MétaCan
Menu
Back to cohort
Record 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 on OpenAlexaboutno aff
David Mirkin, Carrieann Murphy-Barron, Kosuke Iwasaki

Bibliographic record

VenueJournal of Managed Care Pharmacy · 2007
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEndometriosisDiagnosis codePelvic painReferralHealth careRetrospective cohort studyMedical recordFamily medicineDemographyEnvironmental healthGynecologyPopulationInternal medicineSurgery

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.582
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.102
GPT teacher head0.435
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations97
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Managed Care PharmacySame topicEndometriosis Research and TreatmentFrench-language works237,207