Evaluation of National Injury Surveillance Centre, India, 2015-16
Background: Globally, injuries accounts for 9% of all deaths, but India account for 11%. Due to limited data on injury characteristics, National Injury Surveillance Centre (NISC) was established in 2014 in New Delhi. Aim & Objectives: To evaluate attributes of NISC and make evidence-based recomm...
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Published in | Indian journal of community health Vol. 32; no. 1; pp. 51 - 56 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
01.01.2020
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Online Access | Get full text |
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Summary: | Background: Globally, injuries accounts for 9% of all deaths, but India account for 11%. Due to limited data on injury characteristics, National Injury Surveillance Centre (NISC) was established in 2014 in New Delhi. Aim & Objectives: To evaluate attributes of NISC and make evidence-based recommendations. Methods and Material: We conducted cross-sectional study and used US Centers for Disease Control and Prevention guidelines to assess simplicity, flexibility, acceptability, stability, timeliness, representativeness, usefulness, and data quality. We reviewed 2015 records and interviewed 20 key-informants. We used Epi-Info7 for analysis. Results: NISC captured 4043 injuries in 2015 from one hospital. Among five data entry operators, four reported lengthy format, but all reported it easy. Among ten relevant key-informants, all reported data-management software easy. System demonstrated flexibility in three variables. All 20 staff reported willingness to participate, and 90% felt quarterly reporting acceptable. Regarding stability, data was collected for 361/365 days. Quarterly reports were available but only submitted annually. Regarding usefulness, all WHO-recommended variables included. Regarding data quality, 17% data-fields were missing. Conclusion: NISC is simple, flexible, stable, acceptable and potentially useful based on data captured. Timeliness based on annual reporting is high, can be improved to quarterly. We recommend training to improve data quality and integration of additional hospitals to improve representativeness. |
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ISSN: | 0971-7587 2248-9509 |
DOI: | 10.47203/IJCH.2020.v32i01.011 |