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Surgery wait times and specialty services for insured and uninsured breast cancer patients: does hospital safety net status matter?

ABSTRACT: OBJECTIVE: To determine whether safety net and non-safety net hospitals influence inpatient breast cancer care in insured and uninsured women and in white and African American women. DATA SOURCES: Six years of Virginia Cancer Registry and Virginia Health Information discharge data were linked and supplemented with American Hospital Association data. STUDY DESIGN: Hierarchical generalized linear models and linear probability regression models were used to estimate the relationship between hospital safety net status, the explanatory variables, and the days from diagnosis to mastectomy and the likelihood of breast reconstruction. PRINCIPAL FINDINGS: The time between diagnosis and surgery was longer in safety net hospitals for all patients, regardless of insurance source. Medicaid insured and uninsured women were approximately 20 percent less likely to receive reconstruction than privately insured women. African American women were less likely to receive reconstruction than white women. CONCLUSIONS: Following the implementation of health reform, disparities may potentially worsen if safety net hospitals' burden of care increases without commensurate increases in reimbursement and staffing levels. This study also suggests that Medicaid expansions may not improve outcomes in inpatient breast cancer care within the safety net system.

SUBMITTER: Bradley CJ

PROVIDER: S-EPMC3419883 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature

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Surgery wait times and specialty services for insured and uninsured breast cancer patients: does hospital safety net status matter?

Bradley Cathy J CJ Dahman Bassam B Shickle Lisa M LM Lee Woolton W

Health services research 20110923 2

<h4>Objective</h4>To determine whether safety net and non-safety net hospitals influence inpatient breast cancer care in insured and uninsured women and in white and African American women.<h4>Data sources</h4>Six years of Virginia Cancer Registry and Virginia Health Information discharge data were linked and supplemented with American Hospital Association data.<h4>Study design</h4>Hierarchical generalized linear models and linear probability regression models were used to estimate the relations ...[more]

PMID: 22092155

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Project description:BackgroundHealth care funding reforms are being used worldwide to improve system performance but may invoke unintended consequences. We assessed the effects of introducing a targeted hospital funding model, based on fixed price and volume, for hip fractures. We hypothesized the policy change was associated with reduction in wait times for hip fracture surgery, increase in wait times for non-hip fracture surgery, and increase in the incidence of after-hours hip fracture surgery.MethodsThis was a population-based, interrupted time series analysis of 49,097 surgeries for hip fractures, 10,474 for ankle fractures, 1,594 for tibial plateau fractures, and 40,898 for appendectomy at all hospitals in Ontario, Canada between April 2012 and March 2017. We used segmented regression analysis of interrupted monthly time series data to evaluate the impact of funding reform enacted April 1, 2014 on wait time for hip fracture repair (from hospital presentation to surgery) and after-hours provision of surgery (occurring between 1700 and 0700 h). To assess potential adverse consequences of the reform, we also evaluated two control procedures, ankle and tibial plateau fracture surgery. Appendectomy served as a non-orthopedic tracer for assessment of secular trends.ResultsThe difference (95 % confidence interval) between the actual mean wait time and the predicted rate had the policy change not occurred was - 0.46 h (-3.94 h, 3.03 h) for hip fractures, 1.46 h (-3.58 h, 6.50 h) for ankle fractures, -3.22 h (-39.39 h, 32.95 h) for tibial plateau fractures, and 0.33 h (-0.57 h, 1.24 h) for appendectomy (Figure 1; Table 3). The difference (95 % confidence interval) between the actual and predicted percentage of surgeries performed after-hours - 0.90 % (-3.91 %, 2.11 %) for hip fractures, -3.54 % (-11.25 %, 4.16 %) for ankle fractures, 7.09 % (-7.97 %, 22.14 %) for tibial plateau fractures, and 1.07 % (-2.45 %, 4.59 %) for appendectomy.ConclusionsWe found no significant effects of a targeted hospital funding model based on fixed price and volume on wait times or the provision of after-hours surgery. Other approaches for improving hip fracture wait times may be worth pursuing instead of funding reform.

Project description:BackgroundIncreasing rates of obesity have led to growing demand for bariatric surgery. This has implications for wait times, particularly in publicly funded programs. This study examined the impact of patient and operational factors on wait times in a multidisciplinary bariatric surgery program.MethodsA retrospective study was conducted involving patients who were referred to a tertiary care centre (University Health Network, Toronto Western Hospital, Toronto) for bariatric surgery between June 2008 and July 2011. Patient characteristics, dates of clinical assessments and records describing operational changes were collected. Univariable analysis and multivariable log-linear and parametric time-to-event regressions were performed to determine whether patient and operational covariates were associated with the wait time for bariatric surgery (i.e., length of preoperative evaluation).ResultsOf the 1664 patients included in the analysis, 724 underwent surgery with a mean wait time of 440 (standard deviation 198) days and a median wait time of 445 (interquartile range 298-533) days. Wait times ranged from 3 months to 4 years. Univariable and multivariable analyses showed that patients with active substance use (β = 0.3482, p = 0.02) and individuals who entered the program in more recent operational periods (β = 0.2028, p < 0.001) had longer wait times. Additionally, the median time-to-surgery increased over 3 discrete operational periods (characterized by specific program changes related to scheduling and staffing levels, and varying referral rates and defined surgical targets; p < 0.001).InterpretationSome patients could be identified at referral as being at risk for longer wait times. We also found that previous operational decisions significantly increased the wait time in the program since its inception. Therefore, careful consideration must be devoted to process-level decision-making for multistage bariatric surgical programs, because managerial and procedural changes can affect timely access to treatment.

Project description:BackgroundOutpatient parenteral antimicrobial therapy (OPAT) is accepted as safe and effective for medically stable patients to complete intravenous (IV) antibiotics in an outpatient setting. Since, however, uninsured patients in the United States generally cannot afford OPAT, safety-net hospitals are often burdened with long hospitalizations purely to infuse antibiotics, occupying beds that could be used for patients requiring more intensive services. OPAT is generally delivered in one of four settings: infusion centers, nursing homes, at home with skilled nursing assistance, or at home with self-administered therapy. The first three-termed healthcare-administered OPAT (H-OPAT)--are most commonly used in the United States by patients with insurance funding. The fourth--self-administered OPAT (S-OPAT)--is relatively uncommon, with the few published studies having been conducted in the United Kingdom. With multidisciplinary planning, we established an S-OPAT clinic in 2009 to shift care of selected uninsured patients safely to self-administration of their IV antibiotics at home. We undertook this study to determine whether the low-income mostly non-English-speaking patients in our S-OPAT program could administer their own IV antimicrobials at home with outcomes as good as, or better than, those receiving H-OPAT.Methods and findingsParkland Hospital is a safety-net hospital serving Dallas County, Texas. From 1 January 2009 to 14 October 2013, all uninsured patients meeting criteria were enrolled in S-OPAT, while insured patients were discharged to H-OPAT settings. The S-OPAT patients were trained through multilingual instruction to self-administer IV antimicrobials by gravity, tested for competency before discharge, and thereafter followed at designated intervals in the S-OPAT outpatient clinic for IV access care, laboratory monitoring, and physician follow-up. The primary outcome was 30-d all-cause readmission, and the secondary outcome was 1-y all-cause mortality. The study was adequately powered for readmission but not for mortality. Clinical, sociodemographic, and outcome data were collected from the Parkland Hospital electronic medical records and the US census, constituting a historical prospective cohort study. We used multivariable logistic regression to develop a propensity score predicting S-OPAT versus H-OPAT group membership from covariates. We then estimated the effect of S-OPAT versus H-OPAT on the two outcomes using multivariable proportional hazards regression, controlling for selection bias and confounding with the propensity score and covariates. Of the 1,168 patients discharged to receive OPAT, 944 (81%) were managed in the S-OPAT program and 224 (19%) by H-OPAT services. In multivariable proportional hazards regression models controlling for confounding and selection bias, the 30-d readmission rate was 47% lower in the S-OPAT group (adjusted hazard ratio [aHR], 0.53; 95% CI 0.35-0.81; p = 0.003), and the 1-y mortality rate did not differ significantly between the groups (aHR, 0.86; 95% CI 0.37-2.00; p = 0.73). The S-OPAT program shifted a median 26 d of inpatient infusion per patient to the outpatient setting, avoiding 27,666 inpatient days. The main limitation of this observational study-the potential bias from the difference in healthcare funding status of the groups-was addressed by propensity score modeling.ConclusionsS-OPAT was associated with similar or better clinical outcomes than H-OPAT. S-OPAT may be an acceptable model of treatment for uninsured, medically stable patients to complete extended courses of IV antimicrobials at home.

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Surgery wait times and specialty services for insured and uninsured breast cancer patients: does hospital safety net status matter?

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Surgery wait times and specialty services for insured and uninsured breast cancer patients: does hospital safety net status matter?

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