Opioid Prescribing and Outcomes in Patients With Sickle Cell Disease Post–2016 CDC Guideline

Hyeun Ah Kang; Bofei Wang; Jamie C Barner; Kenneth I Ataga; Robert C Mignacca; Alicia Chang; Yahan Zhang

doi:10.1001/jamainternmed.2023.8538

. 2024 Mar 11;184(5):510–518. doi: 10.1001/jamainternmed.2023.8538

Opioid Prescribing and Outcomes in Patients With Sickle Cell Disease Post–2016 CDC Guideline

Hyeun Ah Kang ^1,^✉, Bofei Wang ^2,³, Jamie C Barner ⁴, Kenneth I Ataga ⁵, Robert C Mignacca ^6,⁷, Alicia Chang ^6,⁷, Yahan Zhang ⁸

¹Division of Health Outcomes, College of Pharmacy, The University of Texas at Austin

²Computational Sciences Program, The University of Texas at El Paso

³Department of Leukemia, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston

⁴Division of Health Outcomes, College of Pharmacy, The University of Texas at Austin

⁵Center for Sickle Cell Disease, Department of Medicine, The University of Tennessee Health Science Center at Memphis

⁶Department of Pediatrics, The University of Texas at Austin

⁷Children’s Blood and Cancer Center at Dell Children’s Hospital, Austin, Texas

⁸Division of Health Outcomes, College of Pharmacy, The University of Texas at Austin

Accepted for Publication: December 10, 2023.

Published Online: March 11, 2024. doi:10.1001/jamainternmed.2023.8538

Correction: This article was corrected on February 10, 2025, to fix errors in the Key Points, Abstract, text, Figures, Table 2, and Supplement 1 due to an inaccurate description of the study sample.

^✉

Corresponding Author: Hyeun Ah Kang, PhD, The University of Texas at Austin, 2409 University Ave, Austin, TX 78712 (h.kang@austin.utexas.edu).

Author Contributions: Dr Kang had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Kang, Barner, Mignacca.

Acquisition, analysis, or interpretation of data: Kang, Wang, Ataga, Mignacca, Chang, Zhang.

Drafting of the manuscript: Kang.

Critical review of the manuscript for important intellectual content: Wang, Barner, Ataga, Mignacca, Chang, Zhang.

Statistical analysis: Kang, Wang, Barner, Zhang.

Obtained funding: Kang.

Administrative, technical, or material support: Wang, Mignacca, Chang.

Supervision: Kang.

Conflict of Interest Disclosures: Dr Barner reported grants from Pfizer and Novartis outside the submitted work. Dr Ataga reported research funding from the US Food and Drug Administration; National Heart, Lung, and Blood Institute; Novartis; Novo Nordisk; and Takeda/Shire. Dr Ataga also reported being a member of clinical advisory boards or consulting for Vertex (data monitoring committee member), Novartis, Novo Nordisk, Agios Pharmaceuticals, Roche, Biomarin, Pfizer, Sanofi, Fulcrum Therapeutics, and Hillhurst Biopharmaceuticals. No other disclosures were reported.

Funding/Support: This work was supported by the American Association of Colleges of Pharmacy New Investigator Award.

Role of the Funder/Sponsor: The American Association of Colleges of Pharmacy had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

^✉

Corresponding author.

PMCID: PMC10928539 PMID: 38466269

Key Points

Question

Was the release of the 2016 Centers for Disease Control and Prevention (CDC) guideline for prescribing opioids for chronic pain associated with changes in opioid prescribing and health outcomes among individuals with sickle cell disease (SCD)?

Findings

In this retrospective cohort study of 14 979 individuals with SCD, interrupted time series analysis found significant downward trends in opioid prescribing practices and significant upward trends in pain-related health care resource use after the release of the 2016 CDC guideline.

Meaning

The findings suggest that the release of the 2016 CDC guideline may have unintended negative outcomes on the SCD population.

Abstract

Importance

Although the intention of the 2016 US Centers for Disease Control and Prevention (CDC) Guideline for Prescribing Opioids for Chronic Pain was not to limit pain treatment for patients with sickle cell disease (SCD), clinicians and patients have recognized the possibility that the guideline may have altered outcomes for this population. However, the outcomes of the 2016 guideline for this patient population are unknown.

Objective

To examine changes in opioid prescribing patterns and health outcomes among patients with SCD before and after the release of the 2016 CDC guideline.

Design, Setting, and Participants

This retrospective cohort study conducted interrupted time series analysis of claims data from the Merative MarketScan Commercial Database from January 1, 2011, to December 31, 2019. In this population-based study in the US, individuals with SCD who were at least 1 year of age, had no cancer diagnosis, and had pharmacy coverage for the month of measurement were included. The data were analyzed from January 2021 to November 2023.

Exposure

The CDC Guideline for Prescribing Opioids for Chronic Pain released in March 2016.

Main Outcomes and Measures

The main variables measured in this study included the practice of opioid prescribing among patients with SCD (ie, rate of opioid prescriptions dispensed, mean number of days supplied, mean total morphine milligram equivalents [MME] per patient, and mean daily MME per opioid prescription) and pain-related health outcomes (rates of emergency department visits related to vaso-occlusive crises [VOC] and hospitalizations related to VOC).

Results

The cohort included 14 979 patients with SCD (mean [SD] age, 25.9 [16.9] years; 8520 [56.9%] female). Compared with the preguideline trends, after the guideline was released, there was no change in opioid dispensing rate (−0.01 [95% CI, −0.04 to 0.02]) prescriptions per 100 person-month; P = .56), but there were significant decreases in the number of days supplied per prescription (−0.05 [95% CI, −0.06 to −0.04] days per prescription-month; P < .001) and opioid dosage (−40.0 [95% CI, −60.9 to −19.0] MME per person-month; P = .001; −10.1 [95% CI, −14.6 to −5.6] MME/prescription-month; P < .001). Conversely, significant increases in VOC-related emergency department visits (0.04 [95% CI, 0.02-0.05] visits per 100 person-month; P < .001) and hospitalizations (0.07 [95% CI, 0.05-0.1] hospitalizations per 100 person-month; P < .001) occurred after the guideline release. These changes were observed to a greater extent among adult patients, but pediatric patients experienced similar changes in several measures, even though the guideline focused exclusively on adult patients.

Conclusions and Relevance

This retrospective cohort study showed that the 2016 CDC guideline may have had unintended negative outcomes on the patient population living with SCD.

This retrospective cohort study examines changes in opioid prescribing patterns and health outcomes among patients with sickle cell disease before and after the release of the 2016 US Centers for Disease Control and Prevention (CDC) opioid guideline.

Introduction

In March 2016, the US Centers for Disease Control and Prevention (CDC) released the Guideline for Prescribing Opioids for Chronic Pain to promote safer and more effective use of prescription opioids for adult patients with chronic pain outside of active cancer treatment, palliative care, and end-of-life care.¹ Recent studies have found that the CDC guideline has been effective in decreasing opioid use by reducing the opioid prescribing rate, the number of days supplied per prescription, and dosage among the overall population and patients with chronic pain.^2,3,4,5,6

However, this decrease has also occurred among patient groups that fall outside of the intended scope of the guideline, such as those with cancer and sickle cell disease (SCD).⁷ SCD affects approximately 100 000 people in the US who are born with variants in the gene encoding the β subunit of hemoglobin.^8,9 They often experience recurrent pain episodes called vaso-occlusive crises (VOC) throughout their lifetimes.^8,10 To control VOC pain, disease-specific guidelines recommend opioid analgesics when the pain is not relieved by nonopioids.^11,12,13 However, despite substantial pain management needs, patients often face restrictive access to opioid therapy, in part because SCD predominantly affects African American individuals (approximately 90%),¹⁴ who are less likely than White patients to receive opioid prescriptions in the US.¹⁵ A qualitative study suggested that, from the perspective of adult patients with SCD, the opioid epidemic and subsequent guidelines increased barriers to accessing opioids, stigmatization regarding opioid use, and physicians’ scrutiny of opioid dosage.¹⁶

In February 2019, in response to a letter from the American Society of Hematology and other associations,¹⁷ the CDC publicly acknowledged that the guideline was not intended to prevent individuals with acute or chronic pain from conditions, such as cancer and SCD from receiving clinically necessary opioid therapy.¹⁸ However, according to pain management experts and medical groups such as the American Medical Association, it appears that these warnings have generally been unheeded in the health care community; the guideline has been used to justify inappropriate one-size-fits-all restrictions on opioid analgesics by state legislatures, health insurance plans, and health care organizations.^19,20,21 As a result, the CDC has sought evaluations of the intended and unintended effects of the guideline on clinician and patient outcomes.⁷ However, until the publication of the updated version of the guideline in November 2022,²² no study has examined the outcomes of the guideline on individuals with SCD. The new guideline listed SCD as an excluded condition based on expert panel discussions and studies that discovered inadequate pain management among African American patients.²² Therefore, a quantitative evaluation of the consequences of the 2016 CDC guideline on patients with SCD is necessary to understand the outcomes of the guideline on this vulnerable population and to prevent future unintended negative consequences.

The purpose of this study is to determine if the 2016 CDC guideline has unintended consequences for patients with SCD and, if so, to what extent. To do this, we aimed to examine the association of the release of the CDC guideline with changes in opioid prescriptions filled and pain-related health outcomes among patients with SCD. An exploratory subgroup analysis by age group (<18 years vs ≥18 years) was conducted for all the outcome variables to study if the impact of the guideline is different between pediatric and adult patients because the guideline is intended to apply to patients 18 years and older with chronic pain.¹

Methods

Study Design and Data Source

This retrospective cohort study used an interrupted time series model to evaluate the longitudinal effects of the 2016 CDC guideline. Data for the analyses were derived from the Merative MarketScan Commercial Database for the period January 1, 2011, to December 31, 2019. These data include health insurance claims across the continuum of care (eg, inpatient, outpatient, outpatient pharmacy) as well as enrollment data from large employers and health plans across the US that provide private health care coverage. This database includes information on more than 25 million US residents annually. This study was determined to be exempt from review by The University of Texas at Austin institutional review board because of its secondary use of deidentified data for research purposes. This report adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.²³

Study Population

According to the algorithm of the Centers for Medicare & Medicaid Services Chronic Conditions Data Warehouse,²⁴ we identified individuals with SCD if they had 3 or more nondrug claims of any service type with a diagnosis code for SCD. Among these, we included only those who were at least 1 year of age at index month (the month when the individual appeared in the dataset for the first time), did not have a cancer diagnosis at any point in the study period, and had pharmacy coverage for the month of measurement. Individuals were not required to be continuously enrolled to be included because the analyses were conducted on aggregated outcomes that were calculated at the month level.

Outcomes

Outcomes related to opioid prescribing practices included (1) monthly rate of opioid prescriptions dispensed; (2) mean number of days supplied per opioid prescription; (3) mean total morphine milligram equivalents (MME) per patient per month, for which MME was calculated using the drug-specific morphine conversion factors published in the 2016 CDC opioid guideline¹; and (4) mean daily MME per opioid prescription. The formula to calculate MME and the operational definition of each variable can be found in eTable 1 in Supplement 1. We identified opioid prescriptions using the National Drug Codes (NDCs) that were publicly available from the CDC,²⁵ and excluded common cold and cough products, naloxone, methadone, and buprenorphine for opioid use disorders. Health outcomes related to pain management included monthly rates of VOC-related emergency department (ED) visits and monthly rates of VOC-related hospitalizations. All outcomes were measured every month during the study period (eFigure 1 in Supplement 1).

Statistical Analysis

To describe the demographic characteristics of the study population, frequency and percentage (categorical variables) or mean, standard deviation, median, and interquartile ranges (continuous variables) were used. To determine if there were trend changes in the study outcomes after the release of the guideline compared with the preguideline period, we conducted a total of 6 interrupted time series (ITS) with segmented regressions using monthly repeated measures of each outcome. The coefficients from the regressions were used to estimate the guideline outcomes, which include a one-time change at the time of the guideline’s release (ie, March 2016) and a difference in preguideline and postguideline trends that were assessed by assuming preguideline trends continued unchanged. To test for serial autocorrelation in the regression models, the Durbin-Watson statistic was examined, and significant autocorrelation was adjusted using the Prais-Winsten transformation. The same analysis was performed for the exploratory subgroup analysis by age group. Analyses were conducted with R statistical software, version 4.3.1 (R Project for Statistical Computing), and Stata/SE statistical software, version 18.0 (StataCorp). For all analyses, a 2-sided P value of less than .05 was considered significant.

Sensitivity Analysis

To assess the robustness of the study findings, we performed several sensitivity analyses. First, we used December 2015 as the month of implementation because the draft of the guideline was publicly announced for public comments during this month. Second, we used control outcomes²⁶ because a control group that was unaffected by this federal guideline does not exist. Rates of benzodiazepine prescription fill (for adults only) and ED visits and hospitalizations without a VOC diagnosis were assessed for opioid prescription outcomes and health outcomes, respectively. Benzodiazepine was chosen because of its similarity with opioids in terms of the risk of overuse and regulation in prescribing but no direct effects by the CDC guideline. Due to significant differences in levels and slopes between study and control outcomes in the preguideline period, we used single-group ITS analysis for all control outcomes instead of multiple-group ITS analysis,²⁷ which can be used for indirect comparisons.

Results

The cohort included 14 979 patients with SCD (mean [SD] age, 25.9 [16.9] years; 8520 [56.9%] female). The patients filled 125 135 opioid prescriptions (eTable 2 in Supplement 1). A mean (range) of 5360 patients (4218-6239) were included in each month, and the included individuals were enrolled in their health insurance for a mean (SD) of 37.2 (28.8) months and median (IQR) of 27 (14-50) months during the study period. Approximately 60% of patients lived in the South region (Table 1).

Table 1. Demographic Characteristics of Study Population.

Characteristic	No. (%)	P value
Total	14 979	NA
Age at index date, y^a
Mean (SD)	25.9 (16.9)
Median (IQR)	25.0 (12.0-39.0)
Age group, y^a
1-12	3961 (26.4)	<.001
13-17	1498 (10.0)
18-27	2883 (19.2)
28-45	4293 (28.7)
46-65	2344 (15.6)
Sex
Female	8520 (56.9)	<.001
Male	6459 (43.1)	<.001
Region^b
Northeast	2534 (16.9)	<.001
North Central	2150 (14.4)
South	8992 (60.0)
West	994 (6.6)
Unknown	309 (2.1)

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Abbreviation: NA, not applicable.

^{^a}

Age was reported at the first month of enrollment during the study period.

^{^b}

Region was reported at the first month of enrollment during the study period.

Trend Changes in Opioid Prescription Fills

In January 2011, the rate of receiving 1 or more opioid prescriptions among patients with SCD was 0.24 (approximately 24 prescription fills per 100 patients). This declined until March 2016 at a rate of −0.04 (95% CI, −0.06 to −0.03) prescriptions/100 person-month and continued to decrease at a similar rate thereafter (−0.05 [95% CI, −0.08 to −0.03] prescriptions/100 person-month) through December 2019 (coefficient for change in slope, −0.01 [95% CI, −0.04 to 0.02] prescriptions/100 person-month; P = .56), which resulted in a rate of 0.19 (19 prescription fills per 100 patients) in December 2019 (Table 2, Figure 1). Between January 2011 and March 2016, mean days supplied per opioid prescription continuously increased but started decreasing after March 2016 (coefficient for change in slope, −0.05 [95% CI, −0.06 to −0.04] days/prescription-month; P < .001), which resulted in 2.0 fewer days in December 2019 (15.6 days) compared with no guideline scenario (17.6 days). No significant change immediately after March 2016 was observed either in the monthly dispensing rate or the days supplied. The 2 measures of opioid dosages showed similar patterns to those of the mean number of days supplied, increasing before the CDC guideline and declining afterward, with a peak around the time of the guideline release. Post hoc analysis that excluded the period of large increases, from October 2015 to December 2016, showed similar patterns with smaller coefficients (slopes) (eFigure 2, eFigure 3, eTable 3 in Supplement 1).

Table 2. Interrupted Time Series Regression Analysis of Opioid Prescription Fills and Health Outcomes.

Variable	Intercept (β₀)		Preguideline trajectory^a		Postguideline trajectory^b		Change associated with guideline release
Variable	Constant (95% CI)	P value	Slope^c (95% CI)	P value	Slope^c (95% CI)	P value	Immediate change^d (95% CI)	P value	Change in slope (95% CI)	P value
Opioid prescription fills
Opioid dispensing rate per 100 persons	23.6 (23.0 to 24.2)	<.001	−0.04 (−0.06 to −0.03)	<.001	−0.05 (−0.08 to −0.03)	<.001	0.7 (−0.2 to 1.5)	.13	−0.01 (−0.04 to 0.02)	.56
Days supplied per prescription	14.3 (14.1 to 14.5)	<.001	0.03 (0.03 to 0.04)	<.001	−0.01 (−0.02 to −0.01)	<.001	−0.1 (−0.4 to 0.2)	.58	−0.05 (−0.06 to −0.04)	<.001
Total MME per person	50.8 (−344.8 to 446.5)	.80	19.9 (9.2 to 30.6)	<.001	−20.1 (−36.1 to −4.1)	.01	143.4 (−335.6 to 622.4)	.55	−40.0 (−60.9 to −19.0)	.001
Mean daily MME per prescription	35.8 (−49.1 to 120.7)	.40	4.1 (1.8 to 6.5)	.001	−6.0 (−9.5 to −2.4)	.001	102.3 (−12.7 to 217.2)	.08	−10.1 (−14.6 to −5.6)	<.001
Health outcomes
VOC-related ED visits per 100 persons	5.2 (5.0 to 5.5)	<.001	−0.006 (−0.01 to 0.002)	.13	0.03 (0.02 to 0.04)	<.001	0.02 (−0.4 to 0.4)	.92	0.04 (0.02 to 0.05)	<.001
VOC-related hospitalizations per 100 persons	6.7 (6.2 to 7.2)	<.001	−0.03 (−0.04 to −0.02)	<.001	0.04 (0.02 to 0.06)	<.001	−0.3 (−1.0 to 0.4)	.41	0.07 (0.05 to 0.1)	<.001

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Abbreviations: ED, emergency department; MME, morphine milligram equivalent; VOC, vaso-occlusive crises.

^{^a}

The preguideline period was January 2011 to February 2016 for all outcomes.

^{^b}

The postguideline period was March 2016 to December 2019 for all outcomes.

^{^c}

Slopes represent the change in the indicated variable per month.

^{^d}

Immediate change represents a one-time change at the time of the guideline’s release (ie, March 2016).

Figure 1. — Dashed blue vertical lines represent the month of the Centers for Disease Control and Prevention (CDC) guideline implementation (March 2016). The blue dots and solid black lines represent the actual values and fitted lines, respectively. The change in slope (ie, rate of decrease per month) from before to after the CDC guideline release was statistically significant in panels B, C, and D (B, P < .001; C, P = .001; D, P < .001). MME indicates morphine milligram equivalent.

^aThe change in slope did not reach statistical significance (P = .56).

Trend Changes in Health Outcomes Associated With Pain Management

In January 2011, there were 5.2 ED visits related to VOC per 100 patients. No significant change until March 2016 was observed, but it started increasing after March 2016 (coefficient for change in slope, 0.04 [95% CI, 0.02 to 0.05] ED visits/100 person-month; P < .001), which resulted in a 1.62–percentage-point increase in December 2019 (6.24%) compared with the no-guideline scenario (4.62%) (Table 2 and Figure 2). In January 2011, there were 6.7 hospitalizations related to VOC events per 100 patients. This rate slightly decreased until March 2016 and increased afterward (coefficient for change in slope, 0.07 [95% CI, 0.05-0.1] hospitalizations/100 person-month; P < .001), which resulted in a 3.18–percentage-point increase in December 2019 (6.46%) compared with the no-guideline scenario (3.28%).

Figure 2. — Dashed blue vertical lines represent the month of the Centers for Disease Control and Prevention (CDC) guideline implementation (March 2016). The blue dots and solid black lines represent the actual values and fitted lines, respectively. The change in slope (ie, rate of decrease per month) from before to after the CDC guideline release was statistically significant (A, P < .001; B, P < .001). ED indicates emergency department; VOC, vaso-occlusive crises.

Age-Related Changes in Opioid Prescription Fills and Health Outcomes

Among the included individuals, 5459 (36.4%) were younger than 18 years, with a mean [SD] age of 8.3 [5.3] years. Compared with the adult patients, pediatric patients with SCD received fewer opioid prescription fills with lower dosages of opioids and had fewer VOC-related health care visits throughout the study period. As shown in Figure 3 and eTable 4 in Supplement 1, compared with the preguideline period, children with SCD experienced significant decreases in the number of days supplied per prescription and the total MME per patient and significant increases in the VOC-related hospitalization rate after the guideline release. For the 9520 adults with SCD (mean [SD] age, 36.1 [12.2] years), all opioid-related outcome measures, except for the prescription rate, showed significant downward trends, whereas VOC-related ED visits and hospitalization rates had an upward trend in the postguideline period, compared with the preguideline period (Figure 3; eTable 5 in Supplement 1).

Figure 3. — Dashed blue vertical lines represent the month of the Centers for Disease Control and Prevention (CDC) guideline implementation (March 2016). The blue dots and solid black lines represent the actual values and fitted lines, respectively, for adult patients. The orange dots and dashed black lines represent the actual values and fitted lines, respectively, for pediatric patients. The top slope values in each panel apply to adults; the bottom slope values in each panel apply to children, as noted in panel A. The change in slope (ie, rate of decrease per month) from before to after the CDC guideline release was statistically significant in adults in panels B to F, as well as in children in panels B, C, and F (B, adults: P < .001; children: P < .001; C, adults: P < .001; children: P = .02; D, adults: P < .001; E, adults: P < .001; F, adults: P < .001; children: P = .01). ED indicates emergency department; MME, morphine milligram equivalent; VOC, vaso-occlusive crises.

^aThe change in slope did not reach statistical significance (A, adults: P = .44; children: P = .50; D, children: P = .10; E, children: P = .35).

Sensitivity Analysis

The results from the model using December 2015 as the time of implementation are reported in eTable 6 in Supplement 1. Except for one measure, specifically the immediate increase in total MME in December 2015, all other inferences remained unchanged. Notably, the immediate increase in total MME was deemed significant in December 2015, in contrast with the nonsignificant finding in the primary model (using March 2016). The estimates for the control outcomes showed that there was a slight increase in benzodiazepine dispensing as opposed to no change in opioids, no change in ED visits without a VOC diagnosis, and slight increase in hospitalizations without a VOC diagnosis (0.02 [95% CI, 0.002-0.04] hospitalizations/100 person-month; P = .03 vs 0.07 [95% CI, 0.05-0.1] hospitalizations/100 person-month; P < .001 in hospitalizations with a VOC diagnosis) after the CDC guideline release (eFigure 4-6, eTable 7 in Supplement 1).

Discussion

In this retrospective cohort study using nationally representative data of commercially insured patients, we found that the release of the 2016 CDC guideline was associated with a decrease in opioid prescription outcomes and an increase in pain-related ED visits and hospitalizations in patients with SCD. Downward trends in opioid prescriptions after the 2016 CDC guideline release have been found in other populations, including the overall US adult population, patients naive to opioids, individuals with chronic pain and cancer, and those who underwent surgery.^{2,3,4,5,6,28,29,30,31,32} However, the findings of this study should be interpreted in the context that SCD was outside of the scope of the guideline but was not explicitly listed as an excluded condition in the 2016 published guideline. Decreases in prescription opioids among those with SCD imply that this population was susceptible to the guideline’s recommendations and subsequent changes in regulations by state legislatures and health insurance organizations.

Although no significant change was observed in the monthly opioid prescription trend, it should be noted that patients with SCD already experienced a significant decrease in the prescription rate before the guideline’s introduction. In a study that used single ITS models on similar prescription outcomes in the overall US adult population, the monthly prescription rate declined from −0.02 (95% CI, −0.03 to −0.02) per 100 persons before March 2016 to −0.06 (95% CI, −0.07 to −0.05) per 100 persons afterward. In contrast, among adult patients with SCD, the rate changed from −0.1 (95% CI, −0.12 to −0.07) per 100 persons before March 2016 to −0.08 (95% CI, −0.12 to −0.03) per 100 persons afterward. Additionally, compared with the overall US adult population in the same study, adult patients with SCD experienced a greater decline in the number of days supplied (−0.05 [95% CI, −0.06 to −0.04] vs −0.02 [95% CI, −0.03 to −0.003] per 100 persons).² The substantial increase in daily MME per opioid prescription a few months before and after the guideline publication should also be noted. The reason for this increase is uncertain. One potential reason is that prescribers may have been encouraged to ensure patient access to opioids around the time the guideline became available for public comments (December 2015), assuming they anticipated their own institutions, health plans, or states would implement more restrictive policies per the CDC guideline. This unique trend has not been observed in previous studies with other populations.

Considering the intent of the guideline and the precautions made by the CDC,¹⁸ the changes in opioid prescriptions should be evaluated by the outcomes of pain management. The results of this study indicate that following the release of the guideline, ED visits among adult patients and hospitalizations among both pediatric and adult patients with SCD increased significantly. These findings are particularly important because, in a recent study, a reduction of hospitalizations and ED visits is ranked the number 1 treatment goal of patients and the number 3 goal of physicians (followed by reduction of VOC and prevention of end-organ damage), respectively.³³ These results suggest that the federal guideline’s noninclusion of SCD as an excluded condition, as well as suboptimal communication regarding the importance of employing disease-specific guidelines for SCD, may have contributed to reduced access to opioid prescriptions and, subsequently, poor pain control in this population.

Another unintended spillover outcome of this guideline was observed in pediatric patients. The extent of changes was less prominent in pediatric patients than in adult patients, perhaps due to the lower baseline levels of prescription opioid use and VOC-related health care utilization. However, the decreases in the number of days supplied and total MME per patient and the increase in VOC-related hospitalizations were significant. The decline in opioid prescriptions among children is consistent with studies that investigated cancer³⁰ and assessed the outcomes of state opioid guidelines on children with SCD.³⁴

After the CDC’s acknowledgment regarding the nonapplicability of the 2016 guideline to patients with SCD, SCD has been listed as an excluded condition in the updated 2022 guideline.²² This guideline recommends using disease-specific guidelines, such as the American Society of Hematology 2020 Guidelines for Sickle Cell Disease: Management of Acute and Chronic Pain, for managing pain in this patient population.²² Thus, federal guidelines should be developed with careful consideration of medically vulnerable populations, and their intentions and scope should be clearly communicated with the health care community to avoid unintended consequences. For successful implementation of clinical guidelines and policies, outcome evaluations, as well as stakeholder engagement and education, are critical. Because a new guideline is released with an updated scope and recommendations, evaluation of its intended and unintended outcomes is needed.

Understanding the outcomes of a federal guideline on medically vulnerable, at-risk populations is crucial for mitigating and preventing unintended harms, as well as for the successful implementation of future guidelines. In the future, studies are needed for those who have public insurance, such as Medicaid. In addition, given that interpretation and application of the guideline may vary across regions and different health care settings, especially ED and comprehensive sickle cell centers, examining the relative effects of the guideline is needed to identify the areas that require more attention to prevent unintended harm to this patient population.

Limitations

This study used a single-group interrupted time series analysis because of the absence of a comparable US control group unexposed to the CDC guideline. However, the preintervention segment can serve as a control for the postintervention segment,³⁵ and we conducted sensitivity analyses using a different time of implementation, as well as control outcomes to strengthen the study findings. Second, our measures of filled opioid prescriptions might not equal opioid prescribing. However, declines in opioid prescriptions filled may reflect lower prescribing rather than patients’ reduced opioid filling behaviors, given the increased VOC-related ED visits and hospitalization during the study period. Third, patients with SCD experience both acute and chronic pain. In this study, we do not know what proportion of the opioid prescription fills was associated with chronic or acute pain management. Fourth, this study has limitations that are found in most studies that use administrative claims data. The scope of the study was limited by the information collected in the database, which precluded the examination of other factors possibly associated with the outcomes, such as genotypes and laboratory test results. Additionally, the validity of the results of this study also depends in part on the accuracy of the records in the database. Fifth, because this study evaluated commercial health insurance claims data, the findings may not be generalizable to those with SCD who have public insurance. Finally, this study did not evaluate the appropriateness of individual opioid prescriptions.

Conclusions

In this retrospective cohort study that analyzed nationally representative commercial claims data, the 2016 CDC Guideline for Opioid Prescriptions for Chronic Pain was associated with negative outcomes for the patient population living with SCD. These outcomes include a decrease in opioid prescriptions and an increase in pain-related health care utilization. The federal guideline and policymakers should carefully consider the negative outcomes that their interventions may present in vulnerable populations, as well as clearly communicate the intention and scope of the interventions.

Supplement 1.

eFigure 1. Study timeframe and interrupted time-series segments

eFigure 2. Total opioid dose prescribed for patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain, excluding from October 2015 to December 2016

eFigure 3. Daily opioid dose prescribed for patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain, excluding from October 2015 to December 2016

eFigure 4. Rates of prescriptions for opioid and benzodiazepine medications dispensed for adult patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

eFigure 5. Rate of emergency department visits with and without a vaso-occlusive crisis among patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

eFigure 6. Rate of hospitalizations with and without a vaso-occlusive crisis before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

eTable 1. Operational definition of study variables

eTable 2. Study population attrition

eTable 3. Interrupted time series regression analysis of opioid dose in Morphine Milligram Equivalent (MME) prescribed for patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain, excluding from October 2015 to December 2016

eTable 4. Interrupted time series regression analysis of opioid prescription fills and health outcomes among pediatric patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

eTable 5. Interrupted time series regression analysis of opioid prescription fills and health outcomes among adult patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

eTable 6. Interrupted time series regression analysis of opioid prescription fills and health outcomes among patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain for public review in December 2015

eTable 7. Interrupted time series regression analysis of benzodiazepine prescription fills, non-pain-related health outcomes among patients with sickle cell disease before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

jamainternmed-e238538-s001.pdf^{(1.4MB, pdf)}

Supplement 2.

Data Sharing Statement

jamainternmed-e238538-s002.pdf^{(13.3KB, pdf)}

References

1.Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain—United States, 2016. MMWR Recomm Rep. 2016;65(1):1-49. doi: 10.15585/mmwr.rr6501e1 [DOI] [PubMed] [Google Scholar]
2.Bohnert ASB, Guy GP Jr, Losby JL. Opioid prescribing in the United States before and after the Centers for Disease Control and Prevention’s 2016 opioid guideline. Ann Intern Med. 2018;169(6):367-375. doi: 10.7326/M18-1243 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Dayer LE, Breckling MN, Kling BS, Lakkad M, McDade ER, Painter JT. Association of the CDC Guideline for Prescribing Opioids for Chronic Pain with emergency department opioid prescribing. J Emerg Med. 2019;57(5):597-602. doi: 10.1016/j.jemermed.2019.07.016 [DOI] [PubMed] [Google Scholar]
4.Townsend T, Cerdá M, Bohnert A, Lagisetty P, Haffajee RL. CDC guideline for opioid prescribing associated with reduced dispensing to certain patients with chronic pain. Health Aff (Millwood). 2021;40(11):1766-1775. doi: 10.1377/hlthaff.2021.00135 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Togun AT, Mandic PK, Wurtz R, Jeffery MM, Beebe T. Association of opioid fills with Centers for Disease Control and Prevention opioid guidelines and payer coverage policies: physician, insurance and geographic factors. Int J Clin Pharm. 2022;44(2):428-438. doi: 10.1007/s11096-021-01360-w [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Goldstick JE, Guy GP, Losby JL, Baldwin G, Myers M, Bohnert ASB. Changes in initial opioid prescribing practices after the 2016 release of the CDC guideline for prescribing opioids for chronic pain. JAMA Netw Open. 2021;4(7):e2116860. doi: 10.1001/jamanetworkopen.2021.16860 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Dowell D, Haegerich T, Chou R. No shortcuts to safer opioid prescribing. N Engl J Med. 2019;380(24):2285-2287. doi: 10.1056/NEJMp1904190 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Centers for Disease Control and Prevention . Sickle cell disease. Updated October 3, 2023. Accessed July 14, 2023. https://www.cdc.gov/ncbddd/sicklecell/index.html
9.Mangla A, Ehsan M, Agarwal N, et al. Sickle cell anemia. StatPearls. Updated September 4, 2023. Accessed November 24, 2023. https://www-ncbi-nlm-nih-gov.ezproxy.lib.utexas.edu/books/NBK482164/
10.Ballas SK, Gupta K, Adams-Graves P. Sickle cell pain: a critical reappraisal. Blood. 2012;120(18):3647-3656. doi: 10.1182/blood-2012-04-383430 [DOI] [PubMed] [Google Scholar]
11.National Heart, Lung, and Blood Institute . Evidence-based management of sickle cell disease: expert panel report, 2014. Accessed July 14, 2023. https://www.nhlbi.nih.gov/sites/default /files/media/docs/sickle-cell-disease-report%20020816_0.pdf
12.National Institute for Health and Care Excellence . Sickle cell disease: managing acute painful episodes in hospital. June 27, 2012. Accessed July 14, 2023. https://www.nice.org.uk/guidance /cg143
13.Rees DC, Olujohungbe AD, Parker NE, Stephens AD, Telfer P, Wright J; British Committee for Standards in Haematology General Haematology Task Force by the Sickle Cell Working Party . Guidelines for the management of the acute painful crisis in sickle cell disease. Br J Haematol. 2003;120(5):744-752. doi: 10.1046/j.1365-2141.2003.04193.x [DOI] [PubMed] [Google Scholar]
14.Brousseau DC, Panepinto JA, Nimmer M, Hoffmann RG. The number of people with sickle-cell disease in the United States: national and state estimates. Am J Hematol. 2010;85(1):77-78. doi: 10.1002/ajh.21570 [DOI] [PubMed] [Google Scholar]
15.Joynt M, Train MK, Robbins BW, Halterman JS, Caiola E, Fortuna RJ. The impact of neighborhood socioeconomic status and race on the prescribing of opioids in emergency departments throughout the United States. J Gen Intern Med. 2013;28(12):1604-1610. doi: 10.1007/s11606-013-2516-z [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Sinha CB, Bakshi N, Ross D, Krishnamurti L. Management of chronic pain in adults living with sickle cell disease in the era of the opioid epidemic: a qualitative study. JAMA Netw Open. 2019;2(5):e194410. doi: 10.1001/jamanetworkopen.2019.4410 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.National Comprehensive Cancer Network, American Society of Clinical Oncology, American Society of Hematology . Letter to CDC. February 13, 2019. Accessed July 14, 2023. https://old-prod.asco.org/sites/new-www.asco.org/files/content-files/advocacy-and-policy/documents/2019-NCCN-ASCO-ASH-Letter-CDC.pdf
18.Centers for Disease Control and Prevention . CDC opioid guideline clarification letter. February 28, 2019. Accessed July 14, 2023. https://www.asco.org/sites/new-www.asco.org/files/content-files/advocacy-and-policy/documents/2019-CDC-Opioid-Guideline-Clarification-Letter-to-ASCO-ASH-NCCN.pdf
19.Enos G. Medical leaders: CDC must revise 2016 opioid guideline. Alcohol Drug Abus Wkly. 2019;32(26):1-8. doi: 10.1002/adaw.32764 [DOI] [Google Scholar]
20.Adams K, Guerra M. Unintended consequences of United States chronic pain guidelines. Int J Clin Pharm. 2021;43(2):313-317. doi: 10.1007/s11096-020-01129-7 [DOI] [PubMed] [Google Scholar]
21.Rubin R. Limits on opioid prescribing leave patients with chronic pain vulnerable. JAMA. 2019;321(21):2059-2062. doi: 10.1001/jama.2019.5188 [DOI] [PubMed] [Google Scholar]
22.Dowell D, Ragan KR, Jones CM, Baldwin GT, Chou R. CDC Clinical Practice Guideline for Prescribing Opioids for Pain—United States, 2022. MMWR Recomm Rep. 2022;71(3):1-95. doi: 10.15585/mmwr.rr7103a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147(8):573-577. doi: 10.7326/0003-4819-147-8-200710160-00010 [DOI] [PubMed] [Google Scholar]
24.Chronic Conditions Warehouse . Other chronic health, mental health, and potentially disabling conditions algorithms: sickle cell disease. Updated February 2022. Accessed July 14, 2023. https://www2.ccwdata.org/documents/10280/19140001/oth-cond-algo-scd.pdf
25.Centers for Disease Control and Prevention . File of national drug codes for opioid analgesics, and linked oral morphine milligram equivalent conversion factors. 2020. Accessed February 12, 2024. https://www.cdc.gov/opioids/data-resources/index.html
26.Lopez Bernal J, Cummins S, Gasparrini A. The use of controls in interrupted time series studies of public health interventions. Int J Epidemiol. 2018;47(6):2082-2093. doi: 10.1093/ije/dyy135 [DOI] [PubMed] [Google Scholar]
27.Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J. 2015;15(2):480-500. doi: 10.1177/1536867X1501500208 [DOI] [Google Scholar]
28.Jeffery MM, Hooten WM, Jena AB, Ross JS, Shah ND, Karaca-Mandic P. Rates of physician coprescribing of opioids and benzodiazepines after the release of the Centers for Disease Control and Prevention guidelines in 2016. JAMA Netw Open. 2019;2(8):e198325. doi: 10.1001/jamanetworkopen.2019.8325 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Chen Y, Spillane S, Shiels MS, et al. Trends in opioid use among cancer patients in the United States: 2013-2018. J Natl Cancer Inst Cancer Spectr. 2021;6(1):pkab095. doi: 10.1093/jncics/pkab095 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Hu X, Brock KE, Effinger KE, et al. Changes in opioid prescriptions and potential misuse and substance use disorders among childhood cancer survivors following the 2016 opioid prescribing guideline. JAMA Oncol. 2022;8(11):1658-1662. doi: 10.1001/jamaoncol.2022.3744 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Sutherland TN, Wunsch H, Pinto R, et al. Association of the 2016 US Centers for Disease Control and Prevention opioid prescribing guideline with changes in opioid dispensing after surgery. JAMA Netw Open. 2021;4(6):e2111826. doi: 10.1001/jamanetworkopen.2021.11826 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Langnas E, Bishara A, Croci R, et al. Opioid prescribing practices at hospital discharge for surgical patients before and after the Centers for Disease Control and Prevention’s 2016 opioid prescribing guideline. BMC Anesthesiol. 2022;22(1):141. doi: 10.1186/s12871-022-01678-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Forma Therapeutics . Sickle cell disease trend report: the state of transition. 2021. Accessed July 14, 2023. https://formabridge.com/pdf/Forma_Sickle_Cell_Disease_Trend_Report-The_State_of_Transition.pdf
34.Creary SE, Chisolm DJ, Wrona SK, Cooper JN. Opioid prescription filling trends among children with sickle cell disease after the release of state-issued guidelines on pain management. Pain Med. 2020;21(10):2583-2592. doi: 10.1093/pm/pnaa002 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299-309. doi: 10.1046/j.1365-2710.2002.00430.x [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

eFigure 1. Study timeframe and interrupted time-series segments

eFigure 6. Rate of hospitalizations with and without a vaso-occlusive crisis before and after release of the CDC’s Guideline for Prescribing Opioids for Chronic Pain in March 2016

eTable 1. Operational definition of study variables

eTable 2. Study population attrition

jamainternmed-e238538-s001.pdf^{(1.4MB, pdf)}

Supplement 2.

Data Sharing Statement

jamainternmed-e238538-s002.pdf^{(13.3KB, pdf)}

[ioi230110r1] 1.Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain—United States, 2016. MMWR Recomm Rep. 2016;65(1):1-49. doi: 10.15585/mmwr.rr6501e1 [DOI] [PubMed] [Google Scholar]

[ioi230110r2] 2.Bohnert ASB, Guy GP Jr, Losby JL. Opioid prescribing in the United States before and after the Centers for Disease Control and Prevention’s 2016 opioid guideline. Ann Intern Med. 2018;169(6):367-375. doi: 10.7326/M18-1243 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r3] 3.Dayer LE, Breckling MN, Kling BS, Lakkad M, McDade ER, Painter JT. Association of the CDC Guideline for Prescribing Opioids for Chronic Pain with emergency department opioid prescribing. J Emerg Med. 2019;57(5):597-602. doi: 10.1016/j.jemermed.2019.07.016 [DOI] [PubMed] [Google Scholar]

[ioi230110r4] 4.Townsend T, Cerdá M, Bohnert A, Lagisetty P, Haffajee RL. CDC guideline for opioid prescribing associated with reduced dispensing to certain patients with chronic pain. Health Aff (Millwood). 2021;40(11):1766-1775. doi: 10.1377/hlthaff.2021.00135 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r5] 5.Togun AT, Mandic PK, Wurtz R, Jeffery MM, Beebe T. Association of opioid fills with Centers for Disease Control and Prevention opioid guidelines and payer coverage policies: physician, insurance and geographic factors. Int J Clin Pharm. 2022;44(2):428-438. doi: 10.1007/s11096-021-01360-w [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r6] 6.Goldstick JE, Guy GP, Losby JL, Baldwin G, Myers M, Bohnert ASB. Changes in initial opioid prescribing practices after the 2016 release of the CDC guideline for prescribing opioids for chronic pain. JAMA Netw Open. 2021;4(7):e2116860. doi: 10.1001/jamanetworkopen.2021.16860 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r7] 7.Dowell D, Haegerich T, Chou R. No shortcuts to safer opioid prescribing. N Engl J Med. 2019;380(24):2285-2287. doi: 10.1056/NEJMp1904190 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r8] 8.Centers for Disease Control and Prevention . Sickle cell disease. Updated October 3, 2023. Accessed July 14, 2023. https://www.cdc.gov/ncbddd/sicklecell/index.html

[ioi230110r9] 9.Mangla A, Ehsan M, Agarwal N, et al. Sickle cell anemia. StatPearls. Updated September 4, 2023. Accessed November 24, 2023. https://www-ncbi-nlm-nih-gov.ezproxy.lib.utexas.edu/books/NBK482164/

[ioi230110r10] 10.Ballas SK, Gupta K, Adams-Graves P. Sickle cell pain: a critical reappraisal. Blood. 2012;120(18):3647-3656. doi: 10.1182/blood-2012-04-383430 [DOI] [PubMed] [Google Scholar]

[ioi230110r11] 11.National Heart, Lung, and Blood Institute . Evidence-based management of sickle cell disease: expert panel report, 2014. Accessed July 14, 2023. https://www.nhlbi.nih.gov/sites/default /files/media/docs/sickle-cell-disease-report%20020816_0.pdf

[ioi230110r12] 12.National Institute for Health and Care Excellence . Sickle cell disease: managing acute painful episodes in hospital. June 27, 2012. Accessed July 14, 2023. https://www.nice.org.uk/guidance /cg143

[ioi230110r13] 13.Rees DC, Olujohungbe AD, Parker NE, Stephens AD, Telfer P, Wright J; British Committee for Standards in Haematology General Haematology Task Force by the Sickle Cell Working Party . Guidelines for the management of the acute painful crisis in sickle cell disease. Br J Haematol. 2003;120(5):744-752. doi: 10.1046/j.1365-2141.2003.04193.x [DOI] [PubMed] [Google Scholar]

[ioi230110r14] 14.Brousseau DC, Panepinto JA, Nimmer M, Hoffmann RG. The number of people with sickle-cell disease in the United States: national and state estimates. Am J Hematol. 2010;85(1):77-78. doi: 10.1002/ajh.21570 [DOI] [PubMed] [Google Scholar]

[ioi230110r15] 15.Joynt M, Train MK, Robbins BW, Halterman JS, Caiola E, Fortuna RJ. The impact of neighborhood socioeconomic status and race on the prescribing of opioids in emergency departments throughout the United States. J Gen Intern Med. 2013;28(12):1604-1610. doi: 10.1007/s11606-013-2516-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r16] 16.Sinha CB, Bakshi N, Ross D, Krishnamurti L. Management of chronic pain in adults living with sickle cell disease in the era of the opioid epidemic: a qualitative study. JAMA Netw Open. 2019;2(5):e194410. doi: 10.1001/jamanetworkopen.2019.4410 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r17] 17.National Comprehensive Cancer Network, American Society of Clinical Oncology, American Society of Hematology . Letter to CDC. February 13, 2019. Accessed July 14, 2023. https://old-prod.asco.org/sites/new-www.asco.org/files/content-files/advocacy-and-policy/documents/2019-NCCN-ASCO-ASH-Letter-CDC.pdf

[ioi230110r18] 18.Centers for Disease Control and Prevention . CDC opioid guideline clarification letter. February 28, 2019. Accessed July 14, 2023. https://www.asco.org/sites/new-www.asco.org/files/content-files/advocacy-and-policy/documents/2019-CDC-Opioid-Guideline-Clarification-Letter-to-ASCO-ASH-NCCN.pdf

[ioi230110r19] 19.Enos G. Medical leaders: CDC must revise 2016 opioid guideline. Alcohol Drug Abus Wkly. 2019;32(26):1-8. doi: 10.1002/adaw.32764 [DOI] [Google Scholar]

[ioi230110r20] 20.Adams K, Guerra M. Unintended consequences of United States chronic pain guidelines. Int J Clin Pharm. 2021;43(2):313-317. doi: 10.1007/s11096-020-01129-7 [DOI] [PubMed] [Google Scholar]

[ioi230110r21] 21.Rubin R. Limits on opioid prescribing leave patients with chronic pain vulnerable. JAMA. 2019;321(21):2059-2062. doi: 10.1001/jama.2019.5188 [DOI] [PubMed] [Google Scholar]

[ioi230110r22] 22.Dowell D, Ragan KR, Jones CM, Baldwin GT, Chou R. CDC Clinical Practice Guideline for Prescribing Opioids for Pain—United States, 2022. MMWR Recomm Rep. 2022;71(3):1-95. doi: 10.15585/mmwr.rr7103a1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r23] 23.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147(8):573-577. doi: 10.7326/0003-4819-147-8-200710160-00010 [DOI] [PubMed] [Google Scholar]

[ioi230110r24] 24.Chronic Conditions Warehouse . Other chronic health, mental health, and potentially disabling conditions algorithms: sickle cell disease. Updated February 2022. Accessed July 14, 2023. https://www2.ccwdata.org/documents/10280/19140001/oth-cond-algo-scd.pdf

[ioi230110r25] 25.Centers for Disease Control and Prevention . File of national drug codes for opioid analgesics, and linked oral morphine milligram equivalent conversion factors. 2020. Accessed February 12, 2024. https://www.cdc.gov/opioids/data-resources/index.html

[ioi230110r26] 26.Lopez Bernal J, Cummins S, Gasparrini A. The use of controls in interrupted time series studies of public health interventions. Int J Epidemiol. 2018;47(6):2082-2093. doi: 10.1093/ije/dyy135 [DOI] [PubMed] [Google Scholar]

[ioi230110r27] 27.Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J. 2015;15(2):480-500. doi: 10.1177/1536867X1501500208 [DOI] [Google Scholar]

[ioi230110r28] 28.Jeffery MM, Hooten WM, Jena AB, Ross JS, Shah ND, Karaca-Mandic P. Rates of physician coprescribing of opioids and benzodiazepines after the release of the Centers for Disease Control and Prevention guidelines in 2016. JAMA Netw Open. 2019;2(8):e198325. doi: 10.1001/jamanetworkopen.2019.8325 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r29] 29.Chen Y, Spillane S, Shiels MS, et al. Trends in opioid use among cancer patients in the United States: 2013-2018. J Natl Cancer Inst Cancer Spectr. 2021;6(1):pkab095. doi: 10.1093/jncics/pkab095 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r30] 30.Hu X, Brock KE, Effinger KE, et al. Changes in opioid prescriptions and potential misuse and substance use disorders among childhood cancer survivors following the 2016 opioid prescribing guideline. JAMA Oncol. 2022;8(11):1658-1662. doi: 10.1001/jamaoncol.2022.3744 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r31] 31.Sutherland TN, Wunsch H, Pinto R, et al. Association of the 2016 US Centers for Disease Control and Prevention opioid prescribing guideline with changes in opioid dispensing after surgery. JAMA Netw Open. 2021;4(6):e2111826. doi: 10.1001/jamanetworkopen.2021.11826 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r32] 32.Langnas E, Bishara A, Croci R, et al. Opioid prescribing practices at hospital discharge for surgical patients before and after the Centers for Disease Control and Prevention’s 2016 opioid prescribing guideline. BMC Anesthesiol. 2022;22(1):141. doi: 10.1186/s12871-022-01678-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r33] 33.Forma Therapeutics . Sickle cell disease trend report: the state of transition. 2021. Accessed July 14, 2023. https://formabridge.com/pdf/Forma_Sickle_Cell_Disease_Trend_Report-The_State_of_Transition.pdf

[ioi230110r34] 34.Creary SE, Chisolm DJ, Wrona SK, Cooper JN. Opioid prescription filling trends among children with sickle cell disease after the release of state-issued guidelines on pain management. Pain Med. 2020;21(10):2583-2592. doi: 10.1093/pm/pnaa002 [DOI] [PMC free article] [PubMed] [Google Scholar]

[ioi230110r35] 35.Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27(4):299-309. doi: 10.1046/j.1365-2710.2002.00430.x [DOI] [PubMed] [Google Scholar]

PERMALINK

Opioid Prescribing and Outcomes in Patients With Sickle Cell Disease Post–2016 CDC Guideline

Hyeun Ah Kang, PhD

Bofei Wang, PhD

Jamie C Barner, PhD

Kenneth I Ataga, MD

Robert C Mignacca, MD

Alicia Chang, MD

Yahan Zhang, MS

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposure

Main Outcomes and Measures

Results

Conclusions and Relevance

Introduction

Methods

Study Design and Data Source

Study Population

Outcomes

Statistical Analysis

Sensitivity Analysis

Results

Table 1. Demographic Characteristics of Study Population.

Trend Changes in Opioid Prescription Fills

Table 2. Interrupted Time Series Regression Analysis of Opioid Prescription Fills and Health Outcomes.

Figure 1. Opioid Prescription Patterns Among Individuals With Sickle Cell Disease Before and After 2016 CDC Guideline.

Trend Changes in Health Outcomes Associated With Pain Management

Figure 2. Pain-Related Health Outcomes Among Individuals With Sickle Cell Disease Before and After 2016 CDC Guideline.

Age-Related Changes in Opioid Prescription Fills and Health Outcomes

Figure 3. Opioid Prescription Fills and Pain-Related Health Outcomes Among Pediatric and Adult Patients With Sickle Cell Disease Before and After 2016 CDC Guideline.

Sensitivity Analysis

Discussion

Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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