Validation of a New Risk Measure for Chronic Obstructive Pulmonary Disease Exacerbation Using Health Insurance Claims Data

Nationwide Analysis of Risk Factors Related to Opioid Weaning Following Lumbar Decompression Surgery - A Retrospective Database Study

BACKGROUND

Opioids are often prescribed for patients who eventually undergo lumbar decompression. Given the potential for opioid-related morbidity and mortality, postoperative weaning is often a goal of surgery. The purpose of this study was to examine the relationship between preoperative opioid use and postoperative complete opioid weaning among lumbar decompression patients.

METHODS

We surveyed the IBM Marketscan Databases for patients who underwent lumbar decompression during 2008-2017, had >30 days of opioid use in the year preceding surgery, and consumed a daily average of >0 morphine milligram equivalents in the 3 months preceding surgery. We used multivariable logistic regression and marginal standardization to examine the association between preoperative opioid use duration, average daily dose, and their interactions with complete opioid weaning in the 10-12 months after surgery.

RESULTS

Of the 11,114 patients who met inclusion criteria, most (54.7%, n = 6083) had a preoperative average daily dose of 1-20 morphine milligram equivalents. Postoperatively, 6144 patients (55.3%) remained on opioids. For patients with >180 days of preoperative use, the adjusted probability of weaning increased as the preoperative dose decreased. Obesity increased the likelihood of weaning, whereas older age, several comorbidities, female sex, and Medicaid decreased the odds of weaning.

CONCLUSIONS

Patients who used opioids for longer preoperatively were less likely to completely wean following surgery. Among patients with >180 days of preoperative use, those with lower preoperative doses were more likely to wean. Weaning was also associated with several clinical and demographic factors. These findings may help shape expectations regarding opioid use following lumbar decompression.

Patient and Therapeutic Profiles of Pulmonary Hypertension in Chronic Lung Diseases in Japan: A Cohort Study Using a Claims Database

INTRODUCTION

Pulmonary hypertension (PH) is often complicated by chronic lung diseases (CLDs) such as chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). Differentiating between PH associated with CLD (group 3 PH) and pulmonary arterial hypertension (PAH) in CLD is often difficult and reporting on the efficacy of PAH-specific therapies is inconsistent as a result of the lack of understanding of the heterogeneity of patients with PH.

METHODS

A retrospective observational cohort study was conducted to understand the baseline characteristics, comorbidities, and treatment profiles of patients with PH in CLD in a real-world setting using a large-scale claims database (Medical Data Vision). Administrative and clinical data for patients admitted to acute-care hospitals in Japan between April 2008 and January 2021 were analyzed.

RESULTS

A total of 115,921 patients with CLD (109,578 with COPD and 6343 with ILD, of whom 569 and 176 had PH, respectively) were analyzed. This study found lower PH diagnosis rates among patients with COPD and patients with ILD than in previous studies. The majority of PH with CLD patients were elderly (mean age 75.7 years) and male (80.81%). Among patients with CLD prescribed PAH-specific therapies (105 patients with COPD; 64 patients with ILD), most received these as monotherapy (COPD, 84.76%; ILD, 75.56%); the most common were phosphodiesterase 5 inhibitors (COPD, 42.70%; ILD, 18.37%), prostacyclins (oral; COPD, 48.31%; ILD, 24.49%), and endothelin receptor antagonists (ERA) (COPD, 8.99%; ILD, 18.37%). Comorbidities (e.g., pulmonary, cardiac, kidney), home oxygen therapy (HOT), and echocardiography (ECHO) were factors associated with the diagnosis of PH.

CONCLUSION

This is the first study using an administrative database that provides real-world data on patients with PH in CLD in Japan. Our results indicate that PH may be misdiagnosed or underdiagnosed in Japan which may lead to suboptimal treatment for patients, and supports the need for further evidence to guide appropriate treatment.

Healthcare Utilization in Patients with Chronic Obstructive Pulmonary Disease Discharged from Coronavirus 2019 Hospitalization

Rationale

There is concern that patients with chronic obstructive pulmonary disease (COPD) are at greater risk of increased healthcare utilization (HCU) following Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-COV-2) infection.

Objective

To assess whether COPD is an independent risk factor for increased post-discharge HCU.

Methods

We conducted a retrospective cohort study of patients with COPD discharged home from a hospitalization due to Coronavirus Disease 2019 (COVID-19) between April 1, 2020, and March 31, 2021, using Optum's de-identified Clinformatics® Data Mart Database (CDM). COVID-19 was identified by an International Classification of Diseases, tenth revision, clinical modification (ICD-10-CM) diagnosis code of U07.1. The primary outcome was HCU (ie, emergency department (ED) visits, readmissions, rehabilitation/skilled nursing facility (SNF) visits, outpatient office visits, and telemedicine visits) nine months post-discharge after COVID-19 hospitalization (from here on "post-discharge") in patients with COPD compared to HCU of patients without COPD. Poisson regression modeling was used to calculate relative risk (RR) and confidence interval (CI) for COPD, adjusted for the other covariates.

Results

We identified a cohort of 160,913 patients hospitalized with COVID-19, with 57,756 discharged home and 14,622 (25.3%) diagnosed with COPD. Patients with COPD had a mean age of 75.48 years (±9.49); 55.5% were female and 70.9% were White. Patients with COPD had an increased risk of HCU in the nine months post-discharge after adjusting for the other covariates. Risk of ED visits, readmissions, length of stay during readmission, rehabilitation/SNF visits, outpatient office visits, and telemedicine visits were increased by 57% (RR 1.57; 95% CI 1.53-1.60), 50% (RR 1.50; 95% CI 1.46-1.54), 55% (RR 1.55; 95% CI 1.53-1.56), 18% (RR 1.18; 95% CI 1.14-1.22), 16% (RR 1.16; 95% CI 1.16-1.17), and 28% (RR 1.28; 95% CI 1.24-1.31), respectively. Younger patients (ages 18 to 65 years), women, and Hispanic patients with COPD showed an increased risk for post-discharge HCU.

Conclusion

Patients with COPD hospitalized with COVID-19 experienced increased HCU post-discharge compared to patients without COPD.

Automatically Explaining Machine Learning Predictions on Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Background

Chronic obstructive pulmonary disease (COPD) is a major cause of death and places a heavy burden on health care. To optimize the allocation of precious preventive care management resources and improve the outcomes for high-risk patients with COPD, we recently built the most accurate model to date to predict severe COPD exacerbations, which need inpatient stays or emergency department visits, in the following 12 months. Our model is a machine learning model. As is the case with most machine learning models, our model does not explain its predictions, forming a barrier for clinical use. Previously, we designed a method to automatically provide rule-type explanations for machine learning predictions and suggest tailored interventions with no loss of model performance. This method has been tested before for asthma outcome prediction but not for COPD outcome prediction.

Objective

This study aims to assess the generalizability of our automatic explanation method for predicting severe COPD exacerbations.

Methods

The patient cohort included all patients with COPD who visited the University of Washington Medicine facilities between 2011 and 2019. In a secondary analysis of 43,576 data instances, we used our formerly developed automatic explanation method to automatically explain our model’s predictions and suggest tailored interventions.

Results

Our method explained the predictions for 97.1% (100/103) of the patients with COPD whom our model correctly predicted to have severe COPD exacerbations in the following 12 months and the predictions for 73.6% (134/182) of the patients with COPD who had ≥1 severe COPD exacerbation in the following 12 months.

Conclusions

Our automatic explanation method worked well for predicting severe COPD exacerbations. After further improving our method, we hope to use it to facilitate future clinical use of our model.

International Registered Report Identifier (IRRID)

RR2-10.2196/13783

Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study

Background

Chronic obstructive pulmonary disease (COPD) poses a large burden on health care. Severe COPD exacerbations require emergency department visits or inpatient stays, often cause an irreversible decline in lung function and health status, and account for 90.3% of the total medical cost related to COPD. Many severe COPD exacerbations are deemed preventable with appropriate outpatient care. Current models for predicting severe COPD exacerbations lack accuracy, making it difficult to effectively target patients at high risk for preventive care management to reduce severe COPD exacerbations and improve outcomes.

Objective

The aim of this study is to develop a more accurate model to predict severe COPD exacerbations.

Methods

We examined all patients with COPD who visited the University of Washington Medicine facilities between 2011 and 2019 and identified 278 candidate features. By performing secondary analysis on 43,576 University of Washington Medicine data instances from 2011 to 2019, we created a machine learning model to predict severe COPD exacerbations in the next year for patients with COPD.

Results

The final model had an area under the receiver operating characteristic curve of 0.866. When using the top 9.99% (752/7529) of the patients with the largest predicted risk to set the cutoff threshold for binary classification, the model gained an accuracy of 90.33% (6801/7529), a sensitivity of 56.6% (103/182), and a specificity of 91.17% (6698/7347).

Conclusions

Our model provided a more accurate prediction of severe COPD exacerbations in the next year compared with prior published models. After further improvement of its performance measures (eg, by adding features extracted from clinical notes), our model could be used in a decision support tool to guide the identification of patients with COPD and at high risk for care management to improve outcomes.

International Registered Report Identifier (IRRID)

RR2-10.2196/13783

Impact of influenza infection on the short- and long-term health of patients with chronic obstructive pulmonary disease

BACKGROUND

Influenza is a common cause of acute respiratory infection that leads to exacerbation of underlying chronic obstructive pulmonary disease (COPD). To elucidate the short- and long-term effects of influenza in patients with COPD, we examined health care resource utilization (HRU) and costs up to 13 months following influenza infection.

METHODS

We conducted a retrospective cohort study using U.S. insurance claims data from MarketScan. Patients with an influenza diagnosis during the 2012-2014 influenza seasons and continuous enrollment in a health plan from 12 months before to 13 months after the index influenza diagnosis were identified and propensity score-matched 1:5 to controls without evidence of influenza. COPD- and pneumonia-related outcomes were assessed over 13 months following influenza diagnosis.

RESULTS

COPD-associated outcomes after diagnosis were significantly worse in patients with influenza (n = 7,087) vs. controls (n = 35,435) during the first month (exacerbation: 16.1 vs. 3.4%; outpatient visits: 57.1 vs. 35.2%; emergency department (ED) visits: 10.5 vs. 1.8%; and inpatient visits: 5.6 vs. 0.7%) and months 2-13 (exacerbation: 25.1 vs. 21.1%; outpatient visits: 86.1 vs. 85.8%; ED visits: 20.0 vs. 15.7%; and inpatient visits: 6.5 vs. 5.3%). COPD- and pneumonia-associated costs for months 1 and 2-13 were higher in patients with influenza.

LIMITATIONS

The study was subject to a residual imbalance between cohorts despite propensity score matching. The use of diagnostic codes to select patients and identify complications could introduce inaccuracies in estimating events.

CONCLUSIONS

HRU and costs were higher in COPD patients with influenza during the first month and over the entire year following infection. This suggests influenza has an impact on respiratory health in patients with COPD that lasts beyond the acute infection.

Association of US Food and Drug Administration Removal of Indications for Use of Oral Quinolones With Prescribing Trends

IMPORTANCE

In May 2016, due to concerns of the risks outweighing the benefits, the US Food and Drug Administration (FDA) removed systemic quinolones' indications for acute, uncomplicated urinary tract infection (uUTI), acute sinusitis (AS), and acute exacerbation of chronic obstructive pulmonary disease (AE-COPD). How the change influenced oral quinolone use is unknown.

OBJECTIVE

To assess the association of oral quinolone safety warnings and indication restrictions with use.

DESIGN, SETTING, AND PARTICIPANTS

This interrupted time series (January 2015-November 2018) analysis of the monthly prevalence of oral quinolone-treated infection episodes used a national sample of privately insured patients in outpatient care from the IBM MarketScan Database and included adults with antibiotic treatment of new uUTI, AS, or AE-COPD episodes, excluding patients with conditions that complicate infections, previous hospitalization, or other infections.

EXPOSURES

Time before and after May 2016 when the FDA mandated label changes.

MAIN OUTCOMES AND MEASURES

Monthly oral quinolone use prevalence by each condition before and after the label changes, overall and stratified by prescriber specialty.

RESULTS

In January 2015, quinolone prevalence among antibiotic-treated uUTI episodes (n = 652 235) was 41.6% (95% CI, 40.6%-42.5%); AS (n = 1 742 248) was 8.3% (95% CI, 7.9%-8.6%), and AE-COPD (n = 22 817) was 31.9% (95% CI, 30.3%-33.4%). Before the label changes, trends in monthly quinolone prevalence were nearly flat. The month of the label changes we noted an immediate reduction for uUTI (-7.2%; 95% CI, -8.6% to -5.8%); and to a lesser extent for AS (-1.2%; 95% CI, -1.5% to -0.9%) and AE-COPD (-2.6%; 95% CI, -4.1% to -1.1%), and continued monthly declines thereafter. Falsification tests confirmed an immediate decrease after the label change of quinolone use for uUTI but more obscured effects for AS and AE-COPD. Treatment shifted mostly to first-line (eg, nitrofurantoin in uUTI, amoxicillin in AS, macrolides in AE-COPD) and other second-line agents but use of not recommended antibiotics also increased (eg, tetracyclines in AE-COPD). Prescribing preferences varied, but significant reductions were seen across all prescriber specialties. At the end of the study period, quinolone was used for 19.2% of treated uUTIs, 2.9% of treated AS, and 14.6% of treated AE-COPD episodes.

CONCLUSIONS AND RELEVANCE

Label changes and their announcements was associated with an immediate reduction in oral quinolone use for uUTI and to a lesser extent for AS and AE-COPD. Quinolones continued to contribute a considerable proportion of treatments for uUTI and AE-COPD episodes at the end of the study period, pointing to opportunities for further improvement.

Using Computational Methods to Improve Integrated Disease Management for Asthma and Chronic Obstructive Pulmonary Disease: Protocol for a Secondary Analysis

Background

Asthma and chronic obstructive pulmonary disease (COPD) impose a heavy burden on health care. Approximately one-fourth of patients with asthma and patients with COPD are prone to exacerbations, which can be greatly reduced by preventive care via integrated disease management that has a limited service capacity. To do this well, a predictive model for proneness to exacerbation is required, but no such model exists. It would be suboptimal to build such models using the current model building approach for asthma and COPD, which has 2 gaps due to rarely factoring in temporal features showing early health changes and general directions. First, existing models for other asthma and COPD outcomes rarely use more advanced temporal features, such as the slope of the number of days to albuterol refill, and are inaccurate. Second, existing models seldom show the reason a patient is deemed high risk and the potential interventions to reduce the risk, making already occupied clinicians expend more time on chart review and overlook suitable interventions. Regular automatic explanation methods cannot deal with temporal data and address this issue well.

Objective

To enable more patients with asthma and patients with COPD to obtain suitable and timely care to avoid exacerbations, we aim to implement comprehensible computational methods to accurately predict proneness to exacerbation and recommend customized interventions.

Methods

We will use temporal features to accurately predict proneness to exacerbation, automatically find modifiable temporal risk factors for every high-risk patient, and assess the impact of actionable warnings on clinicians’ decisions to use integrated disease management to prevent proneness to exacerbation.

Results

We have obtained most of the clinical and administrative data of patients with asthma from 3 prominent American health care systems. We are retrieving other clinical and administrative data, mostly of patients with COPD, needed for the study. We intend to complete the study in 6 years.

Conclusions

Our results will help make asthma and COPD care more proactive, effective, and efficient, improving outcomes and saving resources.

International Registered Report Identifier (IRRID)

PRR1-10.2196/27065

Evaluation of Medication Adherence and Rescue Medication Use in Non-Exacerbating Patients with COPD Receiving Umeclidinium/Vilanterol or Budesonide/Formoterol as Initial Maintenance Therapy

Background

Adherence to inhaled maintenance therapy is critical to managing chronic obstructive pulmonary disease (COPD), while increasing rescue medication usage may indicate worsening symptoms. This study evaluated adherence and rescue medication use in patients with COPD without a history of exacerbation who initiated combination therapy with budesonide/formoterol (B/F) or umeclidinium/vilanterol (UMEC/VI).

Methods

Retrospective observational study of commercially insured and Medicare Advantage with Part D enrollees who initiated UMEC/VI or B/F between January 1, 2014 and December 31, 2017 (earliest fill defined as index date). Eligibility criteria included age ≥40 years, 12 months continuous enrollment pre- and post-index, ≥1 pre-index COPD diagnosis, no pre-index asthma diagnosis, COPD-related exacerbations, or medication fills containing inhaled corticosteroids, long-acting β₂-agonists, or long-acting muscarinic antagonists. Inverse probability of treatment weighting (IPTW) was used to balance treatment groups on potential confounders. Medication adherence (primary endpoint) was evaluated by the proportion of days covered (PDC). Rescue medication use (secondary endpoint) was standardized to canister equivalents (1 metered dose inhaler [200 puffs] or ~100 nebulized doses of short-acting β₂-agonist- and/or short-acting muscarinic agonist-containing medication).

Results

After IPTW, covariates were balanced between cohorts (UMEC/VI: N=4082; B/F: N=9529). UMEC/VI initiators had a significantly greater mean PDC (UMEC/VI: 0.47 [0.33]; B/F: 0.38 [0.30]; P<0.001) and significantly higher rates of adherence (PDC≥0.80) than B/F initiators (UMEC/VI: n=1004 [25%], B/F: n=1391 [15%]; relative risk: 1.68, 95% CI: 1.57, 1.81; P<0.001). In the year following initiation, UMEC/VI initiators filled significantly fewer rescue medication canister equivalents than B/F initiators (predicted mean [95% CI]: 1.78 [1.69, 1.88] vs 2.15 [2.08, 2.23]; mean difference [95% CI]: −0.37 [−0.50, −0.24]; P<0.001), corresponding to 17% less (estimated) rescue medication use (incidence rate ratio [95% CI]: 0.83 [0.78, 0.88]).

Conclusion

Among non-exacerbating patients with COPD initiating dual therapy, UMEC/VI demonstrated improved adherence and reduced rescue medication use compared with B/F.

Assessment of COPD-related outcomes in patients initiating a once daily or twice daily ICS/LABA

BACKGROUND

Use of inhaled corticosteroids and long acting beta agonist (ICS/LABA) combination therapy has been shown to decrease the frequency of exacerbations in patients with chronic obstructive pulmonary disease (COPD). In this population, adherence to treatment is associated with better disease control and lower risk of COPD-related exacerbations in the future. Using a treatment with a more convenient regimen or easier-to-use device could improve patient adherence, improve disease control, decrease the frequency of exacerbations and minimize the COPD-related economic burden. Real-world information on the impact on healthcare costs and exacerbation risk of initiating once-daily or twice daily ICS/LABA in this patient population is limited. The objective of this study was to assess COPD-related healthcare costs, adherence, and exacerbations in COPD patients initiating treatment with fluticasone furoate/vilanterol 100/25 (FF/VI) or budesonide/formoterol 160/4.5 (BUD/F) using a large managed care database in the US.

METHODS

This was a retrospective cohort study among COPD patients initiating FF/VI or BUD/F between January 01, 2014 and June 30, 2016. The analysis used the Optum Research Database (ORD) which contains patients from commercial and Medicare Advantage Prescription Drug (MAPD) plans. The study included new initiators of ICS/LABA as either FF/VI or BUD/F for COPD, ≥40 years of age at index, ≥15 months of continuous enrollment (12 months pre-index and ≥3 months post-index). New users of FF/VI or BUD/F were matched on baseline characteristics using propensity score matching (PSM) methods. Multivariate models including ordinary least squares regression, Lin's regression, logistic regression, and Cox proportional hazards were used to assess differences between the cohorts on outcomes of interest.

RESULTS

A total of 18,652 subjects met all inclusion and exclusion criteria with 5044 initiating FF/VI and 13,608 initiating BUD/F. Of these, 9026 subjects were matched at a 1:1 ratio (4513 patients in each cohort) and were included in the final analyses. Proportion of days covered (PDC), was significantly better for FF/VI (mean PDC [SD]: FF/VI: 0.46 [0.31], BUD/F: 0.41 [0.29], p < 0.001) while FF/VI was associated with a 9% lower risk (adj. hazard ratio (HR): 0.91, 95% CI: 0.85-0.96) of having a moderate or severe COPD-related exacerbation. However, COPD-related healthcare costs were not significantly different, $11,521 vs $10,986, p = 0.41 for FF/VI and BUD/F, respectively.

CONCLUSIONS

Patients initiating once-daily FF/VI were more adherent, and were associated with a lower risk of subsequent COPD-related exacerbations compared with twice-daily BUD/F, however this was not associated with a significant difference in costs. (GSK Study HO1617333/206702).

External Validation of a COPD Risk Measure in a Commercial and Medicare Population: The COPD Treatment Ratio

BACKGROUND

Chronic obstructive pulmonary disease (COPD) exacerbations can accelerate disease progression and lead to higher health care costs. To improve patient survival and reduce cost, risk assessment measures should be developed to identify patients at risk for exacerbations and prevent future exacerbations.

OBJECTIVES

To (a) externally validate the COPD treatment ratio (CTR) as a measure of COPD exacerbation risk based on predictive models previously tested and (b) assess the measure's capability to assess risk using only pharmacy claims for use in Medicare Part D programs.

METHODS

This was a retrospective observational study conducted using the Humana research datasets. Separate assessments were performed using pharmacy-only models that excluded risk factors derived from medical claims. Patients were aged ≥ 40 years, with ≥ 1 inpatient hospitalization or ≥ 2 physician's office, emergency department, or urgent care visits with a COPD diagnosis. Using logistic regression models, risk factors (age, exacerbation history, COPD and concomitant medication use, and comorbidities) were assessed during the baseline period (year 1) and were used to predict the risk of exacerbation during year 2. Continuous and dichotomized CTRs were analyzed. A cut-point of 0.3 was initially used for dichotomizing CTR, and subsequently receiver operating characteristics (ROC) analysis was used to determine the optimal cut-point for CTR.

RESULTS

A total of 92,496 patients were identified, the majority of which (96.2%) were Medicare members with a mean age of 69 years. During the baseline period, 14.0% and 11.2% of patients had ≥ 1 moderate or severe exacerbation, respectively. Overall, the CTR performed well in predicting future COPD exacerbations, especially severe exacerbations. ROC analysis suggested that 0.7 was the optimal cut-point for dichotomizing CTR. Patients with a CTR ≥ 0.7 had a 7.9% (OR = 0.921; 95% CI = 0.852-0.995) lower risk of a severe exacerbation, compared with those with a CTR < 0.7. Stronger effects were seen in pharmacy-only models, with patients 17% less likely to experience a severe exacerbation with a CTR ≥ 0.7 compared with patients with a CTR < 0.7.

CONCLUSIONS

This study validated the use of CTR as a modifiable measure of risk of COPD exacerbation in a large commercial and Medicare population and remained a robust predictor when pharmacy-only claims data were available. A CTR of ≥ 0.7 may be a useful target to help reduce the risk of severe exacerbations, and its use by payer or quality organizations has the potential to improve COPD management.

DISCLOSURES

This study was funded by GlaxoSmithKline (GSK; study number HO-15-16651). GSK had a role in the study design, collection, analysis, and interpretation of data and in the writing of the study report but did not place any restrictions on access to the data or on the statements made in the manuscript. The authors were in full editorial control of publication target journal and content and conclusions, accepted full responsibility for final approval of a manuscript describing this GSK-sponsored research, and had final responsibility for the decision to submit for publication. Stanford and Lau are employees of GSK and hold GSK stocks/shares. Li and Stemkowski are employees of Comprehensive Health Insights, which was contracted to conduct the study but did not receive funding for manuscript development. This manuscript was presented in part at the American Thoracic Society 2017 International Conference; May 19-24, 2017; Washington, DC.

Corticosteroid or hyaluronic acid injections to the carpometacarpal joint of the thumb joint are associated with early complications after subsequent surgery

Truven MarketScan® Databases were used to identify patients with thumb carpometacarpal arthritis who underwent surgical treatment. Pre-operative corticosteroid or hyaluronic acid injections were identified, as were post-operative complications. Multivariable regressions assessed the relationship between injections and complications. Of 16,268 patients, 4462 had steroid injections and 252 received hyaluronic acid injections. Twenty-one per cent (3381 patients) had post-operative complications. Diabetes and smoking increased the odds of complications in all models. Odds of any complication, most notably infectious complications, were increased 20% by corticosteroids (OR 1.2; 95% CI: 1.1 to 1.3). More than three injections increased the odds of a complication by 70% (OR 1.7; 95% CI: 1.3 to 2.1). Hyaluronic acid increased the odds of wound-healing complications by 110% (OR 2.1; 95% CI: 1.3 to 3.4). Corticosteroid and hyaluronic acid injections for thumb carpometacarpal arthritis increase the odds of post-operative complications. Level of evidence: IV.

Predicting Acute Exacerbations in Chronic Obstructive Pulmonary Disease

BACKGROUND

With increasing health care costs that have outpaced those of other industries, payers of health care are moving from a fee-for-service payment model to one in which reimbursement is tied to outcomes. Chronic obstructive pulmonary disease (COPD) is a disease where this payment model has been implemented by some payers, and COPD exacerbations are a quality metric that is used. Under an outcomes-based payment model, it is important for health systems to be able to identify patients at risk for poor outcomes so that they can target interventions to improve outcomes.

OBJECTIVE

To develop and evaluate predictive models that could be used to identify patients at high risk for COPD exacerbations.

METHODS

This study was retrospective and observational and included COPD patients treated with a bronchodilator-based combination therapy. We used health insurance claims data to obtain demographics, enrollment information, comorbidities, medication use, and health care resource utilization for each patient over a 6-month baseline period. Exacerbations were examined over a 6-month outcome period and included inpatient (primary discharge diagnosis for COPD), outpatient, and emergency department (outpatient/emergency department visits with a COPD diagnosis plus an acute prescription for an antibiotic or corticosteroid within 5 days) exacerbations. The cohort was split into training (75%) and validation (25%) sets. Within the training cohort, stepwise logistic regression models were created to evaluate risk of exacerbations based on factors measured during the baseline period. Models were evaluated using sensitivity, specificity, and positive and negative predictive values. The base model included all confounding or effect modifier covariates. Several other models were explored using different sets of observations and variables to determine the best predictive model.

RESULTS

There were 478,772 patients included in the analytic sample, of which 40.5% had exacerbations during the outcome period. Patients with exacerbations had slightly more comorbidities, medication use, and health care resource utilization compared with patients without exacerbations. In the base model, sensitivity was 41.6% and specificity was 85.5%. Positive and negative predictive values were 66.2% and 68.2%, respectively. Other models that were evaluated resulted in similar test characteristics as the base model.

CONCLUSIONS

In this study, we were not able to predict COPD exacerbations with a high level of accuracy using health insurance claims data from COPD patients treated with bronchodilator-based combination therapy. Future studies should be done to explore predictive models for exacerbations.

DISCLOSURES

No outside funding supported this study. Samp is now employed by, and owns stock in, AbbVie. The other authors have nothing to disclose. Study concept and design were contributed by Joo and Pickard, along with the other authors. Samp and Lee performed the data analysis, with assistance from the other authors. Samp wrote the manuscript, which was revised by Schumock and Calip, along with the other authors.

Predictors of future exacerbations in a multi-ethnic Asian population with asthma

OBJECTIVE

Exacerbations are important outcomes in asthma. Risk factors for exacerbations may differ in different populations. Although various demographic and clinical variables were examined in previous studies on exacerbation risks in asthma, important variables such as ethnicity, adherence, and medication titration were not included. This study examined independent predictors of future exacerbations in a multi-ethnic asthma population in Asia, while including the variables of ethnicity, medication adherence, and medication change in our analysis.

METHODS

We recruited patients with physician-diagnosed asthma in a tertiary hospital in Singapore over a one-year period. Exacerbations requiring ≥3 days of systemic corticosteroids one year prior to study enrolment (previous exacerbations) and the year following enrolment (future exacerbations) were recorded from electronic medical records. Medication adherence was based on pharmacy refill. An increase or a decrease in the Global Initiative for Asthma treatment steps were considered to be medication up- and down-titration, respectively. A multivariate logistic regression model was constructed to determine independent predictors of future exacerbations.

RESULTS

The study cohort of 340 patients comprised mainly of Chinese (53.2%), Malay (32.9%), and Indian (9.7%) ethnicities. After multivariate analysis, only Indian ethnicity (OR 3.75, 95% CI 1.077-13.051, p = 0.038), Asthma Control Test score (OR 0.913, 95% CI 0.839-0.995, p = 0.037), and the number of previous exacerbations (OR 1.84, 95% CI 1.416-2.391, p < 0.001) were independent predictors of future exacerbations.

CONCLUSIONS

There are ethnic differences in exacerbation risk in Asian populations. Each incremental worsening of the asthma symptom control score and each additional exacerbation also increases the risk of future exacerbations.