Application of Probabilistic Linkage: Compare Health Care Costs among Menopausal Women with Different Symptoms by Linking Women’s Registry & Claims Data

Authors

  • O. Baser The University of Michigan, Department of Internal Medicine, Ann Arbor, MI, USA
  • L. Xie STAT in MED Research, Ann Arbor, MI, 48104, USA
  • J. Du STAT in MED Research, Ann Arbor, MI, 48104, USA

DOI:

https://doi.org/10.6000/1929-6029.2013.02.01.04

Keywords:

Probabilistic linkage, women’s health, propensity score matching.

Abstract

Objectives: Menopause symptoms are a good disease severity proxy for menopausal women, but are not available in claims database. We applied probabilistic linkage to add symptoms recorded in a registry database to claims data, and compare the healthcare costs among women with various symptoms.

Methods: Women age 45 or older who used estrogen only hormone therapy (HT) were selected from a large U.S. claims database (04/01/2005-09/30/2008). Another group who used estrogen only HT with a menopause diagnosis was selected from the University of Michigan Women’s Registry Database. Logistic regression was used to calculate the propensity score for each patient controlling for osteoporosis, gynecological disorders/procedures, genital infection, gynecology system cancer, breast condition, gut condition, hormone disorder, nerve problem, and other individual comorbidities such as rheumatoid disease, depression, and blood clotting. Patients with the closest propensity score from each group were matched, and menopause symptoms for registry patients were added to the claims database records. After repeating probabilistic linkage 250 times, the mean and 95% confidence interval (CI) of healthcare costs during the follow-up period were calculated.

Results: 80 patients from each population were matched after probabilistically linking 20,020 claims database patients with 83 registry database patients. The average cost of patients with at least one symptom was much higher than for patients without symptoms ($13,570 [95% CI: $13,459-$13,680] vs. $3,391 [95%CI: $3,345-$3,436], p-value<0.001). (1 US Dollar= 0.75 Euro) Cost differences were mainly from inpatient, physician visit, and pharmacy costs. Among patients with menopause symptoms, those with hot flashes had the highest costs ($10,127), followed by memory loss ($1,653), vaginal dryness ($864), reduced libido ($568), and mood swings ($358).

Conclusions: Women with menopause symptoms incur higher healthcare costs than those without This study suggests symptoms are important determinants of healthcare expenses and their impact can be assessed by linking registry and claims databases.

Author Biography

O. Baser, The University of Michigan, Department of Internal Medicine, Ann Arbor, MI, USA

Department of Internal Medicine

References

McClellan M, Uncertainty, health-care technologies, and health-care choices. Am Econom Rev 1995; 38-44.

Garrison LP, et al. Using real-world data for coverage and payment decisions: the ISPOR Real-World Data Task Force report. Value Health 2007; 10(5): 326-35. http://dx.doi.org/10.1111/j.1524-4733.2007.00186.x DOI: https://doi.org/10.1111/j.1524-4733.2007.00186.x

Fellegi IP, Sunter AB. A theory for record linkage. J Am Statist Assoc 1969; 64(328): 1183-10. http://dx.doi.org/10.1080/01621459.1969.10501049 DOI: https://doi.org/10.1080/01621459.1969.10501049

Jaro MA. Advances in record-linkage methodology as applied to matching the 1985 census of Tampa, Florida. J Am Statist Assoc 1989; 84(406): 414-20. http://dx.doi.org/10.1080/01621459.1989.10478785 DOI: https://doi.org/10.1080/01621459.1989.10478785

Jaro MA. Probabilistic linkage of large public health data files. Statist Med 2007; 14(5‐7): 491-98. DOI: https://doi.org/10.1002/sim.4780140510

Baser O, Crown WH, Pollicino C. Guidelines for selecting among different types of bootstraps. Curr Med Res Opin 2006; 22(4): 799-808. http://dx.doi.org/10.1185/030079906X100230 DOI: https://doi.org/10.1185/030079906X100230

CB W. Hormone therapy for the management of menopausal symptoms: pharmacotherapy update. J Pharm Pract 2010; 6(23): 540-47. DOI: https://doi.org/10.1177/0897190009360061

RE W. Frequency and severity of vasomotor symptoms among peri-and post menopausal women in the United States. Climacteris 2008; 2008(11): 32-43. DOI: https://doi.org/10.1080/13697130701744696

Howe GR. Use of computerized record linkage in cohort studies. Epidemiol Rev 1998; 20(1): 112-21. http://dx.doi.org/10.1093/oxfordjournals.epirev.a017966 DOI: https://doi.org/10.1093/oxfordjournals.epirev.a017966

Adams MM, et al. Constructing reproductive histories by linking vital records. Am J Epidemiol 1997; 145(4): 339-48. http://dx.doi.org/10.1093/oxfordjournals.aje.a009111 DOI: https://doi.org/10.1093/oxfordjournals.aje.a009111

Whiteman D, et al. Reproductive factors, subfertility, and risk of neural tube defects: a case-control study based on the Oxford Record Linkage Study Register. Am J Epidemiol 2000; 152(9): 823-28. http://dx.doi.org/10.1093/aje/152.9.823 DOI: https://doi.org/10.1093/aje/152.9.823

Baser O, et al. Anticoagulation prophylaxis practice patterns in patients having total hip, total knee replacement in a US health plan. Am Health Drug Benefits 2011; 4(4): 240-48.

Newgard C, et al. Evaluating the Use of Existing Data Sources, Probabilistic Linkage, and Multiple Imputation to Build Population‐based Injury Databases Across Phases of Trauma Care. Acad Emerg Med 2012; 19(4): 469-80. http://dx.doi.org/10.1111/j.1553-2712.2012.01324.x DOI: https://doi.org/10.1111/j.1553-2712.2012.01324.x

Coeli CM, et al. Probabilistic linkage in household survey on hospital care usage. Revista de Saúde Pública 2003; 37(1): 91-99. http://dx.doi.org/10.1590/S0034-89102003000100014 DOI: https://doi.org/10.1590/S0034-89102003000100014

Ford I. Computerised record linkage: compared with traditional patient follow-up methods in clinical trials and illustrated in a prospective epidemiological study. J Clin Epidemiol 1995; 48(12): 1441-52. http://dx.doi.org/10.1016/0895-4356(95)00530-7 DOI: https://doi.org/10.1016/0895-4356(95)00530-7

Fair M, et al. An assessment of the validity of a computer system for probabilistic record linkage of birth and infant death records in Canada. Chronic Dis Can 2000; 21(1): 8-13.

Ramsay C, Campbell M, Glazener C. Linking Community Health Index and Scottish morbidity records for neonates: the Grampian experience. Health Bull 1999; 57: 70-75.

Shannon H, et al. Comparison of individual follow-up and computerized record linkage using the Canadian Mortality Data Base. Can J Public Health. Revue canadienne de sante publique 1989; 80(1): 54.

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Published

2013-02-12

How to Cite

Baser, O., Xie, L., & Du, J. (2013). Application of Probabilistic Linkage: Compare Health Care Costs among Menopausal Women with Different Symptoms by Linking Women’s Registry & Claims Data. International Journal of Statistics in Medical Research, 2(1), 34–39. https://doi.org/10.6000/1929-6029.2013.02.01.04

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General Articles