Operational characteristics of antiretroviral therapy clinics in Zambia: a time and motion analysis

Abstract

Background: The mass scale-up of antiretroviral therapy (ART) in Zambia has taken place in the context of limited infrastructure and human resources resulting in many operational side-effects. In this study, we aimed to empirically measure current workload of ART clinic staff and patient wait times and service utilization.

Methods: We conducted time and motion (TAM) studies from both the healthcare worker (HCW) and patient perspectives at 10 ART clinics throughout Zambia. Trained personnel recorded times for consecutive discrete activities based on direct observation of clinical and non-clinical activities performed by counselors, clinical officers, nurses, and pharmacy technicians. For patient TAM, we recruited consenting patients and recorded times of arrival and departure and major ART services utilized. Data from 10 clinics were pooled to evaluate median time per patient spent for each activity and patient duration of stay in the clinic.

Results: The percentage of observed clinical time for direct patient interaction (median time per patient encounter) was 43.1% for ART counselors (4 min, interquartile range [IQR] 2-7), 46.1% for nurses (3 min, IQR 2-4), 57.2% for pharmacy technicians (2 min, IQR 1-2), and 78.5% for clinical officers (3 min, IQR 2-5). Patient workloads for HCWs were heaviest between 8 AM and 12 PM with few clinical activities observed after 2 PM. The length of patient visits was inversely associated with arrival time - patients arriving prior to 8 AM spent 61% longer at the clinic than those arriving after 8 AM (277 vs. 171 min). Overall, patients spent 219 min on average for non-clinical visits, and 244 min for clinical visits, but this difference was not significant in rural clinics. In comparison, total time patients spent directly with clinic staff were 9 and 12 min on average for non-clinical and clinical visits.

Conclusion: Current Zambian ART clinic operations include substantial inefficiencies for both patients and HCWs, with workloads heavily concentrated in the first few hours of clinic opening, limiting HCW and patient interaction time. Use of a differentiated care model may help to redistribute workloads during operational hours and prevent backlogs of patients waiting for hours before clinic opening, which may substantially improve ART delivery in the Zambian context.

Keywords: Allocation of resources; Antiretroviral therapy care evaluation; Antiretroviral therapy program monitoring; Program efficiency; Time and motion studies; Workload.

Fig. 1

Observed Hours Worked at ART Clinic by Staff. Histogram of four key ART clinic staff showing frequency of observed hours worked at ART clinic. Out of 104 observed staff members, 92 were observed at the ART clinic for fewer than five hours on TAM day and 12 were observed at the clinic for 5+ hours

Fig. 2

Clinic Staff Daily Time Distribution. Clinic staff activities were classified into three groups for the four staff categories. Direct patient interaction includes any activity involving one-to-one interaction between a patient and staff member, administrative work involves activities such as searching for files and updating patient registers, and activities such as chatting or taking a break were included under the “Other” category. Average time (in minutes) spent on each type of activity were graphed for each hour to show the distribution of activities throughout a work day. Times do not necessarily add up to 60 min as the numbers presented represent averages over all staff (some of whom did not contribute time in each time window presented). For all four categories, direct patient interaction is skewed right and peaks from 9 to 10 AM. There is no obvious trend for the administrative and other categories among the four staff categories

Fig. 3

Patient Arrival and Congestion. a Bar graph showing a negative relationship between patient arrival time and the average duration of their clinic visit, superimposed with a line graph showing the number of patients arriving at the clinic within each half-hour block. Patient arrival peaks at 6:30 AM at urban clinics and 6 AM at rural clinics, with a sharp and steady decline in arrival after 7 AM in urban clinics and 8:30 AM in rural clinics. Patients arriving earlier in the day stayed at the clinic longer, on average, than patients arriving later in the day, creating a backlog of patients for clinical staff to see early in the morning. b Utilizing data from a recent CHAI study on patient wait times at Zambian ART clinics, we estimated how much of a patient’s time at the clinic is spent waiting versus receiving care. [6] Assuming that patients are seen on a first-come-first-serve basis, we found that patients arriving prior to clinic opening (before 8 AM) spend a majority of their time waiting for their files to be found and to be called into triage