Evidence map›Paper›PMID 23329430›Full record

SynthesisPharmacoEconomics2013

Acknowledging patient heterogeneity in economic evaluation : a systematic literature review.

Janneke P C Grutters, Mark Sculpher, Andrew H Briggs, Johan L Severens, Math J Candel, James E Stahl, Dirk De Ruysscher, Albert Boer, Bram L T Ramaekers, Manuela A Joore

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in PharmacoEconomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
–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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Preferences for health-related quality of life: do they vary by age? A systematic literature review on the EQ-5D measure.The European journal of health economics : HEPAC : health economics in prevention and care · 2025
    Pooled it
  2. Pooled it
  3. Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration.The European journal of health economics : HEPAC : health economics in prevention and care · 2019
    Trial
  4. Article
  5. Review
  6. Review
  7. Article
  8. Machine Learning and Health Science Research: Tutorial.Journal of medical Internet research · 2024
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Direct Medical Costs of Advanced Breast Cancer Treatment: A Real-World Study in the Southeast of The Netherlands.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2021
    Article
  15. Article
  16. Patient Variability Seldom Assessed in Cost-effectiveness Studies.Medical decision making : an international journal of the Society for Medical Decision Making · 2018
    Review
  17. Review
  18. Should Countries Set an Explicit Health Benefits Package? The Case of the English National Health Service.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2017
    Article
  19. Article
  20. 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

10 authors.

Janneke P C GruttersDepartment for Health Evidence, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500, Nijmegen, The Netherlands. J.Grutters@ebh.umcn.nl
Mark Sculpher
Andrew H Briggs
Johan L Severens
Math J Candel
James E Stahl
Dirk De Ruysscher
Albert Boer
Bram L T Ramaekers
Manuela A Joore

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivePatient heterogeneity is the part of variability that can be explained by certain patient characteristics (e.g. age, disease stage). Population reimbursement decisions that acknowledge patient heterogeneity could potentially save money and increase population health. To date, however, economic evaluations pay only limited attention to patient heterogeneity. The objective of the present paper is to provide a comprehensive overview of the current knowledge regarding patient heterogeneity within economic evaluation of healthcare programmes.

methodsA systematic literature review was performed to identify methodological papers on the topic of patient heterogeneity in economic evaluation. Data were obtained using a keyword search of the PubMed database and manual searches. Handbooks were also included. Relevant data were extracted regarding potential sources of patient heterogeneity, in which of the input parameters of an economic evaluation these occur, methods to acknowledge patient heterogeneity and specific concerns associated with this acknowledgement.

resultsA total of 20 articles and five handbooks were included. The relevant sources of patient heterogeneity (demographics, preferences and clinical characteristics) and the input parameters where they occurred (baseline risk, treatment effect, health state utility and resource utilization) were combined in a framework. Methods were derived for the design, analysis and presentation phases of an economic evaluation. Concerns related mainly to the danger of false-positive results and equity issues.

conclusionBy systematically reviewing current knowledge regarding patient heterogeneity within economic evaluations of healthcare programmes, we provide guidance for future economic evaluations. Guidance is provided on which sources of patient heterogeneity to consider, how to acknowledge them in economic evaluation and potential concerns. The improved acknowledgement of patient heterogeneity in future economic evaluations may well improve the efficiency of healthcare.

Indexed as

Decision MakingReimbursement MechanismsCost-Benefit AnalysisDelivery of Health CareDemographyHumansPatient Preference

Identifiers

What OpenQuestion holds

Textmetadata
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.