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Record W2596643119 · doi:10.11575/prism/30075

Psychotherapy in Alberta: Favorable Returns on Investment Resulting from Integrating Psychological Care into Primary Care Networks

2016· dissertation· en· W2596643119 on OpenAlexaboutno aff
Mason Stott

Bibliographic record

VenueOpen MIND · 2016
Typedissertation
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
Fundersnot available
KeywordsPrimary careInvestment (military)PsychotherapistPsychologyMedicinePolitical scienceFamily medicine

Abstract

fetched live from OpenAlex

Untreated mental illness costs Alberta’s healthcare system an annual $2.3 billion in excess costs. These costs occur because many mentally ill patients are not properly treated. Rather than being treated in preventative methods, patients find themselves in more expensive hospital-delivered acute care. This issue is relevant in today’s policy realm because it represents a unique opportunity for the province of Alberta to realize large cost-savings, and to avoid hundreds of millions of dollars in excess costs to the provincial healthcare system. The relevant literature, family physician opinions, and various case studies illustrate how providing psychological care in an integrated manner is the most promising means of delivering a new program. Integrating such treatment into primary care facilities results in higher patient satisfaction, greater follow-up rates, superior patient recovery, and less mortality. Costs and cost-savings were determined for three different scenarios. Each scenario represents a unique way of delivering PCN-integrated psychological treatment. Scenario 1 offers internet-delivered therapy to all patients. Scenario 2 offers face-to-face therapy to all patients. Scenario 3 combines the two scenarios and offers a mixed model of internet-delivered psychotherapy for mildly mentally ill patients and face-to-face therapy for seriously mentally ill patients. Upon conducting the economic analysis, the Dunning Funnel, ROI and cost-savings estimates, and ease of project implementation were used to choose one recommendation: Scenario 2 was chosen. Scenario 2 offers returns on investment of approximately 434 per cent, and cost-savings of approximately $415,794,000. Costs for the Scenario are estimated at $77,455,521. Before Scenario 2 is fully scaled-up across the province, it is recommended that first it is implemented as a local pilot project – implemented in one PCN rather than in all of Alberta’s 42 PCNs. This will allow for more viable implementation and superior mitigation of financial risk. Furthermore, it will allow for shortcomings of the program to be solved before the project is fully scaled to the provincial level. Consultation plays an important role in this proposed integrated psychological care program. All directly involved healthcare practitioners, including: family physicians, psychiatrists, psychologists, social workers, and nurses, must all be heavily consulted. This must be done in order to gain valuable insight into how best to offer such a proposed program, as well as in order to gain the support of these powerful players in the healthcare community. Communication will play an important role during the implementation stage. A Director of Communications will need to effectively navigate and manage the media in regards to the implementation of Scenario 2. Eventually, funds may be reallocated from existing healthcare departments (such as the Emergency Department and inpatient services) to further finance the ongoing operations of Scenario 2. Better treatment of mental illness in Alberta represents a unique opportunity to save the province money – on the scale of hundreds of millions of annual dollars. All moral reasons for providing care to the ill aside, the financial savings from investing in mental health are the ultimate findings of this report.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.469
Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.153
GPT teacher head0.472
Teacher spread0.319 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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