Factors associatedwith patient waiting time at a medical outpatient clinic: a case study of University of Nairobi health services
Background: Excessive long waiting time in outpatient clinics in Africa is a constant challenge for patients and the health providers of these facilities. Prolonged waiting times are associated with poor adherence to treatment, missed appointment and failure or delay in initiation of necessary treatment. The time a patient spends at each service point before being attended to by a health provider and the overall total time a patient spends in a health facility from the arrival time to the departure time is a major factor towards the perception of the patient towards the care received. Objective: To determine wait time and associated factors among outpatients attending senior staff clinic at University of Nairobi health services.Methodology: In this cross-sectional study, data collection was conducted on 384 outpatient over a period of four weeks using an interviewer administered pretested structured exit questionnaire with a time-tracking section. Simple random sampling was used to select respondents in a walk- in outpatient clinic set up. To analyse all data was cleaned then entered in the Statistical Package for Social Sciences (SPSS) 20. Analysis of variance (ANOVA), and cross tabulation was used to establish associations between the independent variable and dependent variables. Results: In total 384 patients were tracked and interviewed. The average patient waiting time was 55.3mins during the four week study period. Majority of the respondents waited in the clinic for 60 minutes to receive the services they had sought. The longest average patient waiting was 13.1 minutes at the doctor’s office. Most services sought for at the UHS are new consultations and specialised consultations. Whilst most respondents at 69% felt the time they had spent at the clinic was acceptable, many at 52% suggested that improving availability of staff at their stations will help in reducing Patient waiting time at UHS. In this study, gender (P=0.005) and availability of doctors (p=0.000) were found to affect patient waiting time. Conclusion: Identifying the area of delay and the actual mean waiting time at the clinic is the first step for UHS in implementing the needed changes in internal processes and practices at the clinic. Majority of the patients are spending an hour at the facility to be served. Most patients felt the overall time spent in the facility is acceptable but suggested that improving availability of health workers at their stations will reduce the patient waiting time and thus enhance service delivery to the university community.
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