Evidence map›Paper›PMID 42483341›Full record

ArticleJournal of family medicine and primary care2026

Feasibility of stratification of households based on health needs in Mugalur village, Anekal taluk-An exploratory study.

Teny Attokaran, Gokul K Madhav, Farah N Fathima, Vishak S Rao, R Chandan, H Stephen, Twinkle Agrawal

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Article in Journal of family medicine and primary care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Teny AttokaranDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.
Gokul K MadhavDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.
Farah N FathimaDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.
Vishak S RaoDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.
R ChandanDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.
H StephenDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.
Twinkle AgrawalDepartment of Community Health, St John's Medical College, Bengaluru, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Stratifying households helps identify those at higher health risk and supports focused interventions. This study assessed the feasibility of creating a household stratification tool in rural Mugalur village, Anekal Taluk, to enhance community health services by classifying households according to their healthcare needs. Methodology: A stratification tool was developed by a brainstorming session with public health professionals, identifying key health conditions across age groups, along with relevant social and environmental risk factors. These were categorised into high, medium, and low priority, represented by red, yellow, and green colour codes, respectively. High-priority households were scheduled for monthly visits, medium-priority households once every two months, and low-priority households once every six months. The tool was administered to all households in the village. Results: Among 332 households, 18.1% were classified as red, 45.8% as yellow, and 36.1% as green. Chronic conditions were more common among older adults, while the presence of young children or pregnancy often increased household priority. Larger family size and lower socioeconomic status were significantly associated with higher priority status. Notably, several high-priority households were not receiving the recommended frequency of health worker visits, indicating gaps in service delivery. Conclusion: The stratification tool was feasible to implement in this rural setting. By identifying households with greater health needs, it can support community health workers in optimising visit schedules and improving the efficiency and equity of home-based care.

Indexed as

Community health workersexploratory cross-sectional studyhousehold stratificationrisk stratification tool

Identifiers

PMID42483341
PMCPMC13387713

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