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Record W2101902841 · doi:10.1177/0163278710393955

Assessing Costs and Potential Returns of Evidence-Based Programs for Seniors

2010· article· en· W2101902841 on OpenAlex
Thomas R. Miller, Justin B. Dickerson, Matthew Lee Smith, Marcia G. Ory

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEvaluation & the Health Professions · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
FundersNational Center for Chronic Disease Prevention and Health PromotionCenters for Disease Control and PreventionAGE-WELL
KeywordsPublic healthPsychological interventionCost–benefit analysisEconomic evaluationReturn on investmentProgram evaluationCost effectivenessMedicineActuarial scienceEnvironmental healthPublic economicsBusinessNursingEconomicsRisk analysis (engineering)Political science

Abstract

fetched live from OpenAlex

The authors describe the customary tools used by health services researchers to conduct economic evaluations of health interventions. Recognizing the inherent challenges of these tools for utilization in contemporary public health practice, we recommend a practical cost-benefit analysis (PCBA) to allow public health practitioners to assess the economic merits of their existing public health programs. The PCBA estimates what health effects and corresponding medical cost avoidance would be required to support the costs associated with implementing a community-based prevention program. We apply the PCBA to evaluate a statewide evidence-based falls prevention program for seniors in Texas. We estimate a positive return on realized costs due to avoided direct and indirect medical expenses if the program averts 7 falls among 140 participants within the first year. While acknowledging the demonstrated health-related benefits of public health interventions, we provide a practical ex-post economic evaluation methodology to assess return on investment as a more simplistic yet effective alternative for public health practitioners versus contemporary analyses of health services researchers.

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.

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)0.067
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0670.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.682
GPT teacher head0.564
Teacher spread0.119 · 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