Where does healthcare worker time go? Evidence from a time-and-motion study in Malawi

A 2024 time-and-motion study in Malawi reveals that healthcare workers spend less time than contracted and only about half their working hours on direct patient care, highlighting significant opportunities to improve workforce utilization while underscoring the urgent need for sustained investment to address critical staffing shortages.

The Gist

Imagine the healthcare system in Malawi as a massive, bustling kitchen in a busy restaurant. The chefs (healthcare workers) are the most valuable resource, but the restaurant is often short-staffed and the customers (patients) are pouring in faster than expected. The big question for the owners (policymakers) is: "Where does the time of our chefs actually go?"

To answer this, the researchers didn't just ask the chefs to guess; they sent in "time-and-motion" observers who acted like invisible cameras, watching exactly what the chefs did minute-by-minute for several months in 2024. Here is what they found, translated into everyday terms:

1. The "Clock-In" Reality vs. The Contract

The chefs are hired to work a full shift, roughly 9 hours a day. However, the study found that on average, they were actually working about 7.35 hours (including their breaks).

• The Analogy: It's like signing up for a 9-hour shift at a job, but you only end up working about 7 and a half hours. There is a "gap" of about 1.5 hours every day where the contract says they should be working, but they aren't.

2. The "Customer Service" vs. The "Waiting Room"

Of the time the chefs were working, they spent the most time actually cooking and serving customers (direct patient care). This took up about 48% of their day.

• The Good News: They are spending nearly half their time helping people.
• The Bad News: There was a surprisingly large chunk of time—about 12% of the day—that was "Unallocated."
• The Analogy: This is the time a chef spends standing at the stove with an empty pan, waiting for an order to come in. The study found that 71% of this "waiting time" was simply because there were no patients in the room. It wasn't that the chefs were slacking off; they were just idle because the "dining room" was empty at that moment.

3. The "Speed of Service"

The restaurant is incredibly busy. On average, a healthcare worker sees 21 patients a day in outpatient clinics (like a walk-in doctor's office).

• The Problem: Because there are so many people, the time spent with each person is very short. The median time per patient was only 3 minutes.
• The Analogy: Imagine a fast-food line where you have to order, pay, and get your food in 3 minutes. The study notes that official guidelines suggest a consultation should take at least 10 minutes to be done properly. The chefs are rushing through the line because the line is too long.

4. It's Not the Same for Everyone

Just like a restaurant has different stations (grill, salad bar, dessert), the healthcare system has different types of workers and places.

• Different Roles: Some workers (like dentists or radiologists) spent more time per patient, while others (like pharmacists) spent less.
• Different Locations: Workers in city hospitals (Tertiary) spent more time per patient than those in rural clinics. Interestingly, workers in faith-based hospitals (CHAM) spent more time per patient than those in government hospitals.
• The "Weekend" Surprise: On weekends and holidays, the outpatient clinics actually saw more patients per worker than on normal days, even though the workers were there for the same amount of time.

5. The Two Big Takeaways

The study concludes with two main observations about how to fix the kitchen:

1. Better Scheduling: Since there is a lot of "waiting time" (unallocated time) when no patients are present, the system could potentially be more efficient. If patients were spread out more evenly throughout the day (like better appointment scheduling), the chefs could spend that "waiting time" actually helping more people, rather than standing around with empty pans.
2. More Chefs Needed: Even with better scheduling, the line is still too long. The study emphasizes that the current staff is stretched too thin. To give every patient the proper 10 minutes of care they need, the restaurant needs to hire more chefs (expand the workforce) and invest more money in the kitchen.

What the Study Did NOT Say

It is important to note what this study didn't do:

• It didn't test new medical treatments or drugs.
• It didn't say that the current care is "bad" or "wrong," just that the time spent is very short due to high demand.
• It didn't claim that the workers are lazy; in fact, it showed they are often waiting for patients to arrive.

In summary: The healthcare workers in Malawi are working hard, but they are often waiting for patients to show up, and when patients do show up, there are so many of them that the workers can only spend a few minutes with each one. To fix this, the system needs to organize the flow of patients better and, most importantly, hire more staff to handle the crowd.

Technical Summary

Technical Summary: "Where does healthcare worker time go? Evidence from a time-and-motion study in Malawi"

Problem Statement
Low- and middle-income countries (LMICs) face critical shortages of healthcare workers (HCWs) and funding for human resources for health (HRH), often resulting in patients receiving less care time than anticipated. While understanding workforce capacity is essential for improving health system performance, existing evidence in Malawi and similar settings is fragmented. Previous time-and-motion studies (TMS) have typically focused on single cadres (e.g., only doctors or community health workers), limited facility types, or specific disease programs. Furthermore, there is a lack of comprehensive data on "unallocated time"—periods when staff are present but not engaged in direct care, administration, or breaks. Reliance on self-reported data in prior studies has also introduced biases such as recall error and social desirability bias. This study addresses the evidence gap regarding how the existing workforce capacity is utilized across the broader health system.

Methodology
The authors conducted a comprehensive, system-wide time-and-motion study in Malawi between January and May 2024.

• Sampling: The study utilized a stratified random sampling approach based on the 2023 Master Health Facility Register. Facilities were stratified by ownership (Government vs. Christian Health Association of Malawi [CHAM]), location (rural/urban), and catchment population size. The final sample included 27 facilities across all levels of care: 5 tertiary hospitals, 3 district hospitals, 10 community/rural hospitals, and 9 health centres.
• Data Collection: Trained enumerators with clinical backgrounds observed at least 6 HCWs per facility (oversampling for doctors in smaller facilities) for 3 consecutive day shifts or one night shift. Observations were unannounced to minimize the Hawthorne effect. Data were recorded using KoboToolbox, capturing activity labels, start/end times (to the nearest minute), service areas, and patient health conditions.
• Scope: The study covered multiple cadres (Clinical, Nursing/Midwifery, Laboratory, Pharmacy, Dental, Radiography, etc.) and service areas (Outpatient, Inpatient, Emergency).
• Data Processing: A rigorous curation workflow was implemented to correct inconsistencies, standardize cadre definitions, and handle time anomalies. Specifically, 1-minute gaps between activities were evenly allocated (30 seconds to each adjacent activity), and 0-minute activities were adjusted to a 20-second duration to prevent underestimation of time.
• Analysis: Descriptive statistics (median and interquartile range) were calculated for total working time, time allocation (Patient-facing, Administrative, Break, Unallocated), patient load, and time per patient. Subgroup analyses were conducted across cadres, facility types, ownership, regions, and service areas using pairwise Mood's median tests.

Key Contributions

• System-Wide Evidence: This study provides the first holistic, multi-cadre picture of HCW time use in a low-income setting, covering all levels of care and diverse facility types.
• Granular Activity Classification: The study distinguishes between direct patient care, administrative tasks, breaks, and "unallocated time" (time not related to work or breaks, often due to patient absence), offering a more nuanced view of workforce utilization than previous studies.
• Methodological Rigor: The paper details a systematic approach to handling high-frequency data artifacts (e.g., 1-minute gaps and 0-minute activities) common in time-motion studies, providing a template for future research in resource-constrained settings.
• Empirical Baseline: It establishes a baseline for HCW time allocation and patient load metrics in Malawi, which can inform health system planning and modeling.

Key Results

• Working Time: The median daily working time (including breaks) was 7.35 hours, approximately 1.65 hours below the typical contracted schedule of 9 hours.
• Time Allocation:
  • Direct Patient Care: Occupied the majority of time, with a median of 2.82 hours per day (48% of total working time).
  • Breaks: Median 1.25 hours (18%), consistent with contracted expectations.
  • Administrative Tasks: Median 0.30 hours (5.2%).
  • Unallocated Time: Median 0.72 hours (12%). Analysis of field notes indicated that 71% of this time was due to the absence of patients or waiting for patients to arrive.
• Patient Load and Service Time:
  • Outpatient: Median 21 patients per staff member per day; median time per patient was 3 minutes.
  • Inpatient: Median 12 patients per day; median time per patient was 6 minutes.
  • Emergency: Median 14 patients per day; median time per patient was 10 minutes.
• Variability: Significant variations were observed across subgroups. For instance, Clinical cadres spent a higher proportion of time on patient care than Nursing/Midwifery cadres. Government facilities saw higher patient loads than CHAM facilities. Time per patient varied significantly by service area, with surgical and emergency care requiring more time than general outpatient consultations.

Significance and Claims
The paper claims to offer a first system-wide empirical picture of HCW time use in a low-income setting, which is critical for evidence-based workforce planning. The authors argue that the findings highlight two distinct areas for intervention:

1. Efficiency Gains: The gap between contracted and actual working time, combined with significant "unallocated time" (often due to patient absence), suggests scope to improve workforce utilization. Better organization of patient appointments could potentially increase time per patient and service delivery quality without immediate workforce expansion.
2. Capacity Constraints: Despite potential efficiency gains, the high patient loads and very short service times per patient (particularly in outpatient settings, where median time was 3 minutes) indicate that sustained investment in human resources for health and workforce expansion remains essential to meet demand.

The study concludes that while optimizing the use of existing capacity is necessary, it is insufficient on its own to address the systemic pressures of high demand and limited resources in Malawi. The authors emphasize that their findings should inform health systems planning and modeling to better align workforce time use with service delivery needs.