Evidence map›Paper›PMID 36006293›Full record

ArticleTropical medicine and infectious disease2022

Factors Affecting the Transition from Paper to Digital Data Collection for Mobile Tuberculosis Active Case Finding in Low Internet Access Settings in Pakistan.

Christina Mergenthaler, Jake D Mathewson, Abdullah Latif, Hasan Tahir, Vincent Meurrens, Andreas van Werle, Aamna Rashid, Muhammad Tariq, Tanveer Ahmed, Farah Naureen and 1 more

Open access · goldAbstract read
In one paragraph

Article in Tropical medicine and infectious disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 28% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
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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

11 authors at 2 institutions in 2 countries.

Christina MergenthalerKIT Royal Tropical Institute Center for Applied Spatial Epidemiology, 1092 AD Amsterdam, The Netherlands.
Jake D MathewsonKIT Royal Tropical Institute Center for Applied Spatial Epidemiology, 1092 AD Amsterdam, The Netherlands.
Abdullah LatifNational Tuberculosis Program of Pakistan, (Common Management Unit-HIV, TB, Malaria, Ministry of NHSR&C, Government of Pakistan), F-Block, EPI Building, Prime Minister's Health Complex, Chak Shahzad, Islamabad 44000, Pakistan.
Hasan TahirMercy Corps Pakistan, 189/190, Street 6, 1-9/2 Islamabad, Islamabad 44000, Pakistan.
Vincent MeurrensEPCON, 2000 Antwerp, Belgium.
Andreas van WerleEPCON, 2000 Antwerp, Belgium.
Aamna RashidMercy Corps Pakistan, 189/190, Street 6, 1-9/2 Islamabad, Islamabad 44000, Pakistan.ORCID 0000-0001-7200-1211
Muhammad TariqMercy Corps Pakistan, 189/190, Street 6, 1-9/2 Islamabad, Islamabad 44000, Pakistan.
Tanveer AhmedNational Tuberculosis Program of Pakistan, (Common Management Unit-HIV, TB, Malaria, Ministry of NHSR&C, Government of Pakistan), F-Block, EPI Building, Prime Minister's Health Complex, Chak Shahzad, Islamabad 44000, Pakistan.
Farah NaureenMercy Corps Pakistan, 189/190, Street 6, 1-9/2 Islamabad, Islamabad 44000, Pakistan.
Ente RoodKIT Royal Tropical Institute Center for Applied Spatial Epidemiology, 1092 AD Amsterdam, The Netherlands.ORCID 0000-0001-8408-7702
Royal Tropical Institute · NLGovernment of Pakistan · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Between September 2020 and March 2021, Mercy Corps piloted hybrid digital (CAPI) and paper-based (PAPI) data collection as part of its tuberculosis (TB) active case finding strategy. Data were collected using CAPI and PAPI at 140 TB chest camps in low Internet access areas of Punjab and Khyber Pakhtunkhwa provinces in Pakistan. PAPI data collection was performed primarily during the camp and entered using a tailor-performed CAPI tool after camps. To assess the feasibility of this hybrid approach, quality of digital records were measured against the paper "gold standard", and user acceptance was evaluated through focus group discussions. Completeness of digital data varied by indicator, van screening team, and month of implementation: chest camp attendees and pulmonary TB cases showed the highest CAPI/PAPI completeness ratios (1.01 and 0.96 respectively), and among them, all forms of TB diagnosis and treatment initiation were lowest (0.63 and 0.64 respectively). Vans entering CAPI data with high levels of completeness generally did so for all indicators, and significant differences in mean indicator completeness rates between PAPI and CAPI were observed between vans. User feedback suggested that although the CAPI tool required practice to gain proficiency, the technology was appreciated and will be better perceived once double entry in CAPI and PAPI can transition to CAPI only. CAPI data collection enables data to be entered in a more timely fashion in low-Internet-access settings, which will enable more rapid, evidence-based program steering. The current system in which double data entry is conducted to ensure data quality is an added burden for staff with many activities. Transitioning to a fully digital data collection system for TB case finding in low-Internet-access settings requires substantial investments in M&E support, shifts in data reporting accountability, and technology to link records of patients who pass through separate data collection stages during chest camp events.

Indexed as

active case findingCAPIdata qualitydigital toolsPAPItuberculosis

Identifiers

PMID36006293
PMCPMC9415978
OpenAlexW4292575018

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.