Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs
Abstract
Use of prescription opioids and problems of abuse and addiction have increased over the past decade. Claims-based studies have documented substantial economic burden of opioid abuse. This study utilized electronic health record (EHR) data to identify chronic opioid therapy (COT) patients with problem opioid use (POU) and compared costs with those for COT patients without POU. This study utilized EHR and claims data from an integrated health care system. Patients received COT (≥70 days' supply in ≥1 calendar quarter, 2006-2012). Natural language processing (NLP) identified notations of opioid addiction, abuse, misuse, or overuse, and manual validation was performed. Cases had evidence of POU (index = first POU notation), and controls, sampled 9:1, did not. Health care resource utilization was measured and costs estimated using Medicare reimbursement rates. A longitudinal analysis of costs was conducted using generalized estimating equations. Adjusted analyses controlled for baseline age, gender, region, specific comorbidities, and a comorbidity index. The analysis population included 1,125 cases and 10,128 controls. Unadjusted costs were higher for cases in all three years. After controlling for covariates, total costs remained higher in cases and were significantly higher in the first year of follow-up ($38,064 vs. $31,674, P = .0048). The largest cost difference was observed in the first month of follow-up. COT patients with POU experienced significantly higher costs compare…
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Mobilizing SEDH data from the EHR is hindered by heterogeneous provider documentation practices and interoperability issues.
“Mobilizing this data from the electronic health record (EHR) is hindered by heterogeneous provider documentation practices and interoperability issues [1,2,9–22].”
Variability in screening and documentation practices currently limits the ability to mobilize SEDH data for secondary uses.
“the variability in screening and documentation practices currently limits the ability to mobilize SEDH data for secondary uses”
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Societal costs of prescription opioid abuse, dependence, and misuse in the United States
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Patra, B. G., Sharma, M. M., Vekaria, V., Adekkanattu, P., Patterson, O. V., Glicksberg, B., Lepow, L. A., Ryu, E., Biernacka, J. M., Furmanchuk, A., et al. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab170 · Cited by 248 · see citing works
Sood, N., Stetter, C., Kunselman, A., & Jasani, S. (2024) · PLOS Digital Health · doi:10.1371/journal.pdig.0000428 · Cited by 6 · see citing works
- Authors
- Masters, E. T., Ramaprasan, A., Mardekian, J., Palmer, R. E., Gross, D. E., Cronkite, D., Von Korff, M., & Carrell, D. S.
- Corresponding author
- Masters, Elizabeth T.
- Venue
- Journal of Pain & Palliative Care Pharmacotherapy
- Publisher
- Informa UK Limited
- Published
- 2018-07-03
- Volume
- 32
- Issue
- 2-3
- Pages
- 106-115
- ISSN
- 1536-0288 (ISSN-L)
- 1536-0539
- OpenAlex
- W2911677221
- Cited by
- 9
- References
- 1
- Citations by year
- 2024: 1 · 2022: 1 · 2021: 4 · 2020: 2 · 2018: 1
- FWCI
- 1.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Pain & Palliative Care Pharmacotherapy (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Kaiser Permanente Washington
- Pfizer Inc.
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
- Health Sciences › Medicine › Anesthesiology and Pain Medicine › Pain Management and Opioid Use
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Keywords
- long-term opioid therapy, opioid misuse, opioid use disorder, health care costs, natural language processing, electronic health records, healthcare resource utilization, integrated health system
- MeSH terms
- Adolescent, Adult, Aged, Analgesics, Opioid, Female, Follow-Up Studies, Medicare, Humans, Longitudinal Studies, Male, Middle Aged, Opioid-Related Disorders, Natural Language Processing, Retrospective Studies, United States, Case-Control Studies, Health Care Costs, Cost of Illness, Young Adult, Electronic Health Records
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