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  1. Article ; Online: What is in the palliative care 'syringe'? A systems perspective.

    Khayal, Inas S / Barnato, Amber E

    Social science & medicine (1982)

    2022  Volume 305, Page(s) 115069

    Abstract: The diffusion of palliative care has been rapid, yet uncertainty remains regarding palliative care's "active ingredients." The National Consensus Project Guidelines for Quality Palliative Care identified eight domains of palliative care. Despite these ... ...

    Abstract The diffusion of palliative care has been rapid, yet uncertainty remains regarding palliative care's "active ingredients." The National Consensus Project Guidelines for Quality Palliative Care identified eight domains of palliative care. Despite these identified domains, when pressed to describe the specific maneuvers used in clinical encounters, palliative care providers acknowledge that "it's complex." The field of systems has been used to explain complexity across many different types of systems. Specifically, engineering systems develop a representation of a system that helps manage complexity to help humans better understand the system. Our goal was to develop a system model of what palliative care providers do such that the elements of the model can be described concretely and sequentially, aggregated to describe the high-level domains currently described by palliative care, and connected to the complexity described by providers and the literature. Our study design combined methodological elements from both qualitative research and systems engineering modeling. The model drew on participant observation and debriefing semi-structured interviews with interdisciplinary palliative care team members by a systems engineer. The setting was an interdisciplinary palliative care service in a US rural academic medical center. In the developed system model, we identified 59 functions provided to patients, families, non-palliative care provider(s), and palliative care provider(s). The high-level functions related to measurement, decision-making, and treatment address up to 8 states of an individual, including an overall holistic state, physical state, psychological state, spiritual state, cultural state, personal environment state, and clinical environment state. In contrast to previously described expert consensus domain-based descriptions of palliative care, this model more directly connects palliative care provider functions to emergent behaviors that may explain system-level mechanisms of action for palliative care. Thus, a systems modeling approach provides insights into the challenges surrounding the recurring question of what is in the palliative care "syringe."
    MeSH term(s) Humans ; Interdisciplinary Studies ; Palliative Care/psychology ; Qualitative Research ; Rural Population ; Syringes
    Language English
    Publishing date 2022-05-30
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 4766-1
    ISSN 1873-5347 ; 0037-7856 ; 0277-9536
    ISSN (online) 1873-5347
    ISSN 0037-7856 ; 0277-9536
    DOI 10.1016/j.socscimed.2022.115069
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The power of specialty palliative care: moving towards a systems perspective.

    Barnato, Amber E / Khayal, Inas S

    The Lancet. Haematology

    2021  Volume 8, Issue 5, Page(s) e376–e381

    Abstract: Three palliative care clinical trials were presented at the 2020 American Society for Clinical Oncology Annual Meeting. The heterogeneity in populations, models of care, study design, and assessment of clinical outcomes across these three studies show ... ...

    Abstract Three palliative care clinical trials were presented at the 2020 American Society for Clinical Oncology Annual Meeting. The heterogeneity in populations, models of care, study design, and assessment of clinical outcomes across these three studies show the broad opportunities for research into interventions for palliative care. In this Viewpoint, we summarise the characteristics of these studies, discuss their novel features and lingering questions, and offer a suggestion for further expanding the focus of clinical trials for delivery of palliative care in the future. We particularly argue that the propensity to characterise palliative care as if it was a clinical or biomedical intervention hampers the design and evaluation of complex clinical interventions that influence clinicians, systems for health-care delivery, individual patients, and their families.
    MeSH term(s) Adaptation, Psychological ; Antineoplastic Agents/therapeutic use ; Clinical Trials as Topic ; Family/psychology ; Humans ; Neoplasms/drug therapy ; Neoplasms/psychology ; Palliative Care ; Quality of Life
    Chemical Substances Antineoplastic Agents
    Language English
    Publishing date 2021-04-24
    Publishing country England
    Document type Journal Article ; Review
    ISSN 2352-3026
    ISSN (online) 2352-3026
    DOI 10.1016/S2352-3026(21)00099-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Challenges In Understanding And Respecting Patients' Preferences.

    Barnato, Amber E

    Health affairs (Project Hope)

    2017  Volume 36, Issue 7, Page(s) 1252–1257

    Abstract: The Institute of Medicine's report ... ...

    Abstract The Institute of Medicine's report on
    MeSH term(s) Advance Care Planning ; Communication ; Decision Making ; Humans ; Patient Preference/psychology ; Physician-Patient Relations ; Qualitative Research ; United States
    Language English
    Publishing date 2017--01
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 632712-6
    ISSN 1544-5208 ; 0278-2715
    ISSN (online) 1544-5208
    ISSN 0278-2715
    DOI 10.1377/hlthaff.2017.0177
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Implications of Including Hospital Do-Not-Resuscitate Rates in Risk Adjustment for Pay-for-Performance Programs.

    Wiener, Renda Soylemez / Barnato, Amber E

    JAMA network open

    2020  Volume 3, Issue 7, Page(s) e2010915

    MeSH term(s) Diagnosis-Related Groups ; Hospital Mortality ; Hospitals ; Humans ; Patient Readmission ; Patients ; Reimbursement, Incentive ; Resuscitation Orders ; Risk Adjustment
    Language English
    Publishing date 2020-07-01
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Comment
    ISSN 2574-3805
    ISSN (online) 2574-3805
    DOI 10.1001/jamanetworkopen.2020.10915
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Measuring Local-Area Racial Segregation for Medicare Hospital Admissions.

    Akré, Ellesse-Roselee L / Chyn, Deanna / Carlos, Heather A / Barnato, Amber E / Skinner, Jonathan

    JAMA network open

    2024  Volume 7, Issue 4, Page(s) e247473

    Abstract: Importance: Considerable racial segregation exists in US hospitals that cannot be explained by where patients live. Approaches to measuring such segregation are limited.: Objective: To measure how and where sorting of older Black patients to ... ...

    Abstract Importance: Considerable racial segregation exists in US hospitals that cannot be explained by where patients live. Approaches to measuring such segregation are limited.
    Objective: To measure how and where sorting of older Black patients to different hospitals occurs within the same health care market.
    Design, setting, and participants: This retrospective cross-sectional study used 2019 Medicare claims data linked to geographic data. Hospital zip code markets were based on driving time. The local hospital segregation (LHS) index was defined as the difference between the racial composition of a hospital's admissions and the racial composition of the hospital's market. Assessed admissions were among US Medicare fee-for-service enrollees aged 65 or older living in the 48 contiguous states with at least 1 hospitalization in 2019 at a hospital with at least 200 hospitalizations. Data were analyzed from November 2022 to January 2024.
    Exposure: Degree of residential segregation, ownership status, region, teaching hospital designation, and disproportionate share hospital status.
    Main outcomes and measures: The LHS index by hospital and a regional LHS index by hospital referral region.
    Results: In the sample of 1991 acute care hospitals, 4 870 252 patients (mean [SD] age, 77.7 [8.3] years; 2 822 006 [56.0%] female) were treated, including 11 435 American Indian or Alaska Native patients (0.2%), 129 376 Asian patients (2.6%), 597 564 Black patients (11.9%), 395 397 Hispanic patients (7.8), and 3 818 371 White patients (75.8%). In the sample, half of hospitalizations among Black patients occurred at 235 hospitals (11.8% of all hospitals); 878 hospitals (34.4%) exhibited a negative LHS score (ie, admitted fewer Black patients relative to their market area) while 1113 hospitals (45.0%) exhibited a positive LHS (ie, admitted more Black patients relative to their market area); of all hospitals, 79.4% exhibited racial admission patterns significantly different from their market. Hospital-level LHS was positively associated with government hospital status (coefficient, 0.24; 95% CI, 0.10 to 0.38), while New York, New York; Chicago, Illinois; and Detroit, Michigan, hospital referral regions exhibited the highest regional LHS measures, with hospital referral region LHS scores of 0.12, 0.16, and 0.21, respectively.
    Conclusions and relevance: In this cross-sectional study, a novel measure of LHS was developed to quantify the extent to which hospitals were admitting a representative proportion of Black patients relative to their market areas. A better understanding of hospital choice within neighborhoods would help to reduce racial inequities in health outcomes.
    MeSH term(s) Humans ; Aged ; Female ; United States ; Male ; Medicare ; Retrospective Studies ; Cross-Sectional Studies ; Hospitalization ; Hospitals, Teaching ; Social Segregation
    Language English
    Publishing date 2024-04-01
    Publishing country United States
    Document type Journal Article
    ISSN 2574-3805
    ISSN (online) 2574-3805
    DOI 10.1001/jamanetworkopen.2024.7473
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Clinically informed machine learning elucidates the shape of hospice racial disparities within hospitals.

    Khayal, Inas S / O'Malley, A James / Barnato, Amber E

    NPJ digital medicine

    2023  Volume 6, Issue 1, Page(s) 190

    Abstract: Racial disparities in hospice care are well documented for patients with cancer, but the existence, direction, and extent of disparity findings are contradictory across the literature. Current methods to identify racial disparities aggregate data to ... ...

    Abstract Racial disparities in hospice care are well documented for patients with cancer, but the existence, direction, and extent of disparity findings are contradictory across the literature. Current methods to identify racial disparities aggregate data to produce single-value quality measures that exclude important patient quality elements and, consequently, lack information to identify actionable equity improvement insights. Our goal was to develop an explainable machine learning approach that elucidates healthcare disparities and provides more actionable quality improvement information. We infused clinical information with engineering systems modeling and data science to develop a time-by-utilization profile per patient group at each hospital using US Medicare hospice utilization data for a cohort of patients with advanced (poor-prognosis) cancer that died April-December 2016. We calculated the difference between group profiles for people of color and white people to identify racial disparity signatures. Using machine learning, we clustered racial disparity signatures across hospitals and compared these clusters to classic quality measures and hospital characteristics. With 45,125 patients across 362 hospitals, we identified 7 clusters; 4 clusters (n = 190 hospitals) showed more hospice utilization by people of color than white people, 2 clusters (n = 106) showed more hospice utilization by white people than people of color, and 1 cluster (n = 66) showed no difference. Within-hospital racial disparity behaviors cannot be predicted from quality measures, showing how the true shape of disparities can be distorted through the lens of quality measures. This approach elucidates the shape of hospice racial disparities algorithmically from the same data used to calculate quality measures.
    Language English
    Publishing date 2023-10-12
    Publishing country England
    Document type Journal Article
    ISSN 2398-6352
    ISSN (online) 2398-6352
    DOI 10.1038/s41746-023-00925-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Development of dynamic health care delivery heatmaps for end-of-life cancer care: a cohort study.

    Khayal, Inas S / Brooks, Gabriel A / Barnato, Amber E

    BMJ open

    2022  Volume 12, Issue 5, Page(s) e056328

    Abstract: Objective: Measures of variation in end-of-life (EOL) care intensity across hospitals are typically summarised using unidimensional measures. These measures do not capture the full dimensionality of complex clinical care trajectories over time that are ... ...

    Abstract Objective: Measures of variation in end-of-life (EOL) care intensity across hospitals are typically summarised using unidimensional measures. These measures do not capture the full dimensionality of complex clinical care trajectories over time that are needed to inform quality improvement efforts. The objective is to develop a novel visual map of EOL care trajectories that illustrates multidimensional utilisation over time.
    Setting: United States' National Cancer Institute or National Comprehensive Cancer Network (NCI/NCCN)-designated hospitals.
    Participants: We identified Medicare claims for fee-for-service beneficiaries with poor prognosis cancers who died between April and December 2016 and received the preponderance of treatment in the last 6 months of life at an NCI/NCCN-designated hospital.
    Design: For each beneficiary, we transformed each Medicare claim into two elements to generate a two-dimensional individual-level heatmap. On the y-axis, each claim was classified into a categorical description of the service delivered by a healthcare resource. On the x-axis, the date for each claim was converted into the day number prior to death it occurred on. We then summed up individual-level heatmaps of patients attributed to each hospital to generate two-dimensional hospital-level heatmaps. We used four case studies to illustrate the feasibility of interpreting these heatmaps and to shed light on how they might be used to guide value-based, quality improvement initiatives.
    Results: We identified nine distinct EOL care delivery patterns from hospital-level heatmaps based on signal intensity and patterns for inpatient, outpatient and home-based hospice services. We illustrate that in most cases, heatmaps illustrating patterns of multidimensional healthcare utilisation over time provide more information about care trajectories and highlight more heterogeneity than current unidimensional measures.
    Conclusions: This study illustrates the feasibility of representing multidimensional EOL utilisation over time as a heatmap. These heatmaps may provide potentially actionable insights into hospital-level care delivery patterns, and the approach may generalise to other serious illness populations.
    MeSH term(s) Aged ; Cohort Studies ; Death ; Hospice Care ; Humans ; Medicare ; Neoplasms/therapy ; Patient Acceptance of Health Care ; Retrospective Studies ; Terminal Care ; United States
    Language English
    Publishing date 2022-05-19
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2599832-8
    ISSN 2044-6055 ; 2044-6055
    ISSN (online) 2044-6055
    ISSN 2044-6055
    DOI 10.1136/bmjopen-2021-056328
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Development of an Abstraction Tool to Assess Palliative Care Components.

    MacMartin, Meredith A / Barnato, Amber E

    The American journal of hospice & palliative care

    2021  Volume 39, Issue 12, Page(s) 1418–1427

    Abstract: Background: ...

    Abstract Background:
    MeSH term(s) Humans ; Palliative Care ; Pilot Projects ; Reproducibility of Results ; Hospice and Palliative Care Nursing ; Documentation
    Language English
    Publishing date 2021-12-13
    Publishing country United States
    Document type Review ; Journal Article
    ZDB-ID 1074344-3
    ISSN 1938-2715 ; 1049-9091
    ISSN (online) 1938-2715
    ISSN 1049-9091
    DOI 10.1177/10499091211061724
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Clinically informed machine learning elucidates the shape of hospice racial disparities within hospitals

    Inas S. Khayal / A. James O’Malley / Amber E. Barnato

    npj Digital Medicine, Vol 6, Iss 1, Pp 1-

    2023  Volume 9

    Abstract: Abstract Racial disparities in hospice care are well documented for patients with cancer, but the existence, direction, and extent of disparity findings are contradictory across the literature. Current methods to identify racial disparities aggregate ... ...

    Abstract Abstract Racial disparities in hospice care are well documented for patients with cancer, but the existence, direction, and extent of disparity findings are contradictory across the literature. Current methods to identify racial disparities aggregate data to produce single-value quality measures that exclude important patient quality elements and, consequently, lack information to identify actionable equity improvement insights. Our goal was to develop an explainable machine learning approach that elucidates healthcare disparities and provides more actionable quality improvement information. We infused clinical information with engineering systems modeling and data science to develop a time-by-utilization profile per patient group at each hospital using US Medicare hospice utilization data for a cohort of patients with advanced (poor-prognosis) cancer that died April-December 2016. We calculated the difference between group profiles for people of color and white people to identify racial disparity signatures. Using machine learning, we clustered racial disparity signatures across hospitals and compared these clusters to classic quality measures and hospital characteristics. With 45,125 patients across 362 hospitals, we identified 7 clusters; 4 clusters (n = 190 hospitals) showed more hospice utilization by people of color than white people, 2 clusters (n = 106) showed more hospice utilization by white people than people of color, and 1 cluster (n = 66) showed no difference. Within-hospital racial disparity behaviors cannot be predicted from quality measures, showing how the true shape of disparities can be distorted through the lens of quality measures. This approach elucidates the shape of hospice racial disparities algorithmically from the same data used to calculate quality measures.
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: "Postponing it Any Later Would not be so Great": A Cognitive Interview Study of How Physicians Decide to Initiate Goals of Care Discussions in the Hospital.

    Chuang, Elizabeth / Gugliuzza, Sabrina / Ahmad, Ammar / Aboodi, Michael / Gong, Michelle Ng / Barnato, Amber E

    The American journal of hospice & palliative care

    2023  , Page(s) 10499091231222926

    Abstract: Background: There are missed opportunities to discuss goals and preferences for care with seriously ill patients in the acute care setting. It is unknown which factors most influence clinician decision-making about communication at the point of care.: ...

    Abstract Background: There are missed opportunities to discuss goals and preferences for care with seriously ill patients in the acute care setting. It is unknown which factors most influence clinician decision-making about communication at the point of care.
    Objective: This study utilized a cognitive-interviewing technique to better understand what leads clinicians to decide to have a goals of care (GOC) discussion in the acute care setting.
    Methods: A convenience sample of 15 oncologists, intensivists and hospitalists were recruited from a single academic medical center in a large urban area. Participants completed a cognitive interview describing their thought process when deciding whether to engage in GOC discussions in clinical vignettes.
    Results: 6 interconnected factors emerged as important in determining how likely the physician was to consider engaging in GOC at that time; (1) the participants' mental model of GOC, (2) timing of GOC related to stability, acuity and reversibility of the patient's condition, (3) clinical factors such as uncertainty, prognosis and recency of diagnosis, (4) patient factors including age and emotional state, (5) participants' role on the care team, and (6) clinician factors such as emotion and communication skill level.
    Conclusion: Participants were hesitant to commit to the present moment as the right time for GOC discussions based on variations in clinical presentation. Clinical decision support systems that include more targeted information about risk of clinical deterioration and likelihood of reversal of the acute condition may prompt physicians to discuss GOC, but more support for managing discomfort with uncertainty is also needed.
    Language English
    Publishing date 2023-12-18
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1074344-3
    ISSN 1938-2715 ; 1049-9091
    ISSN (online) 1938-2715
    ISSN 1049-9091
    DOI 10.1177/10499091231222926
    Database MEDical Literature Analysis and Retrieval System OnLINE

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