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Record W2603806149 · doi:10.7326/m17-0244

A Tale of Two Countries: How I Saw More Patients With More Joy in Internal Medicine Practice

2017· article· en· W2603806149 on OpenAlexaboutno aff
Dawn E. DeWitt

Bibliographic record

VenueAnnals of Internal Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHealth careBurnoutFamily medicineLicenseLawPolitical science

Abstract

fetched live from OpenAlex

Ideas and Opinions2 May 2017A Tale of Two Countries: How I Saw More Patients With More Joy in Internal Medicine PracticeDawn E. DeWitt, MD, MScDawn E. DeWitt, MD, MScFrom Elson S. Floyd College of Medicine, Washington State University, Spokane, Washington.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/M17-0244 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail After 14 years in Australia and Canada, I dreaded my return to practice in the United States. In 2003, after 10 years of academic practice in Seattle, I moved to Australia to develop rural and regional clinical training for the University of Melbourne. Practicing and teaching internal medicine in Australia was much easier and more rewarding than in the United States. My experience reinforces that complexity, fragmentation, and unnecessary documentation are driving physician burnout, patient dissatisfaction, high costs, and suboptimal outcomes in this country. Simplifying our system could save money, preserve patient choice, and improve outcomes.The data are clear—countries ...References1. Macinko J, Starfield B, Shi L. The contribution of primary care systems to health outcomes within Organization for Economic Cooperation and Development (OECD) countries, 1970-1998. Health Serv Res. 2003;38:831-65. [PMID: 12822915] CrossrefMedlineGoogle Scholar2. Goss E, Fletcher J, Lechuga C, Meissner P, Blank A, Lounsbury D, et al. Teamwork and working at “top of license” among physicians, nursing, and non-professional staff at teaching and non-teaching ambulatory practices. J Gen Int Med. 2011;26 Suppl 1 211. Google Scholar3. Shanafelt TD, Boone S, Tan L, Dyrbye LN, Sotile W, Satele D, et al. Burnout and satisfaction with work–life balance among US physicians relative to the general US population. Arch Intern Med. 2012;172:1377-85. [PMID: 22911330] CrossrefMedlineGoogle Scholar4. Sinsky C, Colligan L, Li L, Prgomet M, Reynolds S, Goeders L, et al. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Ann Intern Med. 2016;165:753-60. [PMID: 27595430]. doi:10.7326/M16-0961 LinkGoogle Scholar5. Wenger N, Méan M, Castioni J, Marques-Vidal P, Waeber G, Garnier A. Allocation of internal medicine resident time in a Swiss hospital: a time and motion study of day and evening shifts. Ann Intern Med. 2017. [Epub ahead of print]. [PMID: 28135724] doi:10.7326/M16-2238 LinkGoogle Scholar6. Erickson SM, Rockwern B, Koltov M; Medical Practice and Quality Committee of the American College of Physicians. Putting patients first by reducing administrative tasks in health care: a position paper of the American College of Physicians. Ann Intern Med. 2017;166:659-61. doi:10.7326/M16-2697 LinkGoogle Scholar Author, Article, and Disclosure InformationAffiliations: From Elson S. Floyd College of Medicine, Washington State University, Spokane, Washington.Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M17-0244.Corresponding Author: Dawn E. DeWitt, MD, MSc, Spokane Academic Center, PO Box 1495, Spokane, WA 99210-1495; e-mail, dawn.[email protected]edu.Author Contributions: Conception and design: D.E. DeWitt.Analysis and interpretation of the data: D.E. DeWitt.Drafting of the article: D.E. DeWitt.Critical revision of the article for important intellectual content: D.E. DeWitt.Final approval of the article: D.E. DeWitt.Collection and assembly of data: D.E. DeWitt.This article was published at Annals.org on 28 March 2017. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoPutting Patients First by Reducing Administrative Tasks in Health Care: A Position Paper of the American College of Physicians Shari M. Erickson , Brooke Rockwern , Michelle Koltov , Robert M. McLean , and A Tale of Two Countries Dawn E. DeWitt A Tale of Two Countries Vaibhav Kumar Metrics Cited byOath to Self-Care and Well-BeingPhysician Burnout in the Electronic Health Record EraN. Lance Downing, MD, David W. Bates, MD, MSc, and Christopher A. Longhurst, MD, MSThe Potential Impact of Scribes on Medical School Applicants and Medical Students with the New Clinical Documentation GuidelinesONE-YEAR TIME ANALYSIS IN AN ACADEMIC DIABETES CLINIC: QUANTIFYING OUR BURDENA Tale of Two CountriesVaibhav Kumar, MD 2 May 2017Volume 166, Issue 9Page: 669-670KeywordsComputersDisclosureElectronic medical recordsHealth carePatientsPrimary care physiciansResidencySub-specialty careSurgeryUrticaria ePublished: 28 March 2017 Issue Published: 2 May 2017 Copyright & PermissionsCopyright © 2017 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0100.009
Scholarly communication0.0200.020
Open science0.0020.011
Research integrity0.0100.030
Insufficient payload (model declined to judge)0.0260.011

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.081
GPT teacher head0.501
Teacher spread0.420 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations6
Published2017
Admission routes1
Has abstractyes

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