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Record W4402745558 · doi:10.2196/56549

Development of a Dementia Case Management Information System App: Mixed Methods Study

2024· article· en· W4402745558 on OpenAlexvenueno aff
Huei‐Ling Huang, Yi‐Ping Chao, Chun-Yu Kuo, Ya-Li Sung, Yea‐Ing Lotus Shyu, Wen-Chuin Hsu

Bibliographic record

VenueJMIR Aging · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaComputer scienceProcess managementData sciencePsychologyBusinessMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Case managers for persons with dementia not only coordinate patient care but also provide family caregivers with educational material and available support services. Taiwan uses a government-based information system for monitoring the provision of health care services. Unfortunately, scheduling patient care and providing information to family caregivers continues to be paper-based, which results in a duplication of patient assessments, complicates scheduling of follow-ups, and hinders communication with caregivers, which limits the ability of case managers to provide cohesive, quality care. OBJECTIVE: This multiphase study aimed to develop an electronic information system for dementia care case managers based on their perceived case management needs and what they would like included in an electronic health care app. METHODS: Case managers were recruited to participate (N=63) by purposive sampling from 28 facilities representing two types of community-based dementia care centers in Taiwan. A dementia case management information system (DCMIS) app was developed in four phases. Phase 1 assessed what should be included in the app by analyzing qualitative face-to-face or internet-based interviews with 33 case managers. Phase 2 formulated a framework for the app to support case managers based on key categories identified in phase 1. During phase 3, a multidisciplinary team of information technology engineers and dementia care experts developed the DCMIS app: hardware and software components were selected, including platforms for messaging, data management, and security. The app was designed to eventually interface with a family caregiver app. Phase 4 involved pilot-testing the DCMIS app with a second group of managers (n=30); feedback was provided via face-to-face interviews about their user experience. RESULTS: Findings from interviews in phase 1 indicated the DCMIS framework should include unified databases for patient reminder follow-up scheduling, support services, a health education module, and shared recordkeeping to facilitate teamwork, networking, and communication. The DCMIS app was built on the LINE (LY Corporation) messaging platform, which is the mobile app most widely used in Taiwan. An open-source database management system allows secure entry and storage of user information and patient data. Case managers had easy access to educational materials on dementia and caregiving for persons living with dementia that could be provided to caregivers. Interviews with case managers following pilot testing indicated that the DCMIS app facilitated the completion of tasks and management responsibilities. Some case managers thought it would be helpful to have a DCMIS desktop computer system rather than a mobile app. CONCLUSIONS: Based on pilot testing, the DCMIS app could reduce the growing challenges of high caseloads faced by case managers of persons with dementia, which could improve continuity of care. These findings will serve as a reference when the system is fully developed and integrated with the electronic health care system in Taiwan.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.027
GPT teacher head0.399
Teacher spread0.372 · 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 designOther design
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

Citations1
Published2024
Admission routes1
Has abstractyes

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