Randomized Clinical Trial Open Access
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Jun 27, 2023; 15(6): 826-840
Published online Jun 27, 2023. doi: 10.4254/wjh.v15.i6.826
Randomized intervention and outpatient follow-up lowers 30-d readmissions for patients with hepatic encephalopathy, decompensated cirrhosis
Antoinette Pusateri, Claire Griffiths, Caitlin Hayes, Sean G Kelly, Sajid Jalil, Khalid Mumtaz, Division of Gastroenterology, Hepatology and Nutrition, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
Kevin Litzenberg, Michelle Manious, Division of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
Bipul Gnyawali, The Ohio State University College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH 43210, United States
Lanla F Conteh, Division of Gastroenterology and Hepatology, The Ohio State Wexner Medical Center, Columbus, OH 43210, United States
Haikady N Nagaraja, Division of Biostatistics, The Ohio State University, Columbus, OH 43210, United States
ORCID number: Antoinette Pusateri (0000-0002-8458-7827); Bipul Gnyawali (0000-0003-4745-2787); Sean G Kelly (0000-0002-9434-9924); Lanla F Conteh (0000-0002-4372-993X); Sajid Jalil (0000-0001-6123-153X); Khalid Mumtaz (0000-0001-7868-6514).
Author contributions: Pusateri A and Mumtaz K study design, team administration, training team members for recruiting, recruiting patients for study, interpreting data, drafting manuscript; both approved the final submitted version of this manuscript; Litzenberg K, Griffiths C, Hayes C, Gnyawali B and Manious M recruiting patients for study, drafting manuscript, approved the final submitted version of manuscript; Jalil S, Kelly S and Conteh L reviewed and edited the final draft of the manuscript; Nagaraja K analyzed data, edited manuscript, and approved the final submitted version of this manuscript.
Supported by GASTR29: Prospective validation of readmission risk score and interventions to prevent readmission in patients with decompensated cirrhosis (CCTS ID#: 6018).
Institutional review board statement: This study was conducted at the Ohio State University Wexner Medical Center (OSUWMC), Columbus, Ohio from July 2019 to December 2020. Our study was approved by OSUWMC Institutional Review Board. All aspects of the studying involving human participants including informed consent for enrollment were in accordance with the ethical standards of our Institutional Review Board and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Clinical trial registration statement: Since our randomized trial was of a nursing intervention only, it was not an official randomized control clinical trial that needed registering on a national level.
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Antoinette Pusateri, MD, Doctor, Division of Gastroenterology, Hepatology and Nutrition, The Ohio State University Wexner Medical Center, 2nd Floor Doan Office Tower 395 W. 12th Avenue, Columbus, OH 43210, United States. antoinette.pusateri@osumc.edu
Received: December 22, 2022
Peer-review started: December 22, 2022
First decision: February 14, 2023
Revised: March 23, 2023
Accepted: April 14, 2023
Article in press: April 14, 2023
Published online: June 27, 2023
Processing time: 185 Days and 2.3 Hours

Abstract
BACKGROUND

We previously reported national 30-d readmission rates of 27% in patients with decompensated cirrhosis (DC).

AIM

To study prospective interventions to reduce early readmissions in DC at our tertiary center.

METHODS

Adults with DC admitted July 2019 to December 2020 were enrolled and randomized into the intervention (INT) or standard of care (SOC) arms. Weekly phone calls for a month were completed. In the INT arm, case managers ensured outpatient follow-up, paracentesis, and medication compliance. Thirty-day readmission rates and reasons were compared.

RESULTS

Calculated sample size was not achieved due to coronavirus disease 2019; 240 patients were randomized into INT and SOC arms. 30-d readmission rate was 33.75%, 35.83% in the INT vs 31.67% in the SOC arm (P = 0.59). The top reason for 30-d readmission was hepatic encephalopathy (HE, 32.10%). There was a lower rate of 30-d readmissions for HE in the INT (21%) vs SOC arm (45%, P = 0.03). There were fewer 30-d readmissions in patients who attended early outpatient follow-up (n = 17, 23.61% vs n = 55, 76.39%, P = 0.04).

CONCLUSION

Our 30-d readmission rate was higher than the national rate but reduced by interventions in patients with DC with HE and early outpatient follow-up. Development of interventions to reduce early readmission in patients with DC is needed.

Key Words: Decompensated cirrhosis; Hospital readmissions; Interventions

Core Tip: Our 30-d readmission rate was higher than the national rate but reduced by interventions in patients with decompensated cirrhosis (DC) with hepatic encephalopathy and early outpatient follow-up. Development of interventions to reduce early readmission in patients with DC is needed.



INTRODUCTION

Cirrhosis affects approximately 5 million annually[1] and has been reported to be the 8th leading cause of death with more than 40000 deaths annually in the United States[2]. A study on the burden of gastrointestinal (GI), liver, and pancreatic diseases in the United States revealed that liver diseases had the highest mortality at 3.1%[3]. In addition to high mortality, cirrhosis is also associated with high morbidity. The sequelae of decompensated cirrhosis (DC) are often managed during hospital admissions and include volume overload in the form of ascites, edema or hepatic hydrothorax, portal hypertension leading to bleeding esophageal or gastric varices, as well as hepatic encephalopathy (HE), hyponatremia, acute kidney injury (AKI), and spontaneous bacterial peritonitis (SBP)[4].

Several studies have demonstrated hospital readmissions in DC place a large financial burden on the United State healthcare system. The 30-d readmission rate has been reported to be 20%-37%[5-14]. We have recently published on early readmission rates up to 27% in patients with DC and developed the Mumtaz readmission risk score based on United States data[15]. We also reported that nearly one-third of patients with HE were readmitted within 30 d, and early readmission adversely impacted healthcare utilization and calendar-year mortality[16].

Interventions to reduce readmissions have been shown to be safe and effective. For instance, Morales et al[17] developed a program including a hepatologist follow-up exam within 7 d after discharge. This program resulted in a reduction in 30-d readmissions, 60-d mortality, emergency department visits and associated costs[17]. Similarly, another group demonstrated that follow-up with a “care management check-up” as opposed to “standard outpatient care” reduced 30-d readmission, 12-mo mortality and saved 1500 euros per patient month of life[18].

There is a paucity of prospective studies on interventions to reduce early readmission rates in patients with DC. Therefore, we prospectively studied 30-d readmission rates in patients with DC and compared various interventions (INT) with standard of care (SOC) to reduce early readmission rates. We hypothesized that DC patients in the INT arm would have decreased 30-d readmission vs the SOC arm.

MATERIALS AND METHODS

This study was conducted at the Ohio State University Wexner Medical Center (OSUWMC), Columbus, Ohio from July 2019 to December 2020. Our study was approved by OSUWMC Institutional Review Board. All aspects of the studying involving human participants including informed consent for enrollment were in accordance with the ethical standards of our Institutional Review Board and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Screening

All patients admitted with DC to the hepatology (inpatient or consult) service were screened for enrollment. Patients meeting inclusion criteria were approached for study consent. Of note, due to the global coronavirus disease 2019 (COVID-19) pandemic, beginning March 2020, only COVID negative patients were approached for informed consent. Elective readmissions for inpatient procedures including endoscopy, trans-arterial chemoembolization, transjugular intrahepatic portosystemic shunt (TIPS), paracentesis or readmissions unrelated to DC such as motor vehicle accidents were excluded.

Randomization and data collection

Study data were collected and managed using research electronic data capture (REDCap) hosted at The Ohio State University Wexner Medical Center[19,20]. Informed consent was obtained from all individual participants included in the study. Consented patients were randomly assigned to either the INT arm or the SOC arm in a 1:1 ratio using the REDCap randomization tool. The following data were collected on all patients via REDCap software including demographics (age, sex, insurance type, income based on the zip code), hospitalization data [date of index admission defined as initial admission during which patient consented for study, reason for admission, length of stay (LOS) defined as difference in days between index admission date and index admission discharge date, discharge disposition, associated cost of care of admission as obtained through medical record billing tab], etiology of cirrhosis (alcoholic and non-alcoholic including viral, non-alcoholic fatty liver disease, autoimmune, primary biliary cirrhosis, primary sclerosing cholangitis or cryptogenic), complications of cirrhosis (HE, AKI, ascites, variceal bleeding, SBP, hepatorenal syndrome, coagulopathy, portal hypertension, hepato-pulmonary syndrome, hepatocellular carcinoma), and procedures performed during admission [esophago-gastro-duodenoscopy, colonoscopy or flexible sigmoidoscopy, paracentesis, TIPS and hemodialysis (HD) on admission and discharge]. We also collected data including Elixhauser comorbidity index, discharge medications, and laboratory data (complete blood counts, serum creatinine, liver function tests including total bilirubin, INR, and sodium). Child Turcotte Pugh (CTP) and Sodium-model for end stage liver disease (MELD-Na) score were calculated from the data. The nurse case manager (CM) also recorded labs & medications at readmission and discharge and associated cost of readmission. Status of early readmission, liver transplantation, and mortality at one year were also collected.

Follow-up

The CM phoned each patient enrolled in either arm weekly for 30 d after index discharge to find out if the patient has been readmitted to OSUWMC or another hospital. In the INT arm, during the call CM also ensured i) early (defined as within 30 d from index admission discharge) outpatient hepatology follow-up ii) compliance of medication, iii) arrangement of outpatient paracentesis if needed, and reviewed outpatient hepatology clinic follow-up records. SOC arm as per our center’s protocol had to be taken care of by the primary inpatient team. This included arranging early outpatient clinic follow-up, providing list of medications, and advice for outpatient paracentesis if needed at the time of discharge. Due to the nature of intervention, the study could not be blinded.

Definition of outcomes

Early readmission was defined as admission within 30 d of index admission discharge. Reasons for readmission were gathered by CM by reviewing the electronic medical record (EMR) of all enrolled patients readmitted at OSUWMC or outside hospital within 30 d of index admission. Predictors of early readmission were also compared in the two arms.

Sample size

Based on the sample size calculation, target of recruitment for the study was 848 patients, admitted to the hospital with DC under the hepatology (inpatient and consult) services. Patients were randomly assigned in a 1:1 ratio into INT or SOC arms. Based on our previous study using the National Readmissions Administrative Database, we expected a 30-d readmission rate of 27% among patients meeting inclusion criteria, which yield 114/424 patients with 30-d readmission events, thus meeting the target sample size. Based on this calculation, a total sample size of 848 (424 per group) provided 80% power to detect a 30% decrease in 30-d readmission rate (from 27% to 19%) with a type I error rate of 0.05. However, planned sample size could not be achieved due to the COVID-19 pandemic related restriction started in our center in March 2020. Therefore, we end up with available sample size of a total of 240 patients. The modified consort flow diagram for enrollment in our study trial is illustrated in Figure 1.

Figure 1
Figure 1 Modified consort flow diagram of patients eligible for enrollment in study trial. INT: Intervention; SOC: Standard of care.
Statistical analysis

Means of continuous response variables between two groups were compared using robust t-test (Welch test). Proportions were compared using χ-test or Fisher’s exact test as applicable. Logarithmic transformation was used for comparing the LOS and admission cost across groups. Level of significance was kept at 0.05 for each comparison. JMP Version 15 (SAS Institute, NC) was used for all the analyses.

RESULTS
Initial screening data

From July 1, 2019, to December 1, 2020, 1392 patients were screened. Due to the COVID-19 pandemic, recruitment was held from March 2020 to July 2020 and subsequently resumed until December 2020. Out of the patients screened, only 499 (35.85%) were eligible for inclusion; however, 240 patients consented and randomized: 120 each into the INT and SOC arm (Figure 1).

Patient demographics and clinical characteristics

The mean age of patients was 56.34 ± 11.19 years, majority were males (135, 56.25%), belonged to White race (n = 202, 84.17%) and non-Hispanic or Latino ethnicity (n = 227, 94.58%). Almost two-thirds of the patients had public insurance (n = 76, 31.67% on Medicare and n = 70, 29.17% on Medicaid); 73 (30.42%) had private insurance. At admission, the mean MELD-Na score and mean CTP Score were 21.89 ± 8.03 and 9.36 ± 1.96, respectively. Major etiology of cirrhosis was alcohol (n = 121, 50.42%) followed by non-alcoholic fatty liver disease (n = 79, 32.92%) and viral hepatitis (n = 43, 17.92%). Furthermore, 116 (48.33%) patients were actively under evaluation for liver transplantation.

Characteristics of index admissions

The index admission mean LOS was 8.13 ± 5.83 d (median 6, range 1-43 d). The mean cost of index admission was $60595 ± $47174 (n = 225, median $42932, range $1630-251991). The top five reasons for index admission included volume overload (n = 111, 46.25%), AKI (n = 65, 27.08%), hepatic encephalopathy (n = 45, 18.75%), variceal bleed (n = 42, 17.50%), lower GI bleed (n = 19, 7.92%) and hyponatremia (n = 16, 6.67%). The top five interventions performed were esophago-gastro-duodenoscopy (n = 136, 56.67%), paracentesis (n = 115, 47.92%), colonoscopy/flexible sigmoidoscopy (n = 24, 10 %), HD (n = 15, 6.25%) and TIPS (n = 10, 4.17%). Most patients were discharged from index admission to home (n = 159, 66.25%) followed by home with health care (n = 42, 17.50%) and skilled nursing facility (n = 32, 13.33 %, Table 1).

Table 1 Characteristic features of index admission by readmission status, n (%).

Total
Not readmitted (n = 159)
Readmitted (n = 81)
P value
Index admission characteristics
Reasons for admission1
    Acute kidney injury65, 27.0841, 25.7924, 29.630.54
    Hyponatremia16, 6.6711, 6.925, 6.171.00
    Hepatic encephalopathy45, 18.7526, 16.3519, 23.460.22
    Volume overload111, 46.2581, 50.9430, 37.040.06
    Variceal bleed42, 17.5031, 19.5011, 13.580.29
    Lower GI bleed19, 7.9211, 6.928, 9.880.45
    SBP21, 8.7514, 8.817, 8.641.00
Complications of cirrhosis during admission1
    Presence of AKI80, 33.3350, 31.4530, 37.040.39
    HE49, 20.4231, 19.5018, 22.220.62
    Ascites139, 57.9295, 59.7544, 54.320.49
    Variceal bleeding37, 15.4226, 16.3511, 13.580.71
    SBP16, 6.6712, 7.554, 4.940.59
    HRS14, 5.838, 5.036, 7.410.56
    Coagulopathy56, 23.3336, 22.6420, 24.690.75
    Portal hypertension46, 19.1734, 21.3812, 14.810.30
    HPS15, 6.258, 5.037, 8.640.27
    HCC11, 4.586, 3.775, 6.170.51
Procedures performed during admission1
    EGD136, 56.6792, 57.8644, 54.320.68
    Paracentesis115, 47.9273, 45.9142, 51.850.41
    Emergent TIPS10, 4.179, 5.661, 1.230.17
    HD15, 6.257, 4.408, 9.880.16
    Colonoscopy/flex sig24, 10.0018, 11.326, 7.410.37
Disposition1
    Home159, 66.25107, 67.3052, 64.200.66
    Home with Home Health Newly Arranged39, 16.2524, 15.0915, 18.52
    Home with Home Health Previously Arranged3, 1.252, 1.261, 1.23
    SNF newly Arranged21, 8.7516, 10.065, 6.17
    SNF Previously Arranged11, 4.585, 3.146, 7.41
    Left Against Medical Advice2, 0.831, 0.631, 1.23
    Transfer (long term acute care hospital)3, 1.252, 1.261, 1.23
    Homeless2, 0.832, 1.260, 0.00
Characteristics and reasons for early readmissions

Overall, 81 (33.75%) patients were readmitted within 30 d of discharge. The major reasons for first readmission included hepatic encephalopathy (n = 26, 32.10%) followed by volume overload (n = 22, 27.16%), AKI (n = 16, 19.75%), variceal bleed (n = 12, 14.82%) and hyponatremia (n = 10, 12.35%). 14 patients were readmitted twice, 3 admitted thrice and one admitted 5 times within 30 d. The mean time to first readmission was 12.65 ± 7.55 d (median 12 d, range 1-30 d). The mean LOS of first readmission was 8.11 ± 8.98 days. The mean cost of stay of first readmission was $55548.29 ± $65164.91 (Table 2). Those readmitted had a higher MELD-Na score on index admission (23.54 ± 7.80 vs 21.05 ± 8.03, P = 0.02) and index discharge (21.67 ± 7.95 vs 19.39 ± 6.89, P = 0.03) than those not readmitted. Similarly, those readmitted had a higher index admission creatinine (1.80 ± 1.53 vs 1.39 ± 1.16, P = 0.03), index discharge creatinine (1.61 ± 1.34 vs 1.20 ± 0.97, P = 0.02), and higher index admission INR (1.80 ± 0.64 vs 1.63 ± 0.50, P = 0.05) than those not readmitted.

Table 2 Characteristics and reasons for readmission.
Readmission statusn%
    No15966.25
    Yes8133.75
Number of readmissions within 30 d
    015966.25
    16326.25
    2145.83
    331.25
    510.42
Location of 1st readmission
    OSUWMC5972.84
    Outside hospital2227.16
Reason for 1st readmission1
    Hepatic encephalopathy2632.10
    Volume overload 2227.16
    Acute kidney injury1619.75
    Variceal bleed1214.82
    Hyponatremia 1012.35
    Lower GI bleed44.94
    Spontaneous Bacterial Peritonitis 33.70
LOS of first readmission (n = 81, mean ± SD), median = 5, range = 1 to 698.11 ± 8.98
LOS of all readmissions (n = 105, mean ± SD), median = 4, range = 0 to 1249.03 ± 14.42
Cost of first readmission (n = 45, mean ± SD), median= $31848.95, range $765-325656.38$55548.29 ± 65164.91
Waiting time for first readmission (n = 81, mean ± SD), median = 12, range = 1-3012.65 ± 7.55
Comparison of demographics and clinical characteristics in two intervention arms

Demographics including age, race, ethnicity, income, and insurance were comparable in two groups, as well as etiology of cirrhosis, MELD-Na score, CTP score, status of evaluation for liver transplant. There were majority females in the INT arm (60/120, 50% vs 45/120, 32.50%) and males in SOC arm (75/120, 62.50% vs 60/120, 50%, P = 0.03, Table 3). Index admission characteristics, disposition and index admission were also comparative in two arms (Tables 4 and 5).

Table 3 Comparison of patient demographics and clinical characteristics by randomization arm, n (%).

Intervention (n = 120)
Standard of care (n = 120)
P value
Patient demographics
Age (mean ± SD)56.54 ± 11.2156.14 ± 11.210.78
Age group
    65+32, 26.6728, 23.330.79
    40-6475, 62.5080, 66.67
    18-3913, 10.8312, 10.00
Gender
    Male60, 50.0075, 62.500.03
    Female60, 50.0045, 32.50
Race
    White105, 87.5097, 80.830.22
    Other15, 12.5023, 19.17
Ethnicity
    Not Hispanic or latino113, 94.17114, 95.000.81
    Hispanic or latino3, 2.501, 0.83
    Unknown / Not reported4, 3.335, 4.17
Zip code income (mean ± SD)$68045 ± $21370$68455 ± $216510.88
Employment status
    Unemployed33, 27.5030, 25.000.78
    Disabled24, 20.0024, 20.00
    Retired26, 21.6730, 20.00
    Employed, part time5, 4.173, 2.50
    Employed, full time23, 19.1728, 23.33
    Other / Unknown9, 7.5014, 11.67
Insurance type
    Self-pay4, 3.333, 2.500.54
    No Charge / Other / Unknown7, 5.837, 5.83
    Private insurance38, 31.6735, 29.17
    Medicare32, 26.6744, 36.67
    Medicaid39, 32.5031, 25.83
Number of admissions at OSU for DC in last 1 year (mean ± SD)1.99 ± 1.611.84 ± 1.480.45
MELD-Na score admit (mean ± SD)21.32 ± 8.1922.47 ± 7.850.27
MELD-Na score discharge (mean ± SD, n = 117+118)20.07 ± 7.7420.25 ± 6.930.84
CTP score admit (mean ± SD)9.31 ± 2.029.41 ± 1.890.69
CTP score discharge (mean ± SD)8.44 ± 1.868.73 ± 1.890.24
Etiology of cirrhosis (Index admission1)
    Alcoholic61, 50.8360, 50.001.00
    Non-alcoholic fatty liver42, 35.0037, 30.830.58
    Viral21, 17.5022, 18.331.00
    Hep B1, 4.763, 13.640.80
    Hep C19, 90.4818, 81.82
    Hep B and C1, 4.761, 4.55
    Cryptogenic6, 5.007, 5.831.00
    Autoimmune1, 0.831, 0.831.00
    Primary sclerosing cholangitis2, 1.672, 1.671.00
    Hemochromatosis 0, 0.03, 2.50.25
    Alpha 1 anti-trypsin deficiency 3, 2.50, 0.00.25
Under evaluation for liver transplant
    No45, 37.5061, 50.830.08
    Yes63, 52.5053, 44.17
    Unknown12, 10.006, 5.00
Table 4 Characteristic features during index admission in two randomization arms, n (%).
Index admission characteristics
Intervention (n = 120)
Standard of care (n = 120)
P value
Reasons for admission1
    Acute kidney injury30, 25.0035, 29.170.56
    Hyponatremia10, 8.336, 5.000.44
    Hepatic encephalopathy22, 18.3323, 19.171
    Volume overload59, 49.1752, 43.330.44
    Variceal bleed21, 17.5021, 17.501
    Lower GI bleed8, 6.6711, 9.170.63
    SBP9, 7.5012, 10.000.65
Complications of cirrhosis during admission1
    Presence of AKI39, 32.5041, 34.170.89
    HE25, 20.8324, 20.001
    Ascites70, 58.3369, 57.501
    Variceal bleeding21, 17.5016, 13.330.48
    SBP10, 8.336, 5.000.44
    HRS7, 5.837, 5.831
    Coagulopathy32, 26.6724, 20.000.29
    Portal hypertension19, 15.8327, 22.500.25
    HPS10, 8.335, 4.170.29
    HCC6, 5.005, 4.171
Procedures performed during admission1
    EGD68, 56.6768, 56.671
    Paracentesis60, 50.0055, 45.830.61
    TIPS7, 5.833, 2.500.33
    HD5, 4.1710, 8.330.29
    Colonoscopy/flex sig13, 10.8311, 9.170.83
Disposition
    Home83, 69.1776, 63.330.44
    Home with home health newly arranged17, 14.1722, 18.33
    Home with home health previously arranged2, 1.671, 0.83
    SNF newly arranged7, 5.8314, 11.67
    SNF previously arranged6, 5.005, 4.17
    Left against medical advice1, 0.831, 0.83
    Transfer (Long term acute care hospital)3, 2.500, 0.00
    Homeless 1, 0.831, 0.83
Table 5 Clinical and laboratory features during index admission and discharge in two randomization arms, n (%).

Intervention (n = 120)
Standard of care (n = 120)
P value
Index admission labs (mean ± SD)
    Sodium 132.59 ± 5.58132.28 ± 6.280.68
    Serum creatinine (mg/dL)1.42 ± 1.111.64 ± 1.470.19
    Total bilirubin (mg/dL)5.90 ± 9.106.19 ± 7.800.79
    Albumin (g/dL)2.83 ± 0.592.85 ± 0.550.72
    INR1.68 ± 0.521.70 ± 0.590.80
    Hemoglobin (g/dL)10.22 ± 2.3410.02 ± 2.040.48
Ascites
    Absent35, 29.1735, 29.170.44
    Slight26, 21.6734, 28.33
    Moderate59, 49.1751, 42.50
Encephalopathy
    None91, 75.8396, 80.000.78
    Grade 1-222, 18.3318, 15.00
    Grade 3-47, 5.836, 5.00
Dialysis at least twice in last week
    No117, 97.50115, 95.830.72
    Yes3, 2.505, 4.17
Index admission discharge labs (mean ± SD)
    Sodium (mmol/L)134.72 ± 4.14134.95 ± 3.570.64
    Serum creatinine (mg/dL)1.31 ± 1.061.37 ± 1.180.69
    Total bilirubin (mg/dL, n = 237)5.50 ± 8.805.39 ± 6.960.92
    Albumin (g/dL, n = 237)2.98 ± 0.642.94 ± 0.610.65
    INR (n = 238)1.71 ± 0.491.69 ± 0.450.65
    Hemoglobin (g/dL)9.30 ± 1.699.21 ± 1.680.68
Ascites
    Absent42, 35.0039, 32.500.35
    Slight56, 46.6766, 55.00
    Moderate22, 18.3315, 12.50
Encephalopathy
    None117, 97.50112. 93.330.10
    Grade 1-22, 1.678, 6.67
    Grade 3-41, 0.830, 0.00
Dialysis at least twice in last week
    No114, 95.00110, 91.670.44
    Yes6, 5.0010, 8.33
Comparison of reasons of 1st readmission and outcomes in the INT vs SOC arm

There was no difference in the readmission rates for patients in the INT (n = 4, 35.83%) vs SOC arm (n = 38, 31.67%, P = 0.59, Table 6). Other outcomes including number of readmissions within 30 d (P = 0.65), index admission cost (P = 0.49), index admission LOS (P = 0.63), 1st readmission LOS (P = 0.58), all readmissions’ LOS (P = 0.82) and waiting time for 1st readmission (P = 0.06) were comparable in two arms.

Table 6 Outcomes and reasons of readmission characteristics by randomization arms, n (%).

Intervention (n = 120)
Standard of care (n = 120)
P value
Readmission
    No77, 64.1782, 68.330.59
    Yes43, 35.8338, 31.67
Number of readmissions within 30 d
    077, 64.17 82, 68.33 0.65
    131, 25.8332, 26.67
    29, 7.505, 4.17
    32, 1.671, 0.83
    51, 0.830, 0.00
Location of 1st readmission
    Our institution 36, 83.7223, 60.530.03
    Outside hospital7, 16.2815, 39.47
Reason for 1st readmission1
    Acute kidney injury10, 23.266, 15.790.58
    Hyponatremia4, 9.306, 15.790.50
    Hepatic encephalopathy9, 20.9317, 44.740.03
    Volume overload13, 30.239, 23.680.62
    Variceal bleed6, 13.956, 15.791.00
    Lower GI bleed1, 2.333, 7.890.34
    Spontaneous bacterial peritonitis2, 4.651, 2.631.00
    Other20, 46.5122, 57.890.37
Index admission cost (mean ± SD, n = 116 + 109)61581 ± 4782559547 ± 466690.46
Index admission LOS (mean ± SD)8.17 ± 5.568.08 ± 6.110.63
First readmission LOS (n = 43 + 38, mean ± SD)7.58 ± 7.578.71 ± 10.410.58
All readmissions LOS (n = 60 + 45, mean ± SD)9.28 ± 16.888.69 ± 10.440.82
Waiting time for first readmission (n = 43 + 38, mean ± SD)11.16 ± 7.1014.34 ± 7.770.06

Statistically significant differences were noticed in INT arm in location of 1st readmission (n = 36, 83.72% at OSU as compared to n = 23, 60.5% outside hospital, P = 0.03), and lesser 1st readmission with HE in the INT arm (n = 9, 20.9%) vs SOC (n = 17, 44.7%, P = 0.03). Finally, contingency analysis of readmission data showed fewer readmissions in patients who attended outpatient follow-up within 30 days of discharge from index admission (n = 17, 23.61% vs n = 55, 76.39%, P = 0.04).

At the end of our study, 47 (19.58%) patients received a liver transplant and 62 (25.83%) died; among those who died, 5 patients were post-transplant and 22 died in hospice. Due to the COVID-19 pandemic we were unable to achieve the anticipated sample size. Therefore, multivariate analysis was not performed.

DISCUSSION

This prospective randomized study investigated early readmission rates and healthcare utilization in patients with DC. Our readmission rate of 33.75% is higher than the United States national average (27%). While our nurse CM interventions did not reduce told readmissions, we found that HE was the top reason for readmission and such interventions were helpful in reducing early readmissions in patients with HE. This is an important lesson learned given increased burden of HE on hospitalizations, falls, mortality, impaired quality of life and caregiver burden[21]. In the validation of readmission using the liver-renal-risk score or “LIRER score”, Freitas et al[22] showed that HE was not only a predictor of 30 d readmission independent of MELD score, index, first-year, two-years and overall mortality, but also HE at admission had significantly higher mean LIRER scores. Furthermore HE patients on Medicare and geographically from the South or Midwest have higher in-hospital mortality[23]. Considerable research has been done to address HE readmissions. Bajaj et al[24] found that efforts to reduce medication-precipitated HE, prevent aspiration pneumonia and optimize HE medications on hospital discharge should be areas of focus to decrease HE readmissions. Tapper et al[25] demonstrated that development of a checklist for HE protocols integrated into the EMR and order entry system reduced odds of 30-d readmission for patients with HE (from 39.2% to 27.6%). Thus, our results are congruent with existing evidence that interventions should be invested in post-discharge education and communication for all patients with cirrhosis, especially with HE.

One of the components of intervention in our study was to arrange appointment of patients in the clinic within a week with their hepatologist. Patients with DC who attended their follow up appointment within 30 d of discharge from index admission had fewer readmissions. This suggests that overall, in our cohort, outpatient linkage with a hepatologist should be a priority to reduce readmission rates[26]. Morales et al[17] in their retrospective program looked at the impact of follow-up of cirrhotics within 7 d after discharge with a hepatologist. They reported reduced 30-d readmission, 60-d mortality and rate of emergency department visits and associated costs in those who followed up within 7 d. Morando et al[18] demonstrated that follow up with a “care management check-up” group as opposed to “standard outpatient care” reduced 30-d readmission, reduced 12-mo mortality, and saved almost 1500 euros per patient month of life. While Kanwal et al[9] found early outpatient follow-up after discharge was associated with a small increase in readmissions, they found an lower overall mortality in their patients with cirrhosis admitted to Veterans Affairs hospitals. Thus our results are also consistent with the current evidence that patients with DC likely benefit from early post-hospitalization follow up with specialty providers[27,28].

One of the major limitations of our study was inability to enroll patients according to the proposed sample size due to the COVID-19 pandemic. Our study was underpowered to perform multiple regression analysis to detect differences in readmission rates in INT vs SOC arm. From March 2020 to July 2020 our recruitment process was put on hold due to hospital regulations to reduce patient and staff exposure. Despite this major limitation, we were able to enroll 80.17% (279 consented out of 348 approached) of patients in our study.

This study was also performed in the setting of a large academic medical center and a high-volume liver transplant center. While our methods and results may be applicable to the clinical practice of other such centers, the same impact may not be appreciated by smaller, community hospitals that are not liver transplant centers.

Future work in patients with DC should continue to focus on prospective intervention strategies to reduce early readmissions and educate patients and providers. To achieve desired sample size, we would suggest collaborations with various centers to identify and recruit patients with DC into a multicenter prospective cohort. Given our finding that there were fewer readmissions in patients with follow-up within 30 d, studies should evaluate the use of telehealth visits for follows up, especially in the COVID19 era, as outlined by Stotts et al[29].

CONCLUSION

In conclusion, this prospective randomized study investigated the impact of various pragmatic interventions to reduce early readmission and healthcare utilization in patients with DC. Our study was underpowered to detect statistically significant differences in readmission rates in INT vs SOC arm. We reported that readmission rate of our medical center was 33.75% and HE was the top reason for readmission. We found a reduction in early readmission in patients with HE in the INT arm and those who attended their follow up appointment within 30 d of discharge from index admission. We demonstrated that simple interventions in patients with DC are pragmatic and there is need for more prospective multicenter trials in this area of research.

ARTICLE HIGHLIGHTS
Research background

Decompensated cirrhosis (DC) is a leading cause of morbidity and mortality in the United States often requiring multiple hospitalizations to manage. Studies show 20%-37% of patients with DC are readmitted within 30 d of index admission, which has significant burden on patients, their families and the healthcare system.

Research motivation

We were motivated to study and reduce readmissions as we see the physical, mental and emotional toll repeated hospitalizations for DC take on our patients and their families.

Research objectives

We sought to enroll patients in a randomized trial seeing if a nurse case manager (CM) ensuring early outpatient follow up, medication compliance and outpatient paracentesis if needed reduced readmissions in patients with DC.

Research methods

We sought to enroll patients in a randomized trial seeing if a nurse CM ensuring early outpatient follow up, medication compliance and outpatient paracentesis if needed reduced readmissions in patients with DC.

Research results

While our calculated sample size was not achieved due to the coronavirus disease 2019 pandemic, we found a 33.75% 30 d readmission rate in our patients admitted with DC. There was no difference in readmission between intervention and standard of care arms. Most patients were re-admitted with hepatic encephalopathy. There was a lower 30 d readmission rate in patients with hepatic encephalopathy in the intervention arm and those who attended early outpatient follow up.

Research conclusions

Our 30 d readmission was higher than the national rate. Further efforts should explore the positive impact of a nurse CM and early outpatient follow up in reducing readmissions for patients with cirrhosis, especially with hepatic encephalopathy.

Research perspectives

Further development of strategies to predict and reduce readmissions for patients with DC should be done.

ACKNOWLEDGEMENTS

This research was supported by the Clinical Research Center/Center for Clinical Research Management of The Ohio State University Wexner Medical Center and The Ohio State University College of Medicine in Columbus, Ohio. The project was entitled “GASTR29: Prospective validation of readmission risk score and interventions to prevent readmission in patients with decompensated cirrhosis (CCTS ID#: 6018)”. This project was funded by the Ohio State University Self Insurance Program and supported by NIH Award Number UL1TROO2733 from the National Center for Advancing Translational Science. We also give a special thanks to our nurse case managers from The Ohio State University Wexner Medical Center Clinical Research Center for their work in the weekly patient calls: Holly Bookless, RN, Elizabeth Cassandra, RN and Dina McGowan, RN.

Footnotes

Provenance and peer review: Invited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country/Territory of origin: United States

Peer-review report’s scientific quality classification

Grade A (Excellent): 0

Grade B (Very good): 0

Grade C (Good): C, C

Grade D (Fair): 0

Grade E (Poor): 0

P-Reviewer: Manrai M, India; Zeng QL, China S-Editor: Liu XF L-Editor: A P-Editor: Yuan YY

References
1.  Blackwell DL VM  Summary Health Statistics for U.S. Adults: National Health Interview Survey, 2016. Hyattsville, United States of America: National Center for Health Statistics, Centers for Disease Control and Prevention, 2018.  [PubMed]  [DOI]  [Cited in This Article: ]
2.  Murphy SL, Xu J, Kochanek KD, Curtin SC, Arias E. Deaths: Final Data for 2015. Natl Vital Stat Rep. 2017;66:1-75.  [PubMed]  [DOI]  [Cited in This Article: ]
3.  Peery AF, Crockett SD, Murphy CC, Lund JL, Dellon ES, Williams JL, Jensen ET, Shaheen NJ, Barritt AS, Lieber SR, Kochar B, Barnes EL, Fan YC, Pate V, Galanko J, Baron TH, Sandler RS. Burden and Cost of Gastrointestinal, Liver, and Pancreatic Diseases in the United States: Update 2018. Gastroenterology. 2019;156:254-272.e11.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 776]  [Cited by in F6Publishing: 974]  [Article Influence: 194.8]  [Reference Citation Analysis (0)]
4.  Talwalkar JA. Prophylaxis with beta blockers as a performance measure of quality health care in cirrhosis. Gastroenterology. 2006;130:1005-1007.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 18]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
5.  Berman K, Tandra S, Forssell K, Vuppalanchi R, Burton JR Jr, Nguyen J, Mullis D, Kwo P, Chalasani N. Incidence and predictors of 30-day readmission among patients hospitalized for advanced liver disease. Clin Gastroenterol Hepatol. 2011;9:254-259.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 120]  [Cited by in F6Publishing: 130]  [Article Influence: 10.0]  [Reference Citation Analysis (0)]
6.  Agrawal K, Kumar P, Markert R, Agrawal S. Risk Factors for 30-Day Readmissions of Individuals with Decompensated Cirrhosis. South Med J. 2015;108:682-687.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 22]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
7.  Volk ML, Tocco RS, Bazick J, Rakoski MO, Lok AS. Hospital readmissions among patients with decompensated cirrhosis. Am J Gastroenterol. 2012;107:247-252.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 303]  [Cited by in F6Publishing: 335]  [Article Influence: 27.9]  [Reference Citation Analysis (0)]
8.  Bajaj JS, Reddy KR, Tandon P, Wong F, Kamath PS, Garcia-Tsao G, Maliakkal B, Biggins SW, Thuluvath PJ, Fallon MB, Subramanian RM, Vargas H, Thacker LR, O'Leary JG; North American Consortium for the Study of End-Stage Liver Disease. The 3-month readmission rate remains unacceptably high in a large North American cohort of patients with cirrhosis. Hepatology. 2016;64:200-208.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 163]  [Cited by in F6Publishing: 177]  [Article Influence: 22.1]  [Reference Citation Analysis (0)]
9.  Kanwal F, Asch SM, Kramer JR, Cao Y, Asrani S, El-Serag HB. Early outpatient follow-up and 30-day outcomes in patients hospitalized with cirrhosis. Hepatology. 2016;64:569-581.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 59]  [Cited by in F6Publishing: 64]  [Article Influence: 8.0]  [Reference Citation Analysis (0)]
10.  Tapper EB, Halbert B, Mellinger J. Rates of and Reasons for Hospital Readmissions in Patients With Cirrhosis: A Multistate Population-based Cohort Study. Clin Gastroenterol Hepatol. 2016;14:1181-1188.e2.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 129]  [Cited by in F6Publishing: 159]  [Article Influence: 19.9]  [Reference Citation Analysis (0)]
11.  Singal AG, Rahimi RS, Clark C, Ma Y, Cuthbert JA, Rockey DC, Amarasingham R. An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmission. Clin Gastroenterol Hepatol. 2013;11:1335-1341.e1.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 65]  [Cited by in F6Publishing: 63]  [Article Influence: 5.7]  [Reference Citation Analysis (0)]
12.  Orman ES, Ghabril M, Emmett TW, Chalasani N. Hospital Readmissions in Patients with Cirrhosis: A Systematic Review. J Hosp Med. 2018;13:490-495.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 40]  [Article Influence: 6.7]  [Reference Citation Analysis (0)]
13.  Morales BP, Planas R, Bartoli R, Morillas RM, Sala M, Cabré E, Casas I, Masnou H. Early hospital readmission in decompensated cirrhosis: Incidence, impact on mortality, and predictive factors. Dig Liver Dis. 2017;49:903-909.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 23]  [Cited by in F6Publishing: 33]  [Article Influence: 4.7]  [Reference Citation Analysis (0)]
14.  Mumtaz K, Issak A, Porter K, Kelly S, Hanje J, Michaels AJ, Conteh LF, El-Hinnawi A, Black SM, Abougergi MS. Validation of Risk Score in Predicting Early Readmissions in Decompensated Cirrhotic Patients: A Model Based on the Administrative Database. Hepatology. 2019;70:630-639.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 19]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
15.  Sobotka LA, Modi RM, Vijayaraman A, Hanje AJ, Michaels AJ, Conteh LF, Hinton A, El-Hinnawi A, Mumtaz K. Paracentesis in cirrhotics is associated with increased risk of 30-day readmission. World J Hepatol. 2018;10:425-432.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 11]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
16.  Kruger AJ, Aberra F, Black SM, Hinton A, Hanje J, Conteh LF, Michaels AJ, Krishna SG, Mumtaz K. A validated risk model for prediction of early readmission in patients with hepatic encephalopathy. Ann Hepatol. 2019;18:310-317.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 5]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
17.  Morales BP, Planas R, Bartoli R, Morillas RM, Sala M, Casas I, Armengol C, Masnou H. HEPACONTROL. A program that reduces early readmissions, mortality at 60 days, and healthcare costs in decompensated cirrhosis. Dig Liver Dis. 2018;50:76-83.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 21]  [Cited by in F6Publishing: 23]  [Article Influence: 3.8]  [Reference Citation Analysis (0)]
18.  Morando F, Maresio G, Piano S, Fasolato S, Cavallin M, Romano A, Rosi S, Gola E, Frigo AC, Stanco M, Destro C, Rupolo G, Mantoan D, Gatta A, Angeli P. How to improve care in outpatients with cirrhosis and ascites: a new model of care coordination by consultant hepatologists. J Hepatol. 2013;59:257-264.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 118]  [Cited by in F6Publishing: 127]  [Article Influence: 11.5]  [Reference Citation Analysis (0)]
19.  Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O'Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, Duda SN; REDCap Consortium. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95:103208.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5422]  [Cited by in F6Publishing: 11975]  [Article Influence: 2395.0]  [Reference Citation Analysis (0)]
20.  Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377-381.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 22435]  [Cited by in F6Publishing: 33017]  [Article Influence: 2063.6]  [Reference Citation Analysis (0)]
21.  Frenette CT, Levy C, Saab S. Hepatic Encephalopathy-Related Hospitalizations in Cirrhosis: Transition of Care and Closing the Revolving Door. Dig Dis Sci. 2022;67:1994-2004.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 6]  [Reference Citation Analysis (1)]
22.  Freitas M, Xavier S, Magalhães R, Magalhães J, Marinho C, Cotter J. LIRER score - a valuable tool to predict medium-long-term outcomes in hepatic cirrhosis decompensation. Scand J Gastroenterol. 2020;55:1079-1086.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
23.  Trieu H, Patel A, Wells C, Saab S, Lee EW. Disparities in Mortality and Health Care Utilization for 460,851 Hospitalized Patients with Cirrhosis and Hepatic Encephalopathy. Dig Dis Sci. 2021;66:2595-2602.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 4]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
24.  Bajaj JS, O'Leary JG, Tandon P, Wong F, Kamath PS, Biggins SW, Garcia-Tsao G, Lai J, Fallon MB, Thuluvath PJ, Vargas HE, Maliakkal B, Subramanian RM, Thacker LR, Reddy KR. Targets to improve quality of care for patients with hepatic encephalopathy: data from a multi-centre cohort. Aliment Pharmacol Ther. 2019;49:1518-1527.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 31]  [Cited by in F6Publishing: 38]  [Article Influence: 7.6]  [Reference Citation Analysis (0)]
25.  Tapper EB, Finkelstein D, Mittleman MA, Piatkowski G, Chang M, Lai M. A Quality Improvement Initiative Reduces 30-Day Rate of Readmission for Patients With Cirrhosis. Clin Gastroenterol Hepatol. 2016;14:753-759.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 102]  [Cited by in F6Publishing: 118]  [Article Influence: 14.8]  [Reference Citation Analysis (0)]
26.  Serper M, Kaplan DE, Shults J, Reese PP, Beste LA, Taddei TH, Werner RM. Quality Measures, All-Cause Mortality, and Health Care Use in a National Cohort of Veterans With Cirrhosis. Hepatology. 2019;70:2062-2074.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 33]  [Cited by in F6Publishing: 34]  [Article Influence: 6.8]  [Reference Citation Analysis (0)]
27.  Chirapongsathorn S, Talwalkar JA, Kamath PS. Strategies to Reduce Hospital Readmissions. Semin Liver Dis. 2016;36:161-166.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 7]  [Article Influence: 0.9]  [Reference Citation Analysis (0)]
28.  Tapper EB, Volk M. Strategies to Reduce 30-Day Readmissions in Patients with Cirrhosis. Curr Gastroenterol Rep. 2017;19:1.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 30]  [Article Influence: 4.3]  [Reference Citation Analysis (0)]
29.  Stotts MJ, Grischkan JA, Khungar V. Improving cirrhosis care: The potential for telemedicine and mobile health technologies. World J Gastroenterol. 2019;25:3849-3856.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in CrossRef: 22]  [Cited by in F6Publishing: 19]  [Article Influence: 3.8]  [Reference Citation Analysis (3)]