Evidence map›Paper›PMID 42170403›Full record

ArticlePakistan journal of medical sciences2026

Time-Motion Analysis of Patient Flow in a Family Medicine Department of a Tertiary Care Hospital in Lahore.

Humayon Khalid Saeed, Osama Tahir, Aqsa Mairaj

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Humayon Khalid SaeedHumayon Khalid Saeed, MBBS, MBA, MCPS, MRCP1. Head of Clinical Operations, Indus Hospital and Health Network, Lahore, Pakistan.
Osama TahirOsama Tahir, BS Software Engineering. Deputy Manager - Applications, IT Department, Indus Hospital and Health Network, Lahore, Pakistan.
Aqsa MairajAqsa Mairaj Assistant Manager Clinical Operations, Indus Hospital and Health Network, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This Time-Motion study used a structured approach to analyze patient flow through the Family Medicine Department, to improve efficiency in healthcare delivery by identifying bottlenecks and opportunities for improving workflow. Methodology: This was a cross-sectional time-motion study and data for six-day-period between 08:00 A.M. to 05:00 P.M. was obtained from the Hospital Management Information System (HMIS) of Indus Hospital and Health Network, Lahore, that automatically records time stamps for key patient flow events (registration, consultation, investigation, and discharge) as part of routine clinical operations. Electronic time stamps were generated from HMIS. 2,762 patient journeys were included, each representing one complete patient visit to the Family Medicine Department during study period. Result: It was found that the average time in doctor's chamber was approximately eight minutes (reasonable for quality consultation), yet subsequent processes like, recording vital signs, phlebotomy, ultrasonography etc, generated significant delays. Doctor-to-ultrasound pathway showed highest average time of 167.5 minutes. This study revealed that non-clinical and post-consultation processes consume a disproportionate share of patient time, overshadowing direct clinical encounters. Bottlenecks were linked to infrastructure and process design constraints. Conclusion: The study identifies significant time delays in diagnostic and pharmacy processes. The findings suggest system-level reforms particularly in increasing diagnostic capacities to optimize workflow.

Indexed as

Family MedicinePatient JourneyTertiary Care HospitalTime-MotionWorkflow Analysis

Identifiers

PMID42170403
PMCPMC13188623

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.