Evidence map›Paper›PMID 28658432›Full record

ArticleClinics (Sao Paulo, Brazil)2017

Predictors of micro-costing components in liver transplantation.

Luciana Bertocco de Paiva Haddad, Liliana Ducatti, Luana Regina Baratelli Carelli Mendes, Wellington Andraus, Luiz Augusto Carneiro D'Albuquerque

Abstract readComparative Study
In one paragraph

Article in Clinics (Sao Paulo, Brazil), 2017. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
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

5 authors.

Luciana Bertocco de Paiva HaddadDivisao de Transplante de Figado e Orgaos do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Universidade de São Paulo, Sao Paulo, SP, BR.
Liliana DucattiDivisao de Transplante de Figado e Orgaos do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Universidade de São Paulo, Sao Paulo, SP, BR.
Luana Regina Baratelli Carelli MendesDivisao de Transplante de Figado e Orgaos do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Universidade de São Paulo, Sao Paulo, SP, BR.
Wellington AndrausDivisao de Transplante de Figado e Orgaos do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Universidade de São Paulo, Sao Paulo, SP, BR.
Luiz Augusto Carneiro D'AlbuquerqueDivisao de Transplante de Figado e Orgaos do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Universidade de São Paulo, Sao Paulo, SP, BR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectives: Although liver transplantation procedures are common and highly expensive, their cost structure is still poorly understood. This study aimed to develop models of micro-costs among patients undergoing liver transplantation procedures while comparing the role of individual clinical predictors using tree regression models.

methods: We prospectively collected micro-cost data from patients undergoing liver transplantation in a tertiary academic center. Data collection was conducted using an Intranet registry integrated into the institution's database for the storing of financial and clinical data for transplantation cases.

results: A total of 278 patients were included and accounted for 300 procedures. When evaluating specific costs for the operating room, intensive care unit and ward, we found that in all of the sectors but the ward, human resources were responsible for the highest costs. High cost supplies were important drivers for the operating room, whereas drugs were among the top four drivers for all sectors. When evaluating the predictors of total cost, a MELD score greater than 30 was the most important predictor of high cost, followed by a Donor Risk Index greater than 1.8.

conclusion: By focusing on the highest cost drivers and predictors, hospitals can initiate programs to reduce cost while maintaining high quality care standards.

Indexed as

Costs and Cost AnalysisFemaleHospital CostsHumansLiver TransplantationMaleMiddle AgedProspective StudiesRisk Assessment

Identifiers

PMID28658432
PMCPMC5463250

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.