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Enregistrement W2162799816 · doi:10.18553/jmcp.2007.13.3.262

Actuarial Analysis of Private Payer Administrative Claims Data for Women With Endometriosis

2007· article· en· W2162799816 sur OpenAlexaboutno aff
David Mirkin, Carrieann Murphy-Barron, Kosuke Iwasaki

Notice bibliographique

RevueJournal of Managed Care Pharmacy · 2007
Typearticle
Langueen
DomaineMedicine
ThématiqueEndometriosis Research and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineEndometriosisDiagnosis codePelvic painReferralHealth careRetrospective cohort studyMedical recordFamily medicineDemographyEnvironmental healthGynecologyPopulationInternal medicineSurgery

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Endometriosis is a painful, chronic disease affecting 5.5 million women and girls in the United States and Canada and millions more worldwide. The usual age range of women diagnosed with endometriosis is 20 to 45 years. Endometriosis has an estimated prevalence of 10% among women of reproductive age, although estimates of prevalence vary greatly. Endometriosis is the most common gynecological cause of chronic pelvic pain, but published information on its associated medical care costs is scarce. OBJECTIVE: The aim of this study was to determine (1) the prevalence of endometriosis in the United States, (2) the amount of health care services used by women coded with endometriosis in a commercial medical claims database during 1999 to 2003, and (3) the endometriosis-related costs for 2003, the most recent data available at the time the study was performed. METHODS: This study was a retrospective review of administrative data for commercial payers, which included enrollment, eligibility, and claims payment data contained in the Medstat Marketscan database for approximately 4 million commercial insurance members. All claims and membership data were extracted for each woman aged 18 to 55 years who had at least 1 medical or hospital claim with a diagnosis code for endometriosis (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 617.00-617.99) for 1999 through 2003. Claims data from 1999 through 2003 were used to determine prevalence and health care resource utilization (i.e., annual admission rate, annual surgical rate, distribution of endometriosis-related surgeries, and prevalence of comorbid conditions). The cost analysis was based on claims from 2003 only. Cost was defined as the payer-allowed charge, which equals the net payer cost plus member cost share. RESULTS: The prevalence of women with medical claims (inpatient and/or outpatient) containing ICD-9-CM codes for endometriosis was 1.1% for the age band of 30 to 39 years and 0.7% over the entire age span of 18 to 55 years. The medical costs per patient per month (PPPM) for women with endometriosis were 63% greater ($706 PPPM) than those of the average woman per member per month ($433) in 2003; inpatient hospital costs accounted for 32% of total direct medical costs. Between 1999 and 2003, these women with endometriosis who were identified by either inpatient and/or outpatient claims had high rates of hospital admission (53% for any reason; 38% for an endometriosis-related reason) and a high annual surgical procedure rate (64%). Additionally, women with endometriosis frequently suffered from comorbid conditions, and these conditions were associated with greater PPPM costs of 15% to 50% for women with an endometriosis diagnosis code, depending on the condition. Interstitial cystitis was associated with 50% greater cost ($1,061 PPPM); depression, 41% ($997 PPPM); migraine, 40% ($988 PPPM); irritable bowel syndrome, 34% ($943 PPPM); chronic fatigue syndrome, 29% ($913 PPPM); abdominal pain, 20% ($846 PPPM); and infertility, 15% ($813 PPPM). CONCLUSIONS: Women with endometriosis have a high hospital admission rate and surgical procedure rate and a high incidence of comorbid conditions. Consequently, these women incur total medical costs that are, on average, 63% higher than medical costs for the average woman in a commercially insured group.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,582
Score d'incertitude au seuil0,492

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,102
Tête enseignante GPT0,435
Écart entre enseignants0,332 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations97
Publié2007
Routes d'admission1
Résumé présentoui

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