Efficacy of Interactive Voice Response (IVR) Systems in Multiple Languages for Disease Reporting

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Dr Raj Kumar Deshmukh

Lecturer

ORCID -Id- https://orcid.org/0009-0003-2497-2031

Abstract— Rapid, complete, and accurate disease reporting is foundational to public health surveillance, particularly in settings with linguistic diversity and variable literacy. Interactive Voice Response (IVR) systems offer a low-cost, device-agnostic channel for real-time reporting from frontline workers and communities, yet the comparative effectiveness of multilingual IVR versus single-language IVR remains underexplored. This manuscript evaluates the efficacy of a multilingual IVR intervention for notifiable disease reporting using a controlled before–after design across matched districts. We examine reporting rate, timeliness, data completeness, positive predictive value (PPV) of alerts, and cost per valid report. The intervention consisted of a DTMF-based IVR menu with professionally recorded prompts available in seven languages, automatic call-back for dropped calls, speech rate controls, and role-based branching logic. Over a 12-month period (6-month baseline; 6-month intervention), 164 facilities and community reporters (N≈2,480 active reporters) generated 48,326 reportable events. Multilevel difference-in-differences models, adjusted for clustering and seasonal trends, indicated that multilingual IVR increased the reporting rate per 100 suspected cases by 13 percentage points (pp) (95% CI: 8–18; p<.001), reduced median reporting delay by 13 hours (95% CI: −18 to −8; p<.001), improved field completeness by 10 pp (95% CI: 4–16; p=.002), and raised PPV by 5 pp (95% CI: 1–9; p=.03) compared with single-language IVR controls. Cost per valid report decreased by US$0.70 (95% CI: −1.26 to −0.14; p=.02). Qualitative debriefs attributed gains to language choice at call start, reduced cognitive load, and greater confidence among lower-literacy reporters. Findings suggest that multilingual IVR meaningfully enhances surveillance performance metrics and equity of participation, particularly in linguistically heterogeneous regions. Public health programs planning digital surveillance scale-up should prioritize multilingual voice channels alongside standards-based data integration and inclusive human-centered design.

Keywords

Interactive Voice Response, Multilingual Systems, Disease Surveillance, Public Health Reporting, mHealth, Equity, Timeliness, Completeness, Usability, Low-Resource Settings

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