Evidence map›Paper›PMID 35238353›Full record

ArticleThe Journal of infectious diseases2021

Healthcare Utilization Survey in the Hybrid Model of the Surveillance for Enteric Fever in India (SEFI) Study: Processes, Monitoring, Results, and Challenges.

Reshma Raju, J Kezia Angelin, Arun S Karthikeyan, Dilesh Kumar, Ranjith Kumar R, Nikhil Sahai, Karthikeyan Ramanujam, Manoj Murhekar, A Elangovan, Prasanna Samuel and 2 more

Open access · hybridAbstract read
In one paragraph

Article in The Journal of infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 26% of its field
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

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Non-typhoidalJAC-antimicrobial resistance · 2024
    Review
  3. Article
  4. Article
  5. Burden of Typhoid and Paratyphoid Fever in India.The New England journal of medicine · 2023
    Article
  6. Typhoid in India: An Age-old Problem With an Existing Solution.The Journal of infectious diseases · 2021
    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

12 authors at 2 institutions in 1 country.

Reshma RajuDepartment of Paediatrics, Christian Medical College Vellore, Vellore, India.ORCID 0000-0001-7247-537X
J Kezia AngelinDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Arun S KarthikeyanDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Dilesh KumarDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Ranjith Kumar RDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Nikhil SahaiDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Karthikeyan RamanujamDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Manoj MurhekarNational Institute of Epidemiology, Indian Council of Medical Research, Chennai, India.
A ElangovanNational Institute of Epidemiology, Indian Council of Medical Research, Chennai, India.
Prasanna SamuelDepartment of Gastrointestinal Sciences, Christian Medical College Vellore, Vellore, India.
Jacob JohnDepartment of Community Health, Christian Medical College Vellore, Vellore, India.ORCID 0000-0003-3654-5099
Gagandeep KangDepartment of Paediatrics, Christian Medical College Vellore, Vellore, India.ORCID 0000-0002-3656-564X
Christian Medical College, Vellore · INIndian Council of Medical Research · IN

Funding

Bill and Melinda Gates Foundation INV-009497-OPP1159351
6 · The paper itself

Abstract

backgroundLack of reliable data in India drove the "Surveillance of Enteric Fever in India" (SEFI) concept. Hybrid surveillance, combining facility-based surveillance for the crude incidence, and a community-based healthcare utilization survey (HCUS) to calculate the factor needed to arrive at the adjusted incidence, was used in 6 sites. The HCUS aimed to determine the percentage of utilization of study facilities by the catchment population for hospitalizations due to febrile illness.

methodsPopulation proportional to size sampling and systematic random sampling, in 2 stages, were used to survey 5000 households per site. Healthcare utilization was assessed.

resultsFebrile illness accounted for 20% of admissions among 137 990 individuals from 30 308 households. Only 9.6%-38.3% of those admitted with febrile illness sought care in the study hospitals. The rate of rural utilization of the private sector for hospitalization was 67.6%. The rate of hospitalization for febrile illness, per 1000 population, ranged from 2.6 in Manali to 9.6 in Anantapur; for 25.8% of the deaths associated with febrile illness, no facility was used before death.

conclusionsOne in 5 hospitalizations were associated with fever. Rural utilization of the private sector for hospitalization due to febrile illness was more than that of the public sector. Healthcare utilization patterns for hospital admissions due to febrile illness varied across sites. A meticulously performed HCUS is pivotal for accurate incidence estimation in a hybrid surveillance. CLINICAL TRIALS REGISTRATION: ISRCTN72938224.

Indexed as

Typhoid FeverHospitalizationHumansIncidenceIndiaPatient Acceptance of Health CareRural Populationcommunity-based surveillanceEnteric feverHealthcare utilization surveyHybrid surveillancemonitoring

Identifiers

PMID35238353
PMCPMC8914874
OpenAlexW3216389886

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LicenceCC BY
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Registered trials

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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.