Modeling the impact of integrating HIV and outpatient health services on patient waiting times in an urban health clinic in Zambia

PLoS One. 2012;7(4):e35479. doi: 10.1371/journal.pone.0035479. Epub 2012 Apr 23.

Abstract

Background: Rapid scale up of HIV treatment programs in sub-Saharan Africa has refueled the long-standing health policy debate regarding the merits and drawbacks of vertical and integrated system. Recent pilots of integrating outpatient and HIV services have shown an improvement in some patient outcomes but deterioration in waiting times, which can lead to worse health outcomes in the long run.

Methods: A pilot intervention involving integration of outpatient and HIV services in an urban primary care facility in Lusaka, Zambia was studied. Data on waiting time of patients during two seven-day periods before and six months after the integration were collected using a time and motion study. Statistical tests were conducted to investigate whether the two observation periods differed in operational details such as staffing, patient arrival rates, mix of patients etc. A discrete event simulation model was constructed to facilitate a fair comparison of waiting times before and after integration. The simulation model was also used to develop alternative configurations of integration and to estimate the resulting waiting times.

Results: Comparison of raw data showed that waiting times increased by 32% and 36% after integration for OPD and ART patients respectively (p<0.01). Using simulation modeling, we found that a large portion of this increase could be explained by changes in operational conditions before and after integration such as reduced staff availability (p<0.01) and longer breaks between consecutive patients (p<0.05). Controlling for these differences, integration of services, per se, would have resulted in a significant decrease in waiting times for OPD and a moderate decrease for HIV services.

Conclusions: Integrating health services has the potential of reducing waiting times due to more efficient use of resources. However, one needs to ensure that other operational factors such as staff availability are not adversely affected due to integration.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Computer Simulation
  • HIV Infections / epidemiology
  • HIV Infections / therapy*
  • Hospitals, Urban / organization & administration*
  • Humans
  • Models, Statistical
  • Patient Care* / methods
  • Time Factors
  • Urban Health
  • Zambia / epidemiology