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Substance Use Disorder as a Predictor of Skilled Nursing Facility Referral Failure

J Gen Intern Med 37(13):3506–8

DOI: 10.1007/s11606-022-07534-0

© The Author(s), under exclusive licence to Society of General Internal

Medicine 2022

INTRODUCTION

Drug and alcohol-related hospitalizations with need for sub- sequent skilled nursing facility (SNF) placement are increas- ing.1 Additionally, current literature illustrates an urgent need to address discharge barriers such as lack of post-acute care options that contribute to unnecessarily long hospitalizations.2

Previous studies have documented discriminatory refusals from post-acute facilities related to opioid use disorder or opioid agonist therapy3,4; however, the inability to secure SNF placement for patients with any substance use disorder (SUD) has not been fully explored.

OBJECTIVE

The primary objective of this study was to measure the in- creased odds of SNF referral failure for patients with SUD versus those without SUD and the secondary objective was to compare the time spent inpatient between SNF referral and discharge for both groups.

METHODS

We reviewed administrative data for all patients discharged from a 400-bed, urban, level 1 trauma-designated US hospital between January 1, 2019, and January 1, 2021 who were also referred to SNF during hospitalization. Patients who died, left against medical advice, or were transferred to another inpatient hospital were excluded. The primary outcome of interest, SNF referral failure, was defined as discharge to home/self-care despite SNF referral. SUD in our administrative data was defined as the presence of a dedicated flag in the patient’s electronic medical record indicating active drug or alcohol use disorder within the previous year. Tobacco use is not included in the SUD flag. The SUD flag is entered by a member of the patient’s care team as part of their standard

screening process and is readdressed at each hospitalization. We chose this method of SUD detection given the reported low sensitivity of other methods such as ICD-10 codes.5

Independent variables related to patient demographics, so- ciodemographic markers, hospitalization details, and mental health comorbidity were also captured. Univariable analysis using chi-square test was conducted and variables with p ≤ 0.25 were then used to create a stepwise binary logistic regres- sion model of the primary outcome. Secondary outcome data was summarized using median with interquartile range and differences between groups were tested using Wilcoxon rank- sum or one-way ANOVA.

RESULTS

Our sample included 3926 hospitalizations with 732 (18.6%) SNF referral failures. Univariable analysis of primary and secondary outcome data is presented in Table 1. Patients with SUD experienced a high proportion of SNF referral failure (278/800; 34.8%) and remained inpatient longer between SNF referral and discharge than those without SUD (median 7.5 days [IQR 3–20] vs. median 4 days [IQR 2–8], p<0.0001). In our fully adjusted model (Table 2), SUD was an independent predictor of SNF referral failure with a 94% increase in odds as compared to patients without SUD (aOR 1.94; 95%CI 1.58– 2.38). Other factors related to increased odds of SNF referral failure included homelessness, primary insurance, and race/ethnicity. Older age and ICU stay were associated with reduced odds of SNF referral failures.

DISCUSSION

In this analysis of all discharges from a public hospital over a 2-year period, patients with SUD referred to SNF were more likely to discharge to self-care and remained longer in the hospital awaiting disposition than those without SUD. These SNF referral failures are important markers of inequitable access to needed resources as well as ongoing marginalization of individuals with SUD. Patients with SUD had longer inpa- tient length of stay awaiting disposition in this study, suggest- ing that additional care coordination activities were required (e.g., SNF referral expansion until all options were exhausted then referrals to outpatient support resources) and/or that patients received outpatient level care in the hospital until appropriate clinical progression had occurred. Further research

Prior Presentations: This material was presented at the 2022 Society of Hospital Medicine national conference.

Received November 2, 2021 Accepted March 29, 2022 Published online April 13, 2022

3506

delineating individual substance use patterns, type of sub- stance used, and primary vs. secondary diagnoses would pro- vide useful insights to better understand SNF referral failures. Furthermore, centering patient-related data such as experi- ences of stigma or mistreatment6 as well as outcomes such as adverse events, discharge against medical advice, etc., is an important area of future work. This study builds upon a growing body of literature highlighting that systemic, targeted intervention by health systems and payors as well as legisla- tive and regulatory bodies is necessary to ensure equitable access and to mitigate the burden borne by hospitals and individual patients in need of SNF-level care.

Kimiam Waters1

Laura Handa, MS RN2

Bianca Caballero, MSW LICSW3

Azmera Telahun, BSN ACM-RN3

Maralyssa Bann, MD4

1University of Washington, Seattle, WA, USA

Table 1 Univariable Analysis of Failed SNF Referral and Days Between SNF Referral and Discharge

Failed SNF referral, n (%) p value Days from referral to discharge, median (IQR)

p value

All patients (n = 3926) 732 (18.6%) 4 (2–10) Substance use disorder <0.0001 <0.0001 Yes (n = 800) 278 (34.8%) 7.5 (3–20) No (n = 3126) 454 (14.5%) 4 (2–8)

Age < 0.0001 <0.0001 < 50 years (n = 590) 206 (34.9%) 9 (4–22) 50–64 years (n = 1098) 297 (27.1%) 6 (3–14) ≥ 65 years (n = 2238) 229 (10.2%) 3 (1–7)

Sex 0.001 <0.0001 Male (n = 2197) 450 (20.5%) 5 (2–12) Female (n = 1729) 282 (16.3%) 4 (2–8)

Race/ethnicity, 24 missing entries < 0.0001 <0.0001 American Indian/Alaska Native (n = 118) 39 (33.1%) 6 (2–16) Asian (n = 319) 50 (15.7%) 4 (2–8) Black/African American (n = 417) 95 (22.8%) 6 (2–14) Hispanic/Latino (n = 219) 47 (21.5%) 6 (2–16) Native Hawaiian/Pacific Islander (n = 28) 6 (21.4%) 8.5 (2.5–31.5) White, non-Hispanic (n = 2801) 491 (17.5%) 4 (2–9)

Preferred language, 6 missing entries 0.79 0.70 English (n = 3503) 655 (18.7%) 4 (2–10) Non-English (n = 417) 75 (18.0%) 4 (2–11)

Primary insurance < 0.0001 <0.0001 Medicare (n = 2402) 285 (11.9%) 3 (1–7) Medicaid (n = 800) 283 (35.4%) 9 (4–21) Private/commercial (n = 543) 127 (23.4%) 6 (3–12) Self-pay (n = 11) 6 (54.6%) 2 (1–6) Other (n = 170) 31 (18.2%) 4.5 (2–11)

Experiencing homelessness <0.0001 <0.0001 Yes (n = 349) 143 (41.0%) 12 (4–28) No (n = 3577) 589 (16.5%) 4 (2–9)

ICU during hospitalization 0.18 <0.0001 Yes (n = 1989) 354 (17.8%) 6 (2–14) No (n = 1937) 378 (19.5%) 3 (2–7)

Discharging service type < 0.0001 0.0003 Medical (n = 1603) 247 (15.4%) 5 (2–10) Surgical (n = 2234) 479 (21.4%) 4 (2–10) ICU (n = 89) 6 (6.7%) 8 (3–15)

Mental health disorder 0.003 <0.0001 Yes (n = 1144) 247 (21.6%) 6 (2–13) No (n = 2782) 485 (17.4%) 4 (2–9)

Table 2 Logistic Regression Model Predicting Odds of SNF Referral Failure

aOR (95%CI) p value

Substance use disorder 1.94 (1.58–2.38) <0.0001 Age <50 years Ref 50–64 years 0.82 (0.65–1.04) 0.10 65+ years 0.40 (0.30–0.53) <0.0001

Male sex 1.07 (0.89–1.29) 0.45 Race/ethnicity White, non-Hispanic Ref American Indian/Alaska Native 1.59 (1.03–2.45) 0.04 Asian 1.17 (0.83–1.64) 0.37 Black/African American 1.08 (0.82–1.42) 0.59 Hispanic/Latino 0.78 (0.54–1.13) 0.19 Native Hawaiian/Pacific Islander 1.34 (0.52–3.44) 0.54

Primary insurance Medicare Ref Medicaid 1.78 (1.37–2.30) <0.0001 Private/commercial 1.48 (1.12–1.97) 0.007 Self-pay 8.58 (2.41–30.53) 0.001 Other 1.31 (0.86–2.03) 0.21

Experiencing homelessness 1.84 (1.41–2.42) <0.0001 ICU during hospitalization 0.72 (0.61–0.87) <0.0001 Discharging service type Medical Ref Surgical 1.44 (1.20–1.74) <0.0001 ICU 0.37 (0.16–0.88) 0.02

Mental health disorder 1.18 (0.98–1.43) 0.08

3507Waters et al.: SUD SNF FailuresJGIM

2Department of Quality Improvement-Harborview Medical Center,

Seattle, WA, USA 3Department of Care Management-Harborview Medi-

cal Center, Seattle, WA, USA 4Department of Medicine, Division of GIM/Hospital

Medicine, Harborview Medical Center-University of Washington,

325 9th Avenue Box 359780, Seattle, WA 98104, USA

Corresponding Author: Maralyssa Bann, MD; Department of Medicine, Division of GIM/Hospital Medicine, Harborview Medical Center-University of Washington, 325 9th Avenue Box 359780, Seattle, WA 98104, USA (e-mail: [email protected]).

Declarations:

Conflict of Interest: The authors declare that they do not have a conflict of interest.

REFERENCES 1. Han BH, Tuazon E, Kunins HV, Paone D. Trends in inpatient discharges

with drug or alcohol admission diagnoses to a skilled nursing facility among older adults, New York City 2008-2014. Harm Reduct J 2020;17(1):99.

2. Meo N, Bann M, Sanchez M, Reddy A, Cornia PB. Getting unstuck: challenges and opportunities in caring for patients experiencing prolonged hospitalization while stable for discharge. Am J Med 2020;133(12):1406– 10.

3. Wakeman SE, Rich JD. Barriers to post-acute care for patients on opioid agonist therapy; an example of systematic stigmatization of addiction. J Gen Intern Med 2017;32(1):17–9.

4. Kimmel SD, Rosenmoss S, Bearnot B, Larochelle M, Walley AY. Rejection of patients with opioid use disorder referred for post-acute medical care before and after an anti-discrimination settlement in Massachusetts. J Addict Med 2021;15(1):20–6.

5. Rowe CL, Santos G-M, Kornbluh W, Bhardwaj S, Faul M, Coffin PO. Using ICD-10-CM codes to detect illicit substance use: A comparison with retrospective self-report. Drug Alcohol Depend 2021;221:108537.

6. Biancarelli DL, Biello KB, Childs E, et al. Strategies used by people who inject drugs to avoid stigma in healthcare settings. Drug Alcohol Depend 2019;198:80–6.

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