1 Introduction

Maternal and neonatal care (MNC) is a core function of primary maternal health services, yet the way these services are experienced by patients in routine practice remains poorly documented. In Indonesia, MNC is largely delivered through public health centers (Puskesmas), where service quality is shaped not only by clinical content but also by care processes such as waiting time, service flow, and continuity of care. This study was conducted within the Empowerment Agency Training (EAT) component of the SPHERES project, which seeks to strengthen patient-centered service delivery by enhancing health worker agency in primary care settings. Using a non-participant observational time-and-motion approach, the study examines MNC visits from the patient’s perspective, capturing real-time patterns of waiting, care sequencing, movement, and interruptions from arrival to exit.The study aims to generate operationally relevant evidence to inform the design and implementation of EAT interventions.

2 Objective

To characterize patient-centered maternal and neonatal care (MNC) visits in real time using time-and-motion methods by quantifying time use, care flow, and visit fragmentation, and comparing patient journeys across MNC visit types in a public primary healthcare setting in Purbalingga.

3 Research Questions

How are maternal and neonatal care (MNC) visits structured and experienced by patients in real time within a Puskesmas setting?
How is patient time allocated between waiting and direct clinical care during MNC visits?
To what extent are MNC visits fragmented, as indicated by repeated waiting periods, patient movement, and service interruptions?
How do patient journeys, including time use, care flow, and fragmentation, vary across MNC visit types?

4 Working Hypotheses

A substantial share of MNC visit time is allocated to non-clinical activities, particularly waiting and administrative processes.
MNC visits are characterized by fragmented care, with multiple short clinical episodes interspersed with waiting and patient movement.
Earlier-stage ANC visits (K1 and K3) are longer and more fragmented than subsequent visits due to greater clinical and administrative demands.
Patient journeys vary in care flow and sequencing, even within the same facility and service unit.

5 Methods

5.1 Data Source

The primary data source is direct, non-participant observation of maternal and neonatal care (MNC) visits, conducted using a structured time-and-motion protocol. Observations were carried out at at six public health centers (Puskesmas) in Purbalingga: Bojong (6 January 2026), Kaligondang (7 January 2026), Bojongsari (8 Januari 2026), Serayu Larangan (13 January 2026), Purbalingga (14 January 2026) and Pengadegan (15 January 2026). with continuous recording of patient activities from arrival to exit.

5.2 Data Collection Tool

Data were collected using Toggl Track, a digital time-tracking application adapted for time-and-motion observation.

5.3 Variable and Operational Definitions

Table 1 presents the variables and operational definitions used in the analysis. The dataset captures patient journeys through facility context, visit characteristics, activity categories, spatial location, and time stamps, allowing precise measurement of time use. Activity durations were derived from start and end times with supplementary notes documenting contextual and system-related factors.

Table 1. Variables and operational definitions used in the analysis
Variable	Description	Categories / Values
phc_id	Identifier of the public health center in which the observation was conducted.	• Puskesmas Bojong • Puskesmas Kaligondang • Puskesmas Bojongsari • Puskesmas Serayu Larangan • Puskesmas Purbalingga • Puskesmas Pengadegan • Puskesmas Padamara • Puskesmas Karangtengah • Puskesmas Rembang • Puskesmas Karanganyar • Puskesmas Bobotsari
observation_date	Calendar date on which the patient shadowing observation took place.	• Calendar date (YYYY-MM-DD)
actor_type	Type of actor involved in the observed activity from the patient’s perspective.	• Midwife • Doctor • Internship Doctor • Dentist • Dental Assistant • Pharmacist • Nutritionist • Administrative staff • Laboratory staff • None (no active provider)
worker_id	Unique identifier assigned to each observed healthcare worker, encoded to reflect professional role.	• ADMxx Administrative staff • BDxx Midwife • NRxx Dental nurse • GZxx Nutritionist • DRxx Dentist • DRxx Doctor • APTxx Pharmacist • LABxx Laboratory personnel • Missing May be missing for activities without an identifiable provider
service_unit	Physical location or service area within the facility where the activity occurred.	• Registration desk • Maternal and Child Health clinic (KIA) • Laboratory • Waiting area • Corridor
patient_id	Identifier of the patient associated with the observed activity.	• Alphanumeric patient code (e.g., P01, P02)
visit_type	Type of antenatal care visit during which the observed activity occurred.	• ANC_K1_Murni • ANC_K1_Ulangan • ANC_K1 • ANC_K2 • ANC_K3 • ANC_K4 • ANC_K5 • ANC_K6 • PNC_KF2 • BAYI • BBL_KN3
activity_type	Coded label representing the primary activity experienced by the patient.	Activity type (definition and category mapping) • Registration → Pre-service initiation Initial administrative procedures to enroll or verify the patient’s visit. • Clinical examination → Clinical service Physical or clinical assessment conducted by a healthcare provider. • Counseling → Clinical service Individualized advice or guidance related to pregnancy, risk, or care planning. • Health education → Clinical service Structured delivery of maternal or pregnancy-related information to the patient. • Administrative procedures → Administration Documentation, record-keeping, or system-related tasks not involving direct clinical care. • Waiting / Idle → Waiting Inactive time while the patient awaits services, providers, or the next step in care. • Walking → Mobility Patient movement between locations within the facility. • Clinical or non-clinical interruption → Interruption Temporary disruptions to care flow due to clinical coordination, equipment malfunction, or personal matters.
activity_detail	Free-text description providing additional contextual information regarding the observed activity.	• Narrative description of activity context • May include reasons for waiting, delays, or interruptions
activity_category	Higher-level classification of activities based on patient engagement and functional role within the care journey.	Activity category (higher-level classification) • Pre-service initiation Activities required to initiate the MNC visit prior to the patient’s first clinical contact. • Clinical service Direct clinical or educational interactions contributing to assessment, decision-making, or health promotion. • Administration Non-clinical administrative tasks supporting service delivery, documentation, or system requirements. • Waiting Periods during which the patient is present in the facility but not actively engaged in care-related activities. • Mobility Physical movement of the patient within the facility between service points or service units. • Interruption Temporary disruptions to the flow of care due to clinical coordination needs or non-clinical factors.
start_time	Time stamp indicating the start of the observed activity.	• HH:MM:SS (24-hour clock)
end_time	Time stamp indicating the end of the observed activity.	• HH:MM:SS (24-hour clock)
duration_seconds	Computed duration of the activity, calculated as the difference between start and end times.	• Numeric value (seconds)
notes	Optional free-text field capturing additional observational notes.	• Optional contextual notes

5.4 Data Preparation and Cleaning

6 Results

6.1 Overview of Observed MNC Visit

Table 2 summarises the scope and characteristics of the observed maternal and neonatal care (MNC) visits. The analysis included 15 visits conducted across six public health centers, generating a total of 266 observed activity episodes. Visit types were unevenly distributed: ANC K5 visits accounted for the largest share of observations, while several visit categories were observed only once, indicating marked heterogeneity in service utilisation and visit composition across facilities. The results presented here are based on data collected up to January 2026. Data collection is ongoing and will continue until saturation is achieved.

Table 2. Overview of observed antenatal care visits
Section	Indicator	Value
Observation coverage	Number of public health centers	11
	Number of observation days	16
	Number of ANC visits observed	33
	Number of patients observed	33
	Total activity episodes	668
Visit type	ANC K1	1 (3%)
	ANC K1 Murni	4 (12.1%)
	ANC K1 Ulangan	2 (6.1%)
	ANC K2	2 (6.1%)
	ANC K3	5 (15.2%)
	ANC K4	4 (12.1%)
	ANC K5	7 (21.2%)
	ANC K6	4 (12.1%)
	BAYI	1 (3%)
	BBL KN3	1 (3%)
	PNC KF2	1 (3%)
	anc_k1_akses	1 (3%)
Visit duration	Median total visit duration (minutes, IQR)	57.8 (32.7–91.2)
Visit duration	Visit duration range (minutes)	13.2–142.8

6.2 Patient Time Use During MNC Visits

6.2.1 Total Visit Duration and Time Allocation

Figure 1 shows that Maternal and Neonatal Care (MNC) visits were heavily dominated by non-clinical activities across all visit types. Waiting accounted for approximately 50–80% of total visit time, while direct Clinical Care comprised only 15–40%, indicating that the vast majority of patient time was spent outside direct provider–patient interactions.

Time use and care flow varied by visit type. While early visits like ANC K1 Murni and ANC K6 exhibited substantial time devoted to Pre-service and administrative processes, later-stage or follow-up visits like ANC K5 and BBL KN3 were even more dominated by waiting. Although some visits appeared more streamlined, waiting remained the largest single component of the patient journey in every category.

Care fragmentation was evident across the entire continuum, with clinical care delivered in short episodes separated by repeated waiting, Mobility (patient movement), and administrative tasks. Overall, the figure highlights excessive waiting time and fragmented care flow as defining features of these MNC visits and key drivers of variation in patient experience across different visit types.

6.2.2 Task Distribution Across Actor Types

Figure 2 shows the distribution of observed working time across various actor types, highlighting how maternal and neonatal care is delivered. For most clinical providers, such as Doctors, Midwives, and Nutritionists, direct Clinical Care accounts for the vast majority of their working time, ranging from approximately 85% to 95%. However, a notable portion of time for other actors is diverted to non-clinical activities. For instance, Internship Doctors spend nearly 70% of their time in Waiting, while Administrative Staff dedicate over 40% of their time to Pre-Service tasks and over 50% to Waiting, significantly limiting their direct engagement in administrative processing.

Interactions with laboratory and pharmacy staff show different patterns of efficiency. Laboratory Staff spend approximately 65% of their time on Clinical Care, with the remainder divided between Waiting, Mobility, and Administration. Pharmacists also show a streamlined focus on Clinical Care (approximately 65%), though a significant 35% of their time is categorized as Interruption. Overall, the figure highlights that while primary clinical providers are highly focused on direct care, other supporting actors face substantial periods of waiting and non-clinical tasks, contributing to the fragmented nature of the overall patient experience.

6.3 Care Flow and Fragmentation of MNC Visits

Figure 3 presents representative shortest, median-length, and longest maternal and neonatal care (MNC) visits, illustrating patient time use, care sequencing, and visit fragmentation in Puskesmas settings. Across all visits, waiting and other non-clinical activities accounted for a substantial share of total visit time, consistently exceeding time spent in direct clinical care. Even the shortest visit showed multiple transitions between activities, while median- and longest-length visits were marked by repeated waiting periods interspersed with brief clinical and administrative episodes. This pattern indicates a fragmented and non-linear care process, with patients repeatedly re-entering queues during a single visit. Overall, the figure demonstrates considerable heterogeneity in patient journeys and highlights that MNC visits are dominated by non-clinical time and fragmented care delivery, reflecting variability in care flow rather than standardized service pathways.

6.4 Variation in Patient Journeys Across MNC Visit Types

6.4.1 Time Allocation Across Service Units by Visit Type

Figure 4 shows that, across all maternal and neonatal care (MNC) visit types, waiting constituted the largest proportion of total visit time, consistently exceeding time spent in direct clinical care. Health facilities such as Puskesmas Serayu Larangan exhibited the most extreme concentration of non-clinical time, where waiting accounted for approximately 90% of the total visit. While facilities like Puskesmas Purbalingga allocated a comparatively greater proportion of time to clinical care, substantial waiting persisted as the dominant component of the patient experience across all settings. Across the board, patient journeys were further fragmented by pre-service activities, administration, and mobility, indicating that most of the visit duration is spent outside direct provider–patient interactions.

6.5 Facility-Level and Patient-Level Variation

6.5.1 Differences Across Public Health Centers

Figure 5 demonstrates substantial between-facility variation in time allocation during maternal and neonatal care (MNC) visits. Across all public health centers, waiting consistently accounted for the largest share of visit time, exceeding direct clinical care, while administrative activities, patient movement, and interruptions varied markedly by facility. These differences indicate fragmented and non-linear care processes shaped by facility-level organization, underscoring heterogeneity in patient experiences of MNC even within the same district.

6.5.2 Within-Facility Variation in Care Experiences

Figure 6 illustrates substantial within-facility variation in time allocation across maternal and neonatal care (MNC) visit types, demonstrating that patient journeys differ not only between facilities but also within the same service setting. Across all facilities and visit types, waiting consistently accounted for a large share of total visit time, frequently exceeding time spent in direct clinical care.

Expert Shadowing Observation Report - Patients

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2026-03-27