© 2014 Wiley Periodicals, Inc.

1

ACQUIRED CARDIOVASCULAR DISEASE ORIGINAL ARTICLE _____________________________________________________________

Predictors for Hospital Readmission After Cardiac Surgery Aleksandar Red
zek, M.D., Ph.D.,*,y Melisa Mironicki, M.D.,y Andrea Gvozdenovic, M.D.,y 9 emerlic-Ad-ic, M.D., Ph.D.,*,y Aleksandra Ilic, M.D.,y Milovan Petrovic, M.D., Ph.D.,*,y Nada C , and Lazar Velicki, M.D., Ph.D.* y *Medical Faculty, University of Novi Sad, Novi Sad, Serbia; and yInstitute of Cardiovascular Diseases Vojvodina, Sremska Kamenica, Sremska Kamenica, Serbia ABSTRACT Background and Aim of the Study: Unplanned hospital readmissions are responsible for increased health care costs and have direct influence on patient quality of life. The aim of the study was to determine the predictors for hospital readmission after open-heart surgery. Methods: Prospective study analyzed all patients who underwent cardiac surgery in the year 2012. Follow-up period was one year from the date of operation. Patients were divided in two groups based on their readmission status. Results: In the study period of one year, 1268 patients who underwent cardiac surgery were included. A total of 121 patients (9.54%) were readmitted within one year after the operation. The main reasons for readmission were congestive heart failure (17.3%), sternal dehiscence (14.9%), rhythm and conduction disturbances (14.9%), wound infection (11.6%), recurrent angina pectoris (11.6%), and pericardial effusion (10.7%). Independent predictors for hospital readmission were previous stroke (p = 0.002), chronic heart failure (p < 0.0005), and postoperative pericardial effusion (p = 0.006). Conclusions: Our study determined risk factors and predictors for hospital readmission after cardiac surgery. This may help to reduce readmission rates. doi: 10.1111/

jocs.12441 (J Card Surg 2015;30:1–6) Thirty-day mortality has been the primary measure for quality assessment after cardiac surgery.1 However, there are other adverse outcomes that might be worthy of consideration. One of these is readmission rate after hospital discharge. Approximately 20% of Medicare patients are readmitted within 30 day of discharge in the United States.2 Readmission rate after cardiac surgery has a direct influence on patient quality of life and health care costs. Only a limited number of studies have examined predictors for readmission of cardiac surgery patients.3–6 The main goal of the study was to determine the predictors for hospital readmission after open-heart surgery. METHODS Study population This prospective study analyzed all patients who underwent cardiac surgery at the Institute of Cardio-

Conflict of interest: The authors acknowledge no conflict of interest in the submission. Address for correspondence: Lazar Velicki, M.D., Ph.D., Institute of Cardiovascular Diseases Vojvodina, Put doktora Goldmana 4, 21204 Sremska Kamenica, Serbia. Fax: þ381 21 66 22 881; e-mail: lazar. [email protected]

vascular Diseases of Vojvodina in the one-year period of 2012. Excluding criteria were the presence of concomitant surgical procedure in the same hospitalization when cardiac surgery was performed (carotid endarterectomy and operation of abdominal aortic aneurysm) or emergent cardiac surgical procedure (operation before the beginning of the next working day after decision to operate). The number of these patients is less than 1% of our annual case load. Fast-track protocols have been implemented for selected patients undergoing cardiac surgery. Patients suitable for fast track protocol were those scheduled for isolated coronary artery bypass grafting (CABG), offpump coronary artery bypass (OPCAB), and isolated aortic valve replacement (AVR), with no significant comorbidities or procedure-related complications. The study was approved by the institutional review board. Follow-up period and risk factors Follow-up period for hospital readmission was one year from the date of the index operation. Only the patients readmitted to our center were followed with no information on how many patients were readmitted to outside hospitals during this time. However, our hospital is the only cardiac surgery center covering the region of about two million inhabitants so one may

2

REDZˇEK, ET AL. READMISSION AFTER CARDIAC SUREGRY

assume that most if not all patients requiring cardiac surgery would be referred to our center. Consequently, any major postoperative complication (such as those examined in this work) would be forwarded back to us. Examined factors were divided in three groups: preprocedural (patient related), procedural, and postprocedural. Preprocedural factors included: gender, age, previous stroke, peripheral arterial obstructive disease (PAOD), low ejection fraction (220 mg/dL), three vessel coronary disease, ‘‘left main’’ stenosis greater than 50%, previous cardiac surgery, or percutaneous intervention. Procedural factors were: type of cardiac surgery intervention, aortic cross-clamp (ACC) time, cardiopulmonary bypass (CPB) time, and surgeon-specific caseload. According to the type of intervention, patients were divided in groups of those who underwent isolated coronary surgery, isolated valvular surgery, and combined (coronary and valvular) surgery. The third group of risk factors included: re-exploration for bleeding and/or tamponade, pericardial drainage due to late pericardial effusion not requiring drainage during the index hospitalization, length of stay in the intensive care unit (ICU), laboratory findings on the first day after the operation (urea, creatinine, CK-MB fraction), and health care insurance region. Statistical analysis Statistical analysis was performed using the SPSS 19.0 (Statistical Package for Social Science for Windows 19). A p value of 220 mg/dL) 3-vessel coronary disease ‘‘Left main’’ stenosis >50% Previous cardiac surgery Previous PCI Chronic renal failure Type of operation Coronary Valvular Combined Postoperative complications Discharged with pericardial effusion

Frequency, n

%

862 406 97 24 183 120 49 568 358 796 646 158 32 90 65

68 32 7.6 1.9 14.4 9.5 3.9 44.8 28.2 62.6 50.9 12.5 2.5 7.1 5.1

784 268 216 190 103

61.8 21.2 17 15 8.1

CVA, cerebrovascular accident; PAOD, peripheral arterial obstructive disease; COPD, chronic obstructive pulmonary disease; MI, myocardial infarction; HLP, hyperlipoproteinemia; PCI, percutaneous coronary intervention.

previous stroke (p ¼ 0.002), PAOD (p ¼ 0.025), previous pulmonary edema (p ¼ 0.026), CHF (p < 0.001), diabetes mellitus (p ¼ 0.05), chronic renal failure (p ¼ 0.021), and insurance region (p < 0.001) as shown on Table 4. From procedure-related factors, ACC time (p ¼ 0.018) and CPB time (p ¼ 0.013) were significantly different between the groups (Table 5) as well as length of stay in ICU (p < 0.001), and mild to moderate postoperative pericardial effusion not requiring pericardial drainage during index hospitalization (p ¼ 0.008) (Table 6). There was a significant difference in length of hospital stay between readmitted and non-readmitted patients (13.17  10.07 vs. 10.82  7.29, p ¼ 0.003), but there was no correlation between the length of hospital stay and subsequent readmissions (r ¼ 0.071, p ¼ 0.437) nor between length of stay in the ICU and subsequent readmission (r ¼ 0.005, p ¼ 0.958). Independent predictors for hospital readmission were previous stroke (p ¼ 0.002), CHF (p < 0.0005), and postoperative pericardial effusion (p ¼ 0.006) (Table 7). An analysis of the difference in patient profiles between patients readmitted early versus late was conducted and the only significant difference was the left ventricular ejection fraction (Fig. 1). Patients readmittied within one month after the surgery had the average value of 52.39  10.29% while those readmitted late had the value of 47.35  12.96% (p ¼ 0.024). Although the threshold for statistical significance was not reached (p ¼ 0.058), it is indicative that among those readmitted within the first month after the operation, 36.9% of them were without CHF while only 18.9% were with CHF.

REDZˇEK, ET AL. READMISSION AFTER CARDIAC SUREGRY

J CARD SURG 2015;30:1–6

3

TABLE 2 Mean Values of Patient- and Procedure-Related Risk Factors in Whole Sample

Age (year) Weight (kg) Hight (cm) EF (%) Aortic cross-clamping time (minute) CPB time (minute) Artificial ventilation time (hours) Time in ICU (days) CK-MB—first postoperative day (IU/L) Urea—first postoperative day (mg/dL) Creatinine—first postop. day (mg/dL)

Mean

Standard Deviation

Min

Max

65.27 80.7 169.3 52.6 70.29 82.8 14 1.63 42.4 20.25 1.29

8.8 14.4 10.6 10.3 31.9 36.3 6.9 1.4 38.3 13.44 0.31

24 40 70 17 11 16 2 1 5 5.32 0.42

88 135 194 74 240 350 39 18 463 277.31 3.76

EF, ejection fraction; CPB, cardiopulmonary bypass; ICU, intensive care unit.

There was no association between the incidence of pericardial effusions and incidence of Coumadin usage (p ¼ 0.308). DISCUSSION Unplanned hospital readmission is a common problem as a frequent, costly, and potentially life-threatening event. In the near future, unplanned hospital readmission will take a new significance. Hospitals will be forced to report their readmission rates and will be penalized for poor performance. A number of studies have tried to identify which patients are most at risk for unplanned readmission.7–9 The relative lack of uniform terminology and methodology makes interpretation of these studies difficult. Identifying the patients at highest risk for readmission will be of great importance in order to reduce preventable hospital readmissions. Morris et al.10 reported deep venous thrombosis, acute renal failure, and increased length of hospital stay and public insurance to be associated with increased risk for readmission. In a cohort study published by Price et al.11 female gender, government insurance, previous cerebrovascular disease, and peripheral vascular disease were identified as predictors for rehospitalization. A prediction model based on simple administrative

TABLE 3 Reasons for Readmission in Period of One Year After Surgery Readmission Reason Total Congestive heart failure Recurrent angina pectoris Rhythm and conduction disturbances Arterial hypertension Pericardial effusion Complication of anticoagulation therapy Pneumonia and pleural effusion Pulmonary thromboembolic event Cerebrovascular event Aortic dissection Sternal dehiscence Wound infection

Frequency, n

%

121 21 14 18 3 13 3 12 2 2 1 18 14

9.54 17.3 11.6 14.9 2.4 10.7 2.5 9.9 1.6 1.6 0.8 14.9 11.6

hospital data designed by Wallmann et al.12 contains 11 predictor variables. Six of these variables were similar to those found in other studies: number of previous admissions, anemia, acute coronary syndrome, congestive heart failure, diabetes, and renal disease. A recent systematic review of risk prediction models for all hospital readmissions found that most models had poor predictive ability, regardless of the type of data used.13 Our data showed statistically significant differences in the presence of a previous stroke, PAOD, previous pulmonary edema, CHF, diabetes mellitus, chronic renal failure, insurance region between readmitted and not-readmitted patients. From procedurerelated factors, ACC time and CPB time were significantly different between the two group of patients as well as postoperative time in the ICU and mild to moderate postoperative pericardial effusion without pericardial drainage. Longer CPB time is a direct measure of the complexity of surgical intervention or procedural complications that could influence late outcomes. Oxlad et al.14 found shorter CPB time as a predictor of readmission, perhaps as a result of an incomplete surgical procedure (not all stenotic vessels being revascularized, irrespective of size, and territory supplied mainly due to diffuse peripheral calcified coronary artery disease). In our study independent predictors for hospital readmission were previous stroke, CHF, and postoperative pericardial effusion. We determined the one year follow-up period to be more representative for detection of operation-related readmissions. Nevertheless, in most published studies 30-day readmission rate was analyzed. In a follow-up period of one year, 9.54% of operated patients were readmitted to our hospital. Thirty-day readmission rate was 4.65%. The literature suggests a higher 30-day readmission rate after CABG, with a range across hospitals of 8.3% to 21.1%.1 A possible reason for lower readmission rates documented in our study is that readmissions (due to minor complications) to hospitals outside our health care network may not have been captured. The most common reasons for readmission in our hospital within one year of discharge are presented in Table 3. Using the data from the New York State Cardiac Surgery Reporting System (CSRS) for more than 30 thousand patients that underwent

4

REDZˇEK, ET AL. READMISSION AFTER CARDIAC SUREGRY

J CARD SURG 2015;30:1–6

TABLE 4 Preoperative Readmission Risk Factors Analysis All (n = 1268)

Risk Factors Preoperative variables Age, years Sex, female, n (%) Weight, kg Height, cm CV disease, n (%) PAD, n (%) Congestive heart failure Previous pulmonary edema, n (%) EF, % MI 50%, n (%) Free vessel coronary disease, n (%) Previous cardiac surgery, n (%) Previous PCI, n (%) Arterial hypertension, n (%) COPD, n (%) Smoking, n (%) Diabetes mellitus, n (%) HLP, n (%) Chronic renal failure, n (%) Primary insurance region, n (%) Branch office 1 Branch office 2 Branch office 3 Branch office 4 Branch office 5 Branch office 6 Branch office 7 Other (no valid data)

65 406 80 170 97 24 183 3 55 49 158 646 32 90 1002 120 568 358 796 65 96 138 49 48 167 490 136 144

(60–72) (32) (71–90) (163–176) (7.6) (1.9) (14.4) (0.2) (47–60) (3.9) (12.5) (50.9) (2.5) (7.1) (79) (9.5) (44.8) (28.2) (62.8) (5.1) (7.6) (10.9) (3.9) (3.8) (13.2) (38.6) (10.7) (11.4)

Readmitted (n = 121)

68 39 77 168 19 6 37 2 50 8 17 61 5 13 100 15 53 44 73 12 7 6 2 3 9 73 17 4

Not Readmitted (n = 1147)

(63–71) (32.2) (66–85) (160–173) (15.7) (5) (30,6) (1.7) (38–59) (6.6) (14) (54) (4.1) (10.7) (82.6) (12.4) (43.8) (36.4) (60.3) (9.8)

65 367 80 170 78 18 146 1 56 41 141 585 27 77 902 105 515 314 723 53

(61–72) (32) (70–90) (163–176) (6.8) (1.6) (12.7) (0.1) (49–60) (3.6) (12.3) (51) (2.4) (6.7) (78.6) (9.2) (44.9) (27.4) (63) (4.6)

(5.8) (5.0) (1.7) (2.5) (7.4) (60.3) (14) (3.4)

89 132 47 45 158 417 119 140

(7.8) (11.5) (4.1) (3.9) (13.8) (36.4) (10.4) (12.3)

P-Value

0.109 0.516 0.968 0.423 0.002 0.025