Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-23T07:26:36.522Z Has data issue: false hasContentIssue false

Trends in the incidence of Clostridioides difficile infection in adults and the elderly insured by Medicaid compared to commercial insurance or Medicare only

Published online by Cambridge University Press:  09 September 2022

Margaret A. Olsen*
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri Department of Surgery, Washington University School of Medicine, St Louis, Missouri
Dustin Stwalley
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri
Andrew D. Tipping
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri
Matthew R. Keller
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri
Holly Yu
Affiliation:
Pfizer, Inc, Pearl River, New York (Present affiliation: Missouri Institute of Mental Health, St Louis, Missouri [A.D.T.])
Erik R. Dubberke*
Affiliation:
Department of Medicine, Washington University School of Medicine, St Louis, Missouri
*
Author for correspondence: Margaret A. Olsen, E-mail: [email protected]. Or Erik R. Dubberke, E-mail: [email protected]
Author for correspondence: Margaret A. Olsen, E-mail: [email protected]. Or Erik R. Dubberke, E-mail: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Objective:

Few data are available to quantify the Clostridioides difficile infection (CDI) burden in US adults depending on Medicaid insurance status; thus, we sought to contribute to this body of information.

Methods:

Retrospective cohort study to identify adults with codes for CDI from 2011 to 2017 in MarketScan commercial and Medicaid databases (for those aged 25–64 years) and the CMS Medicare database (for those aged ≥65 years). CDI was categorized as healthcare-facility–associated (HCA-CDI) and community-associated CDI (CA-CDI). CDI incidence rates were compared by year, insurer, and age group.

Results:

The overall CDI incidence in the elderly was 3.1-fold higher in persons insured by Medicare plus Medicaid than in those insured by Medicare only (1,935 vs 618 per 100,000 person years (PY)), and the CDI incidence was 2.7-fold higher in younger adults with Medicaid compared to commercial insurance (195 vs 73 per 100,000 PY). From 2011 to 2017, HCA-CDI rates declined in the younger Medicaid population (124.0 to 95.2 per 100,000 PY; P < .001) but were stable in those commercially insured (25.9 to 24.8 per 100,000 PY; P = .33). In the elderly HCA-CDI rates declined from 2011 to 2017 in the Medicare-only population (403 to 318 per 100,000 PY; P < .001) and the Medicare plus Medicaid population (1,770 to 1,163 per 100,000 PY; P < .002). Persons with chronic medical conditions and those with immunocompromising conditions insured by Medicaid had 2.8- and 2.7-fold higher CDI incidence compared to the commercially insured population, respectively. The incidence of CDI was lowest in Medicaid and commercially insured younger adults without chronic medical or immunosuppressive conditions (67.5 and 45.6 per 100,000 PY, respectively).

Conclusions:

Although HCA-CDI incidence decreased from 2011 to 2017 in elderly and younger adults insured by Medicaid, the burden of CDI remains much higher in low-income adults insured by Medicaid.

Type
Original Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

Clostridioides difficile is the most common cause of healthcare-associated infection and is increasingly recognized as an important pathogen in the community. Reference Magill, Edwards and Bamberg1 Using laboratory data from 10 states participating in the Emerging Infections Program (EIP), the Centers for Disease Control and Prevention (CDC) estimates that there were >462,000 cases of C. difficile infection (CDI) in 2017. Reference Guh, Mu and Winston2 CDI is associated with increased risk for hospitalization, skilled nursing care, long-term care facility transfer, healthcare costs, and death. Reference Olsen, Stwalley, Demont and Dubberke3Reference Kwon, Olsen and Dubberke6 Much remains unknown regarding risk for CDI in younger adults because most studies focus on infection in the elderly. In addition, few data are available regarding the risk of CDI in adults insured by the Medicaid program, who have higher comorbidity burden compared to adults in general. Reference Chapel, Ritchey, Zhang and Wang7,Reference Boersma and Ward8 A better understanding of CDI burden in younger adults and in those insured by Medicaid is needed to develop newer prevention strategies that can be applied not only to the elderly but also to younger and medically vulnerable adults. Reference Guh, Adkins and Li9,Reference Czepiel, Drozdz and Pituch10

The IBM® MarketScan® commercial database and the multistate Medicaid database include inpatient and outpatient medical claims that can be used to study persons aged <65 years. The Chronic Condition Warehouse database contains medical claims for persons enrolled in fee-for-service Medicare plans. We used these data to determine CDI incidence based on type of health insurance in US adults from 2011 to 2017.

Methods

We conducted a retrospective cohort study using the 2010–2017 Medicare Chronic Condition Warehouse 5% random sample and the IBM MarketScan commercial and multistate Medicaid databases. Eligibility criteria for the MarketScan populations included those aged 25–64 years and for the Medicare population those aged ≥65 and older with Parts A and B fee-for-service enrollment and no health maintenance organization enrollment. Persons with continuous enrollment in Medicare but no claims during the study period were excluded to ensure that persons were alive and using their health benefits.

Patients coded for CDI from 2011 to 2017 were identified using International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis code 008.45 and ICD-10-CM diagnosis codes A04.71 and A04.72 in the inpatient, outpatient services, or facility header files (MarketScan), and the inpatient, outpatient, carrier (ie, physician) or skilled nursing facility files (Medicare). The date of CDI onset was defined as the first date with a coded diagnosis of CDI, unless coding for diarrhea or claims for bacterial stool cultures or C. difficile testing were available to define earlier onset. Reference Dubberke, Olsen and Stwalley11 To avoid misclassification of recurrent CDI as an incident case, at least 84 consecutive days without coding for CDI was required to be eligible for another incident CDI episode.

The MarketScan and Medicare populations were divided into groups based on enrollment in Medicaid using dual status indicators in the Medicare data. CDI episodes were categorized as healthcare-associated CDI (HCA-CDI, including hospital-onset, other facility onset, healthcare facility associated, and indeterminate classification) or community-associated CDI (CA-CDI) using standard surveillance definitions, Reference Cohen, Gerding and Johnson12 as described previously. Reference Olsen, Young-Xu and Stwalley13 Long-term care facility stay was identified in the Medicare data using the Centers for Medicare & Medicaid Services Minimum Data Set version 3.0 assessment of nursing home patients. For the MarketScan data, we used a validated algorithm to identify residents of long-term care facilities. Reference Yun, Kilgore and Curtis14 We categorized CDI as hospitalized if CDI was coded during a hospitalization, or nonhospitalized if CDI was diagnosed and treated solely outside a hospitalization.

To determine subgroups at higher risk of CDI in the MarketScan population, we calculated 1-year CDI incidence rates from 2012 to 2017 based on coding for chronic medical, immunocompromising, or neither chronic medical nor immunocompromising conditions in the first year of insurance enrollment beginning in 2011. Reference Elixhauser, Steiner, Harris and Coffey15,Reference Klabunde, Potosky, Legler and Warren16 Chronic medical and immunosuppressive conditions included those identified as indications for pneumococcal vaccination in nonelderly adults. 17 In calculations of CDI incidence, individuals coded for both chronic medical and immunocompromising conditions were counted only in the immunocompromising category.

Statistical analysis

CDI incidence rates were calculated using all person years (PY) of observation from 2011 to 2017 and individually for each year by insurer and by age group. Comparisons of incidence rates by age group and year were performed using PROC Genmod in SAS software (SAS Institute, Cary, NC) with Poisson link and offset using log(PY). Reference Chu18 Tests for linear trend were performed using PROC GLM. Comparisons of incidence rates between commercially insured and Medicaid-insured individuals were performed using MedCalc version 20.018 software (MedCalc Software, Ostend, Belgium).

The prevalence of chronic medical and immunosuppressive conditions in the MarketScan Medicaid population compared to the commercially insured population was determined using 2 one-sided t tests (TOST) in SAS software using PROC TTEST. The null hypothesis for the TOST test is that prevalence values are different; thus, a significant result indicates equivalence. We used equivalence ranges of ±2.5% and ±5.0% for conditions with prevalence <10% and >10%, respectively. Reference Tatem, Romo and McVeigh19

Results

From 2011 to 2017, 78,166 CDI episodes were identified in 71,668 elderly persons in the Medicare data, for an overall incidence of 798 per 100,000 PY. Of these, 52,242 episodes occurred in persons insured by Medicare only and 25,924 in persons dually insured by Medicare plus Medicaid. Approximately 27% of the younger Medicaid population were Black. In the elderly population, 14% of persons insured by Medicare plus Medicaid were Black compared to 4.5% of the Medicare-only population (Table 1). The overall CDI incidence from 2011 to 2017 was 618 per 100,000 PY in persons insured by Medicare alone, and the CDI incidence was 3.1-fold higher (1,935 per 100,000 PY) in persons dually insured by Medicare plus Medicaid (P < .001). In the same period, 102,240 CDI episodes were identified in 90,587 persons aged 25–64 years in the MarketScan commercial database, and 28,024 episodes in 24,047 persons were identified in the Medicaid database. The overall incidence from 2011 to 2017 in younger adults was 73 per 100,000 PY in the commercially insured population and was 2.7-fold higher (195 per 100,000 PY) in those insured by Medicaid (P <.001). CDI incidence by year and Medicaid status for the 2 populations are shown in Supplementary Table 1 (online).

Table 1. Characteristics of Patients with CDI, 2011–2017, by Medicaid Status

Note. CDI, Clostridioides difficile infection; N/A, not available.

a Healthcare associated CDI using the strict definition of HCA-CDI (healthcare-facility-onset CDI) or community-onset CDI (CA-CDI) with patient discharged from a healthcare facility in the prior 4 weeks.

b Indeterminate CDI was defined as community-onset CDI and patient was discharged from a healthcare facility within the prior 4–12 weeks.

Incidence of healthcare- and community-associated CDI

The HCA-CDI rate declined significantly from 2011 to 2017 in the MarketScan Medicaid population (124.0 to 95.2 per 100,000 PY; P = .028), but it remained stable in the commercially insured population (25.9 to 24.8 per 100,000 PY; P = .85) (Fig. 1A and Supplementary Table 2 online). The percentage of CDI cases categorized as HCA decreased from 67.6% to 56.8% in those insured by Medicaid and from 42.5% to 31.6% in the commercially insured population (Supplementary Fig. 1 online). In the Medicare population, HCA-CDI rates declined significantly from 2011 to 2017 in both the Medicare-only population (403 to 318 per 100,000 PY; P < .001) and the Medicare plus Medicaid population (1,770 to 1,163 per 100,000 PY; P = .002) (Fig. 1B and Supplementary Table 2 online). CA-CDI rates increased slightly from 2011 to 2017 in the MarketScan Medicaid population (59.4 to 72.5 per 100,000 PY; P = .14) but more substantially in the commercially insured population (35.0 to 53.7 per 100,000 PY; P = .003) (Fig. 1C and Supplementary Table 2 online). CA-CDI rates increased significantly in the Medicare-only population (197 to 297 per 100,000 PY; P < .001) but did not change in the Medicare plus Medicaid population from 2011 to 2017 (347 to 358 per 100,000 PY; P = .62) (Fig. 1D and Supplementary Table 2 online).

Fig. 1. Healthcare-associated and community-associated CDI rates per 100,000 person years of observation, 2011–2017. (A) MarketScan aged 25–64 years, healthcare-associated CDI. (B) Medicare aged ≥65 years, healthcare-associated CDI. (C) MarketScan aged 25–64 years, community-associated CDI. (D) Medicare aged ≥65 years, community-associated CDI.

Incidence of healthcare- and community-associated CDI by age group

Incidence rates of HCA-CDI from 2011 and 2017 by age group are shown in Fig. 2 and Supplementary Table 3 (online). The incidence of HCA-CDI increased significantly with age in younger and elderly persons insured by Medicaid. The HCA-CDI incidence rates were lowest in commercially insured younger adults in all years. The reduction in HCA incidence in those insured by Medicaid from 2011 to 2017 was most pronounced in the older age groups in both the younger adult population (aged 50–64 years) and the elderly population (aged ≥75 years).

Fig. 2. Healthcare-associated CDI rates, 2011–2017, by age group and insurer. (A) MarketScan aged 25–64 years. (B) Medicare aged ≥65 years.

Rates of CA-CDI increased with age in younger commercially insured and Medicaid-insured adults and in elderly persons insured by Medicare only (Fig. 3 and Supplementary Table 4 online). Although CA-CDI rates increased with age in older Medicare-plus-Medicaid dually insured adults, the trend of increasing rates with age was not significant from 2014 to 2016.

Fig. 3. Community-associated CDI rates, 2011–2017, by age group and insurer. (A) MarketScan aged 25–64 years. (B) Medicare aged ≥65 years.

Incidence of CDI treated during a hospitalization

Rates of CDI treated in the hospital in the younger Medicaid-insured MarketScan population decreased from 151.9 in 2011 to 116.8 per 100,000 PY in 2017 (P = .022). In contrast, rates of CDI treated in the hospital in the commercially insured population were stable from 2011 to 2017 (35.8 to 36.6 per 100,000 PY, respectively; P = 0.28). In the Medicare plus Medicaid population, rates of CDI treated in the hospital decreased significantly from 2011 to 2017 (1,201 to 778 per 100,000; P = .004), and rates of CDI treated in the hospital in the Medicare-only population decreased from 363 to 299 per 100,000 PY during this period (P = .007) (Supplementary Fig. 2 online and Supplementary Table 5 online).

Incidence of CDI in younger adults with and without chronic medical and immunosuppressive conditions

To further investigate disease burden in the younger MarketScan population by payer we determined the CDI incidence in persons with codes for chronic medical and immunocompromised conditions and the prevalence of those conditions. For comparison, we determined CDI incidence in persons with neither chronic medical nor immunocompromised conditions.

The prevalence of chronic medical conditions was 17.2% in persons aged 25–64 insured by Medicaid compared to 8.6% in the commercially insured population (nonequivalent, 5% threshold). The prevalence of immunocompromising conditions was slightly higher but equivalent in persons insured by Medicaid compared to those who were commercially insured (4.7% and 3.6%, respectively). The prevalence of chronic medical conditions increased progressively with age and were 2.2- to 2.8-fold higher in the Medicaid population compared to the commercially insured population (Fig. 4). The prevalence of immunocompromising conditions was similar in those aged 25–34 years, but this prevalence increased with age more in the MarketScan Medicaid than in commercially insured persons. The Medicaid-to-private prevalence ratios were 1.9 and 1.8 in the 2 older age groups (Fig. 4).

Fig. 4. Prevalence of chronic medical and immunocompromising conditions with age, Marketscan aged 25–64 years.

The CDI incidence in those with chronic medical conditions was 2.8-fold higher in persons insured by Medicaid compared to those who were commercially insured (432.7 vs 156.1 PY; P < .001) (Table 2). Similarly, the incidence of CDI was 2.7-fold higher in persons insured by Medicaid with an immunocompromising condition(s) compared to commercially insured persons (1,359.9 vs 504 PY; P < .001) (Table 2). The incidence of CDI was much lower in persons with neither a chronic medical nor immunocompromised condition in both the Medicaid-insured and commercially insured populations (67.6 and 45.6 per 100,000 PY, respectively). CDI incidence rates for all individual conditions were significantly higher in persons with Medicaid compared to commercial insurance (Table 2).

Table 2. One-Year Incidence of CDI Per 100,000 Person Years from 2012 to 2017 in Persons Aged 25-64 Years with Commercial or Medicaid Health Insurance By Coding for Immunocompetent and Immunocompromising Conditions During their First Year of Enrollment a

Note. CDI, Clostridioides difficile infection; IRR, incidence rate ratio; AIDS, acquired immune-deficiency syndrome.

a The first year of enrollment in the commercial or Medicaid database, 2011–2017.

b All comparisons of incidence rates between commercially insured and Medicaid-insured persons were significant with P < .001, except cystic fibrosis (P = .025) and nephrotic syndrome (P = .002).

CDI incidence in persons with chronic medical conditions increased significantly with age (P = .002 in commercially insured and P < .001 in the Medicaid insured), although CDI incidence in all ages was higher in the Medicaid-insured population than in the commercially insured population, ranging from 2.3- to 3.6-fold (Fig. 5). In contrast, CDI incidence in those with immunocompromised conditions increased slightly with age in the Medicaid population (P = .05) but was stable with increasing age in the commercially insured (P = .70). As with chronic medical conditions, the incidence of CDI was much higher in the Medicaid population compared to commercially insured persons with immunocompromised conditions in all age groups, ranging from 2.0- to 3.2-fold. Although CDI incidence increased with age in both commercially insured persons and Medicaid-insured persons with neither chronic medical nor immunocompromising conditions (both P < .001), the incidence rate ratio (IRR) in those aged 60–64 years versus 25–29 years was greater in those insured by Medicaid (IRR, 3.7) than in the commercially insured population (IRR, 2.5) (Fig. 5).

Fig. 5. One-year incidence of CDI per 100,000 person years from 2012 to 2017 based on prevalence of chronic medical conditions, immunocompromised conditions, and neither conditions in the MarketScan commercial and Medicaid populations by age group.

Discussion

In this study, the overall burden of CDI from 2011 to 2017 was 3-fold higher in lower-income US elderly persons dually insured by Medicare plus Medicaid compared to elderly persons insured by Medicare only. The CDI burden was 2.7-fold higher in the younger population of Medicaid recipients compared to those privately insured. The yearly incidence of CDI declined substantially in elderly persons insured by Medicare plus Medicaid, with a smaller decline in younger persons insured by Medicaid, due to decreases in HCA-CDI. Similarly, rates of CDI resulting in a hospitalization declined by ∼33% from 2011 to 2017 in both younger and elderly persons insured by Medicaid, with a smaller decrease in older persons insured by Medicare only. In younger commercially insured persons and in elderly persons with Medicare insurance only, CA-CDI rates increased ∼50% from 2011 to 2017. CA-CDI incidence also increased ∼20% in younger adults with Medicaid insurance but remained relatively stable in the elderly insured by Medicare plus Medicaid.

A higher risk of CDI in elderly persons dually insured with Medicaid, an indicator of low socioeconomic status, has been reported previously. Reference Olsen, Stwalley, Demont and Dubberke3 Using New Mexico EIP data, Hudspeth et al Reference Hudspeth, Qeadan and Phipps20 found higher incidence of community-acquired CDI in census tracts with a higher proportion of uninsured persons and in Black and American Indian/Native Alaskan men and women. Using 2014–2015 EIP data, Skrobarcek et al Reference Skrobarcek, Mu and Ahern21 found higher CA-CDI rates in lower-income US Census tracts and in tracts with a higher percentage of publicly insured persons. Our work expands on these findings by demonstrating higher risk of CDI in both younger and elderly persons insured by Medicaid, including higher risk of HCA-CDI across the age span in persons insured by Medicaid.

To investigate the higher CDI burden in younger adults insured by Medicaid, we determined the prevalence of chronic medical and immunocompromising conditions. The prevalence of chronic medical conditions was almost three-fold higher in adults aged 25–54 years insured by Medicaid than in those who were commercially insured, and the prevalence of immunocompromising conditions was almost 2-fold higher in Medicaid-insured adults aged 45–64 years compared to those who were commercially insured. This finding is consistent with prior reports that >50% of nonelderly adults insured by Medicaid have at least 1 chronic condition, which is higher than the overall burden of chronic conditions in all adults (including the elderly). Reference Chapel, Ritchey, Zhang and Wang7,Reference Boersma and Ward8 In our analyses of CDI burden, the incidence of CDI was almost 3-fold higher in Medicaid-insured younger adults with a chronic medical condition(s) or with an immunocompromising condition compared to commercially insured adults. Medicaid-insured and commercially insured younger adults without a chronic medical or immunocompromising condition had much lower incidence of CDI. The incidence of CDI increased substantially with age in persons with chronic medical conditions, especially in the Medicaid population. The finding of increased burden of CDI in persons with immunocompromising conditions is not surprising; persons with diseases such as leukemia or lymphoma, end-stage renal disease, and others are at high risk of CDI. Reference van Werkhoven, van der Tempel and Jajou22,Reference Ramesh and Yee23 We speculate that the increased burden of CDI in persons with chronic medical conditions, particularly those insured by Medicaid, is likely due to high exposure to antibiotics. Antibiotic utilization is higher in persons with some chronic medical conditions (eg, diabetes, chronic kidney disease, chronic lung disease, including asthma) than in persons without those conditions, Reference Ramesh and Yee23Reference Chang, Fan and Kuo26 even in the absence of documented infection. Reference Fleming-Dutra, Hersh and Shapiro27 The increased antibiotic exposure could explain the increased CDI incidence in these persons, particularly in comparison to those without a chronic medical or immunocompromising condition.

During the same period as our study, CDC EIP surveillance reported a decrease in HCA CDI from 93 to 67 per 100,000 persons and a corresponding increase in CA-CDI from 48 to 63 per 100,000 persons. Reference Guh, Mu and Winston2 A similar increase in CA-CDI occurred in Quebec from 2008 to 2015. Reference Zanichelli, Garenc and Villeneuve28 Consistent with the reported increase in CA-CDI, the proportion of CA-CDI in patients admitted to a Southeastern network hospital increased from 49% in 2013 to 61% in 2017. Reference Turner, Grambow and Woods29 The percentage of CDI categorized as CA-CDI also increased in Veterans’ Administration patients aged 18–64 years, ranging from 41% in 2011 to 56% in 2016, with higher CA-CDI proportions in younger compared to older veterans. Reference Russo, Kuntz and Yu30

We found that the decrease in overall CDI incidence during this period in persons insured by Medicaid was due to decrease in HCA-CDI. In the Medicare-only population, the decline in HCA rates from 2011 to 2017 was offset by the increase in CA-CDI incidence, such that the overall CDI incidence increased slightly. Among persons insured by Medicaid, the decreases in HCA-CDI incidence were most pronounced in the oldest age groups (50–64 years in the younger population and ≥75 years in the elderly). Similarly, the incidence of CDI treated during a hospitalization decreased significantly in persons insured by Medicaid from 2011 to 2017 in both the younger population and the elderly population insured by Medicaid plus Medicare, but it changed only slightly for commercially insured and individuals insured by Medicare only.

The observed decrease in HCA-CDI rates may be due in part to the implementation of antibiotic stewardship programs in US hospitals. By 2017, 76% of acute-care hospitals reported meeting the CDC Core Stewardship Elements, compared to 41% in 2014. Reference Pollack, van Santen, Weiner, Dudeck, Edwards and Srinivasan31,Reference Neuhauser32 Several investigators have reported an association of antibiotic stewardship programs with decreased hospital-onset CDI, Reference Morgan, Belal, Lisa, Ford, LeMaitre and Psevdos33Reference Tamma, Miller and Dullabh35 which may explain the decrease we and others have noted in HCA-CDI in recent years. In contrast, antibiotic stewardship programs have gained much less traction in the outpatient setting, Reference Eudy, Pallotta and Neuner36,37 despite the facts that most antibiotics are prescribed in ambulatory settings and an estimated 30%–50% of these antibiotic prescriptions are considered inappropriate. Reference Fleming-Dutra, Hersh and Shapiro27,Reference Sanchez, Fleming-Dutra, Roberts and Hicks38 We speculate that the increased CA-CDI rates, particularly in younger commercially insured and older persons with only Medicare coverage, may be due to continued overutilization of antibiotics in the community, in addition to increasing use of nucleic acid amplification tests (NAATs), associated with increased CDI test positivity when used as a single test. Reference Polage, Gyorke and Kennedy39 Although NAATs have been increasingly used for CDI testing in hospitals, the widespread implementation of antibiotic stewardship and also diagnostic stewardship programs may have indirectly resulted in less testing for CDI in hospitalized patients, Reference Kang, Abeles and El-Kareh40,Reference Cook, Nichols, Coogan, Opera and DeHart41 contributing to the decrease in HCA-CDI rates observed in our study and by others.

This study had several limitations. We identified CDI using ICD-9/-10 diagnosis codes, which may have resulted in inaccuracy, lack of information on antibiotic utilization in hospitals, and incomplete availability of outpatient prescriptions. The similarity of our overall calculated CDI incidence rates to those reported by the EIP system suggests that inaccuracy in CDI identification based on diagnosis codes was likely minimal. Our analyses of CDI incidence in the elderly were restricted to the fee-for-service population and, thus, may not be generalizable to the elderly insured by Medicare Advantage plans.

The finding of higher risk in Medicaid-insured younger adults with underlying chronic medical conditions and in both commercially and Medicaid-insured younger adults with immunocompromising conditions is particularly important. Heightened awareness of CDI risk and increased emphasis on appropriate utilization of antibiotics are needed in these medically vulnerable persons. Additional broad-based strategies to prevent CDI, including vaccination, are urgently needed to prevent morbidity and mortality, particularly in lower income persons.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.1017/ice.2022.208

Acknowledgments

Financial support

This work was supported by Pfizer. The sponsor participated in study design, interpretation of the data and final review of the manuscript. Access to data and additional services were provided by the Washington University Center for Administrative Data Research, supported in part by the National Center for Advancing Translational Sciences of the National Institutes for Health (grant no. UL1 TR002345).

Conflicts of interest

M.A. Olsen reports receipt of grant funding from Pfizer in the past 36 months and personal fees from Pfizer for consulting work. D. Stwalley reports stock ownership in Abbvie and Bristol-Myers Squibb. E.R. Dubberke reports receipt of grant funding from Pfizer, Synthetic Biologics, and Ferring in the past 36 months and personal fees from Ferring, Rebiotix, Summit, Merck, Pfizer, and Seres. H. Yu is an employee of Pfizer. All other authors report no conflicts of interest related to this article.

Footnotes

PREVIOUS PRESENCATION. The preliminary results of this study were presented at the 31st European Congress of Clinical Microbiology and Infectious Diseases (ECCMID), on July 9–12, 2021, in Vienna, Austria, held virtually.

References

Magill, SS, Edwards, JR, Bamberg, W, et al. Multistate point-prevalence survey of healthcare-associated infections. N Engl J Med 2014;370:11981208.10.1056/NEJMoa1306801CrossRefGoogle Scholar
Guh, AY, Mu, Y, Winston, LG, et al. Trends in US burden of Clostridioides difficile infection and outcomes. N Engl J Med 2020;382:13201330.10.1056/NEJMoa1910215CrossRefGoogle ScholarPubMed
Olsen, MA, Stwalley, D, Demont, C, Dubberke, ER. Clostridium difficile infection increases acute and chronic morbidity and mortality. Infect Control Hosp Epidemiol 2019;40:6571.10.1017/ice.2018.280CrossRefGoogle ScholarPubMed
Nanwa, N, Kwong, JC, Krahn, M, et al. The economic burden of hospital-acquired Clostridium difficile infection: a population-based matched cohort study. Infect Control Hosp Epidemiol 2016;37:10681078.10.1017/ice.2016.122CrossRefGoogle ScholarPubMed
Nanwa, N, Sander, B, Krahn, M, et al. A population-based matched cohort study examining the mortality and costs of patients with community-onset Clostridium difficile infection identified using emergency department visits and hospital admissions. PLoS One 2017;12:e0172410.10.1371/journal.pone.0172410CrossRefGoogle ScholarPubMed
Kwon, JH, Olsen, MA, Dubberke, ER. The morbidity, mortality, and costs associated with Clostridium difficile infection. Infect Dis Clin North Am 2015;29:123134.10.1016/j.idc.2014.11.003CrossRefGoogle ScholarPubMed
Chapel, JM, Ritchey, MD, Zhang, D, Wang, G. Prevalence and medical costs of chronic diseases among adult Medicaid beneficiaries. Am J Prev Med 2017;53(6 suppl 2):S143S154.10.1016/j.amepre.2017.07.019CrossRefGoogle ScholarPubMed
Boersma, P BL, Ward, BW. Prevalence of multiple chronic conditions among US adults, 2018. Prev Chronic Dis 2020;17:200130.10.5888/pcd17.200130CrossRefGoogle ScholarPubMed
Guh, AY, Adkins, SH, Li, Q, et al. Risk factors for community-associated Clostridium difficile infection in adults: a case–control study. Open Forum Infect Dis 2017;4:ofx171.10.1093/ofid/ofx171CrossRefGoogle ScholarPubMed
Czepiel, J, Drozdz, M, Pituch, H, et al. Clostridium difficile infection: review. Eur J Clin Microbiol Infect Dis 2019;38:12111221.10.1007/s10096-019-03539-6CrossRefGoogle Scholar
Dubberke, ER, Olsen, MA, Stwalley, D, et al. Identification of Medicare recipients at highest risk for Clostridium difficile infection in the US by population attributable risk analysis. PLoS One 2016;11:e0146822.10.1371/journal.pone.0146822CrossRefGoogle ScholarPubMed
Cohen, SH, Gerding, DN, Johnson, S, et al. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA). Infect Control Hosp Epidemiol 2010;31:431455.10.1086/651706CrossRefGoogle Scholar
Olsen, MA, Young-Xu, Y, Stwalley, D, et al. The burden of Clostridium difficile infection: estimates of the incidence of CDI from US administrative databases. BMC Infect Dis 2016;16:177.10.1186/s12879-016-1501-7CrossRefGoogle ScholarPubMed
Yun, H, Kilgore, ML, Curtis, JR, et al. Identifying types of nursing facility stays using Medicare claims data: an algorithm and validation. Health Serv Outcomes Res Method 2010;10:100110.10.1007/s10742-010-0060-4CrossRefGoogle Scholar
Elixhauser, A, Steiner, C, Harris, DR, Coffey, RN. Comorbidity measures for use with administrative data. Med Care 1998;36:827.10.1097/00005650-199801000-00004CrossRefGoogle ScholarPubMed
Klabunde, CN, Potosky, AL, Legler, JM, Warren, JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol 2000;53:12581267.10.1016/S0895-4356(00)00256-0CrossRefGoogle ScholarPubMed
Recommended adult immunization schedule, United States, 2019. Centers for Disease Control and Prevention website. https://www.cdc.gov/vaccines/schedules/downloads/adult/adult-combined-schedule.pdf. Accessed October 19, 2020.Google Scholar
Chu, X. Using SAS to calculate incidence and prevalence rates in a dynamic population. Lex Janssen website. https://www.lexjansen.com/wuss/2012/103.pdf. Published 2012. Accessed December 10, 2021.Google Scholar
Tatem, KS, Romo, ML, McVeigh, KH, et al. Comparing prevalence estimates from population-based surveys to inform surveillance using electronic health records. Prev Chronic Dis 2017;14:E44.10.5888/pcd14.160516CrossRefGoogle ScholarPubMed
Hudspeth, WB, Qeadan, F, Phipps, EC. Disparities in the incidence of community-acquired Clostridioides difficile infection: an area-based assessment of the role of social determinants in Bernalillo County, New Mexico. Am J Infect Control 2019;47:773779.10.1016/j.ajic.2018.12.014CrossRefGoogle ScholarPubMed
Skrobarcek, KA, Mu, Y, Ahern, J, et al. Association between socioeconomic status and incidence of community-associated Clostridioides difficile infection—United States, 2014–2015. Clin Infect Dis 2021;73:722725.10.1093/cid/ciab042CrossRefGoogle ScholarPubMed
van Werkhoven, CH, van der Tempel, J, Jajou, R, et al. Identification of patients at high risk for Clostridium difficile infection: development and validation of a risk prediction model in hospitalized patients treated with antibiotics. Clin Microbiol Infect 2015;21:786788.10.1016/j.cmi.2015.04.005CrossRefGoogle ScholarPubMed
Ramesh, MS, Yee, J. Clostridioides difficile infection in chronic kidney disease/end-stage renal disease. Adv Chronic Kidney Dis 2019;26:3034.10.1053/j.ackd.2019.01.001CrossRefGoogle ScholarPubMed
Mor, A, Berencsi, K, Nielsen, JS, et al. Rates of community-based antibiotic prescriptions and hospital-treated infections in individuals with and without type 2 diabetes: a Danish nationwide cohort study, 2004–2012. Clin Infect Dis 2016;63:501511.10.1093/cid/ciw345CrossRefGoogle ScholarPubMed
Kim, EJ, Ha, KH, Kim, DJ, Choi, YH. Diabetes and the risk of infection: a national cohort study. Diabetes Metab J 2019;43:804814.10.4093/dmj.2019.0071CrossRefGoogle ScholarPubMed
Chang, CH, Fan, PC, Kuo, G, et al. Infection in advanced chronic kidney disease and subsequent adverse outcomes after dialysis initiation: a nationwide cohort study. Sci Rep 2020;10:2938.10.1038/s41598-020-59794-7CrossRefGoogle ScholarPubMed
Fleming-Dutra, KE, Hersh, AL, Shapiro, DJ, et al. Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010–2011. JAMA 2016;315:18641873.10.1001/jama.2016.4151CrossRefGoogle ScholarPubMed
Zanichelli, V, Garenc, C, Villeneuve, J, et al. Increased community-associated Clostridioides difficile infections in Quebec, Canada, 2008–2015. Emerg Infect Dis 2020;26:12911294.10.3201/eid2606.190233CrossRefGoogle ScholarPubMed
Turner, NA, Grambow, SC, Woods, CW, et al. Epidemiologic trends in Clostridioides difficile infections in a regional community hospital network. JAMA Netw Open 2019;2:e1914149.10.1001/jamanetworkopen.2019.14149CrossRefGoogle Scholar
Russo, EM, Kuntz, J, Yu, H, et al. Incidence of Clostridioides difficile infections among young and middle-aged adults: Veterans’ Health Administration. Infect Control Hosp Epidemiol 2019;40:9971005.10.1017/ice.2019.160CrossRefGoogle Scholar
Pollack, LA, van Santen, KL, Weiner, LM, Dudeck, MA, Edwards, JR, Srinivasan, A. Antibiotic stewardship programs in US acute-care hospitals: findings from the 2014 National Healthcare Safety Network Annual Hospital Survey. Clin Infect Dis 2016;63:443449.10.1093/cid/ciw323CrossRefGoogle ScholarPubMed
Neuhauser, M. Antibiotic stewardship: optimizing antibiotic use in inpatient setting. Annual NHSN Training—March 29, 2019. Centers for Disease Control and Prevention website. https://www.cdc.gov/nhsn/pdfs/training/2019/antibiotic-stewardship-508.pdf. Accessed June 11, 2022.Google Scholar
Morgan, F, Belal, M, Lisa, B, Ford, F, LeMaitre, B, Psevdos, G. Antimicrobial stewardship program achieved marked decrease in Clostridium difficile infections in a veterans’ hospital. Am J Infect Control 2020;48:11191121.10.1016/j.ajic.2019.12.023CrossRefGoogle Scholar
Gaffin, N, Spellberg, B. Sustained reductions in unnecessary antimicrobial administration and hospital Clostridioides difficile rates via stewardship in a nonacademic setting. Infect Control Hosp Epidemiol 2021. doi: 10.1017/ice.2021.490.CrossRefGoogle Scholar
Tamma, PD, Miller, MA, Dullabh, P, et al. Association of a safety program for improving antibiotic use with antibiotic use and hospital-onset Clostridioides difficile infection rates among US hospitals. JAMA Netw Open 2021;4:e210235.10.1001/jamanetworkopen.2021.0235CrossRefGoogle ScholarPubMed
Eudy, JL, Pallotta, AM, Neuner, EA, et al. Antimicrobial stewardship practice in the ambulatory setting from a national cohort. Open Forum Infect Dis 2020;7:ofaa513.10.1093/ofid/ofaa513CrossRefGoogle ScholarPubMed
National survey reveals barriers to outpatient antibiotic stewardship efforts. Pew Trusts website. https://www.pewtrusts.org/en/research-and-analysis/issue-briefs/2020/08/national-survey-reveals-barriers-to-outpatient-antibiotic-stewardship-efforts. Published August 6, 2020. Accessed August 19, 2022.Google Scholar
Sanchez, GV, Fleming-Dutra, KE, Roberts, RM, Hicks, LA. Core elements of outpatient antibiotic stewardship. MMWR Recomm Rep 2016;65:112.10.15585/mmwr.rr6506a1CrossRefGoogle ScholarPubMed
Polage, CR, Gyorke, CE, Kennedy, MA, et al. Overdiagnosis of Clostridium difficile infection in the molecular test era. JAMA Int Med 2015;175:17921801.10.1001/jamainternmed.2015.4114CrossRefGoogle ScholarPubMed
Kang, M, Abeles, SR, El-Kareh, R, et al. The effect of Clostridioides difficile diagnostic stewardship interventions on the diagnosis of hospital-onset Clostridioides difficile infections. Jt Comm J Qual Patient Saf 2020;46:457463.Google ScholarPubMed
Cook, PP, Nichols, S, Coogan, M, Opera, J, DeHart, M. Reduction in testing and change in testing algorithm associated with decrease in number of nosocomial Clostridioides (Clostridium) difficile infections. Am J Infect Control 2020;48:10191022.10.1016/j.ajic.2019.12.028CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Characteristics of Patients with CDI, 2011–2017, by Medicaid Status

Figure 1

Fig. 1. Healthcare-associated and community-associated CDI rates per 100,000 person years of observation, 2011–2017. (A) MarketScan aged 25–64 years, healthcare-associated CDI. (B) Medicare aged ≥65 years, healthcare-associated CDI. (C) MarketScan aged 25–64 years, community-associated CDI. (D) Medicare aged ≥65 years, community-associated CDI.

Figure 2

Fig. 2. Healthcare-associated CDI rates, 2011–2017, by age group and insurer. (A) MarketScan aged 25–64 years. (B) Medicare aged ≥65 years.

Figure 3

Fig. 3. Community-associated CDI rates, 2011–2017, by age group and insurer. (A) MarketScan aged 25–64 years. (B) Medicare aged ≥65 years.

Figure 4

Fig. 4. Prevalence of chronic medical and immunocompromising conditions with age, Marketscan aged 25–64 years.

Figure 5

Table 2. One-Year Incidence of CDI Per 100,000 Person Years from 2012 to 2017 in Persons Aged 25-64 Years with Commercial or Medicaid Health Insurance By Coding for Immunocompetent and Immunocompromising Conditions During their First Year of Enrollmenta

Figure 6

Fig. 5. One-year incidence of CDI per 100,000 person years from 2012 to 2017 based on prevalence of chronic medical conditions, immunocompromised conditions, and neither conditions in the MarketScan commercial and Medicaid populations by age group.

Supplementary material: File

Olsen et al. supplementary material

Tables S1-S5 and Figures S1-S2

Download Olsen et al. supplementary material(File)
File 89.7 KB