Key Points
Question
Is hospital financial distress associated with the receipt of immediate breast reconstruction after mastectomy for the treatment of ductal carcinoma in situ?
Findings
In this cohort study of 5760 women with ductal carcinoma in situ who underwent mastectomy, women treated at hospitals under high financial distress and medium financial distress were significantly less likely to receive breast reconstruction surgery than women treated at hospitals with low to no financial distress.
Meaning
A greater understanding of the association between hospital financial stress and the delivery of cancer services is needed to better guide policy and patient care.
Abstract
Importance
Hospital financial distress (HFD) is a state in which a hospital is at risk of closure because of its financial condition. Hospital financial distress may reduce the services a hospital can offer, particularly unprofitable ones. Few studies have assessed the association of HFD with quality of care.
Objective
To examine the association between HFD and receipt of immediate breast reconstruction surgery after mastectomy among women diagnosed with ductal carcinoma in situ (DCIS).
Design, Setting, and Participants
This retrospective cohort study assessed data from the Nationwide Inpatient Sample of 5760 women older than 18 years (mean [SD] age: 57.5 [13.2]) with DCIS who underwent mastectomy in 2008-2012 at hospitals categorized by financial distress. Women treated at 1156 hospitals located in 538 different counties across Arkansas, Arizona, California, Colorado, Connecticut, Florida, Iowa, Kentucky, Massachusetts, Maryland, Missouri, North Carolina, New Hampshire, New Jersey, Nevada, New York, Oregon, Pennsylvania, Rhode Island, Utah, Virginia, Vermont, Washington, Wisconsin, West Virginia, and Wyoming were included. Of these, 2385 women (41.4%) underwent immediate breast reconstruction surgery. Women with invasive cancer were excluded. The database included unique hospital identification variables, and participants were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Data were analyzed from January 1, 2012, to February 28, 2014.
Main Outcomes and Measures
The primary outcome was the adjusted association between HFD and receipt of immediate breast reconstruction surgery after mastectomy.
Results
In this analysis of database information, 2385 of 5760 women (41.4%) received immediate breast reconstruction surgery. Of these, 693 (36.7%) were treated at a hospital under high HFD and received immediate breast reconstruction surgery compared with 863 (44.0%) treated at a hospital under low HFD (P < .001). Reconstruction surgery was associated with younger age, white race, private insurance, treatment at a teaching and cancer hospital, private hospital ownership, and the percentage of individuals in the county with insurance. After adjustment, women treated at hospitals under high HFD (OR, 0.79; 95% CI, 0.62-0.99) and medium HFD (OR, 0.76; 95% CI, 0.61-0.94) were significantly less likely to receive reconstruction than women treated at hospitals with low to no HFD.
Conclusions and Relevance
The financial strength of the hospital where a patient receives treatment is associated with receipt of immediate breast reconstruction surgery. In addition to focusing on patient-related factors, efforts to improve quality should also focus on hospital-related factors.
This cohort study uses data from several large databases to examine the association between hospital financial distress and immediate breast reconstruction surgery after mastectomy among women diagnosed with ductal carcinoma in situ.
Introduction
The clinical guidelines issued by the American Society of Clinical Oncology and the National Initiative for Cancer Care Quality recommend that all women undergoing mastectomy receive information on reconstruction options before they undergo mastectomy. These guidelines are based on studies suggesting that breast reconstruction surgery after mastectomy is associated with long-term benefits, such as increased ratings of self-esteem, body image, and sexual functioning, as well as decreased levels of anxiety and depression. Guidelines for reconstruction are the same for women with ductal carcinoma in situ (DCIS) and invasive breast cancer; both populations should be informed of their options before undergoing a mastectomy.
Previous studies have shown associations between increasing age, black race, being married, rural location, and increased comorbidities and decreased odds of receiving immediate breast reconstruction. In addition, modifiable factors such as insurance status, income level, hospital size, hospital location, and physician volume are associated with receipt of immediate breast reconstruction surgery among women undergoing mastectomy for both DCIS and invasive breast cancer.
Hospitals make choices about which services to offer as well as which type and number of personnel to hire and which capital expenses to prioritize. These choices may be affected by a hospital’s financial condition. A hospital experiencing financial distress may reduce the services it offers, particularly unprofitable services, or encourage physicians to make decisions based on cost. Hospitals can bring in more revenue by prioritizing and performing other more profitable surgical procedures such as cardiothoracic surgery, transplant surgery, and neurologic surgery over breast reconstruction surgery.
While patient financial factors such as insurance type have been associated with receipt of quality health care, only a few studies have evaluated the association of hospital financial condition with the delivery of medical care.
Therefore, the overall aim of this study was to evaluate the extent to which hospital financial distress (HFD) is associated with the receipt of immediate breast reconstruction surgery after mastectomy for the treatment of DCIS. We evaluated only DCIS because women with invasive breast cancer may be advised to delay reconstruction if they require postmastectomy radiotherapy.
Methods
Data Sources
We obtained data from the Nationwide Inpatient Sample (NIS) (patient and hospital-level characteristics between 2004-2008), the Healthcare Cost Report Information System (HCRIS) (hospital-level characteristics), the US Census Bureau (area-level characteristics), and websites maintained by the National Cancer Institute (NCI) and National Comprehensive Cancer Network (NCCN). This study was deemed exempt from the need for approval by the institutional review board of Columbia University, New York, New York, which waived the need for informed patient consent.
Nationwide Inpatient Sample
The NIS is part of the Healthcare Cost and Utilization Project sponsored by the Agency for Healthcare Research and Quality. The NIS approximates a 20% stratified probability sample and is representative of the community hospitals in the United States. Annually, the database captures approximately 2000 inpatient hospital stays for women undergoing mastectomy to treat DCIS and includes basic demographic information and the first 15 procedure and diagnostic codes for each inpatient stay, classified using International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes. Each hospital in the NIS is given a unique identification variable that allows for the calculation of summary statistics based on the discharged patient population from each hospital. In addition, the county, postal code, and address are provided for hospitals as well as the teaching status of the hospital and other hospital-level characteristics. Addresses from this data set were cleaned and geocoded using ArcGIS (version 10; Esri). The cleaned address data were used to link this data set to the HCRIS data set containing information on hospital financial records.
American Community Survey
The American Community Survey is an ongoing survey conducted by the US Census Bureau that provides 1-year, 3-year, and 5-year estimates on socioeconomic characteristics of counties. The estimates were linked to the county identifier provided in the NIS.
Healthcare Cost Report Information System
The HCRIS is a health care cost resource information database compiled by the Centers for Medicare & Medicaid Services from annual reports submitted by Medicare-certified institutional providers. The database provides information on hospital cost reports on a quarterly basis. Data on profit margin (net income divided by total revenues multiplied by 100), a financial factor used to define financial distress, were extracted from the cost report data. This database also provides the address and name of each hospital, which were cleaned, geocoded, and then used to link the hospitals in this data set to the hospitals in the NIS.
National Cancer Institute Cancer Centers
There are 41 comprehensive cancer centers designated by the NCI, some of which are also NCCN institutions. The 41 comprehensive cancer centers are considered by NCI to provide excellent cancer care and treatment. The names and addresses of the 41 comprehensive cancer centers were manually extracted from the NCI website by one of us (C.A.R.) and linked to hospitals in the NIS.
National Comprehensive Cancer Network
The NCCN is an alliance of 27 institutions located throughout the United States that have been designated by the NCI as leaders in cancer treatment and care. The names and addresses of these institutions were manually extracted from the NCCN website by one of us (C.A.R.) and linked to hospitals in the NIS.
Study Sample
Women older than 18 years (mean [SD] age: 57.5 [13.2]) in the NIS with a diagnosis of DCIS (ICD-9-CM code: 233.0) diagnosed between 2004 and 2008, who underwent a mastectomy were included in the cohort. Women with invasive cancer were excluded because the decision-making process with regard to treatment is different for women with invasive cancer, especially stage II or III, than for women with DCIS and the data set did not allow for identification of stage. The types of mastectomy included were subcutaneous (ICD-9-CM procedure codes 85.33-85.36), simple (codes 85.41-85.44), and radical (codes 85.45-85.48). A total of 5760 women treated at 1156 hospitals located in 538 different counties were represented. Women treated in states other than Arkansas, Arizona, California, Colorado, Connecticut, Florida, Iowa, Kentucky, Massachusetts, Maryland, Missouri, North Carolina, New Hampshire, New Jersey, Nevada, New York, Oregon, Pennsylvania, Rhode Island, Utah, Virginia, Vermont, Washington, Wisconsin, West Virginia, and Wyoming were excluded owing to state restrictions.
Definition of Variables
Hospital Financial Distress
The measure of HFD was profit margin, similar to previous research on HFD and patient outcomes. Profit margin is defined as the hospital net income divided by total revenue multiplied by 100. Profit margin was averaged across 3 years and then categorized as low to no financial distress, medium financial distress, and high financial distress based on tertiles of profit margin. The median annual profit margin was also calculated using 3-year means.
Immediate Breast Reconstruction
If a woman had an ICD-9-CM procedure code indicating the insertion of a tissue expander or implant or an ICD-9-CM procedure code indicating that a natural reconstruction was performed, then the woman was classified as having had an immediate breast reconstruction after mastectomy (ICD-9-CM procedure codes 85.33, 85.35, 85.53, 85.54, 85.70-85.76, 85.79, 85.84-85.85, 85.95, 86.70-86.72, 86.74, and 86.75). This classification captures both immediate (ie, 1-stage) reconstruction and immediate-delayed (ie, 2-stage) reconstruction.
Patient Factors
Patient factors included in analyses were race/ethnicity (white, black, Asian, Hispanic, and other), age (18 to <40, 40 to <50, 50 to <65, 65 to <75, and ≥75), and insurance status (private, public, and self-pay).
Additional Hospital Factors
Hospital factors included academic medical center or teaching hospital (yes/no), cancer specialty hospital (ie NCI-designated cancer center) (yes/no), and hospital ownership status (public or private).
County and Region Factors
A dichotomous indicator variable reflecting whether a hospital was located in a county with a high uninsured population (≥75th percentile or <75th percentile) was based on all counties in the sample. Region was defined according to the following 5 designations: Northeast, Midwest, Southeast, Southwest, and West.
Statistical Analysis
First, overall frequencies were calculated for all of the variables as well as frequencies by receipt of immediate breast reconstruction surgery. Variables with respect to receipt of immediate breast reconstruction were calculated using the χ2 statistic to assess unadjusted differences. Next, unadjusted and adjusted 3-level logistic regression models were estimated to account for patient characteristics (level 1), for the clustering of patients within hospitals (level 2), and for clustering of hospitals within counties (level 3). The unadjusted model included dummy variables for profit margin as independent variables. The adjusted model included dummy variables for profit margin, as well as dummy variables for age, race, insurance status, teaching hospital status, public hospital status, cancer center status, and a hospital being located in a county with a high uninsured population. All 3-level logistic regression modeling was performed using the PROC GLIMMIX procedure in SAS (version 9.3; SAS Institute Inc).
Results
The racial demographic of the overall cohort was predominantly white patients (4230 of 5760 [78.0%]) with 460 (8.5%) black patients and 353 (6.5%) Hispanic patients. In addition, 3486 of 5760 patients (60.5%) had private insurance. Overall, 2385 of 5760 of the women (41.4%) diagnosed with DCIS underwent immediate breast reconstruction surgery. There were significant differences in the percentage of women receiving immediate breast reconstruction surgery across the patient and hospital-level variables included in the analyses (Table 1). There was, however, no significant difference in percentage of women receiving immediate breast reconstruction surgery among those living in a county with a high uninsured population vs women not living in a county with a high uninsured population. The median profit margin was calculated across 3 years and then categorized as low to no financial distress (10.24), medium financial distress (4.41), and high financial distress (−0.13).
Table 1. Clinical and Demographic Characteristics of the 5760 Participants.
| Variable | Overall, No. (%) | Receipt of Immediate Breast Reconstruction in 5760 Participants, No. (%)a | P Valueb | |
|---|---|---|---|---|
| Yes (n = 2385) | No (n = 3375) | |||
| Financial distress | <.001 | |||
| Low to none | 1963 (34.1) | 863 (44.0) | 1100 (56.0) | |
| Medium | 1918 (33.3) | 829 (43.2) | 1089 (56.8) | |
| High | 1879 (32.6) | 693 (36.7) | 1186 (63.1) | |
| Race/ethnicity | <.001 | |||
| Black | 460 (8.5) | 131 (28.5) | 329 (71.5) | |
| Hispanic | 353 (6.5) | 119 (33.7) | 234 (66.3) | |
| Asian | 232 (4.3) | 95 (41.0) | 137 (66.7) | |
| Other | 149 (2.7) | 63 (42.3) | 86 (57.7) | |
| White | 4230 (78.0) | 1868 (44.2) | 2362 (55.8) | |
| Age, y | <.001 | |||
| ≥75 | 1196 (20.8) | 104 (8.7) | 1092 (91.3) | |
| 65 to <75 | 1162 (20.2) | 364 (31.3) | 798 (68.7) | |
| 50 to <65 | 1496 (26.0) | 756 (50.5) | 740 (49.5) | |
| 40 to <50 | 1552 (26.9) | 923 (59.5) | 629 (40.5) | |
| 18 to <40 | 354 (6.1) | 238 (67.2) | 116 (32.8) | |
| Insurance status | <.001 | |||
| Private | 3486 (60.5) | 1947 (55.9) | 1539 (44.2) | |
| Public | 2061 (35.8) | 357 (17.3) | 1704 (82.7) | |
| Self-pay | 211 (3.7) | 81 (38.4) | 130 (61.6) | |
| Teaching hospital | <.001 | |||
| Yes | 3382 (58.7) | 1518 (44.9) | 1864 (55.1) | |
| No | 2378 (41.3) | 867 (36.5) | 1511 (63.5) | |
| Cancer hospital | <.001 | |||
| Yes | 871 (15.1) | 486 (55.8) | 385 (44.2) | |
| No | 4889 (84.9) | 1889 (38.8) | 2990 (61.2) | |
| Ownership type | <.001 | |||
| Private | 5194 (90.1) | 2198 (42.3) | 2996 (57.7) | |
| Public | 566 (9.8) | 187 (33.0) | 379 (67.0) | |
| County with a high uninsured population | .23 | |||
| ≥75th Percentile | 1433 (24.9) | 574 (40.1) | 859 (59.9) | |
| <75th Percentile | 4327 (75.1) | 1811 (41.9) | 2516 (58.2) | |
Percent values are calculated from the overall number for each variable.
P value is from a χ2 test.
The Figure shows that 693 women (36.7%) treated at a hospital under high financial distress received immediate breast reconstruction surgery compared with 863 women (44.0%)treated at a hospital with low to no financial distress. In addition, women treated at teaching hospitals were more likely to receive immediate breast reconstruction surgery than women treated at nonteaching hospitals (44.9% vs 36.5%; P < .001). Women treated at designated cancer hospitals were more likely to receive immediate breast reconstruction surgery than women at nondesignated cancer hospitals (55.8% vs 38.8%; P < .001). Finally, women treated at private hospitals were more likely to receive immediate breast reconstruction surgery than women treated at public hospitals (42.3% vs 33.0%; P < .001). Financial distress was associated with all of the patient, insurance, and hospital-level variables used in the analysis (Table 2).
Figure. Hospital Variables and Immediate Breast Reconstruction Surgery.
HFD indicates hospital financial distress. HFD was defined as profit margin (hospital net income divided by total revenue multiplied by 100).
Table 2. Association Between Hospital Financial Distress and the Confounders.
| Variable | HFD Category, No. (%) | P Valuea | ||
|---|---|---|---|---|
| Low to None (n=1879) | Medium (n=1918) | High (n=1963) | ||
| Race/ethnicity | <.001 | |||
| Black | 140 (30.4) | 150 (32.6) | 170 (37.0) | |
| Hispanic | 99 (28.1) | 114 (32.3) | 140 (39.7) | |
| Asian | 81 (34.9) | 69 (29.7) | 82 (35.3) | |
| Other | 27 (18.1) | 55 (36.9) | 67 (45.0) | |
| White | 1519 (35.9) | 1431 (33.8) | 1280 (30.3) | |
| Age, y | .001 | |||
| ≥75 | 131 (37.0) | 135 (38.1) | 88 (24.5) | |
| 65 to <75 | 520 (33.5) | 544 (35.1) | 488 (31.4) | |
| 50 to <65 | 525 (35.1) | 502 (33.6) | 469 (31.4) | |
| 40 to <50 | 406 (35.0) | 372 (32.0) | 384 (33.1) | |
| 18 to <40 | 381 (31.9) | 365 (30.5) | 450 (37.6) | |
| Teaching hospital | <.001 | |||
| Yes | 1000 (29.6) | 1224 (36.2) | 1158 (34.2) | |
| No | 963 (40.5) | 694 (29.2) | 721 (30.3) | |
| Cancer hospital | <.001 | |||
| Yes | 278 (31.9) | 472 (54.2) | 121 (13.9) | |
| No | 1685 (34.5) | 1446 (29.6) | 1758 (36.0) | |
| Ownership type | .02 | |||
| Private | 1800 (34.7) | 1709 (32.9) | 1685 (32.4) | |
| Public | 163 (28.8) | 209 (36.9) | 194 (34.3) | |
| County with a high uninsured population | .01 | |||
| ≥75th Percentile | 538 (37.5) | 444 (31.0) | 451 (31.5) | |
| <75th Percentile | 1425 (32.9) | 1474 (34.1) | 1428 (33.0) | |
Abbreviation: HFD, hospital financial distress. HFD was defined as profit margin (hospital net income divided by total revenue multiplied by 100).
P value is from a χ2 test.
A 3-level logistic regression model was performed to evaluate the association between HFD and immediate breast reconstruction surgery (Table 3). The results from the unadjusted model showed that women treated at hospitals under high levels of financial distress (OR, 0.72; 95% CI, 0.58-0.90; P < .001) and medium levels of financial distress (OR, 0.81; 95% CI, 0.66-0.99; P < .001) were significantly less likely to receive immediate breast reconstruction surgery compared with women treated at hospitals with low to no financial distress. Table 3 also shows the results from the adjusted model. In the adjusted model, the association between HFD and immediate breast reconstruction surgery is very similar to the crude results. In the adjusted model, women treated at hospitals under high levels of financial distress (OR, 0.79; 95% CI, 0.62-0.99) and medium levels of financial distress (OR, 0.76; 95% CI, 0.61-0.94) were still significantly less likely to receive immediate breast reconstruction surgery compared with women treated at hospitals with low to no financial distress. We performed a sensitivity analysis after adding geographic region to the model, and the findings were unchanged.
Table 3. Multivariable Analysis of Factors Associated With Immediate Breast Reconstruction Surgery in Women With DCIS Who Underwent Mastectomy.
| Variable | OR (95% CI) | P Value for Adjusted Model | |
|---|---|---|---|
| Unadjusted Modela | Adjusted Modelb | ||
| Financial distress | |||
| Low to none | 1 [Reference] | 1 [Reference] | |
| Medium | 0.81 (0.66-0.99) | 0.76 (0.61-0.94) | .04 |
| High | 0.72 (0.58-0.90) | 0.79 (0.62-0.99) | .01 |
| Race/ethnicity | |||
| White | 1 [Reference] | 1 [Reference] | |
| Black | 0.54 (0.43-0.69) | 0.48 (0.37-0.61) | <.001 |
| Hispanic | 0.73 (0.56-0.95) | 0.62 (0.47-0.84) | .002 |
| Asian | 0.78 (0.57-1.05) | 0.59 (0.42-0.81) | .001 |
| Other | 1.07 (0.40-2.86) | 0.71 (0.25-2.05) | .53 |
| Age | |||
| 18 to <40 | 1 [Reference] | 1 [Reference] | |
| 40 to <50 | 0.71 (0.54-0.92) | 0.67 (0.51-0.88) | .003 |
| 50 to <65 | 0.48 (0.37-0.63) | 0.46 (0.35-0.60) | <.001 |
| 65 to <75 | 0.21 (0.16-0.28) | 0.25 (0.19-0.34) | <.001 |
| ≥75 | 0.05 (0.03-0.06) | 0.08 (0.05-0.10) | <.001 |
| Insurance status | |||
| Private | 1 [Reference] | 1 [Reference] | |
| Public | 0.18 (0.15-0.20) | 0.49 (0.41-0.59) | <.001 |
| Self-pay | 0.39 (0.22-0.68) | 0.44 (0.24-0.78) | .005 |
| Teaching hospital | |||
| No | 1 [Reference] | 1 [Reference] | |
| Yes | 1.56 (1.27-1.91) | 1.2 (0.97-1.49) | .09 |
| Cancer hospital | |||
| No | 1 [Reference] | 1 [Reference] | |
| Yes | 2.76 (1.79-4.25) | 1.85 (1.19-2.89) | .007 |
| Ownership type | |||
| Public | 1 [Reference] | 1 [Reference] | |
| Private | 1.45 (1.05-2.00) | 1.42 (1.01-1.99) | .04 |
| High uninsured county | |||
| <75th Percentile | 1 [Reference] | 1 [Reference] | |
| ≥75th Percentile | 0.78 (0.58-1.05) | 0.89 (0.66-1.21) | .89 |
Abbreviations: DCIS, ductal carcinoma in situ; OR, odds ratio.
Only 1 variable at a time was included.
All variables listed in this table were included in the model.
Discussion
Using profit margin as a measure of financial distress and controlling for patient and county-level variables, we found that women with DCIS treated at hospitals with high financial distress are less likely to undergo immediate breast reconstruction surgery after mastectomy than patients treated at hospitals with medium or low to no financial distress. We also found that HFD was associated with patient age, race, and hospital-level characteristics.
While this study is, to our knowledge, the first to look at the association between HFD and immediate breast reconstruction surgery, these findings are consistent with 3 previous studies that assessed the association between profit margin and patient outcomes. These studies used various cutoff points for profit margin to define financial distress. In the previous studies, there was a small but consistent association between for profit margin and nursing-related safety events, all patient safety events, in-hospital mortality, process indicators of quality for acute myocardial infarction, congestive heart failure, and pneumonia as well as 30-day readmission rates for acute myocardial infarction, congestive heart failure, and pneumonia.
Depending on the classification of HFD, anywhere from 7% to 30% of hospitals in a given year are under HFD, as defined by a negative profit margin. A range of patient outcomes has been associated with HFD: breast reconstruction; patient safety events; guideline adherence for acute myocardial infraction, pneumonia, and congestive heart failure; readmission rates; and in-hospital mortality. A next step in this area of inquiry will be to evaluate a wide range of inpatient and outpatient procedures to fully understand those associated with HFD. The types of outcomes affected by HFD may in turn affect the types of interventions that may be successful in eliminating these determinants of care. For example, if only outcomes linked to unprofitable procedures were affected, then increasing reimbursement for these procedures could reduce or eliminate the association with HFD.
Consistent with previous studies, we found that older women, nonwhite women, women with public insurance, and women treated at nonteaching hospitals, public hospitals, or non-cancer designated hospitals were all less likely to receive immediate breast reconstruction surgery. Age differences in immediate reconstruction rates may contribute to differences in patient preferences; however age differences in immediate reconstruction rates may also reflect physician reluctance to perform surgery on this population. Racial and ethnic differences may be owing to differences in physician discussion and/or awareness of reconstruction options at the time of mastectomy. Differences in immediate breast reconstruction surgery rates by hospital type are likely associated with differences in practice patterns between hospitals. A total of 2385 of 5760 women (41.4%) with DCIS in this sample had immediate reconstruction. We would not expect the rate to be 100% because some women make the choice not to undergo reconstruction. The years of the study were from 2004 to 2008. Reconstruction rates have continued to increase over time. This may also limit some of the generalizability of our findings.
Limitations
A limitation of this study is that there is no measure of a woman’s preference for breast reconstruction surgery. As a proxy for preference, age, race, and hospital factors were included in the model. Older women are less likely to opt for breast reconstruction if given the choice, and while there may be racial/ethnic differences in preferences, evidence suggests racial differences may be associated with differences in treatment. Therefore, race is included in the model as having a possible association with the type of hospital where a woman seeks treatment, which in turn may influence her ability to choose breast reconstruction surgery. Hospital factors, such as a cancer center designation, are meant to capture women who sought specific types of hospitals because of a strong preference for breast reconstruction surgery. While all of these factors may be a good proxy for a woman’s preference, it is likely that they do not perfectly correlate with a woman’s preference. However, this bias is likely to be nondifferential and may therefore lead to an underestimate.
The sample in this study is limited to women with DCIS because the factors that influence the decision-making process are very different for women with DCIS compared with invasive cancer. Women with DCIS have higher survival rates than those with invasive cancer; thus, women with DCIS may be more focused on life after mastectomy compared with women with invasive cancer. Women with invasive cancer may also be under more psychological pressure to undergo surgery more quickly and therefore forgo further consultations with a plastic surgeon. In addition, there is a controversy in the literature about the appropriate timing of breast reconstruction surgery in patients who receive radiotherapy. Radiation treatment after mastectomy is only recommended for some women with stage II or stage III breast cancer and this does not factor into the decision-making process for women with DCIS. We believe that the presence of a plastic surgeon may be a mediator of the association of HFD with breast reconstruction surgery. Hospital financial distress may affect the availability of plastic surgeons at a hospital, which in turn may affect whether patients receive immediate breast reconstruction surgery. Therefore, adding availability of a plastic surgeon as a covariate would remove part of the association that we want to capture. We were interested in the association, regardless of the reasons.
Conclusions
The findings from this study have implications for women diagnosed with breast cancer. The goal of this study was to test whether HFD was associated with breast reconstruction surgery. We hypothesize that there are a number of mechanisms that explain the association between HFD and breast reconstruction surgery, such as hospitals not offering the services as often, not offering the full range of services, or not prioritizing less profitable services in the operating room. Future studies should address the mechanisms.
To address this issue, legislative action may be required. Health policies related to breast reconstruction surgery have already been established. In 1998, the Women’s Health and Cancer Rights Act was passed to ensure personal financial situations did not impede women from receiving breast reconstruction surgery; in 2010, a state law was passed in New York mandating that breast surgeons discuss reconstruction options with their patients undergoing mastectomy. It is possible that enhancement of these existing policies, such as not reimbursing for the mastectomy if breast reconstruction surgery is not offered or available, is one potential option.
Another approach could be to increase reimbursements for immediate breast reconstruction and to vary reimbursement by the type performed; natural (ie, autologous) or implant-based, as immediate reconstruction surgery, and, in particular, autologous reconstruction, have been shown to be an underfinanced procedure relative to the resources used. A greater understanding of the association between HFD and the delivery of cancer services is necessary to better guide policy and patient care.
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