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Introduction <p>Patients' waiting time is a critical indicator of healthcare efficiency and patient satisfaction. Health Management Information Systems (HMIS) are widely implemented to streamline hospital operations, yet evidence on their impact on waiting time is limited. Understanding the factors influencing delays in both HMIS and non-HMIS settings is essential for improving service delivery. This study aimed to compare factors affecting patients’ waiting time between two healthcare facilities, one with HMIS and one without, in Hyderabad.</p> Methodology <p>A cross-sectional study was conducted among 214 outpatients at two government healthcare facilities in Hyderabad (107 patients per hospital). Data were collected using a structured questionnaire that covered sociodemographic, hospital-visit-related, and system-related factors. Descriptive statistics, Chi-square tests, and binomial logistic regression were performed to identify factors associated with long waiting times (≥ 120&#xa0;min). Adjusted odds ratios (AOR) with 95% confidence intervals were reported to determine independent predictors.</p> Results <p>Long waiting time was reported by 40.2% of patients in the HMIS hospital and 23.4% in the non-HMIS hospital. In the overall model, HMIS presence (AOR = 2.05, 95% CI: 1.04–4.03), high patient load (AOR = 1.84, 95% CI: 1.03–3.46), and technological challenges (AOR = 1.93, 95% CI: 1.04–3.61) were significant predictors. Hospital-specific analyses revealed high patient load at the HMIS hospital and urban residence and limited staff at the non-HMIS hospital as key determinants.</p> Conclusion <p>HMIS implementation alone does not guarantee reduced waiting times; operational factors such as patient load, staff availability, and technological efficiency critically influence delays. Both digital and non-digital hospitals face unique challenges. Targeted interventions focusing on workflow optimization, staff training, and system reliability are essential to enhance patient flow and overall outpatient service efficiency.</p>

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Comparison of the factors influencing the patients’ waiting time between two healthcare facilities with and without health management information system in Hyderabad: a cross-sectional study

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  • 发表日期：

    2026年6月27日

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  • Bindiya C. Gowda,
  • Sachin J,
  • Sudha Bala,
  • Devidas P. Tondare

摘要

Introduction

Patients' waiting time is a critical indicator of healthcare efficiency and patient satisfaction. Health Management Information Systems (HMIS) are widely implemented to streamline hospital operations, yet evidence on their impact on waiting time is limited. Understanding the factors influencing delays in both HMIS and non-HMIS settings is essential for improving service delivery. This study aimed to compare factors affecting patients’ waiting time between two healthcare facilities, one with HMIS and one without, in Hyderabad.

Methodology

A cross-sectional study was conducted among 214 outpatients at two government healthcare facilities in Hyderabad (107 patients per hospital). Data were collected using a structured questionnaire that covered sociodemographic, hospital-visit-related, and system-related factors. Descriptive statistics, Chi-square tests, and binomial logistic regression were performed to identify factors associated with long waiting times (≥ 120 min). Adjusted odds ratios (AOR) with 95% confidence intervals were reported to determine independent predictors.

Results

Long waiting time was reported by 40.2% of patients in the HMIS hospital and 23.4% in the non-HMIS hospital. In the overall model, HMIS presence (AOR = 2.05, 95% CI: 1.04–4.03), high patient load (AOR = 1.84, 95% CI: 1.03–3.46), and technological challenges (AOR = 1.93, 95% CI: 1.04–3.61) were significant predictors. Hospital-specific analyses revealed high patient load at the HMIS hospital and urban residence and limited staff at the non-HMIS hospital as key determinants.

Conclusion

HMIS implementation alone does not guarantee reduced waiting times; operational factors such as patient load, staff availability, and technological efficiency critically influence delays. Both digital and non-digital hospitals face unique challenges. Targeted interventions focusing on workflow optimization, staff training, and system reliability are essential to enhance patient flow and overall outpatient service efficiency.