Evidence map›Paper›PMID 31254089›Full record

ArticleEnvironmental monitoring and assessment2019

Differential effects of distance decay on hospital inpatient visits among subpopulations in Florida, USA.

Peng Jia, Fahui Wang, Imam M Xierali

Abstract read
In one paragraph

Article in Environmental monitoring and assessment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

  1. Article
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  5. Is more better? A multilevel analysis of percutaneous coronary intervention hospital openings and closures on patient volumes.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2024
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  15. Inpatient Flow Distribution Patterns at Shanghai Hospitals.International journal of environmental research and public health · 2020
    Article
  16. Geospatial technology in environmental health applications.Environmental monitoring and assessment · 2019
    Article
  17. Article
  18. Analysis of Patients' Mobility Patterns: Insights From a Process Mining-Based Longitudinal Study.Inquiry : a journal of medical care organization, provision and financing
    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

3 authors.

Peng JiaFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, 7500, The Netherlands. p.jia@utwente.nl.
Fahui WangDepartment of Geography and Anthropology, Louisiana State University, Baton Rouge, LA, 70803, USA. fwang@lsu.edu.
Imam M XieraliDepartment of Family and Community Medicine, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.

Funding

Automated Delineation of Cancer Service AreasR21CA212687 · NCI · DARTMOUTH COLLEGE · PI ONEGA, TRACY, WANG, FAHUI · 2017 to 2018
$392k
NCI NIH HHS R21 CA212687NCI NIH HHS R21CA212687
6 · The paper itself

Abstract

Understanding patients' travel behavior for seeking hospital care is fundamental for understanding healthcare market and planning for resource allocation. However, few studies examined the issue comprehensively across populations by geographical, demographic, and health insurance characteristics. Based on the 2011 State Inpatient Database in Florida, this study modeled patients' travel patterns for hospital inpatient care across geographic areas (by average affluence, urbanicity) and calendar seasons, and across subpopulations (by age, gender, race/ethnicity, and health insurance status). Overall, travel patterns for all subpopulations were best captured by the log-logistic function. Patients in more affluent areas and rural areas tended to travel longer for hospital inpatient care, so did the younger, whites, and privately insured. Longer travel distances may be a necessity for rural patients to cope with lack of accessibility for local hospital care, but for the other population groups, it may indicate rather better mobility and more healthcare choices. The results can be used in various healthcare analyses such as accessibility assessment, hospital service area delineation, and healthcare resource planning.

Indexed as

AdolescentAdultAgedCatchment Area, HealthChildChild, PreschoolDemographyFemaleFloridaHealthcare DisparitiesHumansInfantInfant, NewbornInpatientsInsurance, HealthMaleDistance decay functionFloridaHospital inpatient careHospital utilizationState Inpatient Database (SID)

Identifiers

PMID31254089
PMCPMC6598965

What OpenQuestion holds

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LicenceCC BY
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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.