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Invited Commentary
April 13, 2021

Potentially Preventable Readmissions After Surgery

Author Affiliations
  • 1School of Medicine, Department of Surgery, Washington University in Saint Louis, St Louis, Missouri
  • 2Center for Clinical Excellence, BJC Healthcare, St Louis, Missouri
JAMA Netw Open. 2021;4(4):e216389. doi:10.1001/jamanetworkopen.2021.6389

The study by Brown and colleagues1 provides valuable insights into the burden of potentially preventable hospital readmissions after a selection of important surgical procedures. Brown et al1 conducted a retrospective cohort study of data from the Healthcare Cost and Utilization Project National Readmissions Database, the largest readmissions database for the United States, accounting for more than 58% of all hospitalizations. The investigators examined readmissions within 90 days for 9 high-importance procedures among a weighted estimation sample of 1 937 354 patients.1 The primary outcome was potentially preventable readmissions (PPR). This was based on diagnoses either defined previously by the Agency for Healthcare Research and Quality as ambulatory care–sensitive conditions (ACSC) or diagnoses in 1 of 3 categories particularly relevant to surgery: superficial surgical site infection, acute kidney injury, or aspiration pneumonia or pneumonitis. Patient and hospital characteristics were used to identify factors affecting PPR risk.1

In the study by Brown et al,1 there were 164 755 readmissions (8.5%) overall, with 29 321 (17.8%) of those (1.5% absolute) categorized as PPR.1 The most common reasons for PPR were congestive heart failure exacerbation (34.6% of total readmissions), pneumonia (12.0%), and acute kidney injury (22.5%).1 Hospital costs associated with all readmissions were estimated at $2.01 billion (median [interquartile range] cost per readmission, $8310.96 [$5055.26-$14 344.51]), and for PPRs specifically at $296 million (14.7% of total costs; median [interquartile range] cost per readmission, $7143.16 [$4647.13-$11 637.56]).1 Factors associated with increased readmissions and PPR included increased age, lower income, emergency status, and public insurance enrollment. Brown and colleagues conclude that “In addition to better inpatient care, improved access to ambulatory care may represent an opportunity to reduce costly readmissions among surgical patients.”1 This study invites commentary from a number of perspectives.

Is the Concept of a PPR Robust?

It is important to highlight the framework for the use of the word preventable in this and similar health care applications. If we take prevent to mean stop, then preventable things would be things we can stop from happening. But despite some reason to think we can, we might not know exactly how to prevent these events. Then preventing ceases to be an absolute, and our goal becomes to try. However, the origin of the word prevent goes back to the Middle English word meaning anticipate.2 If we mean to say these are events we should anticipate, perhaps we mean we should remain aware and ready to react. But this seems insufficient. It is also worth noting that there is some controversy on whether all readmissions are undesired. Nonetheless, the best formulation may be that readmissions are undesired unless otherwise stated, and that we want to both anticipate and modify the course, to avert the event. Perhaps the concept of modifiable would also deemphasize the notion of blame that the word preventable sometimes carries. Deemphasizing blame is consistent with our desire for a Just Culture approach to improvement. Therefore, our default becomes that a readmission should generally be avoided, and we seek to know which of them are most modifiable, to change the patient course for the better, without invoking blame. Still, modifiable is a continuous spectrum, not dichotomous, and we do not always know how to modify the course. Given real-world constraints on resources, we would like to know where our efforts to modify are most likely to pay off. There is the rub: where to start?

The ACSC formulation is consistent with this challenge. For ACSCs, the preventable judgment is the belief that the readmission is potentially sensitive to ambulatory care, that is, it might be modified. Defined by modified-Delphi panel methods in 1993,3 and subsequently adopted by the Agency for Healthcare Research and Quality as a hospital quality indicator in 2001,4 ACSCs represent a set of medical conditions for which hospitalization is thought to be potentially preventable by timely and effective outpatient care. This implies that the substitute care is more desired (ie, better or equal and less costly). Starting with this framework, Brown and colleagues1 added 3 surgically relevant diagnoses. How robust is this version of the concept? The implementation of this concept is not perfect but represents a very reasonable application of the Pareto principle, under which a small portion of a population accounts for a disproportionate share of some phenomenon. In this case, finding a small subset of readmissions that account for a large resource burden and that might be most responsive to intervention, ie, most modifiable, could be quite valuable. Such an intervention could be thought of as low-hanging fruit.

In the study by Brown et al,1 the utility of the ACSC concept is supported by the finding that intuitive factors are in fact associated with PPRs. Public insurance enrollment, increased age, and lower income, all of which can reasonably be expected to reduce access to care that could prevent readmission, are associated with increased PPR rates. Thus, the Pareto principle guides us to focus on these and similar risk factors. But questions remain. Brown et al1 state that comorbidities associated with increased odds of PPR included congestive heart failure, dementia, chronic obstructive pulmonary disease, rheumatoid disease, diabetes, chronic kidney disease, liver disease, metastatic cancer, and AIDS. Do these truly increase the risk of preventable readmissions as an early target, or are these only associated with readmission in general? Similarly, the results in the study by Brown et al1 indicate that public insurance type and low income were associated with overall readmissions and PPR, not just PPR. Our ability to narrow the Pareto remains limited. But all readmission types are likely to fall on a continuous spectrum of preventability, which could look different depending on procedure, patient, and environmental factors. Rather than negating the value of establishing readmissions that are most modifiable, this reality encourages and rewards our search for the most preventable readmissions—again, those that could be considered low-hanging fruit.

Readmissions Timing and the Decay Curve

The time course of readmissions reported by Brown et al1 is informative. Total readmissions peaked around postdischarge day 15, and at day 30 aggregate readmissions were 3.6%, but between days 31 and 90, the rate increased another 4.9%, reaching 8.5%.1 This curve tells us that substantial readmissions might be immediately associated more with potentially modifiable comorbid conditions rather than with direct procedural complications. This has been a controversy in the surgical and procedural communities. Procedural readmissions might be as much about transitions across settings in the context of patient status and resources as about procedure risks. Brown and colleagues1 do a great service in highlighting this.

This time course also suggests that several PPRs were still to come after 90 days. Does that make sense? Is this an artifact of ongoing capture of increasingly common admissions for these diagnoses, which are in fact no longer representative of the index procedure? Does this challenge the overall PPR conceptual framework, or can it still provide valuable information? Is this telling us that it is critical to provide the ambulatory care access and transitions of care each time a patient is discharged, but not to expect that to have a significant association with outcomes 60 to 90 days out or longer? Future work carefully examining timing of events will be enlightening.

Implications for Episode-Based At-Risk Payment Structures

What implications does the study by Brown et al1 have for how we manage inside bundled-payment structures, and how might we better design at-risk financing policies? Brown and colleagues reiterate, “… a substantial proportion of readmissions in the postoperative setting may be associated with factors strongly associated with transitions from inpatient to outpatient care rather than inherent risks associated with the procedure or its complications. In this way, postoperative readmissions are not merely a measure of hospital and inpatient care quality but also represent a measure of access to and quality of ambulatory care after hospital discharge.”1 This stance is supported by the evidence that PPR rates are significantly associated with a variety of socioeconomic factors and primary payer status, which are reasonably thought of as proxies for access to care.

The study by Brown et al1 highlights the importance of caring for the comprehensive sets of needs of our patients, even when a patient is admitted for a specific surgical procedure. Currently, clinical care is not always organized in a manner that encourages a hospital-based medical or procedural team to aggressively manage the transitions of care for a patient. Innovative, value-based care models that include a risk-sharing arrangement, such as bundled payments, can be one vehicle to align incentives to manage the patient’s medical conditions comprehensively. This includes managing the transitions of care and maintaining a strong connection from the hospital-based team to the patient’s primary care team. This might also lead us to think about how the primary care physician might be more closely aligned with hospital-based specialists in future value-based care arrangements, unlike the current state of care in the US, in which often primary care and specialty care arrangements are conducted in separate arenas. A focus on improving the transitions of care, effective ambulatory follow-up, and management of chronic disease can improve performance in these models and in parallel, apparently, for PPRs.

Waste and Financial Toxic Effects

The study by Brown and colleagues1 reemphasizes a critical obligation health care practitioners share. A 2019 study by Shrank et al5 estimated that the annual cost of waste in the US health care system ranges from $760 billion to $935 billion, accounting for as much as 25% of total health care spending. As part of this total, $21 billion to $22 billion is expended on readmissions after prior care, and $6 billion to $56 billion is consumed on unnecessary admissions or dealing with avoidable complications.5 This burden on our current health care system will be shouldered by future generations. Furthermore, the current and future burdens are not borne equally across social and demographic strata, with the poor and underprivileged, underresourced, and populations that are targets of bias being disproportionately hurt. The financial toxic effects experienced secondary to health care costs are often felt and experienced by those who have the least resources and slimmest margins of safety. As clinicians, it is clearly our moral obligation to focus on any indication that particular harms might be avoided, for the patients in front of us and our larger communities.

In a recent article, Cutler6 points out that not only do health care expenditures soak up large fractions of gross domestic product (GDP) equivalent, but that health care increasingly consumes additional economic growth at even higher proportions. Cutler states “An enormous share of this economic growth was taken by health care, about 32% of increased GDP between 2007 and 2019 and an even larger share, 39%, between 2000 and 2007. Put another way, roughly one-third of every additional dollar earned in the economy during the past 2 decades was used to pay for medical care.”6 Cutler6 calls out overuse of services (which would include potentially preventable hospital admissions and readmissions), along with high administrative expenses and excessively high prices, as areas for focus. There are not simple, sweeping policy changes to instantaneously target these problems. The work has to happen on the front lines, with granular attention to process and detail. For all intents and purposes, PPRs should provide an easy on-ramp to that work.


The study by Brown and colleagues1 helps to shine the light on very rational starting points for all of us to pick up the challenge of pursuing efficiency and eliminating waste, on behalf of current patients and on behalf of those who today and in future days will bear the costs of health care in the United States. As we highlight the need for better transition and posthospital resources, we will empower examinations of the inequity of those resources currently. It is our moral obligation to pick up these challenges and run.

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Article Information

Published: April 13, 2021. doi:10.1001/jamanetworkopen.2021.6389

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Hall BL et al. JAMA Network Open.

Corresponding Author: Bruce L. Hall, MD, PhD, MBA, BJC Learning Institute, 8300 Eager Rd, Ste 400-A, Mailstop 92-92-241, St Louis, MO 63144 (hallb@wustl.edu).

Conflict of Interest Disclosures: Dr Hall reported serving as the consulting director of the American College of Surgeons National Surgical Quality Improvement Program. No other disclosures were reported.

Brown  CS, Montgomery  JR, Neiman  PU,  et al.  Assessment of potentially preventable hospital readmissions after major surgery and association with public vs private health insurance and comorbidities.   JAMA Netw Open. 2021;4(4):e215503. doi:10.1001/jamanetworkopen.2021.5503Google Scholar
Merriam-Webster. Prevent. Accessed March 16, 2021. https://www.merriam-webster.com/dictionary/prevent
Billings  J, Zeitel  L, Lukomnik  J, Carey  TS, Blank  AE, Newman  L.  Impact of socioeconomic status on hospital use in New York City.   Health Aff (Millwood). 1993;12(1):162-173. doi:10.1377/hlthaff.12.1.162PubMedGoogle ScholarCrossref
 AHRQ Quality Indicators—Guide to Prevention Quality Indicators: Hospital Admission for Ambulatory Care for Sensitive Conditions. Agency for Healthcare Research and Quality; 2001.
Shrank  WH, Rogstad  TL, Parekh  N.  Waste in the US health care system: estimated costs and potential for savings.   JAMA. 2019;322(15):1501-1509. doi:10.1001/jama.2019.13978PubMedGoogle ScholarCrossref
Cutler  D.  Building health care better means reining in costs.   JAMA Health Forum. Published online January 28, 2021. doi:10.1001/jamahealthforum.2021.0117Google Scholar
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