Evidence map›Paper›PMID 38783258›Full record

ArticleBMC musculoskeletal disorders2024

Annual epidemiological and health insurance disease burden of hip osteoarthritis in Hungary based on nationwide data.

Luca Fanni Kajos, Bálint Molics, Diána Elmer, Dalma Pónusz-Kovács, Bettina Kovács, Lilla Horváth, Tímea Csákvári, József Bódis, Imre Boncz

Abstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

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

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

  1. Pooled it
  2. Pooled it
  3. Article
  4. Prevalence and occupational risk of hip osteoarthritis and rotator cuff lesions - claims data analysis.International journal of occupational medicine and environmental health · 2026
    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

9 authors.

Luca Fanni KajosInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary. kajos.luca@gmail.com.
Bálint MolicsInstitute of Physiotherapy and Sport Science, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
Diána ElmerInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
Dalma Pónusz-KovácsInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
Bettina KovácsInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
Lilla HorváthInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
Tímea CsákváriInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
József BódisInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.
Imre BonczInstitute for Health Insurance, Faculty of Health Sciences, University of Pécs, Pécs, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth services utilization related to hip osteoarthritis imposes a significant burden on society and health care systems. Our aim was to analyse the epidemiological and health insurance disease burden of hip osteoarthritis in Hungary based on nationwide data.

methodsData were extracted from the nationwide financial database of the National Health Insurance Fund Administration (NHIFA) of Hungary for the year 2018. The analysed data included annual patient numbers, prevalence, and age-standardized prevalence per 100,000 population in outpatient care, health insurance costs calculated for age groups and sexes for all types of care. Patients with hip osteoarthritis were identified using code M16 of the International Classification of Diseases (ICD), 10th revision. Age-standardised prevalence rates were calculated using the European Standard Population 2013 (ESP2013).

resultsBased on patient numbers of outpatient care, the prevalence per 100,000 among males was 1,483.7 patients (1.5%), among females 2,905.5 (2.9%), in total 2,226.2 patients (2.2%). The age-standardised prevalence was 1,734.8 (1.7%) for males and 2,594.8 (2.6%) for females per 100,000 population, for a total of 2,237.6 (2.2%). The prevalence per 100,000 population was higher for women in all age groups. In age group 30-39, 40-49, 50-59, 60-69 and 70 + the overall prevalence was 0.2%, 0.8%, 2.7%, 5.0% and 7.7%, respectively, describing a continuously increasing trend. In 2018, the NHIFA spent 42.31 million EUR on the treatment of hip osteoarthritis. Hip osteoarthritis accounts for 1% of total nationwide health insurance expenditures. 36.8% of costs were attributed to the treatment of male patients, and 63.2% to female patients. Acute inpatient care, outpatient care and chronic and rehabilitation inpatient care were the main cost drivers, accounting for 62.7%, 14.6% and 8.2% of the total health care expenditure for men, and 51.0%, 20.0% and 11.2% for women, respectively. The average annual treatment cost per patient was 3,627 EUR for men and 4,194 EUR for women.

conclusionsThe prevalence of hip osteoarthritis was 1.96 times higher (the age-standardised prevalence was 1.5 times higher) in women compared to men. Acute inpatient care was the major cost driver in the treatment of hip osteoarthritis. The average annual treatment cost per patient was 15.6% higher for women compared to men.

Indexed as

Osteoarthritis, HipAdolescentAdultAgedAged, 80 and overAmbulatory CareCost of IllnessDatabases, FactualFemaleHealth Care CostsHumansHungaryInsurance, HealthMaleMiddle AgedPrevalenceAcute inpatient careDisease burdenFinancingHealth insuranceHip osteoarthritisOutpatient care

Identifiers

PMID38783258
PMCPMC11112791

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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.