1
|
Glanz JM, Xu S, Narwaney KJ, McClure DL, Rinehart DJ, Ford MA, Nguyen AP, Binswanger IA. Association Between Opioid Dose Reduction Rates and Overdose Among Patients Prescribed Long-Term Opioid Therapy. Subst Abus 2023; 44:209-219. [PMID: 37702046 DOI: 10.1177/08897077231186216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
BACKGROUND Tapering long-term opioid therapy is an increasingly common practice, yet rapid opioid dose reductions may increase the risk of overdose. The objective of this study was to compare overdose risk following opioid dose reduction rates of ≤10%, 11% to 20%, 21% to 30%, and >30% per month to stable dosing. METHODS We conducted a retrospective cohort study in three health systems in Colorado and Wisconsin. Participants were patients ≥18 years of age prescribed long-term opioid therapy between January 1, 2006, and June 30, 2019. Five opioid dosing patterns and drug overdoses (fatal and nonfatal) were identified using electronic health records, pharmacy records, and the National Death Index. Cox proportional hazard regression was conducted on a propensity score-weighted cohort to estimate adjusted hazard ratios (aHRs) for follow-up periods of 1, 3, 6, 9, and 12 months after a dose reduction. RESULTS In a cohort of 17 540 patients receiving long-term opioid therapy, 42.7% of patients experienced a dose reduction. Relative to stable dosing, a dose reduction rate of >30% was associated with an increased risk of overdose and the aHR estimates decreased as the follow-up increased; the aHRs for the 1-, 6- and 12-month follow-ups were 5.33 (95% CI, 1.98-14.34), 1.81 (95% CI,1.08-3.03), and 1.49 (95% CI, 0.97-2.27), respectively. The slower tapering rates were not associated with overdose risk. CONCLUSIONS Patients receiving long-term opioid therapy exposed to dose reduction rates of >30% per month had increased overdose risk relative to patients exposed to stable dosing. Results support the use of slow dose reductions to minimize the risk of overdose.
Collapse
Affiliation(s)
- Jason M Glanz
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Stanley Xu
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Komal J Narwaney
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - David L McClure
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Deborah J Rinehart
- Center for Health Systems Research, Office of Research, Denver Health and Hospital Authority, Denver, CO, USA
- Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Morgan A Ford
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Anh P Nguyen
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
| | - Ingrid A Binswanger
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
- Division of General Internal Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Chemical Dependency Treatment Services, Colorado Permanente Medical Group, Aurora, CO, USA
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA
| |
Collapse
|
2
|
Defining Opioid-related Problems Using a Health Care Safety Net Institution's Inpatient Electronic Health Records: Limitations of Diagnosis-based Definitions. J Addict Med 2023; 17:79-84. [PMID: 35914026 DOI: 10.1097/adm.0000000000001041] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Measuring clinically relevant opioid-related problems in health care systems is challenging due to the lack of standard definitions and coding practices. Well-defined, opioid-related health problems (ORHPs) would improve prevalence estimates and evaluation of clinical interventions, crisis response, and prevention activities. We sought to estimate prevalence of opioid use disorder (OUD), opioid misuse, and opioid poisoning among inpatients at a large, safety net, health care institution. METHODS Our study included events documented in the electronic health records (EHRs) among hospitalized patients at Denver Health Medical Center during January 1, 2017 to December 31, 2018. Multiple EHR markers (ie, opioid-related diagnostic codes, clinical assessment, laboratory results, and free-text documentation) were used to develop diagnosis-based and extended definitions for OUD, opioid misuse, and opioid poisoning. We used these definitions to estimate number of hospitalized patients with these conditions. RESULTS During a 2-year study period, 715 unique patients were identified solely using opioid-related diagnostic codes; OUD codes accounted for the largest proportion (499/715, 69.8%). Extended definitions identified an additional 973 unique patients (~136% increase), which includes 155/973 (15.9%) who were identified by a clinical assessment marker, 1/973 (0.1%) by a laboratory test marker, and 817/973 (84.0%) by a clinical documentation marker. CONCLUSIONS Solely using diagnostic codes to estimate prevalence of clinically relevant ORHPs missed most patients with ORHPs. More inclusive estimates were generated using additional EHR markers. Improved methods to estimate ORHPs among a health care system's patients would more fully estimate organizational and economic burden to more efficiently allocate resources and ensure capacity to provide clinical services.
Collapse
|
3
|
Riggs KR, DeRussy AJ, Leisch L, Shover CL, Bohnert ASB, Hoge AE, Montgomery AE, Varley AL, Jones AL, Gordon AJ, Kertesz SG. Sensitivity of health records for self-reported nonfatal drug and alcohol overdose. Am J Addict 2022; 31:517-522. [PMID: 36000282 PMCID: PMC9617764 DOI: 10.1111/ajad.13327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 08/04/2022] [Accepted: 08/04/2022] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Public health surveillance for overdose sometimes depends on nonfatal drug overdoses recorded in health records. However, the proportion of total overdoses identified through health record systems is unclear. Comparison of overdoses from health records to those that are self-reported may provide insight on the proportion of nonfatal overdoses that are not identified. METHODS We conducted a cohort study linking survey data on overdose from a national survey of Veterans to United States Department of Veterans Affairs (VA) health records, including community care paid for by VA. Self-reported overdose in the prior 3 years was compared to diagnostic codes for overdoses and substance use disorders in the same time period. RESULTS The sensitivity of diagnostic codes for overdose, compared to self-report as a reference standard for this analysis, varied by substance: 28.1% for alcohol, 23.1% for sedatives, 12.0% for opioids, and 5.5% for cocaine. There was a notable concordance between substance use disorder diagnoses and self-reported overdose (sensitivity range 17.9%-90.6%). DISCUSSION AND CONCLUSIONS Diagnostic codes in health records may not identify a substantial proportion of drug overdoses. A health record diagnosis of substance use disorder may offer a stronger inference regarding the size of the population at risk. Alternatively, screening for self-reported overdose in routine clinical care could enhance overdose surveillance and targeted intervention. SCIENTIFIC SIGNIFICANCE This study suggests that diagnostic codes for overdose are insensitive. These findings support consideration of alternative approaches to overdose surveillance in public health.
Collapse
Affiliation(s)
- Kevin R Riggs
- Birmingham VA Health Care System, Birmingham, Alabama, USA
- University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA
| | | | - Leah Leisch
- Birmingham VA Health Care System, Birmingham, Alabama, USA
- University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA
| | - Chelsea L Shover
- University of California David Geffen School of Medicine, Los Angeles, California, USA
| | - Amy S B Bohnert
- Michigan Medicine, Department of Anesthesiology, Ann Arbor, Michigan, USA
- VA Center for Clinical Management Research, Ann Arbor, Michigan, USA
| | - April E Hoge
- Birmingham VA Health Care System, Birmingham, Alabama, USA
| | - Ann E Montgomery
- Birmingham VA Health Care System, Birmingham, Alabama, USA
- University of Alabama at Birmingham School of Public Health, Birmingham, Alabama, USA
| | - Allyson L Varley
- Birmingham VA Health Care System, Birmingham, Alabama, USA
- University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA
| | - Audrey L Jones
- VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Adam J Gordon
- VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Stefan G Kertesz
- Birmingham VA Health Care System, Birmingham, Alabama, USA
- University of Alabama at Birmingham School of Medicine, Birmingham, Alabama, USA
| |
Collapse
|
4
|
Rowe CL, Santos GM, Kornbluh W, Bhardwaj S, Faul M, Coffin PO. Using ICD-10-CM codes to detect illicit substance use: A comparison with retrospective self-report. Drug Alcohol Depend 2021; 221:108537. [PMID: 33621806 PMCID: PMC11008535 DOI: 10.1016/j.drugalcdep.2021.108537] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND Understanding whether International Classification of Disease, 10th Revision, Clinical Modification (ICD-10-CM) codes can be used to accurately detect substance use can inform their use in future surveillance and research efforts. METHODS Using 2015-2018 data from a retrospective cohort study of 602 safety-net patients prescribed opioids for chronic non-cancer pain, we calculated the sensitivity and specificity of using ICD-10-CM codes to detect illicit substance use compared to retrospective self-report by substance (methamphetamine, cocaine, opioids [heroin or non-prescribed opioid analgesics]), self-reported use frequency, and type of healthcare encounter. RESULTS Sensitivity of ICD-10-CM codes for detecting self-reported substance use was highest for methamphetamine (49.5 % [95 % confidence interval: 39.6-59.5 %]), followed by cocaine (44.4 % [35.8-53.2 %]) and opioids (36.3 % [28.8-44.2 %]); higher for participants who reported more frequent methamphetamine (intermittent use: 27.7 % [14.6-42.6 %]; ≥weekly use: 67.2 % [53.7-79.0 %]) and opioid use (intermittent use: 21.4 % [13.2-31.7 %]; ≥weekly use: 52.6 % [40.8-64.2 %]); highest for outpatient visits (methamphetamine: 43.8 % [34.1-53.8 %]; cocaine: 36.8 % [28.6-45.6 %]; opioids: 33.1 % [25.9-41.0 %]) and lowest for emergency department visits (methamphetamine: 8.6 % [4.0-15.6 %]; cocaine: 5.3 % [2.1-10.5 %]; opioids: 6.3 % [3.0-11.2 %]). Specificity was highest for methamphetamine (96.4 % [94.3-97.8 %]), followed by cocaine (94.0 % [91.5-96.0 %]) and opioids (85.0 % [81.3-88.2 %]). CONCLUSIONS ICD-10-CM codes had high specificity and low sensitivity for detecting self-reported substance use but were substantially more sensitive in detecting frequent use. ICD-10-CM codes to detect substance use, particularly those from emergency department visits, should be used with caution, but may be useful as a lower-bound population measure of substance use or for capturing frequent use among certain patient populations.
Collapse
Affiliation(s)
- Christopher L Rowe
- San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, California, 94102, USA; University of California, Berkeley, 2121 Berkeley Way, 5th Floor, Berkeley, California, 94702, USA.
| | - Glenn-Milo Santos
- San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, California, 94102, USA; University of California, San Francisco, 500 Parnassus Avenue, San Francisco, California, 94143, USA
| | - Wiley Kornbluh
- San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, California, 94102, USA
| | - Sumeet Bhardwaj
- San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, California, 94102, USA; Western University, 800 Commissioners Road East, London, Ontario, N61 5W9, Canada
| | - Mark Faul
- Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, Georgia, 30329, USA
| | - Phillip O Coffin
- San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, California, 94102, USA; University of California, San Francisco, 500 Parnassus Avenue, San Francisco, California, 94143, USA
| |
Collapse
|