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Record W3122975512 · doi:10.24926/iip.v12i1.3591

Third-party Reimbursement of Pharmacist-Led Cardiovascular and Diabetes Preventive Health Services for Workplace Health Initiatives: A Narrative Systematic Review

2021· review· en· W3122975512 on OpenAlexaff
Brandon A M Ah Tong, Anita I. Kapanen, Jamie Yuen

Bibliographic record

VenueINNOVATIONS in pharmacy · 2021
Typereview
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReimbursementPharmacistMedicineFamily medicinePaymentMEDLINEStandardizationHealth careNursingPharmacyBusinessFinancePolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize available literature describing third-party payer reimbursement models for pharmacist-led preventive health services as part of workplace health initiatives. METHODS: A combination of search terms related to pharmacists, preventive health, and third-party reimbursement were searched in MEDLINE, EMBASE, and PubMed. Included studies described community pharmacist-led cardiovascular and diabetes preventive health service to employees older than 18 years of age as part of a workplace health program with corresponding third-party reimbursement models. Programs that were reimbursed by government resources or studies lacking reimbursement model details were excluded. One reviewer performed level 1 screening and three reviewers analyzed included studies. RESULTS: The search criteria yielded 863 results. Sixteen articles were reviewed after level 1 screening and 13 were ineligible and excluded. Three studies with varying quality of reporting were included. Reimbursement models varied from $40 USD for a 20-minute visit to $391 to $552 USD total per patient with an average of 6 visits per patient. CONCLUSION: There is a lack of quality literature describing third-party reimbursement models for pharmacist-led preventive health services, which hinders the ability to implement a standardized model. High quality studies evaluating the cost of reimbursing pharmacist-led cardiovascular preventive health services compared to the savings to the third-party payer should be performed to inform the standardization of payment models.

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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.331
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.179
GPT teacher head0.503
Teacher spread0.324 · 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.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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