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Record W3022595475 · doi:10.1186/s12939-020-01160-0

Socioeconomic inequalities in hospitalizations for chronic ambulatory care sensitive conditions: a systematic review of peer-reviewed literature, 1990–2018

2020· review· en· W3022595475 on OpenAlexafffund
Lauren E. Wallar, Eric De Prophetis, Laura C. Rosella

Bibliographic record

VenueInternational Journal for Equity in Health · 2020
Typereview
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanada Excellence Research Chairs, Government of Canada
KeywordsMedicineSocioeconomic statusCINAHLAmbulatory careObservational studyMEDLINEPublic healthAmbulatoryPopulationPsychological interventionHealth careSystematic reviewPsycINFOFamily medicineGerontologyEnvironmental healthPsychiatryNursingInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hospitalizations for chronic ambulatory care sensitive conditions are an important indicator of health system equity and performance. Chronic ambulatory care sensitive conditions refer to chronic diseases that can be managed in primary care settings, including angina, asthma, and diabetes, with hospitalizations for these conditions considered potentially avoidable with adequate primary care interventions. Socioeconomic inequities in the risk of hospitalization have been observed in several health systems globally. While there are multiple studies examining the association between socioeconomic status and hospitalizations for chronic ambulatory care sensitive conditions, these studies have not been systematically reviewed. The objective of this study is to systematically identify and describe socioeconomic inequalities in hospitalizations for chronic ambulatory care sensitive conditions amongst adult populations in economically developed countries reported in high-quality observational studies published in the peer-reviewed literature. METHODS: Peer-reviewed literature was searched in six health and social science databases: MEDLINE, EMBASE, PsycInfo, CINAHL, ASSIA, and IBSS using search terms for hospitalization, socioeconomic status, and chronic ambulatory care sensitive conditions. Study titles and abstracts were first screened followed by full-text review according to the following eligibility criteria: 1) Study outcome is hospitalization for selected chronic ambulatory care sensitive conditions; 2) Primary exposure is individual- or area-level socioeconomic status; 3) Study population has a mean age ± 1 SD < 75 years of age; 4) Study setting is economically developed countries; and 5) Study type is observational. Relevant data was then extracted, and studies were critically appraised using appropriate tools from The Joanna Briggs Institute. Results were narratively synthesized according to socioeconomic constructs and type of adjustment (minimally versus fully adjusted). RESULTS: Of the 15,857 unique peer-reviewed studies identified, 31 studies met the eligibility criteria and were of sufficient quality for inclusion. Socioeconomic constructs and hospitalization outcomes varied across studies. However, despite this heterogeneity, a robust and consistent association between lower levels of socioeconomic status and higher risk of hospitalizations for chronic ambulatory care sensitive conditions was observed. CONCLUSIONS: This systematic review is the first to comprehensively identify and analyze literature on the relationship between SES and hospitalizations for chronic ambulatory care sensitive conditions, considering both aggregate and condition-specific outcomes that are common to several international health systems. The evidence consistently demonstrates that lower socioeconomic status is a risk factor for hospitalization across global settings. Effective health and social interventions are needed to reduce these inequities and ensure fair and adequate care across socioeconomic groups. TRIAL REGISTRATION: PROSPERO CRD42018088727.

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)0.006
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.162
GPT teacher head0.568
Teacher spread0.406 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations51
Published2020
Admission routes2
Has abstractyes

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