Evidence map›Paper›PMID 40182326›Full record

ReviewCureus2025

Hospital Investment Decisions and Prioritization of Clinical Programs.

Bishan Nandy

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

1 author.

Bishan NandyHospital Administration, University of Illinois Hospital & Health Sciences System, Chicago, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Making investment decisions in hospitals and prioritizing clinical programs are crucial to ensure optimal healthcare delivery, responsible use of resources, and long-term sustainability of an organization. This review examines the existing literature to identify the key factors influencing investment decisions, evaluates evidence-based frameworks for prioritizing resources, and articulates challenges and future directions for healthcare organizations. Critical drivers of hospital investments include financial health, demographics, ownership structure, and technology adoption. However, program budgeting and marginal analysis, health technology assessment, multi-criteria decision analysis, and evidence-based design frameworks will ensure that decisions are systematic and transparent. These tools help hospitals balance infrastructure investments, technology, specialized clinical programs, and emergency response. The dependence on past allocation practices, funding constraints, and stakeholder misalignment inhibits the best decision-making. For those barriers to be addressed, predictive analytics and artificial intelligence must already be in the evaluation process, as should configuration processes for interrelated tech, and collaboration among stakeholders should be fostered. Furthermore, investments aligned with sustainability principles and equity goals will be more resilient and adaptive to changes in the healthcare landscape. This review highlights the importance of healthcare organizations implementing holistic, evidence-based frameworks to guide investment decisions, including low-hanging fruit from today and industry best practices for tomorrow, shifting a provider's focus to ensure optimal patient outcomes, operational efficiencies, and sustainable growth.

Indexed as

clinical program prioritizationdecision-making frameworksevidence-based frameworksfinancial constraintshealthcare 4.0 technologieshealthcare sustainabilityhealth technology assessmenthospital investmentpredictive analyticsresource allocation

Identifiers

PMID40182326
PMCPMC11965775

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.