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Record W2472581086 · doi:10.1097/hmr.0000000000000122

An intraorganizational model for developing and spreading quality improvement innovations

2016· article· en· W2472581086 on OpenAlexaff
Katherine C. Kellogg, Lindsay A. Gainer, Adrienne Allen, Tatum O'Sullivan, Sara J. Singer

Bibliographic record

VenueHealth Care Management Review · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsProcess (computing)Process managementWorkflowQuality (philosophy)Quality managementBusinessKnowledge managementComputer scienceMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: Recent policy reforms encourage quality improvement (QI) innovations in primary care, but practitioners lack clear guidance regarding spread inside organizations. PURPOSE: We designed this study to identify how large organizations can facilitate intraorganizational spread of QI innovations. METHODOLOGY/APPROACH: We conducted ethnographic observation and interviews in a large, multispecialty, community-based medical group that implemented three QI innovations across 10 primary care sites using a new method for intraorganizational process development and spread. We compared quantitative outcomes achieved through the group's traditional versus new method, created a process model describing the steps in the new method, and identified barriers and facilitators at each step. FINDINGS: The medical group achieved substantial improvement using its new method of intraorganizational process development and spread of QI innovations: standard work for rooming and depression screening, vaccine error rates and order compliance, and Pap smear error rates. Our model details nine critical steps for successful intraorganizational process development (set priorities, assess the current state, develop the new process, and measure and refine) and spread (develop support, disseminate information, facilitate peer-to-peer training, reinforce, and learn and adapt). Our results highlight the importance of utilizing preexisting organizational structures such as established communication channels, standardized roles, common workflows, formal authority, and performance measurement and feedback systems when developing and spreading QI processes inside an organization. In particular, we detail how formal process advocate positions in each site for each role can facilitate the spread of new processes. PRACTICE IMPLICATIONS: Successful intraorganizational spread is possible and sustainable. Developing and spreading new QI processes across sites inside an organization requires creating a shared understanding of the necessary process steps, considering the barriers that may arise at each step, and leveraging preexisting organizational structures to facilitate intraorganizational process development and spread.

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)0.004
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.485
GPT teacher head0.670
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations12
Published2016
Admission routes1
Has abstractyes

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