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Record W7162134785 · doi:10.82308/8343

Evaluating the impact of electronical medical record systems on patient-centered primary care

2015· dissertation· en· W7162134785 on OpenAlexaboutno aff
Mario Kangeswaren

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicElectronic Health Records Systems
Canadian institutionsnot available
Fundersnot available
KeywordsRelevance (law)Primary careMatching (statistics)Medical recordConceptual frameworkMEDLINEConceptual modelHealth care

Abstract

fetched live from OpenAlex

OBJECTIVESThere is a strong movement towards patient-centered care, as well as electronic medical record systems (EMRS) implementation, particularly in primary care settings. The actual impact of EMRS on patient-centered primary care (PCPC) has yet to be investigated. The Canada Health Infoway national survey offers an opportunity to explore the link between PCPC and EMRS. The objective of this thesis is: (1) to identify a conceptual framework for PCPC that can be used to evaluate the impact of EMRS on PCPC, (2) to evaluate what elements of a screening survey provides relevant information to assess how EMRS impact PCPC, and (3) to evaluate to what extent elements of a screening survey provides adequate information to assess how EMRS impact PCPC.METHODSThe initial step consisted of conducting a literature search using articles from Embase and MEDLINE, to identify an optimal conceptual framework for PCPC to evaluate the impact of EMRS on PCPC. For the subsequent steps, secondary data from the Canada Health Infoway national screening survey was used. Surveys completed from 70 primary care clinics across Canada were obtained. Variable matching was used for each of the survey’s EMRS impact statements to qualitatively identify their relevance to each of the dimensions of the indentified PCPC conceptual framework. Subsequently, PCPC impact scores (%) were calculated from variable matching relevance scores to identify the relevance of patient-centeredness of each of the national survey’s EMRS impact statements in primary care. Additionally, for each dimension, PCPC dimensional relevance (%) as ratios amongst each other, were calculated from variable matching relevance scores to identify if the survey unequivalently captured dimensions. Finally, for each EMRS impact statement, physician agreement and PCPC impact scores were used in combination to capture physician agreement on the degree of the EMRS impact on PCPC.RESULTSThe most prevalently cited conceptual framework for patient-centered care was the 6 dimensional Patient-Centered Clinical Method. Subsequently this framework went on to be revised and condensed into the 5 dimensional Mead and Bower model. Based on these conceptual frameworks the Hudon framework was identified and adopted for this thesis. This framework consists of four over-lapping dimensions of the previous two frameworks, specifically for primary care. Out of the survey`s 20 EMRS impact statements, only 11 were positive for relevance to PCPC (PCPC impact score > 0%). The Canada Health Infoway national screening survey could only assess 12.3% (s.d. 30.2, overall mean PCPC impact score) of EMRS impact on PCPC. The PCPC dimensional relevance revealed that the survey did not equally capture the four PCPC dimensions: 42.9% for Clinician-Patient Relationship (Therapeutic Alliance) dimension, followed by 28.6% for Whole Person Care (BioPsychoSocial Perspective), 14.3% for Common Ground (Sharing Power and Responsibility), and 14.3% for Disease and Illness Experience (Patient As A Person). Physicians were in agreement that the EMRS apparently had no significant impact on PCPC (0.04 s.d. 0.63, on a Likert scale of -2 to +2).CONCLUSIONSThe Hudon conceptual framework for patient centered care was identified as the optimal model for evaluating the impact of EMRS on PCPC. The data from the Canada Health Infoway national survey was able to assess some of the dimensions of PCPC and examine the impact of EMRS on PCPC, but did not capture all the elements consistently. Certain PCPC dimensions may be more sensitive than others to EMRS implementation. Further studies need to be conducted that target the impact of EMRS on PCPC. Additionally, studies need to be conducted to identify if EMRS implementation preferentially affects the distribution of different dimensions of PCPC.

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)0.084
metaresearch head score (Gemma)0.252
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 score0.084
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.252
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.012
Science and technology studies0.0010.001
Scholarly communication0.0050.003
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 head0.140
GPT teacher head0.549
Teacher spread0.409 · 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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