Evidence map›Paper›PMID 40230393›Full record

ArticleOxford open digital health2024

Developing and refining the COVID-19 to Routine Immunization Information System Transferability Assessment (CRIISTA) tool: a decision support tool to leverage COVID-19 immunization information system investments for routine immunization.

Nami Kawakyu, Allison Osterman, Jimi Michel, Dominic Mutai, Edith Jepleting, Grace Njenga, Parysa Oskouipour, Jessica C Shearer

Abstract read
In one paragraph

Article in Oxford open digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

8 authors.

Nami KawakyuMOMENTUM Routine Immunization Transformation and Equity, PATH, 2201 Westlake Avenue, Seattle, WA 98121, USA.
Allison OstermanMOMENTUM Routine Immunization Transformation and Equity, PATH, 2201 Westlake Avenue, Seattle, WA 98121, USA.
Jimi MichelMOMENTUM Routine Immunization Transformation and Equity, John Snow Inc, 44 Farnsworth St, Boston, MA 02210, USA.
Dominic MutaiLiving Labs, PATH, ACS Plaza, 4th floor. Lenana Road, Nairobi, Kenya.
Edith JepletingLiving Labs, PATH, ACS Plaza, 4th floor. Lenana Road, Nairobi, Kenya.
Grace NjengaLiving Labs, PATH, ACS Plaza, 4th floor. Lenana Road, Nairobi, Kenya.
Parysa OskouipourMOMENTUM Routine Immunization Transformation and Equity, John Snow Inc, 44 Farnsworth St, Boston, MA 02210, USA.
Jessica C ShearerMOMENTUM Routine Immunization Transformation and Equity, PATH, Washington, DC, USA.ORCID https://orcid.org/0000-0003-1025-5739

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To achieve the Immunization Agenda 2030 vaccine equity vision of a world where everyone everywhere benefits from vaccines, it is essential to invest in immunization information systems that can support the identification, reach and monitoring of zero-dose and under-immunized children. The rapid nature of COVID-19 vaccine introduction led to the investment of new systems to collect, manage and use immunization data. While many digital health assessment tools exist, there is an absence of tools to support decision-makers to systematically assess the suitability of transferring an immunization information system from one health context to another. To address this gap, the COVID-19 to Routine Immunization Information System Transferability Assessment tool was developed, informed by literature review, expert consultation and usability testing. The tool is organized into five thematic areas: context, functionality, technology, users and resources. Each thematic area has questions about the COVID-19 immunization information system, the current and desired state of the routine immunization information system and the gaps between them. Suitability scores are then calculated to assess whether a COVID-19 immunization information system is suitable for routine immunization so governments can leverage these investments to strengthen routine immunization programs and the broader health information ecosystem. Abrégé Pour réaliser la vision du Programme pour la vaccination à l'horizon 2030 concernant l'équité vaccinale d'un monde où tout le monde, partout, bénéficie des vaccins, il est essentiel d'investir dans des systèmes d'information sur la vaccination capables d'appuyer l'identification, l'accès et le suivi des enfants zéro dose et insuffisamment vaccinés. La nature rapide de l'introduction du vaccin contre la COVID-19 a entraîné l'investissement dans de nouveaux systèmes de collecte, de gestion et d'utilisation des données sur la vaccination. Bien que de nombreux outils numériques d'évaluation de la santé existent, on ne dispose d'aucun outil pour aider les décideurs à évaluer systématiquement la pertinence du transfert d'un système d'information sur la vaccination d'un contexte de santé à un autre. Pour combler cette lacune, l'outil d'évaluation de la transférabilité de la COVID-19 au système d'information sur la vaccination de routine a été élaboré, éclairé par un examen documentaire, des consultations d'experts et des tests bêta. Cet outil s'articule autour de cinq domaines thématiques: contexte, fonctionnalité, technologie, utilisateurs et ressources. Chaque domaine thématique comprend des questions sur le système d'information sur la vaccination contre la COVID-19, l'état actuel et souhaité du système d'information sur la vaccination de routine et les écarts entre eux. Les scores de pertinence sont ensuite calculés pour évaluer si un système d'information sur la vaccination contre la COVID-19 convient à la vaccination de routine afin que les pouvoirs publics puissent tirer parti de ces investissements pour renforcer les programmes de vaccination de routine et l'écosystème de l'information sur la santé dans son ensemble. Resumen Para lograr la visión de la Agenda de Inmunización 2030 de un mundo donde todas las personas de todas partes se beneficien de las vacunas, es esencial invertir en sistemas de información sobre vacunación que puedan apoyar la identificación, el alcance y el monitoreo de niños con dosis cero y subvacunados. La rápida introducción de la vacuna COVID-19 condujo a la inversión en nuevos sistemas para recopilar, administrar y utilizar datos sobre vacunación. Si bien existen muchas herramientas digitales de evaluación de la salud, faltan instrumentos para ayudar a los responsables de la toma de decisiones a evaluar sistemáticamente la idoneidad de transferir un sistema de información sobre vacunación de un contexto sanitario a otro. Para corregir esta deficiencia, se creó el Marco de evaluación de la transferibilidad del sistema de información sobre la vacunación contra la COVID-19 a la vacunación sistemática (CRIISTA), sobre la base de la revisión de literatura, consultas a expertos y pruebas beta. El Marco está organizado en cinco áreas temáticas: contexto, funcionalidad, tecnología, usuarios y recursos. Cada área temática contiene preguntas referidas al sistema de información sobre la vacunación contra la COVID-19, el estado actual del sistema de información sobre la vacunación sistemática y su estado deseado, y las brechas entre ellos. Seguidamente, se calculan las puntuaciones de idoneidad para evaluar si un sistema de información sobre la vacunación contra la COVID-19 es adecuado para la vacunación sistemática, de modo que los Gobiernos puedan aprovechar estas inversiones para fortalecer los programas de vacunación sistemática y el sistema más amplio de información sanitaria.

Indexed as

COVID-19decision support tooldigital healthhealth information systemroutine immunizationscale-up

Identifiers

PMID40230393
PMCPMC11936324

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.