeju
- Department of Anesthesiology, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Thomas R Miller
- Center for Anesthesia Workforce Studies, American Society of Anesthesiologists, Schaumburg, Illinois
| | - James P Rathmell
- Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Boston, Massachusetts; Department of Anaesthesia, Harvard Medical School, Boston, Massachusetts
| | - Daniel J Cole
- Department of Anesthesiology and Perioperative Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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Parameswaran V, Koos H, Kalwani N, Qureshi L, Rosengaus L, Dash R, Scheinker D, Rodriguez F, Johnson CB, Stange K, Aron D, Lyytinen K, Sharp C. Drivers of telemedicine in primary care clinics at a large academic medical centre. J Telemed Telecare 2023:1357633X231219311. [PMID: 38130140 DOI: 10.1177/1357633x231219311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
BACKGROUND COVID-19 disrupted healthcare routines and prompted rapid telemedicine implementation. We investigated the drivers of visit modality selection (telemedicine versus in-person) in primary care clinics at an academic medical centre. METHODS We used electronic medical record data from March 2020 to May 2022 from 13 primary care clinics (N = 21,031 new, N = 207,292 return visits), with 55% overall telemedicine use. Hierarchical logistic regression and cross-validation methods were used to estimate the variation in visit modality explained by the patient, clinician and visit factors as measured by the mean-test area under the curve (AUC). RESULTS There was significant variation in telemedicine use across clinicians (ranging from 0-100%) for the same visit diagnosis. The strongest predictors of telemedicine were the clinician seen for new visits (mean AUC of 0.79) and the primary visit diagnosis for return visits (0.77). Models based on all patient characteristics combined accounted for relatively little variation in modality selection, 0.54 for new and 0.58 for return visits, respectively. Amongst patient characteristics, males, patients over 65 years, Asians and patient's with non-English language preferences used less telemedicine; however, those using interpreter services used significantly more telemedicine. CONCLUSION Clinician seen and primary visit diagnoses were the best predictors of visit modality. The distinction between new and return visits and the minimal impact of patient characteristics on visit modality highlights the complexity of clinical care and warrants research approaches that go beyond linear models to uncover the emergent causal effects of specific technology features mediated by tasks, people and organisations.
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Affiliation(s)
- Vijaya Parameswaran
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Digital Health Care Integration, Stanford Health Care, Stanford, CA, USA
| | - Harrison Koos
- Department of Management Science & Engineering, Stanford University, Stanford, CA, USA
| | - Neil Kalwani
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Lubna Qureshi
- Digital Health Care Integration, Stanford Health Care, Stanford, CA, USA
| | - Leah Rosengaus
- Digital Health Care Integration, Stanford Health Care, Stanford, CA, USA
| | - Rajesh Dash
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - David Scheinker
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Department of Management Science & Engineering, Stanford University, Stanford, CA, USA
| | - Fatima Rodriguez
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Cati-Brown Johnson
- Stanford University School of Medicine, Evaluation Sciences Unit, Division of Primary Care and Population Health, Stanford, CA, USA
| | - Kurt Stange
- Center for Community Health Integration, Case Western Reserve University, Cleveland, OH, USA
| | - David Aron
- Weatherhead School of Management, Case Western Reserve University, Cleveland, OH, USA
| | - Kalle Lyytinen
- Weatherhead School of Management, Case Western Reserve University, Cleveland, OH, USA
| | - Christopher Sharp
- Digital Health Care Integration, Stanford Health Care, Stanford, CA, USA
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Paz-Martin D, Arnal-Velasco D. Can we nudge to reduce the perioperative low value care? Decision making factors influencing safe practice implementation. Curr Opin Anaesthesiol 2023; 36:698-705. [PMID: 37767927 DOI: 10.1097/aco.0000000000001315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
PURPOSE OF THE REVIEW Highlight sources of low-value care (LVC) during the perioperative period help understanding the decision making behind its persistence, the barriers for change, and the potential implementation strategies to reduce it. RECENT FINDINGS The behavioural economics science spread of use through aligned strategies or nudge units offer an opportunity to improve success in the LVC reduction. SUMMARY LVC, such as unneeded surgeries, or preanaesthesia tests for low-risk surgeries in low-risk patients, is a relevant source of waste and preventable harm, most especially in the perioperative period. Despite the international focus on it, initial efforts to reduce it in the last decade have not clearly shown a sustainable improvement. Understanding the shared decision-making process and the barriers to be expected when tackling LVC is the first step to build the change. Applying a structured strategy based on the behavioural science principles may be the path to increasing high value care in an effective an efficient way. It is time to foster nudge units at different healthcare system levels.
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Affiliation(s)
| | - Daniel Arnal-Velasco
- Unit of Anesthesiology and Reanimation, Hospital Universitario Fundacion Alcorcon, Alcorcon, Spain
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Mathis MR, Janda AM, Kheterpal S, Schonberger RB, Pagani FD, Engoren MC, Mentz GB, Shook DC, Muehlschlegel JD. Patient-, Clinician-, and Institution-level Variation in Inotrope Use for Cardiac Surgery: A Multicenter Observational Analysis. Anesthesiology 2023; 139:122-141. [PMID: 37094103 PMCID: PMC10524016 DOI: 10.1097/aln.0000000000004593] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
BACKGROUND Conflicting evidence exists regarding the risks and benefits of inotropic therapies during cardiac surgery, and the extent of variation in clinical practice remains understudied. Therefore, the authors sought to quantify patient-, anesthesiologist-, and hospital-related contributions to variation in inotrope use. METHODS In this observational study, nonemergent adult cardiac surgeries using cardiopulmonary bypass were reviewed across a multicenter cohort of academic and community hospitals from 2014 to 2019. Patients who were moribund, receiving mechanical circulatory support, or receiving preoperative or home inotropes were excluded. The primary outcome was an inotrope infusion (epinephrine, dobutamine, milrinone, dopamine) administered for greater than 60 consecutive min intraoperatively or ongoing upon transport from the operating room. Institution-, clinician-, and patient-level variance components were studied. RESULTS Among 51,085 cases across 611 attending anesthesiologists and 29 hospitals, 27,033 (52.9%) cases received at least one intraoperative inotrope, including 21,796 (42.7%) epinephrine, 6,360 (12.4%) milrinone, 2,000 (3.9%) dobutamine, and 602 (1.2%) dopamine (non-mutually exclusive). Variation in inotrope use was 22.6% attributable to the institution, 6.8% attributable to the primary attending anesthesiologist, and 70.6% attributable to the patient. The adjusted median odds ratio for the same patient receiving inotropes was 1.73 between 2 randomly selected clinicians and 3.55 between 2 randomly selected institutions. Factors most strongly associated with increased likelihood of inotrope use were institutional medical school affiliation (adjusted odds ratio, 6.2; 95% CI, 1.39 to 27.8), heart failure (adjusted odds ratio, 2.60; 95% CI, 2.46 to 2.76), pulmonary circulation disorder (adjusted odds ratio, 1.72; 95% CI, 1.58 to 1.87), loop diuretic home medication (adjusted odds ratio, 1.55; 95% CI, 1.42 to 1.69), Black race (adjusted odds ratio, 1.49; 95% CI, 1.32 to 1.68), and digoxin home medication (adjusted odds ratio, 1.48; 95% CI, 1.18 to 1.86). CONCLUSIONS Variation in inotrope use during cardiac surgery is attributable to the institution and to the clinician, in addition to the patient. Variation across institutions and clinicians suggests a need for future quantitative and qualitative research to understand variation in inotrope use affecting outcomes and develop evidence-based, patient-centered inotrope therapies. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Michael R. Mathis
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Computational Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Allison M. Janda
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Sachin Kheterpal
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | | | - Francis D. Pagani
- Department of Cardiac Surgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA
| | - Milo C. Engoren
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Graciela B. Mentz
- Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Douglas C. Shook
- Department of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Jochen D. Muehlschlegel
- Department of Anesthesiology, Perioperative, and Pain Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
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Koos H, Parameswaran V, Claire S, Chen C, Kalwani N, Osmanlliu E, Qureshi L, Dash R, Scheinker D, Rodriguez F. Drivers of variation in telemedicine use during the COVID-19 pandemic: The experience of a large academic cardiovascular practice. J Telemed Telecare 2022:1357633X221130288. [PMID: 36214200 PMCID: PMC9549164 DOI: 10.1177/1357633x221130288] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 08/28/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND COVID-19 spurred rapid adoption and expansion of telemedicine. We investigated the factors driving visit modality (telemedicine vs. in-person) for outpatient visits at a large cardiovascular center. METHODS We used electronic health record data from March 2020 to February 2021 from four cardiology subspecialties (general cardiology, electrophysiology, heart failure, and interventional cardiology) at a large academic health system in Northern California. There were 21,912 new and return visits with 69% delivered by telemedicine. We used hierarchical logistic regression and cross-validation methods to estimate the variation in visit modality explained by patient, clinician, and visit factors as measured by the mean area under the curve. RESULTS Across all subspecialties, the clinician seen was the strongest predictor of telemedicine usage, while primary visit diagnosis was the next most predictive. In general cardiology, the model based on clinician seen had a mean area under the curve of 0.83, the model based on the primary diagnosis had a mean area under the curve of 0.69, and the model based on all patient characteristics combined had a mean area under the curve of 0.56. There was significant variation in telemedicine use across clinicians within each subspecialty, even for visits with the same primary visit diagnosis. CONCLUSION Individual clinician practice patterns had the largest influence on visit modality across subspecialties in a large cardiovascular medicine practice, while primary diagnosis was less predictive, and patient characteristics even less so. Cardiovascular clinics should reduce variability in visit modality selection through standardized processes that integrate clinical factors and patient preference.
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Affiliation(s)
- Harrison Koos
- Department of Management Science &
Engineering, Stanford University, Stanford, CA, USA
| | - Vijaya Parameswaran
- Division of Cardiovascular Medicine and
the Cardiovascular Institute, Centre for Academic Medicine, Stanford University, Stanford, CA, USA
| | - Sahej Claire
- Department of Management Science &
Engineering, Stanford University, Stanford, CA, USA
| | - Chelsea Chen
- Department of Management Science &
Engineering, Stanford University, Stanford, CA, USA
| | - Neil Kalwani
- Division of Cardiovascular Medicine and
the Cardiovascular Institute, Centre for Academic Medicine, Stanford University, Stanford, CA, USA
| | - Esli Osmanlliu
- Research Institute of the McGill
University Health Centre, McGill University, Montréal, Canada
| | - Lubna Qureshi
- Digital Health Care Integration, Stanford Health Care, Stanford, CA, USA
| | - Rajesh Dash
- Division of Cardiovascular Medicine and
the Cardiovascular Institute, Centre for Academic Medicine, Stanford University, Stanford, CA, USA
| | - David Scheinker
- Department of Management Science &
Engineering, Stanford University, Stanford, CA, USA
| | - Fatima Rodriguez
- Division of Cardiovascular Medicine and
the Cardiovascular Institute, Centre for Academic Medicine, Stanford University, Stanford, CA, USA
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Janda AM, Spence J, Dubovoy T, Belley-Côté E, Mentz G, Kheterpal S, Mathis MR. Multicentre analysis of practice patterns regarding benzodiazepine use in cardiac surgery. Br J Anaesth 2022; 128:772-784. [PMID: 35101244 PMCID: PMC9074791 DOI: 10.1016/j.bja.2021.11.040] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 11/15/2021] [Accepted: 11/22/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND There is controversy regarding optimal use of benzodiazepines during cardiac surgery, and it is unknown whether and to what extent there is variation in practice. We sought to describe benzodiazepine use and sources of variation during cardiac surgeries across patients, clinicians, and institutions. METHODS We conducted an analysis of adult cardiac surgeries across a multicentre consortium of USA academic and private hospitals from 2014 to 2019. The primary outcome was administration of a benzodiazepine from 2 h before anaesthesia start until anaesthesia end. Institutional-, clinician-, and patient-level variables were analysed via multilevel mixed-effects models. RESULTS Of 65 508 patients cared for by 825 anaesthesiology attending clinicians (consultants) at 33 institutions, 58 004 patients (88.5%) received benzodiazepines with a median midazolam-equivalent dose of 4.0 mg (inter-quartile range [IQR], 2.0-6.0 mg). Variation in benzodiazepine dosage administration was 54.7% attributable to institution, 14.7% to primary attending anaesthesiology clinician, and 30.5% to patient factors. The adjusted median odds ratio for two similar patients receiving a benzodiazepine was 2.68 between two randomly selected clinicians and 4.19 between two randomly selected institutions. Factors strongly associated (adjusted odds ratio, <0.75, or >1.25) with significantly decreased likelihoods of benzodiazepine administration included older age (>80 vs ≤50 yr; adjusted odds ratio=0.04; 95% CI, 0.04-0.05), university affiliation (0.08, 0.02-0.35), recent year of surgery (0.42, 0.37-0.49), and low clinician case volume (0.44, 0.25-0.75). Factors strongly associated with significantly increased likelihoods of benzodiazepine administration included cardiopulmonary bypass (2.26, 1.99-2.55), and drug use history (1.29, 1.02-1.65). CONCLUSIONS Two-thirds of the variation in benzodiazepine administration during cardiac surgery are associated with institutions and attending anaesthesiology clinicians (consultants). These data, showing wide variations in administration, suggest that rigorous research is needed to guide evidence-based and patient-centred benzodiazepine administration.
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Affiliation(s)
- Allison M Janda
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
| | - Jessica Spence
- Departments of Anesthesia and Critical Care, McMaster University, Hamilton, ON, Canada; Population Health Research Institute, McMaster University, Hamilton, ON, Canada
| | - Timur Dubovoy
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Emilie Belley-Côté
- Population Health Research Institute, McMaster University, Hamilton, ON, Canada; Divisions of Cardiology and Critical Care, Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Graciela Mentz
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Sachin Kheterpal
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Michael R Mathis
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
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Anesthesiologists' Role in Value-based Perioperative Care and Healthcare Transformation. Anesthesiology 2021; 134:526-540. [PMID: 33630039 DOI: 10.1097/aln.0000000000003717] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Health care is undergoing major transformation with a shift from fee-for-service care to fee-for-value. The advent of new care delivery and payment models is serving as a driver for value-based care. Hospitals, payors, and patients increasingly expect physicians and healthcare systems to improve outcomes and manage costs. The impact of the coronavirus disease 2019 (COVID-19) pandemic on surgical and procedural practices further highlights the urgency and need for anesthesiologists to expand their roles in perioperative care, and to impact system improvement. While there have been substantial advances in anesthesia care, perioperative complications and mortality after surgery remain a key concern. Anesthesiologists are in a unique position to impact perioperative health care through their multitude of interactions and influences on various aspects of the perioperative domain, by using the surgical experience as the first touchpoint to reengage the patient in their own health care. Among the key interventions that are being effectively instituted by anesthesiologists include proactive engagement in preoperative optimization of patients' health; personalization and standardization of care delivery by segmenting patients based upon their complexity and risk; and implementation of best practices that are data-driven and evidence-based and provide structure that allow the patient to return to their optimal state of functional, cognitive, and psychologic health. Through collaborative relationships with other perioperative stakeholders, anesthesiologists can consolidate their role as clinical leaders driving value-based care and healthcare transformation in the best interests of patients.
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Davidson A. Should variation in care drive our clinical trial agenda? Paediatr Anaesth 2020; 30:1290-1291. [PMID: 33280189 DOI: 10.1111/pan.14040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/10/2020] [Accepted: 10/13/2020] [Indexed: 11/26/2022]
Affiliation(s)
- Andrew Davidson
- Department of Anaesthesia, Royal Children's Hospital, Parkville, Vic., Australia.,Melbourne Children's Trials Centre, Murdoch Children's Research Institute, Parkville, Vic., Australia.,Department of Paediatrics, University of Melbourne, Parkville, Vic., Australia
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Implications of Practice Variability: Comment. Anesthesiology 2020; 133:944-945. [DOI: 10.1097/aln.0000000000003466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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