Characteristics of high-cost patients diagnosed with opioid abuse
Open accessAbstract
BACKGROUND: Prescription opioid abuse is associated with substantial economic burden, with estimates of incremental annual per-patient health care costs of diagnosed opioid abuse exceeding $10,000 in prior literature. A subset of patients diagnosed with opioid abuse has disproportionately high health care costs, but little is known about the characteristics of these patients. OBJECTIVE: To describe the characteristics of a subset of patients diagnosed with opioid abuse with disproportionately high health care costs to assist physicians and managed care organizations in targeting interventions at the costliest patients. METHODS: This retrospective claims data analysis identified patients aged 12 to 64 years diagnosed with opioid abuse/dependence in the OptumHealth Reporting and Insights medical and pharmacy claims database, Quarter 1 (Q1) 1999-Q1 2012. Inclusion criteria required that patients had a diagnosis of opioid abuse during or after Q1 2006, no prior diagnoses of opioid abuse, and continuous non-HMO coverage over an 18-month study period. The study period comprised a 12-month observation period centered on the date of the first opioid abuse diagnosis (index date) and a 6-month baseline period immediately preceding the observation period. Patients in the top 20% of total health care costs in the observation period were classified as "high-cost patients," and the remaining patients were classified as "lower-cost patients." Patient characteristics, comorbidities, health care resource use, and health care costs were compared between high-cost patients and lower-cost patients using chi-square tests for dichotomous variables and Wilcoxon rank-sum tests for continuous variables. In addition, multivariate regression was used to assess the relationship between patient characteristics in the baseline period and total health care costs in the observation period among all patients diagnosed with opioid abuse. RESULTS: 9,291 patients diagnosed with opioid abuse met the inclusion criteria. The 20% of patients classified as high-cost patients accounted for approximately two thirds of the total health care costs of patients diagnosed with opioid abuse. Compared with lower-cost patients, high-cost patients were older (42.5 vs. 36.1; P less than 0.001) and more likely to be female (55.9% vs. 42.9%; P less than 0.001). They had a higher comorbidity burden at baseline, as reflected in the Charlson Comorbidity Index (0.8 vs. 0.2; P less than 0.001), and rates of conditions such as chronic pulmonary disease (12.9% vs. 5.6%; P less than 0.001) and mild/moderate diabetes (8.4% vs. 3.4%; P less than 0.001). High-cost patients also had higher rates of nonopioid substance abuse diagnoses (12.4% vs. 8.9%; P less than 0.001) and psychotic disorders (26.5% vs. 13.6%; P less than 0.001). In the observation period, high-cost patients continued to have higher rates of nonopioid substance abuse diagnoses (53.0% vs. 47.2%; P less than 0.001) and psychotic disorders (67.1% vs. 47.5%; P less than 0.001). In addition, they had greater medical resource use across all places of service (i.e., inpatient, emergency department, outpatient, drug/alcohol rehabilitation facility, and other) compared with lower-cost patients. The mean observation period health care costs of high-cost patients was $89,177 compared with $11,653 for lower-cost patients (P less than 0.001). High-cost patients had higher medical costs linked to claims with an opioid abuse diagnosis in absolute terms, but the share of total medical costs attributed to such claims was lower among high-cost patients than among lower-cost patients. While many baseline characteristics were found to have a statistically significant (P less than 0.05) association with observation period health care costs, only 27.3% of the variation in observation period health care costs was explained by patient characteristics in the baseline period. CONCLUSIONS: This study found that the costliest patients diagnosed with opioid abuse had high rates of preexisting and concurrent chronic comorbidities and mental health conditions, suggesting potential indicators for targeted intervention and a need for greater awareness and screening of comorbid conditions. Opioid abuse may exacerbate existing conditions and make it difficult for patients to adhere to treatment plans for those underlying conditions. Baseline patient characteristics explained only a small share of the variation in observation period health care costs, however. Future research should explore the degree to which other factors not captured in administrative claims data (e.g., severity of abuse) can explain the wide variation in health care costs among opioid abusers.
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Studies of healthcare claims data show that the most challenging and costliest OUD patients had high rates of preexisting and concurrent medical comorbidities and mental health disorders.
“Similarly, studies of healthcare claims data reveal that the most challenging and costliest OUD patients had high rates of preexisting and concurrent medical comorbidities and mental health disorders (Shei et al., 2015).”
From Chronic pain among patients with opioid use disorder: Results from electronic health records data (2017) · cites this paper as Shei et al., 2015
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Cites
Romano, P. S., Roos, L. L., & Jollis, J. G. (1993) · Journal of Clinical Epidemiology · doi:10.1016/0895-4356(93)90103-8 · Cited by 1,717 · see citing works
Results from the 2003 National Survey on Drug Use and Health: National Findings
(2004) · PsycEXTRA Dataset · doi:10.1037/e400442005-001 · Cited by 1,245 · see citing works
Trends in Opioid Analgesic Abuse and Mortality in the United States
Dart, R. C., Surratt, H. L., Cicero, T. J., Parrino, M. W., Severtson, S. G., Bucher‐Bartelson, B., & Green, J. L. (2015) · New England Journal of Medicine · doi:10.1056/nejmsa1406143 · Cited by 1,140 · see citing works
Societal costs of prescription opioid abuse, dependence, and misuse in the United States
Birnbaum, H. G., White, A. G., Schiller, M., Waldman, T., Cleveland, J. M., & Roland, C. L. (2011) · Pain Medicine · doi:10.1111/j.1526-4637.2011.01075.x · Cited by 644 · see citing works
Self-citationBecker, W. C., Sullivan, L. E., Tetrault, J. M., Desai, R. A., & Fiellin, D. A. (2007) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2007.09.018 · Cited by 398 · see citing works
Direct Costs of Opioid Abuse in an Insured Population in the United States
White, A. G., Birnbaum, H. G., Mareva, M. N., Daher, M., Vallow, S., Schein, J. R., & Katz, N. P. (2005) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2005.11.6.469 · Cited by 180 · see citing works
Self-citationDirect Costs of Opioid Abuse in an Insured Population in the United States
White, A. G., Birnbaum, H. G., Mareva, M. N., Daher, M., Vallow, S., Schein, J. R., & Katz, N. P. (2020) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2020.26.10.1188 · Cited by 169 · see citing works
Self-citationEconomic Burden of Prescription Opioid Misuse and Abuse
Strassels, S. A. (2009) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2009.15.7.556 · Cited by 148 · see citing works
A Model to Identify Patients at Risk for Prescription Opioid Abuse, Dependence, and Misuse
Rice, J. B., White, A. G., Birnbaum, H. G., Schiller, M., Brown, D. A., & Roland, C. L. (2012) · Pain Medicine · doi:10.1111/j.1526-4637.2012.01450.x · Cited by 141 · see citing works
Self-citationPrevalence of Diagnosed Opioid Abuse and its Economic Burden in the Veterans Health Administration
Başer, O., Xie, L., Mardekian, J., Schaaf, D. T., Wang, L., & Joshi, A. V. (2013) · Pain Practice · doi:10.1111/papr.12097 · Cited by 82 · see citing works
Rice, J. B., Kirson, N. Y., Shei, A., Cummings, A. K. G., Bodnar, K., Birnbaum, H. G., & Ben-Joseph, R. H. (2014) · Applied Health Economics and Health Policy · doi:10.1007/s40258-014-0102-0 · Cited by 65 · see citing works
Self-citationThe Prevalence of Diagnosed Opioid Abuse in Commercial and Medicare Managed Care Populations
Dufour, R., Joshi, A. V., Pasquale, M. K., Schaaf, D. T., Mardekian, J., Andrews, G. A., & Patel, N. C. (2013) · Pain Practice · doi:10.1111/papr.12148 · Cited by 48 · see citing works
Rossiter, L. F., Kirson, N. Y., Shei, A., White, A. G., Birnbaum, H. G., Ben-Joseph, R. H., & Michna, E. (2014) · Journal of Medical Economics · doi:10.3111/13696998.2014.897628 · Cited by 37 · see citing works
Self-citationEconomic Impact of Opioid Abuse, Dependence, and Misuse
White, A. G., Birnbaum, H. G., Schiller, B. M., Waldman, T., Cleveland, J. M., & Roland, P. A. C. L. (2011) · The American Journal of Managed Care · Cited by 34 · see citing works
Self-citationWhite, A. G., Birnbaum, H. G., Rothman, D., & Katz, N. P. (2009) · Applied Health Economics and Health Policy · doi:10.1007/bf03256142 · Cited by 33 · see citing works
Self-citationThe economic burden of diagnosed opioid abuse among commercially insured individuals
Rice, J. B., Kirson, N. Y., Shei, A., Enloe, C. J., Cummings, A. K. G., Birnbaum, H. G., Holly, P., & Ben-Joseph, R. (2014) · Postgraduate Medicine · doi:10.3810/pgm.2014.07.2783 · Cited by 27 · see citing works
Self-citationFishbain, D. A., Johnson, S. H., Webster, L. R., Greene, L., & Faysal, J. M. (2010) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2010.16.4.276 · Cited by 19 · see citing works
Use of prescription opioids with abuse-deterrent technology to address opioid abuse
Michna, E., Kirson, N. Y., Shei, A., Birnbaum, H. G., & Ben-Joseph, R. H. (2014) · Current Medical Research and Opinion · doi:10.1185/03007995.2014.915803 · Cited by 19 · see citing works
Self-citationPatient Perspective, Complexities, and Challenges in Managed Care
Jan, S. (2010) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2010.16.s1-b.22 · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Chronic pain among patients with opioid use disorder: Results from electronic health records data
Hser, Y.-I., Mooney, L. J., Saxon, A. J., Miotto, K., Bell, D. S., & Huang, D. (2017) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2017.03.006 · Cited by 222 · see citing works
“Similarly, studies of healthcare claims data reveal that the most challenging and costliest OUD patients had high rates of preexisting and concurrent medical comorbidities and mental health disorders (Shei et al., 2015).”
BackgroundClewley, D. J., Rhon, D. I., Flynn, T. W., Koppenhaver, S. L., & Cook, C. E. (2018) · PLoS ONE · doi:10.1371/journal.pone.0201348 · Cited by 74 · see citing works
Reinhart, M. L., Scarpati, L. M., Kirson, N. Y., Patton, C., Shak, N., & Erensen, J. G. (2018) · Applied Health Economics and Health Policy · doi:10.1007/s40258-018-0402-x · Cited by 65 · see citing works
Self-citationFactors Associated with Direct Health Care Costs Among Patients with Migraine
Bonafede, M., Cai, Q., Cappell, K. A., Kim, G., Sapra, S. J., Shah, N. A., Widnell, K. L., Winner, P. K., & Desai, P. (2017) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2017.23.11.1169 · Cited by 40 · see citing works
Carrell, D., Albertson-Junkans, L. H., Ramaprasan, A., Scull, G., Mackwood, M., Johnson, E. A., Cronkite, D., Baer, A. B., Hansen, K., Green, C. A., et al. (2020) · Journal of Drug Assessment · doi:10.1080/21556660.2020.1750419 · Cited by 26 · see citing works
Meredith, L. S., Komaromy, M. S., Cefalu, M. S., Murray-Krezan, C. M., Page, K., Osilla, K. C., Dopp, A. R., Leamon, I. M., Tarhuni, L., Hindmarch, G., et al. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106354 · Cited by 23 · see citing works
Substance Use Disorders and Related Health Problems in an Aging Offender Population
Gates, M. L., Staples-Horne, M., Walker, V., & Turney, A. (2017) · Journal of Health Care for the Poor and Underserved · doi:10.1353/hpu.2017.0057 · Cited by 20 · see citing works
D'Amico, M. J., Walley, A. Y., Cheng, D. M., Forman, L. S., Regan, D., Yurkovic, A., Samet, J. H., & Weinstein, Z. (2019) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2019.08.013 · Cited by 20 · see citing works
“Patients receiving a psychiatry consult had higher odds of receiving an addiction consult, and it has been shown that patients diagnosed with OUD have high rates of concurrent medical comorbidities and mental health conditions (Shei et al., 2015).”
BackgroundDonohue, J. M., Barry, C. L., Stuart, E. A., Greenfield, S. F., Song, Z., Chernew, M. E., & Huskamp, H. A. (2017) · Journal of Addiction Medicine · doi:10.1097/adm.0000000000000368 · Cited by 15 · see citing works
“In addition, costs are highly concentrated in the 20% of OUD patients who account for two-thirds of excess healthcare costs associated with the disorder (Shei et al., 2015).”
BackgroundAnnis, I., Jordan, R., & Thomas, K. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-059414 · Cited by 10 · see citing works
Healthcare use and costs of adults with anorexia nervosa and bulimia nervosa in Taiwan
Tseng, M. M., Tu, C., & Chang, Y. (2020) · International Journal of Eating Disorders · doi:10.1002/eat.23419 · Cited by 14 · see citing works
Comorbid opioid use is undertreated among forensic patients with schizophrenia
Kivimies, K., Repo‐Tiihonen, E., Kautiainen, H., & Tiihonen, J. (2018) · Substance Abuse Treatment Prevention and Policy · doi:10.1186/s13011-018-0177-y · Cited by 13 · see citing works
“The burden of disease consequent of drug dependence is highest when it is question of opioid use disorder [34], and patients diagnosed with this comorbidity belong to the costliest group of all patients with opioid use disorder [35].”
BackgroundEconomic burden of opioid crisis and the role of pharmacist-led interventions
Sanyal, C. (2020) · Journal of the American Pharmacists Association · doi:10.1016/j.japh.2020.11.006 · Cited by 12 · see citing works
Opioid Use Disorder during Antepartum and Postpartum Hospitalizations
Kern‐Goldberger, A. R., Huang, Y., Polin, M., Siddiq, Z., Wright, J. D., D’Alton, M. E., & Friedman, A. M. (2019) · American Journal of Perinatology · doi:10.1055/s-0039-1694725 · Cited by 12 · see citing works
Ndanga, M., & Srinivasan, S. S. (2019) · Cureus · doi:10.7759/cureus.6516 · Cited by 11 · see citing works
“This correlates with other previous studies that have identified a similar pattern of cooccurrence of substance-related disorders and personality or mood disorders [26-27].”
ResultHurley, R. W., Bland, K. T., Chaskes, M. D., Guth, D., Hill, E., & Adams, M. C. B. (2025) · Pain Medicine · doi:10.1093/pm/pnaf116 · Cited by 9 · see citing works
Opioid Abuse and Dependence in Those Hospitalized Due to Head and Neck Cancer
Nalliah, R. P., Karhade, D. S., Stein, K. M., Chandrasekaran, S., Rampa, S., Allareddy, V., & Allareddy, V. (2018) · Journal of Oral and Maxillofacial Surgery · doi:10.1016/j.joms.2018.06.010 · Cited by 8 · see citing works
Cohort profile: the provincial opioid agonist treatment cohort in Ontario, Canada
Morin, K. A., Tatangelo, M., Acharya, S., & Marsh, D. C. (2025) · European Journal of Epidemiology · doi:10.1007/s10654-025-01202-3 · Cited by 6 · see citing works
“People who use opioids (PWUO) experience co-occurring mental disorders [6–8], infections [9–11], and chronic illnesses [12], compounded by elevated rates of poverty [13] and homelessness [13–15].”
Alsultan, M. M., & Guo, J. J. (2022) · PubMed Central · Cited by 6 · see citing works
Rautiainen, E., Ryynänen, O., Laatikainen, T. K., & Kekolahti, P. (2020) · Healthcare Informatics Research · doi:10.4258/hir.2020.26.2.129 · Cited by 4 · see citing works
“Thus, our results are in line with those of previous studies identifying an association between the number of comorbidities and increased costs of care among patients with chronic conditions [22,29,30].”
ResultWhat’s holding back abuse-deterrent opioid formulations? Considering 12 U.S. stakeholders
Pergolizzi, J. V., Taylor, R., LeQuang, J. A., & Raffa, R. B. (2018) · Expert Opinion on Drug Delivery · doi:10.1080/17425247.2018.1473374 · Cited by 3 · see citing works
Cima, M. J. (2017) · doi:10.33915/etd.5369
“, 2014) opioid abusers tend to have more comorbidities, (McAdamMarx et al., 2010; Shei et al., 2015) and costs associated with opioid abuse are significant.”
BackgroundMethodSchneider, J. E. (2026) · Global perspectives on wealth and distribution · doi:10.1007/978-3-032-20355-7_6
- Authors
- Shei, A., Rice, J. B., Kirson, N. Y., Bodnar, K., Enloe, C. J., Birnbaum, H. G., Holly, P., & Ben-Joseph, R.
- Affiliations
- Analysis Group (United States) (US)
- Venue
- Journal of Managed Care & Specialty Pharmacy
- Publisher
- Academy of Managed Care Pharmacy
- Published
- 2015-10
- Volume
- 21
- Issue
- 10
- Pages
- 902-912
- ISSN
- 2376-0540 (ISSN-L)
- 2376-1032
- PMC
- PMC10397972
- OpenAlex
- W2285568355
- Cited by
- 23
- References
- 19
- Citations by year
- 2026: 1 · 2025: 2 · 2022: 2 · 2021: 1 · 2020: 4 · 2019: 3 · 2018: 5 · 2017: 5
- FWCI
- 3.57
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Managed Care & Specialty Pharmacy (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Keywords
- prescription opioid abuse, opioid use disorder, high-cost patients, health care costs, health care utilization, comorbidity burden, chronic lung disease, chronic kidney disease, chronic liver disease, substance use disorders, managed care, patient characteristics, gender differences, age differences, Charlson Comorbidity Index, claims data analysis, targeted interventions
- MeSH terms
- Adolescent, Adult, Analgesics, Opioid, Mental Disorders, Child, Female, Humans, Male, Managed Care Programs, Middle Aged, Opioid-Related Disorders, Retrospective Studies, Comorbidity, Multivariate Analysis, Health Care Costs, Cost of Illness, Young Adult, Prescription Drug Misuse
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