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Thirty-Day Readmissions in Adults Hospitalized for COPD or Bronchiectasis: Findings From the Nationwide Readmission Database 2013 FREE TO VIEW

Kshitij Chatterjee, MD; Abhinav Goyal, MD; Manish Joshi, MD
Author and Funding Information

aDepartment of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR

bDivision of Pulmonary and Critical Care Medicine, Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR

cDepartment of Internal Medicine, Einstein Medical Center, Philadelphia, PA

CORRESPONDENCE TO: Kshitij Chatterjee, MD, Department of Internal Medicine, University of Arkansas for Medical Sciences, 4301 W Markham St, Slot 634, Little Rock, AR, 72205


Copyright 2017, American College of Chest Physicians. All Rights Reserved.


Chest. 2017;151(4):943-945. doi:10.1016/j.chest.2016.12.034
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We commend Dr Ford for the extensive analysis of inpatient admissions, ED visits, and readmissions for COPD and bronchiectasis in an article published in CHEST (April 2015). The National Inpatient Sample and online query system HCUPnet (http://hcupnet.ahrq.gov) were used by the author to generate 30-day readmission rates for adults (aged ≥ 18 years) with index hospitalizations for COPD or bronchiectasis (not associated with cystic fibrosis). Although the readmission rate analysis by the author was extensive, age was the only demographic described, and predictors of readmission were not identified due to a limitation of the HCUPnet system. We conducted a similar analysis using the Nationwide Readmissions Database for 2013, which includes 14 million discharges from 21 states, representing 49.1% of all US hospitalizations. We identified our index admissions as adults, with Clinical Classification Software diagnostic category 127 as their principal diagnosis, similar to Ford’s approach. We used the criteria for index admissions and 30-day readmissions as defined by the Centers for Medicare and Medicaid Services. We excluded patients who died during the index admission, as they were not at risk of readmission, as well as patients with index discharges in December, due to lack of sufficient time to capture 30-day readmissions, and patients with missing information on key variables. We also excluded patients who were not residents of the state of the index hospitalization, since readmission across state boundaries could not be identified in the Nationwide Readmission Database. Manufacturer-provided sampling weights were used to produce national-level estimates.

A total of 511,940 index hospitalizations (weighted) due to COPD were identified during the year 2013. Ninety-six thousand nine hundred thirty-four (18.9%) of these had at least one 30-day readmission. The total number of 30-day readmissions was 111,999 (about 22 readmissions per 100 index admissions). Compared with index admissions without any subsequent readmission, patients with index admissions who experienced readmissions were older, were less often females, and had longer lengths of stay (Table 1). We performed multivariate logistic regression to identify predictors for any-cause 30-day readmission while adjusting for patient demographics, hospital characteristics, and comorbidities. Male sex, congestive heart failure, depression, alcohol or drug abuse, and Medicare or Medicaid as the primary insurance (vs private insurance) were all associated with a significantly higher chance of readmission (Fig 1A).

Table Graphic Jump Location
Table 1 Demographic Characteristics, Comorbidities, and Outcomes of Index Admissions (With and Without Readmissions)

All cells in the table represent percentage distribution unless otherwise specified.

P value in the last column represents the significance of difference of characteristics between index admission without readmission group and index admission with at least one readmission group. ICF = intermediate care facility; IQR = interquartile range; SNF = skilled nursing facility.

Figure Jump LinkFigure 1 A, Forest plot demonstrating adjusted OR for readmission for key demographic characteristics and comorbidities. The adjustment was done by multivariate logistic regression and included age categories, sex, Elixhauser comorbidities, hospital characteristics (teaching status, bed size, location), length of stay for index admission, disposition (routine home discharge vs others), and median household income quartile, and primary insurance. Detailed OR with 95% CI for these variables are available in e-Table 1. B, Proportions of readmissions (any cause) against number of days after discharge from index hospitalization.Grahic Jump Location

Among all 30-day readmissions, 53.7% were primarily due to respiratory diseases or complications as identified by Clinical Classification Software diagnostic categories 122 to 134 as the principal diagnosis. Of these, 56.3% (or 30.2% of all readmissions) were specifically related to COPD or bronchiectasis, similar to the findings reported by Dr Ford. Figure 1B shows the distribution of the proportion of readmissions across the number of days after the index discharge. The maximum number of readmissions occurred on day 1 after the index discharge and decreased thereafter. In general, the factors leading to COPD readmissions are complex and often need a multifaceted approach to reduce them beyond usual clinical care.

Ford E.S. . Hospital discharges, readmissions, and ED visits for COPD or bronchiectasis among US adults: findings from the nationwide inpatient sample 2001-2012 and Nationwide Emergency Department Sample 2006-2011. Chest. 2015;147:989-998 [PubMed]journal. [CrossRef] [PubMed]
 
HCUPnet: A tool for identifying, tracking, and analyzing national hospital statistics.https://hcupnet.ahrq.gov/#setup. Accessed February 22, 2016.
 
Health Care Cost and Utilization Project. NRD overview.https://www.hcup-us.ahrq.gov/nrdoverview.jsp. Accessed December 16, 2016.
 
Centers for Medicare and Medicaid Services. Measure methodology.https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html. Accessed December 13, 2016.
 
Chappidi M.R. .Kates M. .Stimson C.J. .Bivalacqua T.J. .Pierorazio P.M. . Quantifying nonindex hospital readmissions and care fragmentation after major urological oncology surgeries in a nationally representative sample. J Urol. 2017;197:235-240 [PubMed]journal. [PubMed]
 
Raghavan D. .Bartter T. .Joshi M. . How to reduce hospital readmissions in chronic obstructive pulmonary disease? Curr Opin Pulm Med. 2016;22:106-112 [PubMed]journal. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1 A, Forest plot demonstrating adjusted OR for readmission for key demographic characteristics and comorbidities. The adjustment was done by multivariate logistic regression and included age categories, sex, Elixhauser comorbidities, hospital characteristics (teaching status, bed size, location), length of stay for index admission, disposition (routine home discharge vs others), and median household income quartile, and primary insurance. Detailed OR with 95% CI for these variables are available in e-Table 1. B, Proportions of readmissions (any cause) against number of days after discharge from index hospitalization.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 Demographic Characteristics, Comorbidities, and Outcomes of Index Admissions (With and Without Readmissions)

All cells in the table represent percentage distribution unless otherwise specified.

P value in the last column represents the significance of difference of characteristics between index admission without readmission group and index admission with at least one readmission group. ICF = intermediate care facility; IQR = interquartile range; SNF = skilled nursing facility.

References

Ford E.S. . Hospital discharges, readmissions, and ED visits for COPD or bronchiectasis among US adults: findings from the nationwide inpatient sample 2001-2012 and Nationwide Emergency Department Sample 2006-2011. Chest. 2015;147:989-998 [PubMed]journal. [CrossRef] [PubMed]
 
HCUPnet: A tool for identifying, tracking, and analyzing national hospital statistics.https://hcupnet.ahrq.gov/#setup. Accessed February 22, 2016.
 
Health Care Cost and Utilization Project. NRD overview.https://www.hcup-us.ahrq.gov/nrdoverview.jsp. Accessed December 16, 2016.
 
Centers for Medicare and Medicaid Services. Measure methodology.https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html. Accessed December 13, 2016.
 
Chappidi M.R. .Kates M. .Stimson C.J. .Bivalacqua T.J. .Pierorazio P.M. . Quantifying nonindex hospital readmissions and care fragmentation after major urological oncology surgeries in a nationally representative sample. J Urol. 2017;197:235-240 [PubMed]journal. [PubMed]
 
Raghavan D. .Bartter T. .Joshi M. . How to reduce hospital readmissions in chronic obstructive pulmonary disease? Curr Opin Pulm Med. 2016;22:106-112 [PubMed]journal. [CrossRef] [PubMed]
 
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