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Record W3080513233

Return on Investment of the Primary Health Care Integrated Geriatric Services Initiative Implementation.

2020· article· en· W3080513233 on OpenAlexaffabout
Nguyễn Xuân Thành, Tanmay Patil, C. Calvert Knudsen, Sharon Hamlin, H. Douglas Lightfoot, Heather Hanson, Dennis Cleaver, Karenn Chan, James Silvius, Scott Oddie, Scott Fielding

Bibliographic record

VenuePubMed · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsAlberta Health
Fundersnot available
KeywordsReturn on investmentMedicineHealth carePrescription drugInvestment (military)Medical prescriptionBusinessMedical emergencyNursingEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Since June 2017, the Primary Health Care Integrated Geriatric Services Initiative (PHC IGSI) has been implemented in Alberta, Canada to, among other aims, reduce costs of unplanned health service utilization while maximizing the utilization of available community resources to support people living with dementia living in communities. AIM OF THE STUDY: We performed an economic evaluation of this initiative to inform policy regarding sustainability, scale up and spread. METHODS: We used a cohort design together with a difference-in-difference approach and a propensity score matching technique to calculate impacts of the intervention on patient's health service utilization, including inpatient, outpatient and physician services, as well as prescription drugs. We then used a decision tree to compare between benefits and costs of the intervention and reported net benefits (NB) and return on investment ratios (ROI). We used a health system perspective and a time horizon of 1 year. Both deterministic and probabilistic sensitivity analyses were performed for the uncertainty of parameters. We analyzed real-world data extracted from the Alberta Health Administrative Databases. All costs/savings were inflated to 2019 CAD (CAD 1 \sim = USD 0.75) using the Canadian Consumer Price Index. RESULTS: The intervention reduced the use of hospital (inpatient, emergency, and outpatient) services by increasing the use of community services (physician and prescription drug). As hospital services are expensive, the PHC IGSI community intervention resulted in a NB from CAD 554 to 4,046 per patient-year for the health system, and a ROI from 1.3 to 3.1 meaning that every CAD invested in PHC IGSI would bring CAD 1.3 to 3.1 in return. The probability of PHC IGSI to be cost-saving was 56.4% to 69.3%. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE: The PHC IGSI is cost-effective in Alberta. IMPLICATIONS FOR HEALTH POLICY: The savings would be larger if the initiative is sustained, scaled up and spread because of not only a reduced cost of intervention in the sustainability phase, but also because of the increased number of patients that would be impacted. IMPLICATIONS FOR FURTHER RESEARCH: Future studies taking a societal perspective to also include costs for families and health and social sectors at the community level, would be desirable. Additionally, future works to determine how wellbeing is impacted by the PHC IGSI as vertical and horizontal integration interventions are implemented at the community level, are essential to undertake. Finally, in addition to people living with dementia, the PHC IGSI also supports people living in the community with frailty and other geriatric syndromes, therefore, the cost-savings estimated in this study are likely underestimated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.265
GPT teacher head0.379
Teacher spread0.114 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations7
Published2020
Admission routes2
Has abstractyes

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