Fragmentation of postoperative care after surgical management of ovarian cancer at 30 days and 90 days

Journal Pre-proof Fragmentation of postoperative care after surgical management of ovarian cancer at 30-days and 90-days Stephanie Cham, MD, Timothy Wen, MD, MPH, Alexander Friedman, MD, MPH, Jason D. Wright, MD PII:

S0002-9378(19)31110-X

DOI:

https://doi.org/10.1016/j.ajog.2019.09.005

Reference:

YMOB 12876

To appear in:

American Journal of Obstetrics and Gynecology

Received Date: 26 July 2019 Revised Date:

2 September 2019

Accepted Date: 5 September 2019

Please cite this article as: Cham S, Wen T, Friedman A, Wright JD, Fragmentation of postoperative care after surgical management of ovarian cancer at 30-days and 90-days, American Journal of Obstetrics and Gynecology (2019), doi: https://doi.org/10.1016/j.ajog.2019.09.005. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.

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Fragmentation of postoperative care after surgical management of ovarian cancer at 30days and 90-days Stephanie CHAM, MD1, Timothy WEN MD, MPH2,3, Alexander Friedman, MD, MPH2,3, Jason D. Wright MD2,3,4 1

Brigham and Women’s Hospital Columbia University College of Physicians and Surgeons 3 New York Presbyterian Hospital 4 Herbert Irving Comprehensive Cancer Center 2

Corresponding Author: Jason D. Wright, M.D. Division of Gynecologic Oncology Department of Obstetrics and Gynecology Columbia University College of Physicians and Surgeons 161 Fort Washington Ave, 4th Floor New York, NY 10032 Telephone: (212) 305-3410 Fax: (212) 305-3412 Email: [email protected]

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Dr Friedman is supported by a career development award (K08HD082287) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health. Acknowledgements: Dr. Wright has served as a consultant for Tesaro and Clovis Oncology and received research funding from Merck. No other authors have any conflicts of interest or disclosures. Presented at the 50th annual meeting of the Society of Gynecologic Oncology, Honolulu, HI on March 16-20th, 2019 Word count (abstract): 336 Word count (main text): 2756

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1

Condensation: Postoperative readmission for ovarian cancer at 30 and 90 days commonly

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results in fragmented care and is associated with increased mortality at 90 days.

3 4

Short Title: Fragmentation of care after ovarian cancer surgery at 30 and 90 days

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1 2

AJOG at a Glance: A. Fragmentation of care, wherein a patient is readmitted to a different hospital, is

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associated with adverse outcomes. However, this trend is not well characterized in

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ovarian cancer. Our primary goal was to assess the risk factors and outcomes of

5

fragmented care after surgery for ovarian cancer.

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B. At 30 days, 13.3% of patients were readmitted, and at 90 days 18.0%. Of these patients,

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20.8% and 25.7% of readmissions at 30 and 90 days were fragmented. Risk factors for

8

fragmentation included lower income quartiles, and non-routine discharge to facility.

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Fragmented readmission at 90 days was associated with a 22% increased risk of

10 11 12

mortality. C. Readmission after ovarian cancer surgery is higher than previously reported. Fragmented care is common and is associated with an increased risk of mortality at 90 days.

13 14 15

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1

Abstract

2

Background: Fragmentation of care, wherein a patient is discharged from an index hospital and

3

undergoes an unexpected readmission to a non-index hospital, is associated with increased risk

4

of adverse outcomes. Fragmentation is not well characterized in ovarian cancer.

5 6

Objective: The objective of this study was to assess risk factors and outcomes associated with

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fragmentation of care among women who undergo surgical treatment of ovarian cancer.

8 9

Study Design: The Nationwide Readmission Database was used to identify all-cause 30-day and

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90-day postoperative readmissions following surgical management of ovarian cancer between

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2010-2014. Postoperative fragmentation was defined as readmission to a hospital other than the

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index hospital of the initial surgery. Multivariable regression analyses were used to identify

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predictors of fragmentation in both 30-day and 90-day readmissions. Similarly, multivariable

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models were developed to determine the association between fragmentation and mortality among

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women who were readmitted.

16 17

Results: A total of 10,445 patients (13.3%) were readmitted at 30-days and 14,124 patients

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(18.0%) were readmitted at 90-days. Of these, there was a 20.8% and 25.7% rate of

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postoperative care fragmentation for 30-day and 90-day readmissions, respectively. Patient risk

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factors associated with fragmented postoperative care included Medicare insurance, lower

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income quartiles, and non-routine discharge to facility. Hospital factors associated with

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decreased risk of fragmentation included operation at a metropolitan teaching hospital, and

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performance of extended procedures. Cost and length of stay for the readmission were similar

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1

among those who had fragmented and non-fragmented readmissions at both 30 and 90-days.

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While there was no association between mortality and fragmentation for patients readmitted

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within 30-days (OR=1.19; 95% CI, 0.93-1.51), patients who had a fragmented readmission at 90-

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days were 22% more likely to die than those readmitted at 90-days to their index hospital

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(OR=1.22; 95% CI, 1.00-1.49)

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Conclusion: Fragmentation of care is common in women with ovarian cancer who require

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postoperative readmission. Fragmented postoperative care is associated with an increased risk of

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mortality among women readmitted within 90-days of surgery.

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1

Introduction

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In 2012, the Hospital Readmission Reduction Program began to penalize hospital Medicare

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reimbursements for higher than average readmission rates. In 2012 there were 3.3 million

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hospital readmissions with an associated cost of $41 billion.1 Currently, hospitals receive up to a

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3% reduction in reimbursement if higher than average readmission rates are noted. Initially, six

7

chronic medical conditions were tracked including acute myocardial infarction, chronic

8

obstructive pulmonary disease, heart failure, pneumonia, and coronary artery bypass grafting. In

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2014, the policy was expanded to major joint surgery (elective total hip arthroplasty and knee

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arthroplasty). Thirty-day readmission has become an important quality measure and there has

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been increasing interest in expanding this metric to other procedures and surgeries.2

12 13

Prior studies have examined risk factors and rates of readmission postoperatively for ovarian

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cancer. Observational studies have indicated a 30-day readmission rate between 6-19% and

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single institution retrospective studies have indicated a 12-19% rate of 30-day readmission.3-10

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One study of the SEER-Medicare database of stage III/IV ovarian cancer patients found risk

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factors for readmission included discharge to a skilled nursing facility and hospital stay greater

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than 8 days. In this report, readmission was associated with a significantly greater one-year

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mortality rate (41.1% vs 25.1%).3 However, most of these studies are limited by readmission

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within the same institution and do not account for patients readmitted to other hospitals.

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Fragmentation of care, wherein a patient undergoes readmission to a non-index hospital, has

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been well studied in other surgical specialties and has been associated with adverse outcomes.11-

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1

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2

more likely to be readmitted to their index hospital for postoperative complications (23% vs

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13%, p<0.0001), with readmission to their index hospital associated with a 26% lower risk of 90-

4

day mortality.19 One study of readmission to non-index hospitals after other major cancer

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surgeries found a 23% rate of 90-day readmission, with 20% of readmissions to a non-index

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hospital. In this study, fragmentation of care was associated with type of procedure,

7

comorbidities, discharge to a nursing facility, and surgery at a teaching hospital.16 The objective

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of our study was to identify 30 and 90-day readmissions to examine the risk factors and

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outcomes associated with fragmentation of care among women who underwent surgical

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An examination of Medicare claims data for 12 major surgical procedures found patients were

management of ovarian cancer.

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Materials and Methods

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Data Source

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The 2010 to 2014 Nationwide Readmissions Database (NRD) was utilized for this analysis. The

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NRD is one of the largest all-payer databases assembled by the Healthcare Cost and Utilization

17

Project (HCUP) that contains state-level data capable of tracking patients across hospitalizations

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within a state during a single year.20 The data is weighted to allow for the calculation of national

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estimates of all patient readmissions and is representative of nearly 36 million discharges

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annually. The NRD contains information from a wide variety of practice settings and has been

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widely utilized to evaluate readmission hospitalizations in numerous medical scenarios. As of

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2014, the NRD accounted for 51% of US residents an 49% of all US hospitalization across 22

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1

states.20 The study was determined to be non-human subjects research by the Columbia

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University Institutional Review Board.

3 4

Study Population

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Index surgical admissions for ovarian cancer were identified utilizing International Classification

6

of Diseases, Ninth Edition, Clinical Modification (ICD-9CM) codes. Patients diagnosed with

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ovarian cancer (183.x) who underwent a concomitant abdominal oophorectomy (65.3x-65.6x)

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were identified as index surgical admissions. Readmissions were identified using HCUP

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methodology at 30-days and 90-days. Because NRD datasets are year-based and cannot be linked

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across years, only hospitalizations where discharge occurred from January 1st through November

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30th were included for 30-day readmissions analysis and discharges from January 1st through

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September 30th were included for the 90-day analysis as the subsequent 30-day and 90-day,

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respectively, follow up period could not be fully ascertained. Postoperative fragmentation status

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was defined as readmission to a hospital different than the original hospital at which the surgery

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was performed at.

16 17

Demographic Factors

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The NRD contains patient and hospital factors that were utilized in the analysis. Demographic

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factors included patient age (categorized as <40, 40-49, 50-59, 60-69, 70-79, and >80 years old),

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payer information (Medicare, Medicaid, Private, Self-pay, Other, No charge), AHRQ

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comorbidity scale (0, 1, 2+), and median income quartile based on ZIP code. Hospital factors

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included hospital bed size (small, medium, large), teaching status (metropolitan non-teaching,

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metropolitan teaching, non-metropolitan), and safety net burden (low, medium, high).21 Hospital

8

1

safety net burden was analyzed based on the proportion of patients with no insurance or

2

Medicaid/Medicare coverage and classified into high-burden hospitals (highest quartile),

3

medium-burden (middle two quartiles), and low-burden hospitals (lowest quartile).22,23

4 5

Clinical factors identifying severity of admission included discharge disposition (routine

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discharge, transfer to short-term hospital, transfer to skilled nursing/intermediate care facility,

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home health care, against medical advice, and missing/unknown), the presence of extended

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surgical procedures (small bowel, colonic, rectosigmoid, liver, diaphragmatic, bladder, splenic,

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gastric resections, ileostomy, and colostomy), lymphadenectomy, postoperative transfusion, and

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medical and surgical complications (conversion of cardiac rhythm, temporary tracheostomy,

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ventilation, severe anesthesia complications, sepsis, shock, acute myocardial infarction, acute

12

renal failure, acute respiratory distress syndrome, cardiac arrest/ventricular fibrillation,

13

disseminated intravascular coagulopathy, pulmonary edema/acute heart failure). See

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Supplemental Table 1 for all ICD-9CM codes.

15 16

We also identified the primary reason for readmission utilizing the primary diagnosis field and

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classified these diagnoses based on ICD-9CM codes into the following categories:

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bleeding/hemorrhage, cardiac, chemotherapy, cerebrovascular accidents, failure to thrive,

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gastrointestinal, genitourinary, infections, bowel obstruction, postoperative complication,

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respiratory, trauma, urinary tract infection, venous thromboembolism, and wound complications

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(See Appendix for a full list of ICD-9CM codes). We calculated frequencies, mean readmission

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length of stay, and mean total adjusted costs by readmission diagnosis, stratified by

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fragmentation status.

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1 2

The length of stay for the readmission was calculated for each patient. Total charges were

3

included in the NRD and converted into costs using their charge-to-cost conversion software.

4

Dollar amounts were adjusted for inflation and represent 2016 dollars.

5 6

Statistical Analysis

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Clinical and demographic characteristics of patients readmitted to the index or non-index

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(fragmented) hospital were compared. Separate analyses were performed for 30 and 90-day

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readmissions. Furthermore, we conducted univariable analyses assessing the relationship

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between specific diagnoses and fragmentation utilizing log linear regression techniques. We

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developed multivariable log linear regression models to determine factors associated with

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fragmented care for patients readmitted at 30 and 90-days. Clinical, demographic and hospital

13

characteristics were included in the models. Results are reported as risk ratios (RR) with 95%

14

confidence intervals (CI). Similar models were developed to examine the risk of mortality among

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women who were readmitted. These models included the site of readmission as a covariate.

16 17

A series of sensitivity analyses were developed to examine the robustness of our findings. We

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developed models of readmission which included only women who had a routine discharge to

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home. Similarly, a sensitivity analysis was conducted that excluded readmissions for

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chemotherapy or planned readmissions. All analyses were conducted using SAS 9.4 (Cary, NC).

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A P-value < 0.05 was considered significant.

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Results

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1

We identified 78,503 ovarian cancer patients who underwent surgery. At 30-days, 10,445

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patients (13.3%) were readmitted. Overall, 20.8% of the readmissions were fragmented. At 90-

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days, 14,124 patients (18.0%) were readmitted and 25.7% of those readmissions were

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fragmented. (Figure 1)

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Baseline patient and hospital demographics comparing patients with readmission to index (non-

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fragmented) and non-index (fragmented) hospitals at 30-days are shown in Table 1. Results were

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similar for 90-days as seen in Table 2. Length of stay of both the initial admission and

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readmission as well as the cost of the initial admission and readmission were similar for patients

10

who had fragmented and non-fragmented readmission (Table 3).

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A multivariable logistic regression model indicated that at 30-days fragmentation of care was

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most likely to occur in patients 80 years or older (OR=1.33, 95% CI; 1.04-1.7 vs patients <40

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years old) and in patients with non-routine discharge to a skilled nursing facility or inpatient

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rehabilitation center (OR=1.32, 95% CI; 1.15-1.51). Increased risk of fragmentation was also

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seen in patients with Medicare coverage, in those in the lower three income quartiles, and those

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discharged against medical advice (AMA). Patients were 19% less likely to be readmitted to a

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non-index facility if they underwent an extended surgical procedure (OR=0.81, 95% CI; 0.73-

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0.89) or lymphadenectomy (OR 0.90, 95% CI 0.83-0.99) (Table 4). Similar findings were noted

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at 90-days for an increased risk of fragmentation for Medicare recipients and those with lower

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three quartiles of income (Table 4). Hospital factors at both 30 and 90-days that were associated

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with readmission to an index hospital (non-fragmentation) included large bed size and

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metropolitan teaching hospitals (Table 4).

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1 2

While there was no association between mortality and fragmentation for patients readmitted

3

within 30-days (OR 1.19, 95% CI 0.93-1.51), patients who had a fragmented readmission at 90-

4

days were 22% more likely to die than those readmitted to their index hospital at 90-days

5

(OR=1.22, 95% CI; 1.00-1.49) (Table 5). Non-routine discharge was associated with a higher

6

odds of mortality at 30-days (OR 2.87, 95% CI 2.13-3.89) and at 90-days (OR 2.38, 95% CI

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1.81-3.13). Two or more comorbid conditions was associated with increased mortality at 30-days

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(OR 2.08, 95% CI 1.39-3.1) and 90-days (OR 2.0, 95% CI 1.43-2.81). Both postoperative

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transfusion and medical and surgical complication at time of initial surgery were also predictive

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of increased rate of mortality, whereas performance of extended procedures was associated with

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decreased rate of in hospital mortality at 30 and 90-days (Table 5).

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Rates of fragmentation by readmission diagnosis can be seen in Figure 2A and 2B and

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Supplemental Table 4A and 4B. The most common reasons for readmission were

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chemotherapy, infection, other gastrointestinal conditions, intestinal obstruction, and failure to

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thrive. At 30-days, the diagnoses with the highest rate of fragmented readmission included

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cerebrovascular accident (49.9%) and cardiac indications (45.1%). Similar results were seen for

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90-day readmissions.

19 20

Sensitivity analyses were performed to exclude chemotherapy or planned readmissions and

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patients discharged to a facility. Findings were largely unchanged at 30 and 90-days for both risk

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factors for fragmentation and mortality upon readmission (Supplemental Tables 2 and 3).

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1

Comment

2

Principal Findings

3

Our analysis indicates that rates of readmission after ovarian cancer surgery are approximately

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13% and 18% and the rates of fragmentation of care are 20% and 25% at 30 and 90-days,

5

respectively. We found patient factors associated with fragmented care included Medicare

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coverage, lower income, advanced age, and non-routine discharge. Hospital factors associated

7

with fragmentation included small bed size and non-teaching hospital status. Fragmentation of

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care in our study was associated with a 22% increased risk of mortality at 90-days.

9 10

Results

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Several studies have reported readmission rates of 6-19% among women who underwent surgery

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for ovarian cancer. 3-5,7-10 However, these studies are limited by single institution data or

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databases with readmission to the same hospital. Here we illustrate that these rates may be

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greater than previously described due to patients with fragmented readmission. While some have

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argued 30-day readmission rates may be a poor marker of quality, these outcomes do identify

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areas of potential improvement for healthcare resource utilization.5,24 In our study, we found the

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most common reasons for readmission were chemotherapy, infection, other gastrointestinal

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conditions, intestinal obstruction, and failure to thrive. Despite some of these potentially

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representing a non-urgent diagnosis (e.g. failure to thrive) or advanced disease and/or poor

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performance status (e.g. chemotherapy), a significant number of these were fragmented

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readmissions and indicate a potential area of systems-based improvement for postoperative

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management.

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1

While our data indicated unchanged cost and length of stay between fragmented and non-

2

fragmented readmissions, there may be other long-term implications. One study of the New York

3

Statewide Planning and Research Cooperative System Database of radical cystectomy for

4

bladder cancer found those with fragmented care had a shorter length of stay and lower hospital

5

charges but higher rate of transfer and subsequent readmission and ICU stay at 90-days,

6

indicating in the long term fragmented care may have a larger impact on healthcare systems than

7

previously described.13

8 9

Several studies in other surgical disciplines support our findings of increased risk of mortality

10

with postoperative readmission to a non-index hospital.11,12,15-17,19 However, these findings may

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be of even greater consequence to patients with cancer. Compared to benign gynecologic

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surgery, readmission rates of gynecologic oncologic patients have been noted to be 2.8 times

13

than for similar surgeries performed for benign indications.25 In this study, the highest

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readmission rates were in ovarian cancer at 11% likely due to higher rates of surgical

15

complication and the frequent occurrence of medical comorbidities in this patient population.25

16 17

One study of head and neck cancer found that when surgical and radiation care was fragmented,

18

the survival benefit of surgery at an academic center was negated, potentially due to delayed

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initiation of radiation or disparate quality of care between facilities.17 In ovarian cancer, delay of

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chemotherapy may affect survival.26 Given the long-term and multi-disciplinary care needed for

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ovarian cancer patients, fragmented care may have an even greater impact than just in the

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perioperative period.

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1

Clinical Implications

2

We identified several patient and hospital risk factors associated with fragmented postoperative

3

care. Patient factors were those associated with vulnerable populations including the elderly, low

4

income, Medicare recipients, and women who had a non-routine discharge. Hospital factors

5

included small bed size and non-teaching status. These finding are in line with a systematic

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review and meta-analysis of 23 studies that found risk factors for non-index readmission were

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often non-modifiable patient access factors including distance from the index hospital, older age,

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residence in a rural area, and lower income.18 Several other studies have elucidated the impact of

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distance traveled and rural residence as factors resulting in non-index postoperative

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readmission.15,27,28 Disparities in ovarian cancer care and survival have notably been attributed to

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the impact of limited access to high quality care due to proximity to a high volume urban

12

hospital.29-32 Furthermore, geographic disparities in the density of practicing gynecologic

13

oncologists indicates this disparity will only continue to grow for rural patients.33 Here we add to

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the repository of data suggesting that even when vulnerable populations receive surgery at a high

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volume center or teaching institutions, they are at risk for fragmented postoperative care.

16 17

Research Implications

18

Given the impact of high volume hospitals on outcomes, initiatives supporting regionalized

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surgical cancer care have been initiated and will likely intensify in the future.34 However, the

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question remains as to how we might mitigate or lose the benefit of use high volume surgical

21

centers secondary to consequences of fragmented care, particularly for these vulnerable

22

populations. One potential area of improvement includes improved discharge planning and

23

coordination of care. We found a major factor in fragmented care and mortality with readmission

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1

was non-routine discharge (e.g. to a skilled nursing facility or inpatient rehab center), which has

2

also been a risk factor identified in other studies.27,35 This is a readily identifiable inefficiency in

3

care that could be improved with mechanisms to transition patients between their facility and

4

their index hospital.

5 6

Some have proposed the use of “perioperative surgical homes” which is a new model of an

7

anesthesia led multidisciplinary team, wherein the same group assists in care during the

8

preoperative, intraoperative, and 30-day postoperative periods.35,36 A second potential

9

mechanism for reducing the adverse effects of fragmented care is the use of integrated healthcare

10

information systems for clinical data exchange (e.g. shared or universally accessible electronic

11

medical records), particularly as the use of tertiary/affiliated institutions or “hubs” begin to rise.

12

Distance traveled and rural residence are non-modifiable factors that may prevent readmission to

13

an index hospital. Even when distance is not an issue, a study performed by Tsai et al found even

14

when patients were re-admitted to a different hospital the same distance as their index hospital

15

patients still had 48% higher risk of mortality, indicating that access to data or knowledge of a

16

patient may be of utmost importance when caring for them upon readmission.28 Finally, a

17

prospective area of improvement may be enhanced triage systems to educate patients, caregivers,

18

and allied healthcare providers on readmission urgency. Our data indicated a significant number

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of non-urgent diagnoses in which fragmented readmission could have be avoided and thus

20

potentially improve healthcare resource utilization.

21 22

Strengths and Limitations

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1

Limitations to our study are those inherent to analyses from large administrative databases. We

2

were unable to differentiate readmission by primary diagnosis to differentiate truly emergent

3

diagnoses. However, based on ICD-9 codes associated with readmission we were able to make

4

some assumptions regarding the potential cause for readmission. Our data indicate CVA and

5

cardiac diagnoses were among the most common non-index readmissions and may be a result of

6

patients accessing emergency medical services appropriately resulting in care triaged to a closer

7

facility for more emergent issues. However, a significant number of other non-urgent diagnoses

8

were still identified to contribute to non-index readmissions indicating room for systems

9

improvements. Data on distance traveled was not available to determine if this contributed to

10

fragmentation. As patterns of care for ovarian cancer, including the incorporation of neoadjuvant

11

chemotherapy, have changed somewhat, analysis of more contemporaneous data will be of great

12

value as it becomes available. Cancer specific data (e.g. stage, pathology, primary vs interval

13

debulking) were unavailable. Ethnicity and race were unavailable which are variables known to

14

impact care and survival. Finally, we cannot exclude the possibility that fragmentation status was

15

misclassified in a small number of women.

16 17

Conclusion

18

We found a significant number of patients, particularly vulnerable populations, experience

19

fragmented postoperative care, which was associated with an increased risk of mortality. As we

20

begin to expand the use of regionalized high-volume cancer centers healthcare delivery systems

21

must respond to improve efficiency of healthcare resource utilization in the postoperative period.

22

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16. Zafar SN, Shah AA, Channa H, Raoof M, Wilson L, Wasif N. Comparison of Rates and Outcomes of Readmission to Index vs Nonindex Hospitals After Major Cancer Surgery. JAMA Surg 2018;153:719-27. 17. Zheng C, Habermann EB, Shara NM, et al. Fragmentation of Care after Surgical Discharge: Non-Index Readmission after Major Cancer Surgery. J Am Coll Surg 2016;222:780-9 e2. 18. Juo YY, Sanaiha Y, Khrucharoen U, Chang BH, Dutson E, Benharash P. Care fragmentation is associated with increased short-term mortality during postoperative readmissions: A systematic review and meta-analysis. Surgery 2019;165:501-9. 19. Brooke BS, Goodney PP, Kraiss LW, Gottlieb DJ, Samore MH, Finlayson SR. Readmission destination and risk of mortality after major surgery: an observational cohort study. Lancet (London, England) 2015;386:884-95. 20. Introduction to the HCIP Nationwide Readmissions Database (NRD) 2010-2015. (Accessed November 2017, at https://www.hcupus.ahrq.gov/db/nation/nrd/Introduction_NRD_2010-2015.pdf.) 21. Wakeam E, Hevelone ND, Maine R, et al. Failure to rescue in safety-net hospitals: availability of hospital resources and differences in performance. JAMA Surg 2014;149:229-35. 22. Bakhsheshian J, Ding L, Tang A, et al. Safety-Net Hospitals Have Higher Complication and Mortality Rates in the Neurosurgical Management of Traumatic Brain Injuries. World Neurosurg 2018;119:e284-e93. 23. Hoehn RS, Wima K, Vestal MA, et al. Effect of Hospital Safety-Net Burden on Cost and Outcomes After Surgery. JAMA Surg 2016;151:120-8. 24. Barber EL, Rossi EC, Gehrig PA. Surgical readmission and survival in women with ovarian cancer: Are short-term quality metrics incentivizing decreased long-term survival? Gynecol Oncol 2017;147:607-11. 25. Cory L, Latif N, Brensinger C, et al. Readmission After Gynecologic Surgery: A Comparison of Procedures for Benign and Malignant Indications. Obstet Gynecol 2017;130:28595. 26. Wright J, Doan T, McBride R, Jacobson J, Hershman D. Variability in chemotherapy delivery for elderly women with advanced stage ovarian cancer and its impact on survival. Br J Cancer 2008;98:1197-203. 27. Cloyd JM, Huang L, Ma Y, Rhoads KF. Predictors of readmission to non-index hospitals after colorectal surgery. Am J Surg 2017;213:18-23. 28. Tsai TC, Orav EJ, Jha AK. Care fragmentation in the postdischarge period: surgical readmissions, distance of travel, and postoperative mortality. JAMA Surg 2015;150:59-64. 29. Temkin SM, Rimel BJ, Bruegl AS, Gunderson CC, Beavis AL, Doll KM. A contemporary framework of health equity applied to gynecologic cancer care: A Society of Gynecologic Oncology evidenced-based review. Gynecol Oncol 2018;149:70-7. 30. Wright JD, Chen L, Hou JY, et al. Association of Hospital Volume and Quality of Care With Survival for Ovarian Cancer. Obstet Gynecol 2017;130:545-53. 31. Wright JD, Herzog TJ, Siddiq Z, et al. Failure to rescue as a source of variation in hospital mortality for ovarian cancer. J Clin Oncol 2012;30:3976-82. 32. Bristow RE, Chang J, Ziogas A, Anton-Culver H, Vieira VM. Spatial analysis of adherence to treatment guidelines for advanced-stage ovarian cancer and the impact of race and socioeconomic status. Gynecol Oncol 2014;134:60-7.

19

1 2 3 4 5 6 7 8 9 10 11

33. Ricci S, Tergas AI, Long Roche K, et al. Geographic disparities in the distribution of the U.S. gynecologic oncology workforce: A Society of Gynecologic Oncology study. Gynecol Oncol Rep 2017;22:100-4. 34. Ivatury SJ, Wong SL. Regionalization, Readmissions, and Repercussions of Major Cancer Surgery. JAMA Surg 2018;153:727. 35. Dexter F, Epstein RH, Sun EC, Lubarsky DA, Dexter EU. Readmissions to Different Hospitals After Common Surgical Procedures and Consequences for Implementation of Perioperative Surgical Home Programs. Anesth Analg 2017;125:943-51. 36. Kain ZN, Vakharia S, Garson L, et al. The perioperative surgical home as a future perioperative practice model. Anesth Analg 2014;118:1126-30.

12

20

100 90

18.2

13.8

14.9

15.7

18.2

21.4 35.3

80

6.6

12.5

14.2 25.3

12.3

28.4

35.3 45.1

49.9

70 60 50 40 30

81.8

86.2

85.1

84.3

81.8

78.6 64.7

93.4

87.5

85.8 74.7

71.6

64.7 55.0

20 10 0

Non-fragmented

Fragmented

50.1

87.7

100 90

16.9

17.5

25.4

19.7

22.7

80

11.7

15.6 23.2 39.0

35.1

36.9

40.6

45.7

35.8 47.0

70 60 50 40 30

83.1 74.6

82.5

80.3

88.3

84.4

77.3

76.8 61.0

64.9

63.1 54.3

20 10 0

Non-fragmented

Fragmented

59.4

64.2 53.0

Supplemental Table 1. Appendix: ICD-9CM codes Inclusion criteria Ovarian cancer Open oophorectomy Extended procedures Small bowel resection

Colonic resection Rectosigmoid resection Liver resection Bladder resection Diaphragmatic resection Splenectomy Gastric resection Lymphadenectomy Ileostomy Colostomy Medical/Surgical Complications Blood transfusion Conversion of cardiac rhythm Temporary tracheostomy Ventilation Severe anesthesia complications Sepsis Shock Acute myocardial infarction Acute renal failure

183.x 65.3, 65.39, 65.4, 65.49, 65.5, 65.51, 65.52, 65.6, 65.61, 65.62

45.6, 45.61, 45.62, 45.63, 45.91 45.7, 45.71, 45.72, 45.73, 45.74, 45.75, 45.76, 45.79, 45.8, 45.82, 45.83, 45.93, 45.94, 17.3, 17.31, 17.32, 17.33, 17.34, 17.35, 17.36, 17.39 45.76, 48.5, 48.50, 48.52, 48.59, 48.62, 48.63, 48.64, 48.65, 48.69 50.22, 50.3, 50.4 57.6, 57.7, 57.71, 75.79 34.81, 34.84 41.43, 41.5 43.4, 43.42, 43.49, 43.5, 43.6, 43.7, 43.8, 43.81, 43.89, 43.9, 43.91, 43.99 40.1, 40.11, 40.2, 40.29, 40.3, 40.5, 40.50, 40.52, 40.53, 40.59 46.2, 46.20, 46.21, 46.22, 46.23, 46.24, 46.01 46.1, 46.10, 46.11, 46.13, 46.14

99.0x 99.6x 31.1 93.90, 96.01-96.05 668.0x*, 668.1x, 668.2x 038.xx, 995.91, 995.92, 670.2x 669.1x, 785.5x, 995.0, 995.4, 998.0x 410.xx 584.5, 584.6, 584.7, 584.8, 584.9, 669.3x 518.5, 518.51, 518.52, 518.53, 518.81, 518.82, 518.84, 799.1 427.41, 427.42*, 427.5

Acute respiratory distress syndrome Cardiac arrest/ventricular fibrillation Disseminated intravascular coagulopathy Pulmonary edema/acute heart failure

286.6, 286.9, 666.3, 666.3, 666.30, 666.32, 666.34 518.4, 428.1

Readmission Diagnoses Bleeding

285.1, 280, 568.81, 790.92, 459, 578, 998.11,

Cardiac

Chemotherapy Cerebrovascular accident

Failure to thrive

Other gastrointestinal conditions Genitourinary

Infection Intestinal obstruction Pain Postoperative complication

Respiratory Trauma Urinary tract infection Deep vein thrombosis, pulmonary embolus Wound complications

998.12 427.31, 401.9, 423.9, 424.1, 426, 427, 427.1, 428, 414.01, 427.32, 427.81, 427.89, 428.21, 428.23, 428.3, 428.31, 428.33, 428.43, 429.83, 786.5, 786.59 V58.11, 183, 197.6, 284.1, 285.3, 287.5, 284.11, 284.19, 284.89, 285.22, 288, 288.03, 999.31, 999.32 431, 434.11, 434.91, 435.9 263.9, 275.2, 276.1, 276.7, 276.8, 285.9, 458, 458.9, 536.3, 584.9, 783.7, 275.42, 276.51, 285.29, 458.29, 780.79, 780.97, 787.01, 787.02, 787.03, 789.59 88, 90, 566, 536.2, 540.9, 552.1, 557.9, 558.1, 558.9, 569.3, 577, 578.1, 619.1, 531.4, 532.4, 535.5, 562.11, 567.29, 569.49, 569.62, 569.69, 569.81, 569.83, 787.91, 997.49, 997.4, 998.6, V552 , V553 591, 592, 592.1, 593.3, 593.4, 593.9, 619, 997.5, 590.8, 595.82, 599.6, 996.39, 996.65, 996.76 112.5, 380, 383, 388, 389, 845, 112.5, 381.1, 381.2, 384, 384.2, 384.3, 384.9, 682.6, 790.7, 567.22, 567.23, 567.38, 780.6, 780.62, 998.59 552.21, 560.1, 560.32, 560.81, 560.89, 560.9, 564, 564.09 338.3, 338.18, 789, 789.01, 789.06, 789.07, 789.09 998.2, 998.89 466, 486, 491.21, 491.22, 493.22, 493.92, 507, 511.81, 511.89, 511.9, 518.81, 518.84, 786.05, 786.09, 997.39 820.8, 820.09, 733.13, 820.21, 805.4, 813.44 112.2, 590.1, 599, 996.64 415.11, 415.13, 415.19, 453.2, 453.4, 453.41, 453.42, 453.82 553.21, 682.2, 998.13, 998.3, 998.31, 998.32, 998.51, 998.83

Supplemental Table 2. Sensitivity analysis of patient and hospital factors and their association with fragmented readmission at 30 and 90-days with chemotherapy readmissions and nonroutine discharges excluded 30-day readmission 90-day readmission Variable Odds Ratio (95% CI) Odds Ratio (95% CI) Age <40 years old 40-49 years old 50-59 years old 60-69 years old 70-79 years old >= 80 years old Comorbidity score None One condition Two or more conditions Insurance Medicare Medicaid Private Insurance Self-pay No Charge Other Income quartile 0-25% 26-50% (median) 51-75% 76-100% Hospital bedsize Small Medium Large Hospital teaching facility type Metropolitan non-teaching Metropolitan teaching Non- Metropolitan Burden Low burden Medium burden High burden

Reference 0.95 (0.77 - 1.17) 1.13 (0.94 - 1.36) 1.03 (0.84 - 1.25) 1.12 (0.90 - 1.40) 1.43 (1.12 - 1.81)

Reference 0.91 (0.78-1.07) 0.92 (0.8-1.06) 0.89 (0.7701.03) 0.98 (0.83-1.16) 1.03 (0.86-1.24)

Reference 0.95 (0.83 - 1.09) 0.98 (0.87 - 1.11)

Reference 1.02 (0.92-1.14) 1.08 (0.98-1.18)

1.20 (1.05 - 1.37) 1.06 (0.90 - 1.24) Reference 1.10 (0.84 - 1.45) 0.84 (0.34 - 2.11) 0.85 (0.60 - 1.20)

1.15 (1.04-1.28) 0.97 (0.86-1.1) Reference 1.05 (0.85-1.28) 0.98 (0.52-1.82) 0.78 (0.61-1.00)

1.18 (1.04 - 1.35) 1.30 (1.14 - 1.47) 1.29 (1.14 - 1.46) Reference

1.16 (1.05-1.28) 1.25 (1.13 -1.37) 1.18 (1.07-1.30) Reference

Reference 1.08 (0.92 - 1.28) 0.66 (0.57 - 0.77)

Reference 0.98 (0.86-1.13) 0.70 (0.62-0.8)

Reference 0.87 (0.78 - 0.96) 1.14 (0.84 - 1.54)

Reference 0.83 (0.77-0.90) 1.03 (0.81-1.31)

Reference 0.92 (0.83 - 1.02) 0.89 (0.78 - 1.02)

Reference 1.00 (0.92-1.09) 0.96 (0.87-1.07)

Extended procedures No extended procedure Extended procedure Lymphadenectomy No lymphadenectomy Lymphadenectomy Transfusion No transfusion Postoperative transfusion Medical/surgical complication No Yes

Reference 0.80 (0.72 - 0.88)

Reference 0.80 (0.75 - 0.87)

Reference 0.90 (0.82 - 0.98)

Reference 0.89 (0.83-0.96)

Reference 0.87 (0.79 - 0.95)

Reference 0.97 (0.9-1.04)

Reference 1.15 (1.03 - 1.29)

Reference 0.99 (0.9-1.08)

Supplemental Table 3. Sensitivity analysis of patient and hospital factors and their association with mortality on readmission at 30 day and 90 days with chemotherapy readmissions, planned readmissions, and non-routine discharges excluded

Variable Fragmented care No Yes Age <40 years old 40-49 years old 50-59 years old 60-69 years old 70-79 years old >= 80 years old Comorbidity score None One condition Two or more conditions Insurance Medicare Medicaid Private Insurance Self-pay No Charge Other Income quartile 0-25% 26-50% (median) 51-75% 76-100% Hospital bedsize Small Medium Large Hospital teaching facility type Metropolitan non-teaching Metropolitan teaching Non- Metropolitan

30-day readmission Odds Ratio (95% CI)

90-day readmission Odds Ratio (95% CI)

Reference 1.26 (0.99 - 1.60)

Reference 1.25 (1.02 - 1.52)

Reference 0.64 (0.35 - 1.19) 0.86 (0.50 - 1.47) 1.02 (0.59 - 1.75) 1.12 (0.61 - 2.05) 2.27 (1.23 - 4.18)

Reference 0.77 (0.46 - 1.27) 0.88 (0.56 - 1.37) 1.01 (0.64 - 1.59) 1.13 (0.68 - 1.87) 1.74 (1.02 - 2.96)

Reference 1.02 (0.64 - 1.64) 2.24 (1.51 - 3.34)

Reference 1.13 (0.76 - 1.68) 2.17 (1.55 - 3.04)

1.06 (0.76 - 1.48) 0.60 (0.35 - 1.03) Reference 2.82 (1.70 - 4.68) 2.88 (0.81 - 10.29) 1.57 (0.76 - 3.27)

0.96 (0.72 - 1.28) 0.70 (0.46 - 1.07) Reference 2.75 (1.82 - 4.15) 3.16 (1.15 - 8.71) 1.26 (0.69 - 2.31)

1.30 (0.95 - 1.78) 1.18 (0.86 - 1.63) 1.22 (0.89 - 1.66) Reference

1.21 (0.93 - 1.59) 1.05 (0.80 - 1.38) 1.14 (0.87 - 1.49) Reference

Reference 0.87 (0.56 - 1.34) 0.79 (0.53 - 1.17)

Reference 0.70 (0.47 - 1.05) 0.75 (0.53 - 1.07)

Reference 1.18 (0.89 - 1.57) 0.51 (0.15 - 1.78)

Reference 0.98 (0.78 - 1.23) 0.63 (0.25 - 1.54)

Burden Low burden Medium burden High burden Extended procedures No extended procedure Extended procedure Lymphadenectomy No lymphadenectomy Lymphadenectomy Transfusion No transfusion Postoperative transfusion Medical/surgical complication No Yes

Reference 0.93 (0.72 - 1.20) 0.65 (0.46 - 0.93)

Reference 1.11 (0.88 - 1.40) 1.07 (0.79 - 1.44)

Reference 0.79 (0.62 - 0.99)

Reference 0.86 (0.70 - 1.05)

Reference 0.75 (0.60 - 0.95)

Reference 0.68 (0.55 - 0.83)

Reference 1.31 (1.05 - 1.63)

Reference 1.33 (1.10 - 1.61)

Reference 1.58 (1.25 - 2.00)

Reference 1.67 (1.36 - 2.05)

Supplemental Table 4A. Rate of fragmentation by primary diagnoses at 30-day readmission, top 15 readmission diagnoses Primary diagnosis at readmission All available patients with diagnoses Chemo Infection Other GI conditions Intestinal obstruction FTT Respiratory condition Wound complication DVT/PE Bleeding Cardiac UTI Pain GU CVA Postop complication Trauma

Total N (% of all diagnoses)

Non-fragmented N (%)

Fragmented N (%)

4432 (100%)

3511 (79.8%)

921 (20.2%)

765 (17.3%) 613 (13.8%) 501 (11.3%) 367 (8.3%) 297 (6.7%) 210 (4.7%) 197 (4.4%) 179 (4.0%) 113 (2.5%) 78 (1.8%) 74 (1.7%) 66 (1.5%) 47 (1.1%) 20 (0.5%) 14 (0.3%) 5 (0.1%)

619 (81.8%) 528 (86.2%) 433 (85.1%) 306 (84.3%) 235 (81.8%) 141 (64.7%) 168 (85.8%) 117 (64.7%) 85 (78.6%) 40 (55.0%) 54 (74.7%) 55 (87.5%) 36 (71.6%) 10 (50.1%) 13 (93.4%) 4 (87.7%)

146 (18.2%) 85 (13.8%) 68 (14.9%) 61 (15.7%) 62 (18.2%) 69 (35.3%) 29 (14.2%) 62 (35.3%) 28 (21.4%) 38 (45.1%) 20 (25.3%) 11 (12.5%) 11 (28.4%) 10 (49.9%) 1 (6.6%) 1 (12.3%)

Supplemental Table 4B. Rate of fragmentation by primary diagnoses at 90-day readmission, top 15 readmission diagnoses Primary diagnosis at readmission All available patients with diagnoses Chemo Infection Other GI conditions Intestinal obstruction FTT Respiratory condition DVT/PE Wound complication Cardiac

Total N (% of all diagnoses)

Non-Fragmented N (%)

Fragmented N (%)

6057 (100%) 1321 (21.8%) 597 (9.9%) 522 (8.6%) 521 (8.6%) 439 (7.2%) 259 (4.3%) 244 (4.0%) 199 (3.3%) 147 (2.4%)

4458 (74.5%) 974 (74.6%) 498 (83.1%) 432 (82.5%) 412 (80.3%) 325 (77.3%) 162 (61.0%) 158 (63.1%) 169 (84.4%) 76 (54.3%)

1599 (25.5%) 347 (25.4%) 99 (16.9%) 90 (17.5%) 109 (19.7%) 114 (22.7%) 97 (39.0%) 86 (36.9%) 30 (15.6%) 71 (45.7%)

UTI Bleeding GU CVA Postop complication Trauma

119 (2.0%) 107 (1.8%) 66 (1.1%) 32 (0.5%) 15 (0.2%) 14 (0.2%)

77 (64.9%) 79 (76.8%) 41 (59.4%) 15 (53.0%) 13 (88.3%) 8 (64.2%)

42 (35.1%) 28 (23.2%) 25 (40.6%) 17 (47.0%) 2 (11.7%) 6 (35.8%)

Chemo – chemotherapy, GI – gastrointestinal, FTT – failure to thrive, DVT – deep vein thrombosis, PE – pulmonary embolus, UTI – urinary tract infection, GU – genitourinary, CVA – cerebrovascular accident

Table 1. Patient and hospital characteristics of index and non-index readmissions at 30-days. Index (NonNon-index Variable N Fragmented) (Fragmented) All 10445 8271 (79.2%) 2174 (20.8%) Hospital bed size Small 669 478 (5.8%) 191 (8.8%) Medium 1861 1301 (15.7%) 560 (25.8%) Large 7915 6492 (78.5%) 1423 (65.4%) Hospital teaching facility type Metropolitan non-teaching 1843 1404 (17.0%) 439 (20.2%) Metropolitan teaching 8449 6761 (81.7%) 1688 (77.6%) Non- Metropolitan 153 106 (1.3%) 47 (2.2%) Income quartile 0-25% 2547 2015 (24.4%) 532 (24.5%) 26-50% (median) 2412 1869 (22.6%) 543 (23.0%) 51-75% 2515 1953 (23.6) 562 (25.9%) 76-100% 2775 2305 (27.9%) 470 (21.6%) Unknown 197 67 (3.1%) 130 (1.6%) Age <40 years old 866 706 (8.5%) 160 (7.4%) 40-49 years old 1329 1105 (13.4%) 225 (10.3%) 50-59 years old 2385 1896 (22.9%) 488 (22.5%) 60-69 years old 2952 2385 (28.8%) 567 (26.1%) 70-79 years old 2095 1616 (19.5%) 479 (22.1%) >= 80 years old 817 563 (6.8%) 254 (11.7%) Burden Low burden 2811 2197 (26.6%) 614 (28.2%) Medium burden 5552 4424 (53.5%) 1128 (51.9%) High burden 2083 1650 (20.0%) 433 (19.9%) Comorbidity score None 2090 1680 (20.3%) 410 (18.9%) One condition 2472 1993 (24.1%) 479 (22.0%) Two or more conditions 5884 4598 (55.6%) 1285 (59.1%) Dispo Routine 6850 5493 (66.4%) 1357 (62.4%) Short-term hospital 29 20 (0.2%) 9 (0.4%) SNF, ICF, or Other 1188 831 (10.0%) 357 (16.4%) Home health care 2358 1915 (23.2%) 443 (20.4%) AMA 17 7 (0.1%) 9 (0.4%) Missing/Unknown 4 4 (0.0%) 0 (0%)

Extended procedures No extended procedure 7239 5362 (64.8%) Extended procedure 3206 2909 (35.2%) Lymphadenectomy No lymphadenectomy 5983 4648 (56.2%) Lymphadenectomy 4462 3623 (43.8%) Medical/surgical complication No 8484 6762 (81.8%) Yes 1961 1509 (18.2%) Insurance Medicare 4480 3400 (41.1%) Medicaid 1130 915 (11.1%) Private Insurance 4291 3507 (42.4%) Self-pay 284 227 (2.8%) No Charge 27 23 (0.3%) Other 225 191 (2.3%) Missing/Unknown 9 9 (0.1%) Transfusion No transfusion 6961 5451 (65.9%) Postoperative transfusion 3484 2820 (34.1%) SNF – skilled nursing facility, ICF – intermediate care facility

1536 (70.6%) 638 (29.4%) 1335 (61.4%) 839 (38.6%) 1722 (79.2%) 452 (20.8%) 1080 (49.7%) 216 (9.9%) 783 (36.0%) 57 (2.6%) 5 (0.2%) 34 (1.6%) 0 (0%) 1510 (69.5%) 664 (30.5%)

Table 2. Patient and hospital characteristics of index and non-index readmissions at 90-days. Index (NonNon-index Variable N Fragmented) (Fragmented) All 14124 10490 (74.3%) 3634 (25.7%) Hospital bed size Small 865 574 (5.5%) 291 (8.0%) Medium 2447 1631 (15.5%) 816 (22.5%) Large 10812 8285 (79.0%) 2527 (69.5%) Hospital teaching facility type Metropolitan non-teaching 2540 1785 (17.0%) 756 (20.8%) Metropolitan teaching 11371 8566 (81.7%) 2805 (77.2%) Non- Metropolitan 213 139 (1.3%) 74 (2.0%) Income quartile 0-25% 3307 2437 (23.2%) 870 (24.0%) 26-50% (median) 3300 2363 (22.5%) 937 (25.8%) 51-75% 3502 2573 (24.5%) 929 (25.6%) 76-100% 3743 2926 (27.9%) 817 (22.5%) Unknown 271 190 (1.8%) 81 (2.2%) Age <40 years old 1172 869 (8.3%) 303 (8.3%) 40-49 years old 1652 1268 (12.1%) 384 (10.6%) 50-59 years old 3340 2543 (24.2%) 797 (21.9%) 60-69 years old 4073 3089 (29.4%) 984 (27.1%) 70-79 years old 2841 2017 (19.2%) 823 (22.7%) >= 80 years old 1046 704 (6.7%) 342 (9.4%) Burden Low burden 3731 2776 (26.5%) 954 (26.3%) Medium burden 7792 5781 (55.1%) 2011 (55.3%) High burden 2602 1932 (18.4%) 669 (18.4%) Comorbidity score None 2847 2173 (20.7%) 674 (18.5%) One condition 3260 2469 (23.5%) 792 (21.8%) Two or more conditions 8017 5848 (55.7%) 2169 (59.7%) Dispo Routine 9407 6994 (66.7%) 2413 (66.4%) Short-term hospital 49 37 (0.4%) 12 (0.3%) SNF, ICF, or Other 1544 1077 (10.3%) 467 (12.8%) Home health care 3101 2372 (22.6%) 730 (20.1%) AMA 19 5 (0.0%) 13(0.4%) Missing/Unknown 4 4 (0.0%) 0 (0.0%)

Extended procedures No extended procedure 9429 6834 (65.1%) Extended procedure 4695 3655 (34.8%) Lymphadenectomy No lymphadenectomy 8087 5863 (55.9%) Lymphadenectomy 6037 4627 (44.1%) Medical/surgical complication No 11616 8630 (82.3%) Yes 2508 1860 (17.7%) Insurance Medicare 6026 4281 (40.8%) Medicaid 1391 1065 (10.1%) Private Insurance 5903 4518 (43.1%) Self-pay 398 297 (2.8%) No Charge 41 31 (0.3%) Other 351 287 (2.7%) Missing/Unknown 13 11 (0.1%) Transfusion No transfusion 9462 6990 (66.6%) Postoperative transfusion 4662 3499 (33.4%) SNF – skilled nursing facility, ICF – intermediate care facility

2595 (71.4%) 1039 (28.6%) 2224 (61.2%) 1410(38.8%) 2987 (82.2%) 647 (17.8%) 1745 (48.0%) 326 (9.0%) 1386 (38.1%) 101 (2.8%) 10 (0.3%) 64 (1.8%) 2 (0.0%) 2472 (68.0%) 1163 (32.0%)

Table 3. Comparison of cost and length of stay of index and non-index readmission at 30 and 90-days. Index (NonNon-Index Fragmented) (Fragmented) 30 Day Readmission (N=10,445) Initial admission length of stay (mean days)

9.1

9.4

Readmit length of stay (mean days)

6.3

6.3

Initial admission total cost (mean $)

$27,006

$25,949

Readmit total cost (mean $)

$13,490

$13,838

Initial admission length of stay (mean days)

8.9

8.4

Readmit length of stay (mean days)

5.8

5.7

Initial admission total cost (mean $)

$12,572

$13,006

Readmit total cost (mean $)

$26,133

$24,131

90 Day Readmission (N=14,124)

Table 4. Patient and hospital factors and their association with fragmented readmission at 30 and 90-days. 30-day readmission 90-day readmission Variable Odds Ratio (95% CI) Odds Ratio (95% CI) Age <40 years old Reference Reference 40-49 years old 0.96 (0.78 - 1.18) 0.92 (0.79 - 1.07) 50-59 years old 1.13 (0.94 - 1.36) 0.92 (0.8 - 1.06) 60-69 years old 1.03 (0.85 - 1.26) 0.9 (0.78 - 1.03) 70-79 years old 1.11 (0.88 - 1.38) 0.99 (0.84 - 1.16) >= 80 years old 1.33 (1.04 - 1.7) 1.03 (0.85 - 1.24) Comorbidity score None Reference Reference One condition 0.96 (0.84 - 1.1) 1.03 (0.93 - 1.14) Two or more conditions 0.98 (0.87 - 1.11) 1.08 (0.98 - 1.19) Insurance Medicare 1.17 (1.02 - 1.34) 1.15 (1.04 - 1.28) Medicaid 1.04 (0.89 - 1.22) 0.97 (0.85 - 1.1) Private Insurance Reference Reference Self-pay 1.12 (0.85 - 1.47) 1.05 (0.85 - 1.28) No Charge 0.84 (0.34 - 2.11) 0.97 (0.52 - 1.81) Other 0.82 (0.58 - 1.16) 0.77 (0.6 - 0.99) Income quartile 0-25% 1.19 (1.04 - 1.35) 1.16 (1.05 - 1.28) 26-50% (median) 1.29 (1.13 - 1.46) 1.24 (1.13 - 1.37) 51-75% 1.28 (1.13 - 1.45) 1.18 (1.07 - 1.3) 76-100% Reference Reference Hospital bedsize Small Reference Reference Medium 1.1 (0.93 - 1.3) 0.99 (0.86 - 1.13) Large 0.67 (0.58 - 0.79) 0.71 (0.63 - 0.8) Hospital teaching facility type Metropolitan non-teaching Reference Reference Metropolitan teaching 0.87 (0.78 - 0.97) 0.84 (0.77 - 0.91) Non- Metropolitan 1.18 (0.87 - 1.6) 1.04 (0.81 - 1.32) Burden Low burden Reference Reference Medium burden 0.91 (0.82 - 1.01) 1 (0.92 - 1.08) High burden 0.89 (0.78 - 1.02) 0.96 (0.87 - 1.07) Dispo

Routine Short-term hospital SNF, ICF, or Other Home health care AMA Extended procedures No extended procedure Extended procedure Lymphadenectomy No lymphadenectomy Lymphadenectomy Transfusion No transfusion Postoperative transfusion Medical/surgical complication No Yes

Reference 1.41 (0.72 - 2.74) 1.32 (1.15 - 1.51) 0.96 (0.86 - 1.08) 2.35 (1.22 - 4.52)

Reference 0.88 (0.5 - 1.57) 1.04 (0.93 - 1.17) 0.92 (0.84 - 1.01) 2.38 (1.38 - 4.11)

Reference 0.81 (0.73 - 0.89)

Reference 0.81 (0.75 - 0.87)

Reference 0.90 (0.83 - 0.99)

Reference 0.89 (0.84 - 0.96)

Reference 0.86 (0.78 - 0.95)

Reference 0.97 (0.9 - 1.04)

Reference 1.09 (0.97 - 1.22)

Reference 0.98 (0.9 - 1.08)

SNF – skilled nursing facility, ICF – intermediate care facility

Table 5. Patient and hospital factors and their association with mortality on readmission at 30 day and 90 days. 30 day readmission 90 day readmission Variable Odds Ratio (95% CI) Odds Ratio (95% CI) Fragmented care No Reference Reference Yes 1.19 (0.93 - 1.51) 1.22 (1 - 1.49) Age <40 years old Reference Reference 40-49 years old 0.59 (0.32 - 1.09) 0.74 (0.45 - 1.22) 50-59 years old 0.79 (0.46 - 1.36) 0.83 (0.53 - 1.3) 60-69 years old 0.92 (0.53 - 1.58) 0.93 (0.59 - 1.46) 70-79 years old 0.93 (0.5 - 1.7) 0.99 (0.6 - 1.65) >= 80 years old 1.52 (0.81 - 2.84) 1.34 (0.78 - 2.3) Comorbidity score None Reference Reference One condition 1.04 (0.65 - 1.67) 1.12 (0.76 - 1.67) Two or more conditions 2.08 (1.39 - 3.1) 2 (1.43 - 2.81) Insurance Medicare 0.91 (0.65 - 1.28) 0.83 (0.62 - 1.12) Medicaid 0.56 (0.33 - 0.97) 0.66 (0.43 - 1.01) Private Insurance Reference Reference Self-pay 2.92 (1.75 - 4.86) 2.78 (1.84 - 4.2) No Charge 3.37 (0.94 - 12.05) 3.67 (1.33 - 10.11) Other 1.38 (0.66 - 2.89) 1.19 (0.65 - 2.18) Income quartile 0-25% 1.34 (0.98 - 1.83) 1.21 (0.93 - 1.58) 26-50% (median) 1.18 (0.85 - 1.62) 1.05 (0.79 - 1.38) 51-75% 1.25 (0.92 - 1.7) 1.15 (0.88 - 1.5) 76-100% Reference Reference Hospital bedsize Small Reference Reference Medium 0.85 (0.55 - 1.31) 0.69 (0.46 - 1.03) Large 0.78 (0.52 - 1.16) 0.74 (0.52 - 1.06) Hospital teaching facility type Metropolitan non-teaching Reference Reference Metropolitan teaching 1.18 (0.89 - 1.56) 1 (0.8 - 1.26) Non- Metropolitan 0.52 (0.15 - 1.8) 0.7 (0.28 - 1.73) Burden Low burden Reference Reference

Medium burden High burden Dispo Routine Short-term hospital SNF, ICF, or Other Home health care AMA Extended procedures No extended procedure Extended procedure Lymphadenectomy No lymphadenectomy Lymphadenectomy Transfusion No transfusion Postoperative transfusion Medical/surgical complication No Yes

0.93 (0.72 - 1.19) 0.69 (0.49 - 0.99)

1.13 (0.89 - 1.42) 1.11 (0.82 - 1.5)

Reference 2.49 (0.55 - 11.25) 2.87 (2.13 - 3.89) 1.53 (1.15 - 2.02) 4.14 (0.81 - 21.04)

Reference 2.29 (0.78 - 6.72) 2.38 (1.81 - 3.13) 1.76 (1.39 - 2.22) 9.58 (3.85 - 23.85)

Reference 0.74 (0.59 - 0.94)

Reference 0.79 (0.64 - 0.96)

Reference 0.78 (0.62 - 0.98)

Reference 0.7 (0.57 - 0.85)

Reference 1.23 (0.99 - 1.54)

Reference 1.28 (1.05 - 1.54)

Reference 1.26 (0.98 - 1.61)

Reference 1.36 (1.09 - 1.68)

SNF – skilled nursing facility, ICF – intermediate care facility

Figure 1. Flowchart of study selection. Figure 2A. Rate of Fragmentation by primary diagnoses at 30 day readmission. Figure 2B. Rate of fragmentation by primary diagnoses at 90 day readmission. Chemo – chemotherapy, GI – gastrointestinal, FTT – failure to thrive, DVT – deep vein thrombosis, PE – pulmonary embolus, UTI – urinary tract infection, GU – genitourinary, CVA – cerebrovascular accident