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Record W3033411417 · doi:10.12998/wjcc.v8.i11.2266

Utilising digital health to improve medication-related quality of care for hypertensive patients: An integrative literature review

2020· article· en· W3033411417 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of Clinical Cases · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychological interventionDigital healthScopusHealth careTelehealthMEDLINEmHealthBlood pressureFamily medicineTelemedicineNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hypertension or high blood pressure is considered as a significant contributor and risk factor to many serious conditions, approximately 1.13 billion people have hypertension globally. However, the integrated technologies can upscale health provisions and improve the effectiveness of the healthcare system. WHO has recommended that the digital health interventions (DHIs) and the Health System Challenges should be used in tandem in addressing health. AIM: To summarise the outcomes from a range of research which investigated the use of DHI to improve the medication-related quality of care (MRQOC) for hypertensive patients. METHODS: An integrative literature review was undertaken in October 2019 using the Medline, Cumulative Index of Nursing and Allied Health Literature, and Scopus databases for publications in English with no date limit. RESULTS: In total, 18433 participants were included in this review from 28 studies meeting the eligibility criteria. There were 19 DHI identified within eight countries: Australia, Canada, India, South Korea, Lebanon, Pakistan, the United Kingdom, and the United States of America. The DHI were provided as community-based, clinical-based and home-based program through mobile phone, mobile health system, short message service, and telehealth, digital medicine, and online healthcare (web-based). The mean age of participants was 59 ranging from 42 to 81 years with an average mean systolic blood pressure of 143.3 mmHg at baseline, ranging from 129.0 mmHg to 159.0 mmHg. The proportion of male participants ranged from 13.9% to 92.0%. Eighteen interventions showed evidence of reduction in blood pressure and improvement of self-management in relation to medication adherence and blood pressure control. The reduction of systolic blood pressure ranged between 1.9 mmHg and 26.0 mmHg, with a mean of 10.8 mmHg. The digital health was found positively associated with the MRQOC for hypertensive patients such as improvement in medication adherence and medication management; better blood pressure control; maintaining follow-ups appointment and self-management; increasing access to healthcare particularly among patients living in rural area; and reducing adverse events. However, some interventions found no significant effect on hypertensive care. The follow up duration varied between 2 mo and 18 mo with an average attrition rate of 10.1%, ranging from 0.0% to 17.4%. CONCLUSION: Utilising digital health innovation for hypertensive care in different settings with tailored interventions positively impacted on MRQOC leading to an improvement of patient outcomes and their quality of life. Nevertheless, inconclusive findings were found in some interventions, and inconsistent outcomes between DHI were noted. A future research and evidence-based DHI for hypertension or chronic diseases should be developed through the evidence-to-decision framework and guidelines.

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.

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)0.002
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.787
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.157
GPT teacher head0.551
Teacher spread0.394 · 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