Determining risk factors that increase hospitalizations in patients with systemic lupus erythematosus

Telemedicine for Patients With Systemic Lupus Erythematosus in a Publicly Funded Hospital System: Retrospective Study

BACKGROUND

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that requires frequent clinic and laboratory visits. However, patients with SLE, particularly those who are underresourced, have unacceptably high rates of no-shows.

OBJECTIVE

This study aims to determine no-show rates associated with telemedicine visits during the COVID-19 pandemic in comparison to no-show rates associated with contemporaneous and historic in-person visits.

METHODS

We performed a retrospective cohort study in a publicly funded county hospital system in Houston, Texas. We identified a cohort of established patients with SLE by the International Classification of Diseases codes that were independently confirmed as SLE by a review of medical records. We identified patients who were seen from March to December in 2018, 2019, and 2020 (to reflect the height of the COVID-19 pandemic and account for seasonal changes in disease activity). Our primary outcome was the percentage of no-shows for rheumatology clinic appointments. Our secondary outcome was laboratory use adherence, which was defined as lupus-specific blood and urine studies conducted within 30 days of the scheduled appointment. Covariates included age, sex, race, ethnicity, and SLE-related prescription drugs.

RESULTS

We included 156 patients with SLE in our analysis. Most were female (n=141, 90.4%), were Hispanic (n=75, 49.3%), and had a median age of 43 (range 19-80) years. In 2020, the no-show rate for telemedicine was 5.5% (10/182) compared to a no-show rate of 16.2% (31/191) for in-person visits (P=.002). After multivariable adjustment for covariates, the odds of no-show were lower for telemedicine visits (odds ratio 0.39, 95% CI 0.20-0.77). There were no differences in adherence to laboratory testing.

CONCLUSIONS

Telemedicine visits had decreased odds of no-shows without difference in laboratory testing adherence after adjustment for covariates. More research is needed to determine the clinical impact of telemedicine on patients with SLE.

Risk factors for hospitalization in Mexican patients with systemic lupus erythematosus

INTRODUCTION

Systemic lupus erythematosus (SLE) is an autoimmune disease that often requires hospitalization. Most hospitalizations are due to infections and/or disease activity, for which several risk factors have been described in non-Mestizo patients.

OBJECTIVE

To identify risk factors for hospitalization in patients with systemic lupus erythematosus (SLE).

METHODS

This was an observational case-control study of patients with SLE in San Luis Potosí, Mexico, evaluated from January 2019 to October 2020. We compared hospitalized lupus patients with non-hospitalized lupus patients. We used descriptive statistics and logistic regression to describe potential risk factors.

RESULTS

Of a total of 202 patients, 89 (45.1%) were hospitalized; these patients were younger, had shorter disease duration, higher disease activity scores (systemic lupus erythematosus disease activity index-SLEDAI), and more accumulated damage than non-hospitalized patients. The primary reasons for hospitalization were disease activity (60.7%), kidney disease, infection, and drug toxicity (5.6%). Multivariate analysis revealed several risk factors associated with hospitalization, including elevated creatinine, C-reactive protein, neutrophil levels, and constitutional symptoms, while prolonged international normalized ratio (INR), longer stay in the intensive care unit (ICU), and vasopressor use were associated with mortality. The use of antimalarials was a protective factor against hospitalization. Survival analysis revealed that patients with hospital-acquired infections had a lower probability of survival.

CONCLUSIONS

Disease activity was the most common reason for hospitalization; kidney, constitutional, and hematological factors were associated with hospitalization; and the use of antimalarial was a protective factor for hospitalization.

Direct medical charges in a population-based systemic lupus erythematosus cohort

AIM

This study aimed to obtain estimates for the direct medical charges associated with hospitalizations and emergency department visits of validated SLE cases in a diverse Systemic Lupus Erythematosus (SLE) population.

METHODS

The Georgians Organized Against Lupus (GOAL) cohort is a population-based cohort of adult SLE patients from metropolitan Atlanta, GA USA, an area having a diverse SLE population. The GOAL cohort aims to study the impact of social determinants of health (SDoH) on outcomes relevant to patients, healthcare providers, and policymakers. For this study, survey data collected during 2011-2012 was linked to the Georgia Hospital Discharge Database (HDD) to capture hospital admissions (HAs) and emergency department visits (EDVs) throughout Georgia from 2012 through 2013. Direct medical charges were summarized by HCU type among all patients, among those with actual visits, and by socio-demographics and healthcare factors.

RESULTS

Among 829 patients (94% women, 78% Black, 64% non-private insurance, 64% not-employed, mean age of 46), 170 (20.5%) and 300 (36.2%) participants had at least one HA and one EDV in 1-year of follow-up, respectively, with 111(13.4%) having both HA and EDV. On average, each patient experienced 0.38 HAs and 0.91 EDVs, with per-patient direct medical charges of $14,968 for HAs & $3,022 for EDVs, and $39,645 per HA & $3,305 per EDV. Patients with higher social vulnerability or more severe disease had higher charges for both HA and EDV (p < 0.01), likely due to the delayed care and neglected health needs leading to more advanced and costly medical treatments. Living below the federal poverty level was associated with higher charges for EDVs (p < 0.001) but with lower charges for HAs (p = 0.036).

CONCLUSIONS

This study underscores the economic burden of SLE on vulnerable populations, emphasizing the importance of including socio-economic factors in healthcare planning. Policy efforts should prioritize reducing disparities in access to care and implementing preventive strategies.

Exploration of machine learning methods to predict systemic lupus erythematosus hospitalizations

OBJECTIVES

Systemic lupus erythematosus (SLE) is a heterogeneous disease characterized by disease flares which can require hospitalization. Our objective was to apply machine learning methods to predict hospitalizations for SLE from electronic health record (EHR) data.

METHODS

We identified patients with SLE in a longitudinal EHR-based cohort with ≥2 outpatient rheumatology visits between 2012 and 2019. We applied multiple machine learning methods to predict hospitalizations with a primary diagnosis code for SLE, including decision tree, random forest, naive Bayes, logistic regression, and an ensemble method. Candidate predictors were derived from structured EHR features, including demographics, laboratory tests, medications, ICD-9/10 codes for SLE manifestations, and healthcare utilization. We used two approaches to assess these variables over longitudinal follow-up, including the incorporation of lagged features to capture changes over time of clinical data. The performance of each model was evaluated by overall accuracy, the F statistic, and the area under the receiver operator curve (AUC).

RESULTS

We identified 1996 patients with SLE. 4.6% were hospitalized for SLE in their most recent year of follow-up. Random forest models had highest performance in predicting SLE hospitalizations, with AUC 0.751 and AUC 0.772 for two approaches (averaging and progressive), respectively. The leading predictors of SLE hospitalizations included dsDNA positivity, C3 level, blood cell counts, and inflammatory markers as well as age and albumin.

CONCLUSION

We have demonstrated that machine learning methods can predict SLE hospitalizations. We identified key predictors of these events including known markers of SLE disease activity; further validation in external cohorts is warranted.

Predictors of hospitalization in patients with systemic lupus erythematosus: a 10-year cohort study

INTRODUCTION/OBJECTIVES

Recognising systemic lupus erythematosus (SLE) patients at higher risk for hospitalization, aiming at developing tailored management strategies, may help minimize admissions and improve long-term health outcomes. Our study aimed to identify predictors for hospitalization in patients with SLE.

METHOD

Cohort study of SLE patients followed in a referral centre. All hospitalizations from study baseline up to 120 months were identified, and the primary indication for admission was categorized as follows: (1) SLE disease activity; (2); infection; and (3) other conditions. Demographic, clinical, and laboratory parameters at baseline were sought as predictors of hospitalization for (i) any cause, (ii) disease activity, and (iii) infection using survival analysis with Kaplan-Meier curves and log-rank tests. Potential predictors were further tested using multivariate Cox proportional hazards regression models.

RESULTS

We included 398 patients (median follow-up: 120 months). The incidence rate of hospitalization was 17.7 per 100 patient-years. The most frequent indications for hospitalization were SLE disease activity (29.4%) and infection (23.4%). In multivariate analysis, male gender, age > 50 years, antiphospholipid antibodies positivity (aPL), SLEDAI-2 K > 5, organ damage, and prednisone daily dose (PDN) predicted hospitalization for any cause. SLEDAI-2 K > 5, aPL, PDN, and IS medication predicted hospitalization for active SLE. Male gender, prior biopsy-proven lupus nephritis, aPL, organ damage, and ongoing treatment with high-risk IS predicted hospitalization for infection. Treatment with antimalarials was associated with a lower risk of hospitalization for any cause and for infection.

CONCLUSIONS

Positive aPL identifies SLE patients presenting a higher risk of hospitalization, while medication with antimalarials was associated with a lower risk. Key Points • Positive aPL is predictive of hospitalization for any medical condition, disease activity, and infection • Organ damage is predictive of hospitalization for any condition and infection • Antimalarials are predictive of a lower risk of hospitalization for any condition and infection.

Health care utilization and costs of systemic lupus erythematosus in the United States: A systematic review

OBJECTIVES

To evaluate health care utilization and costs for patients with systemic lupus erythematosus (SLE) by disease severity.

METHODS

We searched PubMed and Embase from January 2000 to June 2020 for observational studies examining health care utilization and costs associated with SLE among adults in the United States. Two independent reviewers reviewed the selected full-text articles to determine the final set of included studies. Costs were converted to 2020 US $.

RESULTS

We screened 9224 articles, of which 51 were included. Mean emergency department visits were 0.3-3.5 per year, and mean hospitalizations were 0.1-2.4 per year (mean length of stay 0.4-13.0 days). Patients averaged 10-26 physician visits/year. Mean annual direct total costs were $17,258-$63,022 per patient and were greater for patients with moderate or severe disease ($19,099-$82,391) compared with mild disease ($12,242-$29,233). Mean annual direct costs were larger from commercial claims ($24,585-$63,022) than public payers (Medicare and Medicaid: $18,302-$27,142).

CONCLUSIONS

SLE remains a significant driver of health care utilization and costs. Patients with moderate to severe SLE use more health care services and incur greater direct and indirect costs than those with mild disease.

Identification and Characterization of a High-Need, High-Cost Group Among Hospitalized Patients With Systemic Lupus Erythematosus

OBJECTIVE

To identify a high-need, high-cost (HNHC) group among hospitalized lupus patients and to compare clinical and social factors of the HNHC group with those of other patients with lupus.

METHODS

All hospitalizations for lupus in a tertiary care center over a 3-year period were recorded. The number of admissions, 30-day readmissions, length of stay (LOS), and cost of admissions were compared for high-risk patients with those of all other hospitalized lupus patients (OHLP) during this period. We then compared clinical measures (double-stranded DNA [dsDNA] levels, complement proteins, body mass index, Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index [SDI] scores, and Case Mix Index [CMI] scores) for the HNHC cohort with those of the OHLP group. We additionally differentiated social factors (age, race and ethnicity, poverty, and medication adherence) between the 2 groups.

RESULTS

A total of 202 patients with lupus accounted for 467 hospitalizations over the study period. The total cost of admissions was $13,192,346. Forty-four patients had significantly higher admissions, 30-day readmissions, and LOS. Furthermore, the cost for this group was 6-fold that for the OHLP group, confirming the presence of an HNHC cohort. The HNHC group had significantly higher dsDNA levels, SDI scores, and CMI scores compared with the OHLP group. Infections were the most common cause of admission for both groups. Patients in the HNHC group were more likely to be African American, younger, diagnosed with lupus at an earlier age, to have lower medication adherence, and to be significantly more likely to live in areas of poverty.

CONCLUSION

A small group of patients with lupus (the HNHC group) accounts for most of the hospitalizations and cost. The HNHC group has both social and clinical factors significantly different from other patients with lupus.

Patient-Reported Lupus Flare Symptoms Are Associated with Worsened Patient Outcomes and Increased Economic Burden

BACKGROUND

Lupus flares significantly contribute to health resource utilization and hospitalizations. Identification of flare activity may be hindered since validated assessment scales are rarely used in clinical practice and flare severity may fall below clinician-assessed thresholds. Therefore, patient-reported outcomes of lupus flare frequency are important assessment tools for lupus management.

OBJECTIVE

To better understand the relationship between lupus flares as reported by persons with lupus and specific direct and indirect costs, including hospital admission, unplanned urgent care (UC)/emergency department (ED) visits, work productivity loss, and nonwork activity impairment.

METHODS

In this cross-sectional analysis, persons with lupus were drawn from 2 enriched sampling sources. Data were collected via an online survey and included individuals with self-reported physician's diagnosis of systemic lupus erythematosus, skin or discoid lupus, or lupus nephritis. Respondents were asked the total number of hospitalizations and ED/UC visits for any reason and for lupus-related hospitalizations and ED/UC visits. Work productivity loss and nonwork activity impairment were measured via the Work Productivity and Activity Impairment - General Health scale. The sample was stratified into those with 0 flares, 1-3 flares, 4-6 flares, and 7 or more flares, with 0 flares used as the reference. Chi-square tests for trend and analyses of variance were used to evaluate differences among flare frequency groups. Multivariable regression modeling was conducted to evaluate the independent relationship of flare frequency to health care use and productivity loss.

RESULTS

We studied 1,288 survey respondents with known flare frequency in the past 12 months. Flare frequency increased with duration of illness. The mean number of lupus-related hospital admissions was significantly associated with increasing flare frequency for the total sample (F = 3.9; P < 0.009). Compared to patients with no flare, those who reported flare activities had 1.72-3.13 times higher rates of hospitalizations. The mean number of lupus-related ED/UC visits were also found to be significantly associated with increasing flare frequency for the total sample (F = 23.4; P < 0.001), and rates were increased by 6.98- to 16.12-fold for unplanned ED/UC visits depending on flare frequency. Rates of employment were significantly related to increasing flare frequency. With respect to work-related impairment, absenteeism increased with greater lupus flare frequency (F = 6.2; P < 0.001), as did presenteeism (F = 31.5; P < 0.001) and the combined value of total work productivity loss (F = 30.4; P < 0.001). Mean work-related activity impairment was 12%-32% more among patients who reported flare activities compared to those who reported no flares.

CONCLUSIONS

Increased lupus-related flare frequency is associated with worsened patient outcomes as measured by increased hospitalizations, visits to the ED/UC, work productivity loss, and activity impairment. This association may be an important indicator of disease severity and resource burden and therefore suggests an unmet need among patients experiencing lupus-related flares.

DISCLOSURES

This study was sponsored by Mallinckrodt Pharmaceuticals via grants to Vedanta Research and The Lupus Foundation of America. Katz received consulting fees from Vedanta Research, which received grant support from Mallinckrodt Pharmaceuticals to support data collection and analysis. Nelson and Connolly-Strong are employees of Mallinckrodt Pharmaceuticals and are stockholders in the company. Reed is an employee of Vedanta Research. Daly and Topf are employees of the Lupus Foundation of America, which received grant funding to support data collection. This study was a podium presentation at The American College of Rheumatology (ACR) Annual Meeting 2018; October 19-24, 2018; Chicago, IL.

Impact of the Affordable Care Act Medicaid Expansion on Access to Care and Hospitalization Charges for Lupus Patients

OBJECTIVE

To examine the impact of the Affordable Care Act on preventable hospitalizations and associated charges for patients living with systemic lupus erythematosus, before and after Medicaid expansion.

METHODS

A retrospective, quasi-experimental study, using an interrupted time series research design, was conducted to analyze data for 8 states from the Healthcare Cost and Utilization Project state inpatient databases. Lupus hospitalizations with a principal diagnosis of predetermined ambulatory-care sensitive (ACS) conditions were the unit of primary analysis. The primary outcome variable was access to care measured by preventable hospitalizations caused by an ACS condition.

RESULTS

There were 204,150 lupus hospitalizations in the final analysis, with the majority (53.5%) of lupus hospitalizations in states that did not expand Medicaid. In unadjusted analysis, Medicaid expansion states had significantly lower odds of having preventable lupus hospitalizations (odds ratio [OR] 0.958); however, after adjusting for several covariates, Medicaid expansion states had increased odds of having preventable lupus hospitalizations (OR 1.302). Adjusted analysis showed that those individuals with increased age, public insurance (Medicare or Medicaid), no health insurance, rural residence, or low income had significantly higher odds of having a preventable lupus hospitalization. States that expanded Medicaid had $523 significantly more charges than states that did not expand Medicaid. Older age and rural residence were associated with significantly higher charges.

CONCLUSION

Our findings suggest that while Medicaid expansion increased health insurance coverage, it did not address other issues related to access to care that could reduce the number of preventable hospitalizations.