MétaCan
Menu
Back to cohort
Record W2901487406 · doi:10.2147/jmdh.s155205

The logistics of voucher management: the underreported component in family planning voucher discussions

2018· review· en· W2901487406 on OpenAlex
Moazzam Ali, Madeline Farron, Syed Khurram Azmat, Waqas Hameed

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2018
Typereview
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsHospital for Sick Children
FundersWorld Health OrganizationDavid and Lucile Packard Foundation
KeywordsVoucherComponent (thermodynamics)Computer scienceData scienceBusinessOperations researchWorld Wide WebEngineering

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of health care vouchers or coupons is to receive a health service in exchange which is fully or partially subsidized, such as any treatment offered for communicable disease; for immunization; antenatal care-/postnatal care-related maternal health services; a family planning (FP) service; or to get a health commodity like a medicine. Vouchers are targeted for a group of people who can benefit the most such as on the basis of poverty ranking, marginalized or living in rural areas. According to the World Health Organization, voucher schemes in the area of sexual and reproductive health are considered of high value if they are implemented to address the issues of contraceptive commodity or service unavailability or to address the barriers to access such services through contracting out health services, for example, through social franchising (SF). FP vouchers can substantially expand contraceptive access and choice and empower the underserved populations. Literature cites voucher's effectiveness in better targeting, increasing use, and improving program outcomes in FP programs; however, there is little research or explanation of how voucher management is done in practice. DISCUSSION: The paper attempts to describe various components of voucher management system and its functioning using example of a voucher program in Pakistan. There are challenges such as high upfront cost, targeting the appropriate clients, validation of vouchers, and quality assurance, but these can be managed with better preparation at the planning and design stage. Strong monitoring and evaluation are integral to successful implementation of the voucher program. Also, voucher interventions that are targeted and adopt a pro-poor strategy have been found to improve access to care within poor and marginalized populations. Such programs have the capacity to bridge health inequities in developing nations. Targeted voucher schemes such as those which are designed as pro-poor or pro-rural are known to reduce barriers to access for those living with poverty or for the ones considered as marginalized population. Hence, such interventions have the capacity to fulfill the gaps in health inequities, especially, in low- and/or middle-income countries. CONCLUSION: Voucher programs should report the voucher logistics and management to build a larger evidence base of best practices. All voucher schemes must be designed, implemented, and evaluated on the basis of set objectives through addressing the local context. But any voucher implementing organization also conducting the in-house voucher management simultaneously may be considered as a weakness in program design, in turn providing rationale for either failure or success of that particular voucher intervention. Therefore, separating implementation and management of a voucher initiative can lead to enhanced transparency, improved accountability, allow for independent validation of services, and facilitate compliance for payments.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.769
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.129
GPT teacher head0.437
Teacher spread0.307 · 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