Evidence map›Paper›PMID 37047998›Full record

ArticleInternational journal of environmental research and public health2023

Evaluating Drivers of the Patient Experience Triangle: Stress, Anxiety, and Frustration.

Sumaya Almaazmi, Mecit Can Emre Simsekler, Andreas Henschel, Abroon Qazi, Dounia Marbouh, Rana Adel Mahmoud Ali Luqman

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Can AI chatbots accurately answer patient questions regarding vasectomies?International journal of impotence research · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sumaya AlmaazmiDepartment of Industrial and Systems Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
Mecit Can Emre SimseklerDepartment of Industrial and Systems Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.ORCID 0000-0002-1555-5012
Andreas HenschelDepartment of Electrical Engineering and Computer Science, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.ORCID 0000-0003-1386-5372
Abroon QaziSchool of Business Administration, American University Sharjah, Sharjah 26666, United Arab Emirates.ORCID 0000-0001-6648-3306
Dounia MarbouhDepartment of Industrial and Systems Engineering, Khalifa University of Science and Technology, Abu Dhabi 127788, United Arab Emirates.
Rana Adel Mahmoud Ali LuqmanMubadala Healthcare, IPIC Square, Abu Dhabi 45005, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patient experience is a widely used indicator for assessing the quality-of-care process during a patient's journey in hospital. However, the literature rarely discusses three components: patient stress, anxiety, and frustration. Furthermore, little is known about what drives each component during hospital visits. In order to explore this, we utilized data from a patient experience survey, including patient- and provider-related determinants, that was administered at a local hospital in Abu Dhabi, UAE. A machine-learning-based random forest (RF) algorithm, along with its embedded importance analysis function feature, was used to explore and rank the drivers of patient stress, anxiety, and frustration throughout two stages of the patient journey: registration and consultation. The attribute 'age' was identified as the primary patient-related determinant driving patient stress, anxiety, and frustration throughout the registration and consultation stages. In the registration stage, 'total time taken for registration' was the key driver of patient stress, whereas 'courtesy demonstrated by the registration staff in meeting your needs' was the key driver of anxiety and frustration. In the consultation step, 'waiting time to see the doctor/physician' was the key driver of both patient stress and frustration, whereas 'the doctor/physician was able to explain your symptoms using language that was easy to understand' was the main driver of anxiety. The RF algorithm provided valuable insights, showing the relative importance of factors affecting patient stress, anxiety, and frustration throughout the registration and consultation stages. Healthcare managers can utilize and allocate resources to improve the overall patient experience during hospital visits based on the importance of patient- and provider-related determinants.

Indexed as

AnxietyFrustrationAnxiety DisordersHumansPatient Outcome AssessmentSurveys and Questionnairesmachine learningpatient anxietypatient datapatient experiencepatient frustrationpatient satisfactionpatient stressqualityrandom forest

Identifiers

PMID37047998
PMCPMC10094497

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.