Evidence map›Paper›PMID 42622045›Full record

ArticleCureus2026

A Guide to Developing a Neurosurgery Quality Dashboard From Scratch: A Technical Report.

Arshad Ali, Chithra Joseph

Abstract read
In one paragraph

Article in Cureus, 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

2 authors.

Arshad AliDepartment of Clinical Academic Sciences, Qatar University, Doha, QAT.
Chithra JosephDepartment of Nursing, Hamad Medical Corporation, Doha, QAT.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measurement is the foundation of quality improvement, yet many neurosurgical departments, particularly those early in their quality journey or with limited informatics resources, lack a structured way to track their performance. Most published neurosurgery dashboards originate from well-resourced academic centers, rely on electronic medical records or business intelligence platforms, and are described only after they have matured. We report the design and implementation, from first principles, of a manually maintained neurosurgery quality dashboard at the Neuroscience Institute, Hamad Medical Corporation, Doha, Qatar, during 2021, at the height of the COVID-19 pandemic. The dashboard was organized into eight quality bundles (Volume, Timely Discharge, Throughput, Service, Clinical Care, Patient Satisfaction, Infection Control, and Patient Safety), each defined in advance by its component indicators, numerator and denominator, data source, and sampling frame. A multidisciplinary team was formed; each bundle was assigned a named frontline owner and a backup; data were collected on standardized spreadsheets, compiled monthly into charts, and reviewed by the team to guide action. We present one year of data as a worked illustration. The dashboard surfaced several actionable signals, including a low rate of discharge before noon, most often attributed to delayed physician orders; episodic transfer-out delays; suboptimal glycemic control; higher physician-domain satisfaction scores in the second half of the year than in the first; consistently high hand-hygiene compliance with no device-related infections; and a low absolute burden of safety events. These observations are descriptive and uncontrolled, were not statistically tested, and are presented to illustrate the dashboard rather than to establish cause or effect. The experience shows that a functional, action-oriented neurosurgery dashboard can be built without advanced informatics when its metrics are clearly defined, its responsibilities are assigned, and its review is disciplined. We offer the eight-bundle structure as a template for departments beginning a quality program, including in resource-limited settings.

Indexed as

care bundlesneurosurgerypatient safetyperformance metricsquality dashboardquality improvementresource-limited setting

Identifiers

PMID42622045
PMCPMC13489548

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LicenceCC BY
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Registered trials

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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.