Private equity acquisitions of hospitals and the changing landscape of care for patients with gastrointestinal cancer

Abstract

Background

The growing presence of private equity (PE) in the United States (U.S.) healthcare raises concern about access, costs, care quality, and outcomes. This study explores the specific impact of PE-owned hospitals on gastrointestinal (GI) cancer care.

Methods

Patients undergoing GI cancer surgery were identified from the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database (2012–2020). Propensity score matching compared PE and non-PE hospitals. Difference-in-difference and multivariable models evaluated GI surgical outcomes, adjusting for patient and hospital-level characteristics.

Results

Among 1,887 GI cancer patients (hepatopancreatic: n=127, 6.7%; colorectal: n=1,760, 93.3%), the majority were male (n=1,030, 54.6%), White (n=1,526, 80.9%), with early-stage disease (stage I/II: n=1,009, 54%) and a median age of 75 [interquartile range (IQR), 70–82] years. Surgeries at PE-owned hospitals comprised 31.7% (n=599). Compared to non-PE hospitals, patients treated at PE-owned centers were more often Black (18.7% vs. 12.1%), socioeconomically vulnerable (48.4% vs. 36.1%), and had early-stage cancer (57.1% vs. 52.5%) (P<0.05). PE ownership correlated with reduced clinical staffing (physicians: −19; nurses: −43), fewer Medicaid patients (−194), and lower surgical costs (−$341) (all P<0.05). Hospital-acquired infections rose post-acquisition (30.4% to 43.7%, P=0.02), while non-PE hospitals maintained lower rates (11.2% to 19.6%, P<0.001). The risk of perioperative-complications [risk ratio (RR) =0.80; 95% confidence interval (CI): 0.54–1.20], hospital-acquired infections (RR =0.77; 95% CI: 0.37–1.63), and 90-day-mortality (RR =1.27; 95% CI: 0.60–2.66) were comparable at PE-acquired versus non-acquired hospitals.

Conclusions

PE hospital acquisitions reduce staffing, limit Medicaid patient’s access, and increase infection risks—underlining the need to protect equity and quality in GI cancer care.

Highlight box.

Key findings

• Private equity (PE) ownership of hospitals was associated with significant changes in gastrointestinal (GI) cancer care delivery. Compared to non-PE hospitals, PE-acquired hospitals had fewer clinical staff, reduced Medicaid patient access, and increased hospital-acquired infection rates post-acquisition. However, perioperative complications and short-term mortality were comparable between PE and non-PE hospitals.

What is known and what is new?

• PE investment in the United States healthcare has grown rapidly, raising concerns about its impact on care quality, costs, and patient outcomes. Prior studies have focused largely on financial performance and staffing changes, with limited evidence on cancer care outcomes.

• This study is among the first to examine the effect of PE hospital ownership on GI cancer surgery outcomes using Surveillance, Epidemiology, and End Results-Medicare data. We found that PE acquisitions were linked to reduced staffing and increased infection rates, while surgical complications and mortality remained similar. These findings highlight nuanced effects of PE ownership beyond financial metrics.

What is the implication, and what should change now?

• The results underscore the need for policy oversight to ensure that PE-driven operational changes do not compromise patient safety and equity in cancer care. Regulatory bodies should monitor staffing levels and infection control practices post-acquisition. Additionally, transparency in ownership and quality reporting should be mandated to safeguard vulnerable populations and maintain care standards.

Introduction

Healthcare delivery in the United States (U.S.) operates within a highly complex, and decentralized framework, encompassing multiple stakeholders, including public programs such as Medicare, Medicaid, private sector entities, employer-sponsored insurance, and direct out-of-pocket payments (1-3). This multifaceted structure contributes to significant variability in healthcare access, expenditures, quality of care, and patient outcomes, often reinforcing disparities across geographic and socioeconomic groups (1-3). While reforms like value-based care and patient-centered models have gained traction in addressing these systematic challenges, the landscape continues to reshaped by the increasing influence of private sector investment (4,5). PE firms have emerged as dominant players health care financing and infrastructure (4,5). Over the past two decades, PE investment in healthcare has surged, culminating in nearly $200 billion devoted to hospital acquisitions in 2021 alone (6,7). This expansion reflects a strategic investment model built on “anchor assets” and a business orientation centered on optimizing financial returns (8). Despite these trends, concerns have persisted over the potential misalignment between profitability and care quality, particularly for medically complex patients, including those requiring surgical intervention (9,10). This underscores a growing need to examine the broader implications of PE acquisitions for clinical practice, health equity, providers, and policymakers. In this context, PE ownership represents a complex phenomenon that may introduce both potential efficiencies and risks, with outcomes varying across financial, staffing, and clinical domains.

Although the stated intent PE acquisition is to enhance efficiency and streamline administrative operations, mounting evidence raises concerns that financial objectives may supersede commitments to care quality (8-10). These concerns are even more relevant in surgical oncology, where patients often present with multifaceted care needs and require integrated, multidisciplinary management. Existing literature on the clinical impact of PE acquisition offers mixed findings (11). For instance, Cerullo et al. reported no deterioration in outcomes following PE acquisition of ambulatory surgery centers (12). In contrast, Williams et al. found that patients undergoing thoracic procedures at PE-owned facilities experienced lower quality of care compared to those at non-acquired centers (13). Such divergent findings highlight the nuanced, context-dependent effects of PE ownership, which may vary across settings, specialties, and outcome metrics (11,14-17).

Patients with cancer, especially those diagnosed with gastrointestinal (GI) malignancies, constitute a substantial proportion of the surgical population and typically require resources-intensive and highly coordinated, treatment pathways. This patient subgroup may be especially vulnerable to administrative restructuring and cost-reduction strategies following PE acquisition. Despite PE’s growing presence in healthcare, limited empirical research has examined its effects on patient outcomes and healthcare resource utilization among individuals with GI cancer undergoing surgery. Accordingly, the present study seeks to address this gap by evaluating the association between PE hospital ownership and postoperative clinical and financial outcomes within this high-need population. We present this article in accordance with the STROBE reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-702/rc).

Methods

Study design, cohort selection and data sources

Patients who were 65 years of age or older and underwent GI cancer surgery between 2012 and 2020 were identified from the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database (18). GI cancers were defined as hepatopancreatic (HP) or colorectal cancer using International Classification of Diseases (ICD), ninth and tenth edition codes (19). Patients who were continuously enrolled in Medicare Part A and B for at least a year before and after the cancer diagnosis were considered. However, patients who were enrolled in health maintenance organization (HMO), and those with incomplete demographic or hospital-level data were excluded. Hospitals with incomplete reporting of cost or staffing data were also excluded. The final analytic cohort included 1,887 patients across 1,048 hospitals. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Hospitals were classified as either PE-owned or non-PE hospitals based on available ownership records (without stratification by degree of control) from the Private Equity Hospital Tracker, the Center for Medicaid and Medicare services (CMS) change of ownership (CHOW) database, and the Agency for Healthcare Research and Quality (AHRQ) Compendium of the U.S. health systems (7,20,21). The Private Equity Hospital Tracker database is maintained by the Private Equity Stakeholder Project and catalogs information on PE-owned health centers across the U.S. (7). This was further supplemented with the AHRQ compendium that provides information on ownership status of health systems defined as having at least one acute care hospital and one physician group (21). The CMS CHOW database offered detailed records of hospital ownership changes, including transaction dates with seller/buyer information. Cost-to-charge ratio (CCR) data were obtained from the Hospital Cost Tool (HCT), maintained by the National Academy for State Health Policy (20). Subsequently, these data sources were merged with the SEER-Medicare linked database to analyze the impact of PE acquisition on clinical outcomes (18). In accordance with SEER-Medicare’s data use agreement, counts fewer than 11 were censored during reporting. The Institutional Review Board at Ohio State University approved this study and waived the requirement for informed consent, because the data were limited.

Covariates

Patient-level variables included age, sex, race/ethnicity [White, Black, Hispanic, or other (i.e., Asian, American Indian, or Alaska Native)], cancer type, disease stage, year of diagnosis, residential area (urban or rural), admission type (urgent or elective), Charlson comorbidity index (CCI), and county-level Social Vulnerability Index (SVI) (Table 1). Sex was predefined in the SEER-Medicare database as male or female based on sex assigned at birth. The CCI is a widely used tool to stratify patients into low (CCI ≤2) and high comorbidity (CCI >2) groups based on their baseline comorbidities, consistent with previous validation studies (22). The SVI, a composite indicator of socioeconomic and demographic vulnerability, incorporates metrics such as income, education, housing, and transportation access. Patients were categorized into high or low SVI groups using the median value for their county-level index score (23,24). Patients with incomplete demographic or hospital-level data were excluded. For variables with <5% missingness, imputation was performed using the median (continuous variables) or mode (categorical variables). Hospital-level variables included CMS geographic region, procedure volume, teaching status, disproportionate share hospital payment status, accreditation status, total bed count, and staffing capacity measured by full-time equivalent (FTE) physicians and nurses. Hospital volume was defined as the average annual number of cancer-specific procedures performed annually by each institution over the study period.

Table 1. Baseline characteristics of patients.

Characteristics	Total	Private equity	Non-private equity	P value
Number	1,887	599 (31.7)	1,288 (68.3)	–
Age (years)	75 [70, 82]	75 [70, 81]	75 [70, 82]	0.77
Sex				0.92
Female	857 (45.4)	271 (45.2)	586 (45.5)
Male	1,030 (54.6)	328 (54.8)	702 (54.5)
CCI				0.12
≤2	1,596 (84.6)	518 (86.5)	1,078 (83.7)
>2	291 (15.4)	81 (13.5)	210 (16.3)
Race				0.001
White	1,526 (80.9)	462 (77.1)	1,064 (82.6)
Black	268 (14.2)	112 (18.7)	156 (12.1)
Hispanic	60 (3.2)	18 (3)	42 (3.3)
Other	33 (1.7)	7 (1.2)	26 (2.0)
Metro				0.21
Rural	417 (22.1)	143 (23.9)	274 (21.3)
Urban	1,470 (77.9)	456 (76.1)	1,014 (78.7)
Region
Midwest	50 (2.6)		50 (3.9)	<0.001
Northeast	166 (8.8)	53 (8.8)	113 (8.8)
South	482 (25.5)	117 (19.5)	365 (28.3)
West	1,189 (63.0)	429 (71.6)	760 (59)
SVI				<0.001
Low	676 (35.8)	146 (24.4)	530 (41.1)
Moderate	456 (24.2)	163 (27.2)	293 (22.7)
High	755 (40.0)	290 (48.4)	465 (36.1)
Cancer site				<0.001
Colon	1,504 (79.7)	441 (73.6)	1,063 (82.5)
Rectum	256 (13.6)	86 (14.4)	170 (13.2)
HPB	127 (6.7)	72 (12.0)	55 (4.3)
Stage of disease				0.007
I	429 (23.0)	128 (21.5)	301 (23.6)
II	580 (31.0)	212 (35.6)	368 (28.9)
III	556 (29.7)	177 (29.7)	379 (29.7)
IV	213 (11.4)	49 (8.2)	164 (12.9)
Unknown	91 (4.9)	29 (4.8)	66 (4.9)
Urgent				<0.001
No	1,189 (63.1)	411 (68.6)	778 (60.5)
Yes	695 (36.9)	188 (31.4)	507 (39.5)

Data are presented as median [interquartile range] or n (%). HPB cancers include malignancies affecting the liver, pancreas, and biliary system. CCI, Charlson comorbidity index; HPB, hepatopancreatobiliary; SVI, Social Vulnerability Index.

Outcome of interest, and measures

The primary outcomes of interest were categorized into three domains: health workforce, hospital finance, and service delivery. These three categories aligned with core components of the World Health Organization (WHO) health system building blocks (25). The health workforce domain was defined by the number of employed physicians and registered nurses at each hospital. Hospital finance encompassed operational expenses, CCR, hospital operational costs per adjusted discharge, and direct labor cost for patient care. Additionally, detailed expenditures related to index surgeries were examined, including operating room charges, medical supply expenses, and intensive care unit (ICU)-related costs (Table S1). Service delivery was assessed using quality indicators such as hospital acquired infections (HAIs), all-cause 90-day mortality, 90-day readmission, peri-operative complications, extended length of stay (LOS), and fragmented care (Table S2). Additionally, the total number of annual patients discharged including both Medicare and Medicaid discharges were examined.

Statistical analysis

Descriptive statistics were presented as medians with interquartile ranges (IQRs) for continuous variables and frequencies (percentages) for categorical variables. Group differences at baseline differences were assessed using the Kruskal-Wallis test for continuous variables and the Chi-squared or Fisher exact test for categorical variables. To minimize confounding effects related to hospital characteristics, propensity score matching (PSM) was performed using a greedy nearest-neighbor approach with caliper width of 0.15. The PE-acquired hospitals were matched to non-PE acquired hospitals in a 1:3 ratio based on hospital-level volume, teaching status, disproportionate share hospital payment, CMS geographic region, bed size, and accreditation status. The acquisition date served as the index date for PE hospitals; corresponding matched non-PE acquired hospitals were assigned the same index date to allow temporal comparisons. Matching quality was evaluated using standardized mean differences (<0.1) and significance testing (P>0.05).

Multivariable regression models were used to examine associations between PE ownership and changes in outcomes, adjusting for patient-level variables including age, sex, CCI, cancer type, admission type, and year of admission. Generalized estimating equations (GEEs) accounted for hospital level clustering, ensuring robust variance estimation across matched hospitals. Adjusted difference-in-differences (DIDs) models were applied to evaluate the impact of PE acquisition on service delivery outcomes, including HAIs, perioperative complications, extended LOS, 90-day readmissions, and 90-day mortality (26).

Financial outcomes, including total charges and cost center-level expenses for GI cancer surgeries, were examined using Wilcoxon rank-sum tests and multivariable models. Analysis of covariance (ANCOVA) models were specifically used to assess changes in hospital charges and discharge counts (Medicare and Medicaid) before and after PE acquisition, controlling for patient-specific factors. All statistical analyses were conducted using SAS version 9.4 and R version 4.2.0, with a two-sided significance threshold of P<0.05.

Results

Baseline characteristics of the study cohort

The matched cohort included 1,887 patients who underwent GI surgery for malignant indication, comprising (HP: n=127, 6.7%; colorectal: n=1,760, 93.3%), most individuals were male (n=1,030, 54.6%) and White (n=1,526, 80.9%), had low CCI score (i.e., ≤2) (n=1,596, 84.6%) with a median age of 75 (IQR, 70–82) years (Table 1). Most patients resided in metropolitan areas (n=1,470, 77.9%), particularly within the West region (n=1,189, 63%) of the U.S. Similarly, most patients lived in socially vulnerable communities (n=755, 40%) and underwent an elective surgical procedure (n=1,189, 63.1%), and treated for stage II cancer (n=580, 31%). Overall, 31.7% (n=599) of patients underwent surgery at PE acquired hospitals, whereas 1,288 (68.3%) were treated at non-PE hospitals.

Patients treated at PE-acquired hospitals were more likely to be Black (18.7% vs. 12.1%; P<0.001) and more frequently underwent non-urgent surgical procedures (68.6% vs. 60.5%; P<0.001). No significant differences were observed between PE and non-PE hospital cohorts in terms of sex (male: 45.2% vs. 45.5%), age (both medians: 75 years, IQR, 70–82 years), or baseline comorbidity status (CCI >2: 13.5% vs. 16.3%) (all P>0.052). However, PE hospitals were more likely to serve patients from highly vulnerable communities (SVI: 48.8% vs. 36.1%) and the western region (71.6% vs. 59%) with stage II cancer (35.6% vs. 28.9%) (all P<0.054).

Hospital characteristics

Among 1,048 hospitals, 15 (1.4%) were PE-owned, with the remaining 1,033 (98.6%) classified as non-PE institutions (Table 2). Prior to matching, notable differences were observed between the two groups. PE-owned hospitals were less likely to be teaching institutions (40% vs. 44.5%), and more often categorized as low- or medium-volume facilities (80% vs. 78.7%). They also received higher disproportionate hospital (DSH) payments (93.3% vs. 78%) and were more likely to originate as non-profit organizations (60% vs. 59%). PE hospitals exhibited geographic clustering in cities such as Boston, Atlanta, Dallas, and San Francisco, whereas non-PE hospitals were more widely distributed across eight of the 10 CMS regions. Despite these differences, accreditation status and urban location were comparable between groups. Following PSM, 15 PE hospitals were paired with 41 non-PE counterparts, eliminating significant differences in hospital-level characteristics.

Table 2. Hospital basic characteristics before and after matching.

Characteristics	Hospital characteristics before matching				Hospital characteristics after matching
	Private equity	Non-private equity	P value		Private equity	Non-private equity	P value
Number	15 (1.5)	1,033 (98.5)	–		15 (26.7)	41 (73.2)	–
Location			–				–
Urban	15 (100.0)	1,033 (100.0)			15 (100.0)	41 (100.0)
Teaching			–				0.69
Yes	CMS	460 (44.5)			CMS	14 (34.1)
Hospital volume			0.50				0.97
Low	CMS	820 (78.7)			12 (80.0)	33 (80.5)
Medium	CMS	149 (14.3)			CMS	8 (19.5)
High	–	73 (7.0)			–	–
Accredited status			0.97				0.92
No	CMS	620 (59.5)			CMS	24 (58.5)
Yes	CMS	422 (40.5)			CMS	17 (41.5)
Disproportionate share			0.15				0.93
Yes	14 (93.3)	806 (78.0)			14 (93.3)	38 (92.7)
Ownership status			0.07				0.17
Non-profit	CMS	727 (69.7)			CMS	26 (63.4)
For-profit	CMS	70 (6.7)			CMS	3 (7.3)
Government	–	245 (23.6)			–	12 (29.2)
CMS region code			<0.001				0.99
Boston	CMS	39 (3.7)			CMS	9 (22.0)
New York	–	84 (8.1)			–	–
Philadelphia	–	50 (4.8)			–	–
Atlanta	CMS	232 (22.3)			CMS	17 (41.5)
Chicago	–	90 (8.6)			–	–
Dallas	CMS	108 (10.4)			CMS	9 (22.0)
Kansas City	–	102 (9.8)			–	–
Denver	–	34 (3.3)			–	–

Data are presented as n (%). As per CMS reporting guidelines, private equity specific values less than 11 are not reported. CMS, Center for Medicare and Medicaid services.

Change in staffing levels and hospital discharges

Among PE-acquired hospitals, the median number of FTE physicians (before acquisition: 1.0, IQR, 0–5.0 vs. after acquisition: 1.0, IQR, 0–5.0; P=0.81) and registered nurses (before acquisition: 213, IQR, 150–324 vs. after acquisition: 213, IQR, 150–311; P=0.73). In contrast, non-PE hospitals showed a significant increase in the number of FTE registered nurses: 244, IQR, 122–405 before vs. 267, IQR, 122–433 after, P=0.040) during the same period (Figure 1A). Total number of hospital beds increased modestly in both PE (155, IQR, 102–274, before vs. 175, IQR, 123–274, after, and non-PE: 200, IQR, 118–276, before vs. 209, IQR, 118–276, after, P=0.82) hospitals. Similarly, PE-acquired facilities showed a decrease in inpatient discharges reimbursed by Medicare and Medicaid following acquisition. Specifically, the median number of Medicare discharges decreased from 2,275 (IQR, 1,183–3,693) to 1,810 (IQR, 920–2,535) after acquisition (P=0.52), and Medicaid discharge dropped significantly from 838 (IQR, 669–1,552) to 546 (IQR, 202–956) post-acquisition (P<0.001) (Figure 1B). By comparison, non-PE hospitals saw a minimal change in Medicare discharges over the same period with a median of 3,137 (IQR, 2,230–4,816) before acquisition and 3,095 (IQR, 1,829–3,095) after, P=0.52 (Table 3).

Figure 1.

Overtime change in (A) adjusted mean number of registered nurses and (B) adjusted number of Medicaid insured patients discharged at private equity acquired and non-acquired health centers. PE, private equity.

Table 3. Comparison of staffing levels in PE and non-PE hospitals.

Indicator	PE hospital (n=15)†			Non-PE hospital (n=41)†			ANCOVA model
	Before acquisition	After acquisition		Before acquisition	After acquisition		PE, coefficients (95% CI)	P value
No. of physicians	1.0 (0, 5.0)	1.0 (0, 5.0)		1.5 (0, 13)	2.0 (0, 15)		−19 (−29, −9)	<0.001
No. of RN	213 (150, 324)	213 (150, 311)		244 (122, 405)	267 (122, 433)		−43 (−86, −1)	0.046
No. of hospital beds	155 (102, 274)	175 (123, 274)		200 (118, 276)	209 (118, 276)		1 (−8, 10)	0.82
No. of patients discharged	6,466 (2,776, 10,876)	5,825 (2,530, 13,445)		8,271 (4,676, 15,803)	9,274 (4,077, 16,004)		49.7 (−833, 932)	0.91
Medicare discharges	2,275 (1,183, 3,693)	1,810 (920, 2,535)		3,137 (2,230, 4,816)	3,095 (1,829, 3,095)		105 (−213, 424)	0.52
Medicaid discharges	838 (669, 1,552)	546 (202, 956)		599 (148, 1,604)	613 (179, 1,602)		−194 (−287, −101)	<0.001

^†, data are presented as median (interquartile range). ANCOVA, analysis of covariance; CI, confidence interval; PE, private equity; RN, registered nurses.

Many hospitals targeted by PE were already underperforming in staffing levels prior to acquisition. A comparison of registered nurse counts in healthcare facilities over a 6-year period—3 years before and 3 years after PE acquisition—shows that non-PE facilities consistently maintain higher staffing levels, averaging 275–290 nurses with minimal fluctuation. In contrast, PE-acquired facilities begin with fewer nurses, approximately 200–220, and exhibit only a modest increase post-acquisition. These facilities remain below non-PE levels, highlighting persistent disparities in nurse availability between PE and non-PE hospitals both before and after acquisition (Figure 2).

Figure 2.

Number of registered nurses in healthcare facilities before and after PE acquisition. PE, private equity.

Multivariable modeling demonstrated significantly lower staffing levels at PE hospitals over time, with reductions in FTE physicians [−19, 95% confidence interval (CI): −29 to −9; P<0.001] and registered nurses (43, 95% CI: −86 to −1; P<0.053). These estimates reflect adjusted DID results, and are displayed in Figure 2 to illustrate pre- and post-acquisition trends. Medicaid patients discharges were also lower in PE facilities (average difference: −94 per hospital; 95% CI: −287 to −101; P<0.001). On the other hand, the total number of hospital beds remained relatively stable following PE acquisition (coefficient: 1; 95% CI: −8 to 10; P=0.82). In addition, Medicare discharges showed no significant changes post-acquisition (coefficient: 105; 95% CI: −213 to 424; P=0.52). The decline in total discharges in PE hospitals was not statistically significant in multivariable model (coefficient: 49.7; 95% CI: −833 to 932; P=0.91) (Table 3).

Comparison of financial outcomes among PE acquired and non-acquired hospitals

Financial comparisons showed PE hospitals experienced declines in several key metrics following acquisition (Table S1). Operational costs decreased from $180 million (IQR, $87–$259 million) to $155 million (IQR, $81–$189 million), and direct patient care labor costs fell from $54 million (IQR, $26–$67 million) to $47 million (IQR, $22–$63 million). The CCR declined from 0.24 (IQR, 0.18–0.31) to 0.20 (IQR, 0.15–0.24). Operational cost per adjusted discharge dropped from $8,343 (IQR, $7,629–$12,372) to $7,613 (IQR, $6,645–$9,913). In contrast, non-PE hospitals experienced increases in all four metrics. Multivariable analysis confirmed significant reductions in operating costs (−$12.39 million; 95% CI: −12.40 to −12.38; P<0.001), adjusted discharge costs (coefficient: −$341; 95% CI: −$398 to −$285; P<0.001), and direct patient care labor costs (−$2.99 million; 95% CI: −2.98 to −3.0; P<0.001) among PE-owned hospitals (Table S1). Index surgical charges rose at both PE and non-PE hospitals, with operating room charges increasing in PE hospitals from $23,186 (IQR, $14,662–$40,433) to $27,599 (IQR, $17,417–$42,927; P=0.051) and in non-PE hospitals from $20,039 (IQR, $13,676–$29,862) to $25,679 (IQR, $17,255–$36,500; P<0.001). Medical supplies charges remained stable across both groups. The further breakdown of cost to charge ratio for index surgical procedure is outlined in Table S1.

However, non-PE hospitals also experienced an increase in median charges from $20,039 (IQR, $13,676–$29,862) to $25,679 (IQR, $17,255–$36,500) in the same period (P<0.001). Similar trends were observed in medical supplies charges in PE and non-PE hospitals [$8,794 (IQR, $5,734–$13,922) before PE acquisition to $8,860 (IQR, $5,162–$16,388) after PE acquisition (P=0.57); non-PE: $9,569 (IQR, $6,355–$13,379) before PE acquisition to $9,475 (IQR, $6,488–$12,759) after PE acquisition (P=0.53)].

Comparison of short-term health outcomes among PE acquired and non-acquired hospitals

Short-term health outcomes varied post-acquisition. Fragmented care rates dropped in PE hospitals from 28% to 21.6%, preoperative complications declined from 20.9% to 15.8%, and 90-day readmissions fell from 26.8% to 23.4%. However, HAIs rose sharply from 30.4% to 43.7% (P=0.02), LOS extended to 19.6%, and postoperative mortality increased from 9.5% to 13.3%. Non-PE hospitals also saw an uptick in HAIs (from 11.2% to 19.6%; P<0.001), while readmission and mortality rates remained statistically unchanged. Despite modest improvements in select indicators, the substantial increase in HAIs and mortality in PE hospitals raises questions about the clinical impact of PE ownership on surgical outcomes.

Multivariable analysis on short-term health outcomes among PE-acquired and non-acquired health centers showed no significant differences. Fragmented care rates [PE vs. non-PE centers: risk ratio (RR) =1.26; 95% CI: 0.79–2.04]; preoperative complications (PE vs. non-PE centers: RR =0.80; 95% CI: 0.54–1.20), HAIs (PE vs. non-PE centers: RR =0.77; 95% CI: 0.37–1.63), 90-day readmissions (PE vs. non-PE centers: RR =0.90; 95% CI: 0.61–1.35), 90-day mortality (PE vs. non-PE centers: RR =1.27; 95% CI: 0.60–2.66), or extended LOS (PE vs. non-PE centers: RR =0.91; 95% CI: 0.67–1.23) (all P>0.053) (Table S2).

Discussion

A recent increase in PE investments is transforming the landscape and dynamics of the U.S. healthcare (3,5,7,11,25). The primary goal of PE acquisition is to increase the profitability and operational efficiency of health centers, with the intent to sell them at a higher market multiple, typically within 3 to 7 years, for substantial financial return (27,28). Profitability is typically increased by streamlining hospital operations, leveraging economies of scale, and expanding service lines (27,28). However, there are concerns that changes in administrative structure that are primarily driven by the goal to maximize capital returns may compromise the focus on patient care. There is conflicting evidence of the impact of PE acquisition on patient outcomes with varying impact noticed among different patient populations (29-31). The impact of acquisition is even more relevant among patients with complex care needs such as surgical patients with underlying cancer (32,33). The current study is important as it focused on surgical patients with GI cancer, who represent a remarkable proportion of all surgical patients and are particularly vulnerable to policy changes and shifts in care delivery models. Of note, this study demonstrated that PE-acquired hospitals, compared to non-acquired hospitals, were associated with a reduction in overall hospital operational costs by $12 million and in direct patient care hospital labor costs by approximately $3 million. This reduction was associated with fewer employed physicians (number of physicians: −19; 95% CI: −29 to −9) and nurses (no. of registered nurses: −43; 95% CI: −86 to −1) over time in PE compared to non-acquired hospitals. Of note, the odds of adverse surgical outcomes, for instance perioperative complications and 90-day mortality were comparable among patients who underwent surgery at private acquired versus non-acquired centers. However, hospitals acquired by PE may already be underperforming prior to acquisition, which complicates attribution of observed changes solely to ownership effects (34,35).

Hospitals located in socially vulnerable communities often lack capital and have operational challenges (36). Similarly, the hospitals serving vulnerable patient population (i.e., Medicaid/uninsured patients) often receive government benefits such DSH payments to offset financial shortfalls (37). Such characteristics can present a lucrative investment opportunity for PE firms to apply their “fix and flip” strategy, and can help aim for quicker, profitable returns with relatively lower capital investment. Similarly, the availability of backup revenue stream (i.e., federal or state bailouts) helps cushion financial volatility and mitigate investment risks. Interestingly, the current study demonstrated that patients from the socially vulnerable communities were more often treated PE-acquired hospitals compared to non-acquired centers (48.4% vs. 36.1%). The higher presence of PE-acquired centers in underserved areas is often viewed as a way to increase healthcare access for underprivileged populations but concerns remain that such acquisitions may paradoxically erode access to care. It is important to note that although the majority of PE-acquired hospitals in the current study were Disproportionate Share Hospitals, the proportion of Medicaid patients declined over time at PE-acquired centers compared to non-acquired hospitals. These trends may reflect incentives for hospitals to prioritize commercially insured patients over those who are uninsured or covered by Medicaid. According to a report by Medicaid and CHIP Payment and Access Commission (MACPAC), DSH payments often go towards offsetting Medicaid shortfalls but do not obligate hospitals to maintain Medicaid patient volumes (38). As such, the policies must be carefully structured and monitored to ensure they fulfill their intended purpose of expanding patient access to care rather than being leveraged primarily for business gains.

Proponents of PE acquisition often believe in the cost-effectiveness models inculcated following acquisition (29-31). The current study also demonstrated that operational expenses were lowered (−$12.39; 95% CI: −$12.40 to −$12.38) over time compared to non-acquired centers. However, the more pressing question is how these cost reductions are actually achieved. While PE firms often attribute savings to economies of scale and streamlined operational logistics, others argue that cost cuts may stem from reductions in human resources and clinical workforce (27,28). Interestingly, the current study found that the number of employed physicians (−19; 95% CI: −29 to −9) and nurses (−43; 95% CI: −86 to −1) declined over time at PE-acquired hospitals compared to non-acquired centers. This trend was reinforced by a corresponding decrease in direct patient care hospital labor costs (−$2.99; 95% CI: −$3.00 to −$2.98). These findings were consistent with other studies that reported worse nurse to bed ratio among PE acquired compared to non-acquired centers (39). Of note, PE-acquired hospitals billed roughly four times the actual cost of patient care (CCR: 0.20; 95% CI: 0.15–0.24) and this CCR was comparable to that of non-acquired centers. These findings indicate an association profitability in PE-acquired hospitals can be largely driven by cost reductions through decreased staffing relative to operational innovations. Of note, patients are not seeing any corresponding benefits in the billing with comparable cost to charge ratio among patients treated at PE versus non-acquired centers irrespective of these cuts in workforce. In fact, there are concerns that reductions in nursing or physician staffing could be associated with unmet surgical goals for patients, potentially resulting in indirect financial or health burdens (40). These insights underscore the urgent need to scrutinize not only how PE firms pursue profitability but also to establish boundaries on which cost-saving strategies are acceptable.

Changes in administrative structures following acquisitions may be associated with differences in clinical outcomes. However, this impact is highly variable and can vary among different patient populations. This can be due to the fact that dedicated specialties with more coherent team structure can mitigate the impact of operational changes. Consequently, there is conflicting evidence of impact of PE acquisition on patient outcomes in different reports. For instance, Bruch et al. demonstrated that hospitals acquired by PE firms showed modest enhancements in quality metrics related to cardiopulmonary conditions such as pneumonia and acute myocardial infarction (41). However, another report by Gupta et al. demonstrated that PE acquisitions of nursing homes were associated with higher short-term mortality rates and a simultaneous drop in indicators of patient well-being (42). Similarly, studies among patients undergoing major cardiothoracic surgical procedures such as coronary artery bypass grafting or lung resection at PE acquired centers demonstrated relatively higher odds of surgical complications compared to those who underwent procedures at non-acquired centers (13,39,43). Interestingly, the current study with a primary focus on patients with cancer demonstrated no differences in surgical outcomes over time among those treated at PE-acquired versus non-acquired centers. This finding may be attributed to the inherent complexity of cancer surgery which often rely on highly coordinated and multidisciplinary care teams with well-established perioperative protocols. Such structured clinical environments may buffer the influence of administrative restructuring on patient outcomes. As such, these results underscore the importance of recognizing that the effects of PE acquisition are not uniform across all clinical settings or patient populations. Policymakers and stakeholders should avoid “one-size-fits-all” assumptions and instead consider tailored evaluations for each patient population. Reports from different patient populations can be utilized as case studies that may offer a more nuanced understanding of the risks versus benefits of PE ownership. These findings should be interpreted as associations rather than causal effects, and in some cases financial restructuring under PE ownership may have preserved access or improved efficiency in hospitals that were otherwise at risk of closure. While our DID analyses demonstrated reductions in staffing and Medicaid discharges, other outcomes such as operational costs, readmissions, and mortality remained stable or modestly improved, underscoring that PE ownership may also be interpreted as achieving comparable efficiency even if such gains come at the expense of workforce or equity. This will ultimately support a more well-informed and patient-centered policy decisions.

Interpretation of findings should consider several limitations. The SEER-Medicare database primarily captures older adults (aged 65–99 years), which can limit generalizability to younger patient populations. Administrative datasets like Medicare rely on ICD codes that are susceptible to data entry errors, and potential underreporting of complications. This may induce misclassification bias; however, the database has been validated in multiple prior studies that focused on clinical outcomes. Additionally, reliance on hospital-reported cost data (e.g., the HCT) may compromise accuracy, as these sources are subject to reporting variability and may not fully reflect operational realities under PE ownership. The retrospective study design precludes establishing causal relationships; our findings should be interpreted as associations rather than direct effects of PE acquisition. The current study incorporated a robust statistical methodology of PSM and adjusted DID analyses, yet residual confounding remains. Moreover, hospitals acquired by PE may already be underperforming prior to acquisition, with baseline vulnerabilities in staffing, financial performance, or infection control. As such, reverse causation represents a major limitation of this study, and future research should incorporate longer pre‑acquisition trend analyses to better isolate causality. Finally, the binary PE versus non-PE classification oversimplifies a heterogeneous exposure, as data on degree of ownership, time since acquisition, and management control were unavailable and thus could not be incorporated.

Conclusions

PE acquisition was associated with significant operational and equity-related changes in GI cancer care, including reduced clinical staffing, lower Medicaid discharge rates, and increased presence in socially vulnerable communities. While PE-owned hospitals achieved lower operational costs, these savings appeared to stem from staffing reductions rather than improved efficiency, and CCRs remained unchanged, suggesting limited financial benefit for patients. Importantly, surgical outcomes such as complications, readmissions, and mortality were comparable between PE and non-PE hospitals, indicating that the impact of PE ownership is not uniform across all clinical domains. Reverse causation remains a limitation, as many acquired hospitals may have been underperforming prior to acquisition. Future research should incorporate longer pre-acquisition trend analyses to better isolate causality. Overall, these findings underscore the need for targeted policy oversight to balance financial incentives with equity and quality in cancer care.

Supplementary

The article’s supplementary files as

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.