Before the current work, we knew from previous study with the identical, public data set that there were the 23,108 unweighted readmissions within 30 days.17 In addition, for urological surgery, 20.7% of readmissions were at a different hospital than where the surgery was performed.18 Therefore, we predicted that our smallest sample size (ie, Question #3) would have a numerator for the logistic regression of approximately 4780 (ie, 20.7% of 23,108), sufficiently large to achieve a narrow CI.
Among discharges for common surgical DRGs with nationwide median LOS ≥ 3 days (Table 2), 16.15% had a disposition of “not to home” (ie, transfer to a skilled nursing facility or an inpatient rehabilitation hospital; 95% CI, 15.14%–17.22%), and 30.01% had a disposition of “home health care” (95% CI, 28.00%–32.10%). In contrast, among the 3.78% of discharges that were followed by readmission within 30 days (95% CI, 3.60%–3.99%), 0.88% were to a different hospital than the original hospital where the surgery was performed (0.82%–0.95%).
Patients readmitted to a different hospital than where the surgery was performed were 23.3% of the patients readmitted (23.3% = 0.88%/3.78%; 95% CI, 22.0%–24.6%). Adjusting for DRG, disposition “not to home” was associated with greater odds of readmission and to a different hospital than where the surgery was performed (2.11, 95% CI, 1.96–2.27; Figure 1; P < .0001, answering Question #2). This was caused by 2 associations. First, disposition “not to home” was associated with greater odds of readmission (1.90, 95% CI, 1.82–1.98; P < .0001), as expected19,20 and as shown by the sensitivity analyses to be at least in part an indirect effect of patient acuity (Table 5). Second, among the subset of patients who were readmitted, disposition “not to home” was associated with greater odds that the readmission was to a different hospital than where the surgery was performed (1.20, 95% CI, 1.11–1.31; P < .0001).
Adjusting for DRG (Table 2), there was no association between the hospitals’ median LOS for the DRG and the odds that the readmission would be at a different hospital (P = .82, answering Question #3). The odds ratio per each decrease in the hospital median LOS by 1 day was 1.01 (95% CI, 0.91–1.12). Figure 2 shows the forest plot.c,21,22 There were no significant changes in estimates for any of the 6 sensitivity analyses, including patients’ comorbidities (Table 6).23
Based on our 3 observations from the Nationwide Readmissions Database, departments and hospitals wishing to document the value of their Perioperative Surgical Home initiatives should prioritize obtaining access to accurate data on resource use at postacute care facilities such as skilled nursing facilities. This aligns with payers’ goals of reducing the cost of perioperative care, which goes beyond reducing the cost of hospitalization. In addition, approximately one-quarter of readmissions are to different hospitals than where surgery was originally performed. Provided this is known and incorporated in analyses such as risk-based contracts, obtaining information on clinical processes, workflow, and resource use from those different acute care hospitals is less important than getting the postacute care facility data.
From Question #1, many more patients receive postacute care than are readmitted and to a different hospital than where the surgery was performed. This result is likely to be reliable. One reason was that we included all causes of hospital admission within 30 days of discharge, not just readmissions due to complications of the surgery. The second reason was that we considered postdischarge care only at skilled nursing facilities and inpatient rehabilitation hospitals. Home health care can also be labor intensive, and it is used heterogeneously among hospitals.24–26 Home health care reduces readmission rates after major surgery and is net cost saving.27
Although our current findings are for all US patients, older economic studies using US Medicare data are consistent with our conclusions; there were greater total payments among all patients for postacute care facilities than for readmission.28–30 For each of several types of surgical procedures, hospitals were divided into quintiles based on Medicare’s total 30-day payments for their patients. For spine surgery in 2005 to 2007, Medicare payments for patients at the hospitals in the third quintile were greater for postacute care ($3633) than for readmission ($991).28 If we apply our finding that approximately 24.7% of these readmissions were to a different hospital than where the surgery was performed (Table 4), the readmission value would be approximately $245, an amount that is small relative to the $3633. The difference between the fifth (highest) and first (lowest) quintile among hospitals where surgery was performed (ie, an indication that informatics and change in processes can reduce costs) was greater for postacute care ($3788) than for readmission ($1086).28 For colorectal surgery, the Medicare 30-day median payment in 2004 to 2006 was also greater for postacute care ($4666) than for readmission ($730).29 For hip replacement, the fifth and first quantiles among hospitals were greater for postacute care ($3840 and $9725) than for readmission ($582 and $1052), as were the differences ($5885 vs $470).30 For coronary artery bypass grafting, the fifth and first quantiles were greater for postacute care ($2833 and $5165) than for readmission ($1810 and $2715), as were the differences ($2332 vs $905).30
Our conclusion from the answer to Question #2 should not be interpreted that hospitals should make decisions to know and reduce resource use at postacute care facilities in lieu of concern about readmissions. The hospital could promote selection of specific postacute care facilities based, in part, on the facilities’ quality at achieving low rates of readmission. From an informatics point of view, the incidence of postacute care (eg, skilled nursing facility) would not be the end point used (eg, as is currently done31). Rather, the end point would be the quality of functional recovery, resources used (eg, frequency of labor used or based on application of patient condition), and costs.32 The American Hospital Association described that the way for US hospitals to achieve the largest reduction in readmission rates is through partnership with postacute care facilities.33 From MedPAC’s recommendations to the US Congress, skilled nursing facilities’ quality can be measured by their readmission rates.34 The National Quality Forum endorsed measuring all-cause readmission rates during the first 30 days of home health care, all-cause readmission within 30 days of the preceding hospitalization among patients admitted to skilled nursing facilities, and all-cause unplanned readmission for 30 days after discharge from inpatient rehabilitation hospitals.35
Regarding Question #3, Perioperative Surgical Home and enhanced recovery programs typically are implemented at individual hospitals in an effort to reduce the average LOS of patients with specific DRGs or groups of related DRGs. Associations between hospitals’ average (median) LOS and the incidences of subsequent readmission have previously been characterized by using before/after designs for specific procedures.36–43 What has been unknown are the effects on results from absence of data from a readmission, or even knowledge that a patient was readmitted, because this occurred at a different hospital. Such confounding could be caused, for example, by the patient (or family) preferring not to return to the hospital with the relatively short LOS based on a perception that premature discharge was associated with the need for readmission. If so, each decrease in median hospital LOS would be associated with greater odds of readmission to a different hospital. Statistically speaking, readmissions to different hospitals than where the surgery was performed could result in data that are not missing completely at random. Our results in Figure 2 show that, for before/after studies of individual hospitals implementing a Perioperative Surgical Home/enhanced recovery program, the change in the readmission rate at the hospital where surgery was performed would likely remain valid, provided that control chart analysis is used, because of relatively equal incidences of missing data before and after the change in LOS. Note that our results would not apply to hospitals (rather than insurers3,35) benchmarking readmission rates if only some hospitals make efforts to know about readmissions at different hospitals, because those hospitals’ readmission rates would appear falsely higher than that of hospitals that make no effort to record such data.
We limited consideration to DRGs with median LOS nationwide of at least 3 days. We did so to avoid including procedures most commonly performed on an outpatient basis, but for which some cases would be inpatient. Otherwise, we could not study the potential confounding of heterogeneity among hospitals in median LOS on the odds that readmission would be at a different hospital than where the surgery was performed. An important consequence of the 3-day requirement was that there was substantive use of skilled nursing facilities. Medicare pays for skilled nursing facilities postoperatively only after a LOS of 3 days.44 Results would likely be different for bariatric surgery.45 Among US Medicare patients in 2011 undergoing bariatric surgery, the mean total postacute care cost (including home health care and physician visits) was only $365, with $39 being the mean skilled nursing facility cost.45 The means were so small because Medicare’s reimbursements were 0 for most patients, because most patients did not receive any skilled nursing facility care.
The Nationwide Readmissions Database is limited in not providing identifiable geographic information; this is for privacy considerations. We found unexpectedly that patients being transferred to short-term care facilities had greater odds that, if readmitted, the readmission was to a different hospital than where the surgery was performed (P < .0001). A confounding factor affecting the choice of the readmission hospital, or even perhaps the causal factor, may be the distance from the short-term care facility to the original hospital where the surgery was performed. Although we cannot study this explanation, such considerations do not affect our conclusions related to informatics.
Resource use, clinical processes and services, costs, and outcome data are not available in the Nationwide Readmissions Database for the short-term care facilities. Even if Medicare payment data were available, according to the Medicare Payment Advisory Commission, payments are inaccurate measures of costs for these facilities.34 For rural areas in the United States, accurate cost accounting would require detailed operational data,2 because federally certified skilled nursing and inpatient rehabilitation facilities can be virtualized as “swing beds” (ie, otherwise empty acute care beds dynamically designated for short-term care use).46 From the perspective of hospitals, informatics, and Perioperative Surgical Home, our study of incidence of use was reasonable because hospitals generally have 1 information system and 1 method of coordinating data flow with skilled nursing facilities, home health care organizations, and so on. Thus, informatics decisions often are weighted by numbers of patients (as we studied) because that is what influences the time spent by clinicians (ie, nurse practitioners and physicians) filling out order entry forms for postdischarge care.
Finally, for each DRG, we limited consideration to hospitals with at least 100 discharges for elective surgery over 11 months (Table 1). We do not know how this assumption would affect conclusions for smaller hospitals. We suggest treating our results as applying to hospitals with large amounts of inpatient surgery.
In conclusion, we cataloged incidences of readmissions going to different hospitals than where surgery was performed. For Perioperative Surgical Home interventions, the principal informatics focus for postdischarge care should be the resources used, costs, and outcomes related to postacute care that many patients receive, such as at skilled nursing facilities. Afterward and/or if there is a substantial budget, focus on information from the different acute care hospitals to where patients may be readmitted.
The authors thank Jennifer Espy of the University of Iowa for her assistance with editing of the manuscript and preparation for the Journal.
Name: Franklin Dexter, MD, PhD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Name: Richard H. Epstein, MD.
Contribution: This author helped conduct the study and write the manuscript.
Name: Eric C. Sun, MD, PhD.
Contribution: This author helped analyze the data and write the manuscript.
Name: David A. Lubarsky, MD, MBA.
Contribution: This author helped write the manuscript.
Name: Elisabeth U. Dexter, MD, FACS.
Contribution: This author helped design the study and write the manuscript.
This manuscript was handled by: Nancy Borkowski, DBA, CPA, FACHE, FHFMA.
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