Impact of a COPD comprehensive case management program on hospital length of stay and readmission rates

Abstract

Background

COPD accounts for the highest rate of hospital admissions among major chronic diseases. COPD hospitalizations are associated with impaired quality of life, high health care utilization, and poor prognosis and result in an economic and a social burden that is both substantial and increasing.

Aim

The aim of this study is to determine the efficacy of a comprehensive case management program (CCMP) in reducing length of stay (LOS) and risk of hospital admissions and readmissions in patients with COPD.

Materials and methodology

We retrospectively compared outcomes across five large hospitals in Vancouver, BC, Canada, following the implementation of a systems approach to the management of COPD patients who were identified in the hospital and followed up in the community for 90 days. We compared numbers, rates, and intervals of readmission and LOS during 2 years of active program delivery compared to 1 year prior to program implementation.

Results

A total of 1,564 patients with a clinical diagnosis of COPD were identified from 2,719 hospital admissions during the 3 years of study. The disease management program reduced COPD-related hospitalizations by 30% and hospitalizations for all causes by 13.6%. Similarly, the rate of readmission for all causes showed a significant decline, with hazard ratios (HRs) of 0.55 (year 1) and 0.51 (year 2) of intervention (P<0.001). In addition, patients’ mean LOS (days) for COPD-related admissions declined significantly from 10.8 to 6.8 (P<0.05).

Conclusion

A comprehensive disease management program for COPD patients, including education, case management, and follow-up, was associated with significant reduction in hospital admissions and LOS.

Keywords:

• COPD
• CCP
• admission
• readmission
• length of stay

Supplementary materials

Descriptive analysis

All hospital visits among our patient cohort were identified from available inpatient and emergency department (ED) data across the five hospitals during April 2011 to March 2014. Given the need for multidisciplinary teams to be recruited, the case management program was not implemented at the same time in all facilities (start dates varied between September 2011 and February 2012), we identified for each hospital a “preprogram” period and matched “program year 1” and “program year 2” periods of equal length. For a facility beginning program delivery on February 1, 2012, for example, the preprogram, year 1, and year 2 periods were defined as April 2011 to January 2012, April 2012 to January 2013, and April 2013 to January 2014, respectively. In this way, each period for a facility was comparable both in terms of duration and time of the year. These three periods were used to calculate and compare basic descriptive statistics on the numbers and proportions of patients and admissions and on the lengths of stay, before, and after implementation of the program. Our analyses focus on inpatient admissions with a primary diagnosis of COPD (ICD-10 codes J440, J441, J448, and J449), although we also considered patterns for “all-cause admissions” as well as in ED visits where discharge diagnosis contained the phrase “chronic obstructive”.

Inferential analysis

Recurrent events regression modeling was used to assess changes in readmission rates in relation to the program.¹ For this analysis, each patient’s earliest hospital admission for COPD in our dataset was used as the starting point (time =0) or “index admission”, for tracking through the entire study period. Time-at-risk (days) was accumulated for each patient using their discharge-to-readmission intervals (ie, not including duration of hospital stays) starting from the discharge date of their index admission. The final at-risk interval for each individual runs from their last documented discharge to end of study (March 31, 2014), with individuals being censored after their last discharge. Time-at-risk was calculated both for all-cause readmissions and for readmissions with a primary diagnosis of COPD only. The model analyzed the readmission rates for patients according to their index admission (before program implementation, during year 1 of program delivery, or beyond year 1) and included as covariates gender, hospital, age, number of previous readmissions (1, 2, 3, 4, 5, and >5), fiscal year, and resource intensity weight (RIW, a relative measure of a patient’s total resource use, used here as a proxy for severity of illness).² This “counting process” model, an extension of the Cox regression model, estimates hazard ratios (HR) and cumulative mean readmissions by index COPD period adjusted for covariates.³ Standard errors were calculated using the robust sandwich variance estimator to account for the nonindependence of multiple readmissions by a single individual. Linear regression modeling was used to compare average length of stay (LOS) for COPD readmissions in relation to the program. Log-transformed LOS was regressed against covariates age, gender, hospital, RIW, and fiscal year, and the best-fit model was selected using backward stepwise elimination of nonsignificant interaction terms. The nonindependence of observations on individuals was accounted for using generalized estimating equations (GEE) model fitting.

Intervention

Home visit aimed at assessing patients’ vitals, symptoms, review of medications, inhaler technique, immunization status, review of self-management information including deep breathing, relaxation exercises, effective cough technique, and smoking cessation counseling. Moreover, patients were also provided with teaching sessions regarding COPD management with emphasis on early detection of a flare up and encouragement to discuss with their family physician and to obtain prescriptions for antibiotics and prednisone. Written information was provided in patient’s language (when available). If no written plan and/or prescriptions had been previously provided by the family physician, the patient encouraged to make appointment and discuss with family physician an alternate plan of action for future exacerbations. Support and education for family members, caregivers, facility, and home support care staff were also provided.

COPD teams proactively informed primary care physicians via faxed letter (usual) or phone call (if more urgent matter), regarding the disposition of their patients, respiratory status, and any outstanding issues from home visit, and provided with suggestions for treatment or changes to treatment based on COPD guidelines including referral for outpatient spirometry if it had not been done previously or if it needed repeating, as well as referral for pulmonary rehabilitation or specialist respiratory consultations if indicated.

Community support services were provided if ongoing chronic disease management needed beyond 3 months (respiratory therapy, physiotherapy, occupational therapy, social worker, home support, meal delivery service, etc.). After discharge from formal follow-up in program, patient encouraged to contact team for any future questions or issues.

Table S1 Parameter estimates from Cox regression model for all-cause readmissions

Table S2 Parameter estimates and hazard ratios from Cox regression model for MR Dx COPD readmissions

Table S3 Mean LOS in days among inpatients with primary diagnosis of COPD during selected periods before and after program implementation

References

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Acknowledgments

The abstract of this paper was presented at the Chest 2015 Annual Meeting in Montreal, Quebec, Canada, October 24–28, 2015, and the abstract published in the Chest Journal Abstracts Meeting. 2015;148(4_MeetingAbstracts):715A. doi:10.1378/chest.2278816. We would like to acknowledge the members of the COPD transition team program: Carmen Rempel RRT, CRE; Jane Burns RT, CAE; Elizabeth Leonardis NP; Erin Toplak RRT, CRE; Grace Wei RN, BSN; Christine Hinds RRT, CRE; Laura Lotzer RN, MN; and Alessandria Ferraro. We also would like to express our appreciation to the COPD patients who adopted and appreciated the benefits of this program from its initiation. Funding for this program was provided through the Provincial Government Patient Focused Funding (PFF) project, BC, Vancouver, Canada.

Disclosure

The authors report no conflicts of interest in this work.