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  1. Article ; Online: To J.R.C. with L.O.V.E.

    Rubenfeld, Gordon D / Halpern, Scott D

    Journal of pain and symptom management

    2022  Volume 63, Issue 6, Page(s) e577–e578

    Language English
    Publishing date 2022-05-18
    Publishing country United States
    Document type Editorial
    ZDB-ID 639142-4
    ISSN 1873-6513 ; 0885-3924
    ISSN (online) 1873-6513
    ISSN 0885-3924
    DOI 10.1016/j.jpainsymman.2022.04.165
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    Zs.A 2252: Show issues Location:
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  2. Article ; Online: Learning about End-of-Life Care from Grandpa.

    Halpern, Scott D

    The New England journal of medicine

    2020  Volume 384, Issue 5, Page(s) 400–401

    MeSH term(s) Family Relations ; Grandparents ; Hospice Care ; Humans ; Learning ; Male ; New Jersey ; Palliative Care ; Suicide ; Suicide, Assisted/legislation & jurisprudence ; Terminal Care
    Language English
    Publishing date 2020-10-21
    Publishing country United States
    Document type Journal Article ; Personal Narrative
    ZDB-ID 207154-x
    ISSN 1533-4406 ; 0028-4793
    ISSN (online) 1533-4406
    ISSN 0028-4793
    DOI 10.1056/NEJMp2026629
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    Ua VI Zs.34: Show issues Location:
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  3. Article ; Online: Goal-Concordant Care - Searching for the Holy Grail.

    Halpern, Scott D

    The New England journal of medicine

    2019  Volume 381, Issue 17, Page(s) 1603–1606

    MeSH term(s) Advance Directives ; Electronic Health Records ; Goals ; Humans ; Patient Care Planning ; Patient Participation
    Language English
    Publishing date 2019-10-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 207154-x
    ISSN 1533-4406 ; 0028-4793
    ISSN (online) 1533-4406
    ISSN 0028-4793
    DOI 10.1056/NEJMp1908153
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    Ua VI Zs.34: Show issues Location:
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  4. Article ; Online: Chess Lessons: Harnessing Collective Human Intelligence and Imitation Learning to Support Clinical Decisions.

    Weissman, Gary E / Ungar, Lyle H / Halpern, Scott D

    Annals of internal medicine

    2023  Volume 176, Issue 2, Page(s) 274–275

    MeSH term(s) Humans ; Imitative Behavior ; Intelligence ; Recreation ; Learning
    Language English
    Publishing date 2023-01-31
    Publishing country United States
    Document type Editorial
    ZDB-ID 336-0
    ISSN 1539-3704 ; 0003-4819
    ISSN (online) 1539-3704
    ISSN 0003-4819
    DOI 10.7326/M22-2998
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    Ua VI Zs.178/2: Show issues Location:
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  5. Article ; Online: How do surrogates make treatment decisions for patients with dementia: An experimental survey study.

    Nicholas, Lauren Hersch / Langa, Kenneth M / Halpern, Scott D / Macis, Mario

    Health economics

    2024  

    Abstract: Despite the growing need for surrogate decision-making for older adults, little is known about how surrogates make decisions and whether advance directives would change decision-making. We conducted a nationally representative experimental survey that ... ...

    Abstract Despite the growing need for surrogate decision-making for older adults, little is known about how surrogates make decisions and whether advance directives would change decision-making. We conducted a nationally representative experimental survey that cross-randomized cognitive impairment, gender, and characteristics of advance care planning among hospitalized older adults through a series of vignettes. Our study yielded three main findings: first, respondents were much less likely to recommend life-sustaining treatments for patients with dementia, especially after personal exposure. Second, respondents were more likely to ignore patient preferences for life-extending treatment when the patient had dementia, and choose unwanted life-extending treatments for patients without dementia. Third, in scenarios where the patient's wishes were unclear, respondents were more likely to choose treatments that matched their own preferences. These findings underscore the need for improved communication and decision-making processes for patients with cognitive impairment and highlight the importance of choosing a surrogate decision-maker with similar treatment preferences.
    Language English
    Publishing date 2024-02-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 1135838-5
    ISSN 1099-1050 ; 1057-9230
    ISSN (online) 1099-1050
    ISSN 1057-9230
    DOI 10.1002/hec.4810
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    Zs.A 3555: Show issues Location:
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  6. Article ; Online: Assessing treatment effect heterogeneity in the presence of missing effect modifier data in cluster-randomized trials.

    Blette, Bryan S / Halpern, Scott D / Li, Fan / Harhay, Michael O

    Statistical methods in medical research

    2024  Volume 33, Issue 5, Page(s) 909–927

    Abstract: Understanding whether and how treatment effects vary across subgroups is crucial to inform clinical practice and recommendations. Accordingly, the assessment of heterogeneous treatment effects based on pre-specified potential effect modifiers has become ... ...

    Abstract Understanding whether and how treatment effects vary across subgroups is crucial to inform clinical practice and recommendations. Accordingly, the assessment of heterogeneous treatment effects based on pre-specified potential effect modifiers has become a common goal in modern randomized trials. However, when one or more potential effect modifiers are missing, complete-case analysis may lead to bias and under-coverage. While statistical methods for handling missing data have been proposed and compared for individually randomized trials with missing effect modifier data, few guidelines exist for the cluster-randomized setting, where intracluster correlations in the effect modifiers, outcomes, or even missingness mechanisms may introduce further threats to accurate assessment of heterogeneous treatment effect. In this article, the performance of several missing data methods are compared through a simulation study of cluster-randomized trials with continuous outcome and missing binary effect modifier data, and further illustrated using real data from the Work, Family, and Health Study. Our results suggest that multilevel multiple imputation and Bayesian multilevel multiple imputation have better performance than other available methods, and that Bayesian multilevel multiple imputation has lower bias and closer to nominal coverage than standard multilevel multiple imputation when there are model specification or compatibility issues.
    MeSH term(s) Randomized Controlled Trials as Topic/statistics & numerical data ; Bayes Theorem ; Humans ; Cluster Analysis ; Data Interpretation, Statistical ; Bias ; Models, Statistical ; Treatment Outcome ; Computer Simulation ; Treatment Effect Heterogeneity
    Language English
    Publishing date 2024-04-03
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 1136948-6
    ISSN 1477-0334 ; 0962-2802
    ISSN (online) 1477-0334
    ISSN 0962-2802
    DOI 10.1177/09622802241242323
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    Zs.A 3564: Show issues Location:
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  7. Article ; Online: Using Default Options and Other Nudges to Improve Critical Care.

    Halpern, Scott D

    Critical care medicine

    2018  Volume 46, Issue 3, Page(s) 460–464

    MeSH term(s) Critical Care/methods ; Critical Care/standards ; Decision Making ; Humans ; Quality Improvement
    Language English
    Publishing date 2018-02-23
    Publishing country United States
    Document type Journal Article
    ZDB-ID 197890-1
    ISSN 1530-0293 ; 0090-3493
    ISSN (online) 1530-0293
    ISSN 0090-3493
    DOI 10.1097/CCM.0000000000002898
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    Zs.A 1261: Show issues Location:
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  8. Article ; Online: Why Diverse Clinical Trial Participation Matters.

    Schwartz, Aaron L / Alsan, Marcella / Morris, Alanna A / Halpern, Scott D

    The New England journal of medicine

    2023  Volume 388, Issue 14, Page(s) 1252–1254

    MeSH term(s) Humans ; Motivation ; Patient Participation ; Clinical Trials as Topic/standards ; Diversity, Equity, Inclusion ; Patient Selection ; Patient Acceptance of Health Care ; Health Equity
    Language English
    Publishing date 2023-04-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 207154-x
    ISSN 1533-4406 ; 0028-4793
    ISSN (online) 1533-4406
    ISSN 0028-4793
    DOI 10.1056/NEJMp2215609
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    Ua VI Zs.34: Show issues Location:
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  9. Article ; Online: Pragmatic Trials and the Evolution of Serious Illness Research.

    Courtright, Katherine R / Halpern, Scott D

    JAMA internal medicine

    2020  Volume 180, Issue 8, Page(s) 1079–1080

    MeSH term(s) Advance Care Planning ; Humans ; Nursing Homes ; Research Design
    Language English
    Publishing date 2020-10-05
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2699338-7
    ISSN 2168-6114 ; 2168-6106
    ISSN (online) 2168-6114
    ISSN 2168-6106
    DOI 10.1001/jamainternmed.2020.2916
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    Ua VI Zs.119: Show issues Location:
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  10. Article ; Online: A vignette-based evaluation of ChatGPT's ability to provide appropriate and equitable medical advice across care contexts.

    Nastasi, Anthony J / Courtright, Katherine R / Halpern, Scott D / Weissman, Gary E

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 17885

    Abstract: ChatGPT is a large language model trained on text corpora and reinforced with human supervision. Because ChatGPT can provide human-like responses to complex questions, it could become an easily accessible source of medical advice for patients. However, ... ...

    Abstract ChatGPT is a large language model trained on text corpora and reinforced with human supervision. Because ChatGPT can provide human-like responses to complex questions, it could become an easily accessible source of medical advice for patients. However, its ability to answer medical questions appropriately and equitably remains unknown. We presented ChatGPT with 96 advice-seeking vignettes that varied across clinical contexts, medical histories, and social characteristics. We analyzed responses for clinical appropriateness by concordance with guidelines, recommendation type, and consideration of social factors. Ninety-three (97%) responses were appropriate and did not explicitly violate clinical guidelines. Recommendations in response to advice-seeking questions were completely absent (N = 34, 35%), general (N = 18, 18%), or specific (N = 44, 46%). 53 (55%) explicitly considered social factors like race or insurance status, which in some cases changed clinical recommendations. ChatGPT consistently provided background information in response to medical questions but did not reliably offer appropriate and personalized medical advice.
    MeSH term(s) Humans ; Female ; Insurance Coverage ; Language ; Social Factors ; Uterus
    Language English
    Publishing date 2023-10-19
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-45223-y
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