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Record W3109907142

Cost analysis and Potential Reduction of Medication Errors Due to Implementation of CPOE & BCMA in the Fraser Health Authority

2018· article· en· W3109907142 on OpenAlexaffvenueabout
Kane Christian Larson

Bibliographic record

VenueUBC Faculty of Medicine medical journal · 2018
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineMedical emergencyPatient safetyHealth careOrder entryComputerized physician order entryEmergency medicineOperations management
DOInot available

Abstract

fetched live from OpenAlex

Medication errors are blunders in the patient treatment process that have the potential to cause harm. Currently, there are an estimated 70,000 preventable adverse events per year in Canada, and one-quarter of the events are related to medication errors; resulting in 700 deaths a year. The cost of these medication errors is estimated to be $2.6 billion per year in Canada, each preventable adverse drug event in a hospitalized patient is estimated to cost $4,685 CAD ($6,750 inflation adjusted to 2017) and increases the length of stay by 4.6 days.   The most frequently cited method for preventing medication errors is incorporating a closed-loop medication management system (CLMM). The ideal CLMM system seamlessly integrates information technology from automated dispensing devices (ADD), computerised provider order entry (CPOE), and bedside bar-coded medication administration (BCMA). The integration will enable each stage of the medication management process such as prescribing, transcription, dispensing, and administration to be consolidated into an efficient and save structure to optimize patient health. Given the significant capital investment required to implement CLMM, the question Fraser Health Authority executives may have is how many medication errors can realistically be prevented and is it worth the cost?   Fraser Health is British Columbia’s largest Health Authority, it is comprised of 12 acute care hospitals, 7,760 residential care beds, 25,000 staff, and had an operating budget of over $3 billion. Presently, Abbotsford Regional Hospital, Surrey Memorial, Royal Columbian, and Chilliwack Hospital have deployed ADDs, and the rest of the Fraser Health hospitals will eventually receive them; however, implementation of CPOE and BCMA is only in the planning stages.   When modelling the cost-benefit of a CLMM system, challenges include estimating the true number of medication errors (as these are often self-reported), estimating the cost of change management, and estimating the cost of inevitable implementation delays. In the published literature, economic analyses of the individual components of CLMM systems can be found. For example, the average cost of implementing CPOE in a single hospital is estimated to be $5.3 million ranging from $2.3 million for a hospital with less than 200 beds to $20.3 million for a hospital with more than 500 beds (the numbers are inflation adjusted to 2017 and currency converted to CAD). Nonetheless, investment in CPOE appears to be cost-effective over time, one NHS study showed that predicted effects of CPOE implementation on a 400 bed hospital had a net health valuations of 62 million CAD (currency converted and inflation adjusted to 2017) over a 5-year period . Another study at Brigham and Women’s Hospital (793 beds), where CPOE was pioneered, estimated a net benefit of $4.3 million CAD (inflation adjusted 2017) per year, just in time-savings with staff (unit clerks, nurses and pharmacists). With regards to improving safety, it is estimated that CPOE can reduce up to 50% to 88% of medical errors within US hospitals.   The other CLMM component that Fraser Health has yet to incorporate is BCMA, a technology that checks the 5 rights of medication administration (right drug, right dose, right route, right patient, and right time) at the bedside. BCMA has been shown to reduce medication errors by up to 49% to 51% and generate an annual savings of $2.2 million from time saving. Thus, we hypothesize that If a CLMM system was previously deployed in Fraser Health, a significant number of medication errors would have been prevented, partially or completely offsetting its cost. This analysis examines the potential benefits of implementing BCMA and CPOE in Fraser Health, a system that will already have ADDs.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.132
GPT teacher head0.500
Teacher spread0.367 · 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 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
Published2018
Admission routes3
Has abstractyes

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