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Association of a Lay Health Worker Intervention With Symptom Burden, Survival, Health Care Use, and Total Costs Among Medicare Enrollees With Cancer

2020· article· en· W3011502446 on OpenAlexaboutno aff
Manali I. Patel, David A. Ramirez, Richy Agajanian, Hilda H. Agajanian, Tumaini R. Coker

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institutes of Health
KeywordsMedicineReferralQuality of life (healthcare)Psychological interventionIntervention (counseling)Health carePhysical therapyFamily medicinePsychiatryNursing

Abstract

fetched live from OpenAlex

Importance: Undertreated patient symptoms require approaches that improve symptom burden. Objective: To determine the association of a lay health worker-led symptom screening and referral intervention with symptom burden, survival, health care use, and total costs among Medicare Advantage enrollees with a new diagnosis of solid or hematologic malignant neoplasms. Design, Setting, and Participants: This quality improvement study conducted at 9 community oncology practices from November 1, 2016, to October 31, 2018, compared newly diagnosed Medicare Advantage enrollees with solid or hematologic malignant neoplasms with patients diagnosed and treated 1 year prior. Analysis was conducted from August 1, 2019, to January 11, 2020. Interventions: Usual care augmented by a lay health worker trained to screen symptoms and refer patients to palliative care and behavioral medicine. Main Outcomes and Measures: The primary outcome was change in symptoms using the Edmonton Symptom Assessment Scale and the 9-item Patient Health Questionnaire at baseline and 6 and 12 months after enrollment. Secondary outcomes were between-group comparison of survival, 12-month health care use, and costs. Results: Among 425 patients in the intervention group and 407 patients in the control group, the mean (SD) age was 78.8 (8.3) years, 345 (41.5%) were female, and 407 (48.9%) were non-Hispanic white. Patients in the intervention group experienced a lower symptom burden as measured by the Edmonton Symptom Assessment Scale score over time compared with patients in the control group (mean [SD] difference, -1.9 [14.2]; 95% CI, -3.77 to -0.19; P = .01 for the intervention group and 2.32 [17.7]; 95% CI, 0.47 to 4.19; P = .02 for the control group). Similar findings were noted in 9-item Patient Health Questionnaire depression scores (mean [SD] difference, -0.63 [3.99]; 95% CI, -1.23 to -0.028; P = .04 for the intervention group and 1.67 [5.49]; 95% CI, 0.95 to 2.37; P = .01 for the control group). Patients in the intervention group compared with patients in the control group had fewer mean (SD) inpatient visits (0.54 [0.77]; 95% CI, 0.47-0.61 vs 0.72 [1.12]; 95% CI, 0.61-0.83; P = .04) and emergency department visits (0.43 [0.76]; 95% CI, 0.36-0.50 vs 0.57 [1.00]; 95% CI, 0.48-0.67; P = .002) per 1000 patients per year and lower total costs (median, $17 869 [interquartile range, $6865-$32 540] vs median, $18 473 [interquartile range, $6415-$37 910]; P = .02). A total of 180 patients in the intervention group and 189 patients in the control group died within 12 months. Among those who died, patients in the intervention group had greater hospice use (125 of 180 [69.4%] vs 79 of 189 [41.8%]; odds ratio, 3.16; 95% CI, 2.13-4.69; P < .001), fewer mean (SD) emergency department and hospital visits (emergency department: 0.10 [0.30]; 95% CI, 0.06-0.14 vs 0.30 [0.46]; 95% CI, 0.24-0.38; P = .001; hospital: 0.27 [0.44]; 95% CI, 0.21-0.34 vs 0.43 [0.82]; 95% CI, 0.32-0.55; P = .02), and lower costs (median, $3602 [interquartile range, $1076-$9436] vs median, $12 726 [interquartile range, $5259-$22 170]; P = .002), but there was no significant difference in inpatient deaths (18 of 180 [10.0%] vs 30 of 189 [15.9%]; P = .14). Conclusions and Relevance: This study suggests that a lay health worker-led intervention may be one way to improve burdensome and costly care.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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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Citations37
Published2020
Admission routes1
Has abstractyes

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