Dataset Information

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics.

ABSTRACT:

Importance

No consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding.

Objective

To examine characteristics of SNHs as classified under 3 common definitions.

Design, setting, and participants

This cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for fiscal year 2015, linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and to the American Hospital Association Annual Survey. Data were analyzed from March 1 through September 30, 2018.

Exposures

Hospital characteristics including organizational characteristics, scope of services provided, and financial attributes.

Main outcomes and measures

Definitions of SNH based on Medicaid and Medicare Supplemental Security Income inpatient days historically used to determine Medicare Disproportionate Share Hospital (DSH) payments; Medicaid and uninsured caseload; and uncompensated care costs. For each measure, SNHs were defined as those within the top quartile for each state.

Results

The 2066 hospitals in this study were distributed across the Northeast (340 [16.5%]), Midwest (587 [28.4%]), South (790 [38.2%]), and West (349 [16.9%]). Concordance between definitions was low; 269 hospitals (13.0%) or fewer were identified as SNHs under any 2 definitions. Uncompensated care captured smaller (200 of 523 [38.2%]) and more rural (65 of 523 [12.4%]) SNHs, whereas DSH index and Medicaid and uncompensated caseload identified SNHs that were larger (264 of 518 [51.0%] and 158 of 487 [32.4%], respectively) and teaching facilities (337 of 518 [65.1%] and 229 of 487 [47.0%], respectively) that provided more essential services than non-SNHs. Uncompensated care also distinguished remarkable financial differences between SNHs and non-SNHs. Under the uncompensated care definition, median (interquartile range [IQR]) bad debt ($27.1 [$15.5-$44.3] vs $12.8 [$6.7-$21.6] per $1000 of operating expenses; P?Conclusions and relevanceDifferent SNH definitions identify hospitals with different characteristics and financial conditions. The new DSH formula, which accounts for uncompensated care, may lead to redistributed payments across hospitals. Our results may inform which types of hospitals will experience funding changes as DSH payment policies evolve.

SUBMITTER: Popescu I

PROVIDER: S-EPMC6686776 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics.

Popescu Ioana I Fingar Kathryn R KR Cutler Eli E Guo Jing J Jiang H Joanna HJ

JAMA network open 20190802 8

<h4>Importance</h4>No consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding.<h4>Objective</h4>To examine characteristics of SNHs as classified under 3 common definitions.<h4>Design, setting, and participants</h4>This cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Util ...[more]

PMID: 31390034

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Project description:ImportanceMedical patients discharged from safety-net hospitals (SNHs) experience higher readmission rates compared with those discharged from non-SNHs. However, little is known about whether this association persists for surgical patients.ObjectivesTo examine differences in readmission rates between SNHs and non-SNHs among surgical patients after discharge and determine whether hospital characteristics might account for some of the variation.Design, setting, and participantsThis observational retrospective study linked the Healthcare Cost and Utilization Project State Inpatient Databases of the Agency for Healthcare Research and Quality from January 1, 2011, through December 31, 2014, for 4 states (New York, Florida, Iowa, and Washington) with data from the 2014 American Hospital Association annual survey. After identifying surgical discharges, SNHs were defined as those with the top quartile of inpatient stays paid by Medicaid or self-paid. Hospital-level risk-standardized readmission rates (RSRRs) for surgical discharges were calculated. The association between hospital RSRRs and hospital characteristics was evaluated with bivariate analyses. An estimated multivariable hierarchical linear regression model was used to examine variation in hospital RSRRs, adjusting for hospital characteristics, state, year, and SNH status. Data were analyzed from June 1, 2017, through March 1, 2018.ExposuresSurgical care at an SNH.Main outcomes and measuresReadmission after an index surgical admission.ResultsA total of 1 252 505 patients across all 4 years and states were included in the analysis (51.7% women; mean [SD] age, 52.7 [18.1] years). Bivariate analyses found that SNHs had higher mean (SD) surgical RSRRs compared with non-SNHs; significant differences were found for New York (9.6 [0.1] vs 10.9 [0.1]; P < .001) and Florida (11.6 [0.1] vs 12.1 [0.1]; P = .001). The SNHs also had higher RSRRs in these 2 states when stratified by hospital funding (nonfederal government SNHs in New York, 11.9 [0.2]; for-profit, private SNHs in Florida, 13.1 [0.2]; P < .001 for both); however, bed size was a significant factor for higher mean (SD) RSRRs only for New York (200 to 399 beds, 12.0 [0.4]; P = .006). Similar results were found for multivariable linear regression models; RSRRs were 1.02% higher for SNHs compared with non-SNHs (95% CI, 0.75%-1.29%; P < .001). Increased RSRRs were observed for hospitals in New York and Florida, teaching hospitals, and investor-owned hospitals. Factors associated with reduced RSRRs included presence of an ambulatory surgery center, cardiac catheterization capabilities, and high surgical volume.Conclusions and relevanceAccording to results of this study, surgical patients treated at SNHs experienced slightly higher RSRRs compared with those treated at non-SNHs. This association persisted after adjusting for year, state, and hospital factors, including teaching status, hospital bed size, and hospital volume.

Project description:ImportanceAlthough readmission rates are declining under Medicare's Hospital Readmissions Reduction Program (HRRP), concerns remain that the HRRP will harm quality at safety-net hospitals because they are penalized more often. Disparities between white and black patients might widen because more black patients receive care at safety-net hospitals. Disparities may be particularly worse for clinical conditions not targeted by the HRRP because hospitals might reallocate resources toward targeted conditions (acute myocardial infarction, pneumonia, and heart failure) at the expense of nontargeted conditions.ObjectiveTo examine disparities in readmission rates between white and black patients discharged from safety-net or non-safety-net hospitals after the HRRP began, evaluating discharges for any clinical condition and the subsets of targeted and nontargeted conditions.Design, setting, and participantsCohort study conducting quasi-experimental analyses of patient hospital discharges for any clinical condition among fee-for-service Medicare beneficiaries from 2007 to 2015 after controlling for patient and hospital characteristics. Changes in disparities were measured within safety-net and non-safety-net hospitals after the HRRP penalties were enforced and compared with prior trends. These analyses were then stratified by targeted and nontargeted conditions. Analyses were conducted from October 1, 2017, through August 31, 2018.Main outcomes and measuresTrends in 30-day readmission rates among white and black patients by quarter and differences in trends across periods.ResultsThe study sample included 58 237 056 patient discharges (black patients, 9.8%; female, 57.7%; mean age [SD] age, 78.8 [7.9] years; nontargeted conditions, 50 372 806 [86.5%]). Within safety-net hospitals, disparities in readmission rates for all clinical conditions widened between black and white patients by 0.04 percentage point per quarter in the HRRP penalty period (95% CI, 0.01 to 0.07; P = .01). This widening was driven by nontargeted conditions (0.05 percentage point per quarter [95% CI, 0.01 to 0.08]; P = .006), whereas disparities for the HRRP-targeted conditions did not change (with an increase of 0.01 percentage point per quarter [95% CI, -0.07 to 0.10]; P = .74). Within non-safety-net hospitals, racial disparities remained stable in the HRRP penalty period across all conditions, whether the conditions were HRRP-targeted or nontargeted.Conclusions and relevanceFindings from this study suggest that disparities are widening within safety-net hospitals, specifically for non-HRRP-targeted conditions. Although increases in racial disparities for nontargeted conditions were modest, they represent 6 times more discharges in our cohort than targeted conditions.

Project description:OBJECTIVE:The 340B program allows safety-net hospitals to acquire discounted outpatient drugs and charge payers full price. We examined whether 340B participation increases safety-net engagement. DATA SOURCES:340B participation data, Medicare hospital cost reports, American Hospital Association Survey, and Schedule 990 nonprofit hospital tax returns. STUDY DESIGN:Quasi-experimental difference-in-differences design comparing 340B hospitals (the "treatment" group) before and after participating to changes over time to three alternative "control" groups: all other nonprofit and public hospitals, hospitals that are not participating during our study, and hospitals that were not-yet-participating but started after 2015. Outcome measures include a range of safety-net care measures that are alternatives to the standard uncompensated care: charity care, community benefit spending, charity care policies, and low-profit service-line provision. DATA EXTRACTION:We extracted data on all nonprofit and public hospitals from 2011 to 2015. We linked 340B participation data to Medicare hospital cost reports and American Hospital Association data using Medicare hospital identifiers. 990 Data was linked on name and address. PRINCIPAL FINDINGS:New 340B participation was not associated with a change in uncompensated care, but was associated with a 28.9 percent increase in charity care spending (SE = 8.8), or about $880,000 per hospital. However, total community benefit spending (including charity care) did not change. 340B was associated with an increase in the probability of offering discounted care (4.3 percentage points, SE = 1.6) from 84 to 88 percent and an increase in the income eligibility limit for discounted care (18.9 percentage points, SE = 5.6) from 294 to 313 percent. Participation was not associated with the probability of offering low-profit medical care services. CONCLUSIONS:Alternative measures show that newly participating hospitals may increase charity care, potentially through offering more patients discounted care. However, increases appear to be fully offset by reductions in other community benefit programs.

Project description:ImportanceHigh-sensitivity cardiac troponin T (hs-cTnT) protocols for the evaluation of chest pain in the emergency department (ED) may reduce unnecessary resource use and overcrowding.ObjectiveTo determine whether the implementation of a novel hs-cTnT protocol, which incorporated troponin values drawn at 0, 1, and 3 hours after ED presentation and the modified HEART score (history, electrocardiogram, age, risk factors), was associated with improvements in resource use while maintaining safety.Design, setting, and participantsThis retrospective cohort study from Parkland Health and Hospital System, a large safety net hospital in Dallas, Texas, included data on 31 543 unique ED encounters in which patients underwent electrocardiographic and troponin testing from January 1, 2017, to October 16, 2018. The hs-cTnT protocol was implemented in December 2017.Main outcomes and measuresResource use outcomes included trends in ED dwell time, troponin to disposition decision time (the difference between the first troponin draw time and the time an order was placed for inpatient admission, admission to observation, or discharge), and final patient disposition. Safety outcomes included readmission for myocardial infarction and death.ResultsIn 31 543 encounters, mean (SD) patient age was 54 (14.4) years and 14 675 patients (48%) were female. Department dwell time decreased by a mean of -1.09 (95% CI, -2.81 to 0.64) minutes per month in the preintervention period. The decline was steeper after the intervention (-4.69 [95% CI, -9.05 to -0.33] minutes per month) (P for interaction = .007). The troponin to disposition time was increasing in the preintervention period by 1.72 (95% CI, 1.08 to 2.36) minutes per month; postintervention, the mean difference increased more slowly (0.37 [95% CI, -1.25 to 1.99 minutes per month; P value for interaction = .007]). The proportion of patients discharged from the ED increased after the intervention (48% vs 54%, P < .001). Thirty-day major adverse cardiac event rates were low and did not differ before and after the intervention.Conclusions and relevanceImplementation of a novel protocol incorporating serial hs-cTnT measurements over 3 hours with the Modified HEART Score was associated with reduction in ED dwell times and attenuation of temporal increases in time from troponin measurement to disposition. This or similar protocols to rule out myocardial infarction have the potential to reduce ED overcrowding and improve health care quality while maintaining safety.

Project description:Massachusetts' health care reform substantially decreased the percentage of uninsured residents. However, less is known about how reform affected access to care, especially according to insurance type.To assess access to care in Massachusetts after implementation of health care reform, based on insurance status and type.We surveyed a convenience sample of 431 patients presenting to the Emergency Department of Massachusetts' second largest safety net hospital between July 25, 2009 and March 20, 2010.Demographic and clinical characteristics, insurance coverage, measures of access to care and cost-related barriers to care.Patients with Commonwealth Care and Medicaid, the two forms of insurance most often newly-acquired under the reform, reported similar or higher utilization of and access to outpatient visits and rates of having a usual source of care, compared with the privately insured. Compared with the privately insured, a significantly higher proportion of patients with Medicaid or Commonwealth Care Type 1 (minimal cost sharing) reported delaying or not getting dental care (42.2 % vs. 27.1 %) or medication (30.0 % vs. 7.0 %) due to cost; those with Medicaid also experienced cost-related barriers to seeing a specialist (14.6 % vs. 3.5 %) or getting recommended tests (15.6 % vs. 5.9 %). Those with Commonwealth Care Types 2 and 3 (greater cost sharing) reported significantly more cost-related barriers to obtaining care than the privately insured (45.0 % vs. 16.0 %), to seeing a primary care doctor (25.0 % vs. 6.0 %) or dental provider (58.3 % vs. 27.1 %), and to obtaining medication (20.8 % vs. 7.0 %). No differences in cost-related barriers to preventive care were found between the privately and publicly insured.Access to care improved less than access to insurance following Massachusetts' health care reform. Many newly insured residents obtained Medicaid or state subsidized private insurance; cost-related barriers to access were worse for these patients than for the privately insured.

Project description:ImportanceIn the US, federal value-based incentive programs are more likely to penalize safety-net institutions than non-safety-net institutions. Whether these programs differentially change the rates of targeted health care-associated infections in safety-net vs non-safety-net hospitals is unknown.ObjectiveTo assess the association of Hospital-Acquired Condition Reduction Program (HACRP) and Hospital Value-Based Purchasing (HVBP) implementation with changes in rates of targeted health care-associated infections and disparities in rates among safety-net and non-safety-net hospitals.Design, setting, and participantsThis interrupted time series included all US acute care hospitals enrolled in the Preventing Avoidable Infectious Complications by Adjusting Payment study that participated in mandatory reporting to the National Healthcare Safety Network from January 1, 2013, through June 30, 2018. Hospital characteristics were obtained from the 2015 American Hospital Association annual survey. Penalty statuses for 2015 to 2018 were obtained from Hospital Compare. Data were analyzed between July 9, 2018, and October 1, 2019.ExposuresHACRP and HVBP implementation in fiscal year 2015 or 2016.Main outcomes and measuresThe primary outcomes were rates of 4 health care-associated infections: central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI) after colon surgical procedures, and SSI after abdominal hysterectomy procedures. Regression models were fit using generalized estimating equations to assess the association of HACRP and HVBP implementation with health care-associated infection rates and disparities in infection rates.ResultsOf the 618 acute care hospitals included in this study, 473 (76.5%) were non-safety net and 145 (23.5%) were considered safety net. In these hospitals, HACRP and HVBP implementation was not associated with improvements in level or trend for any health care-associated infection examined (eg, CAUTI in safety-net hospitals: incidence rate ratio [IRR] for level change, 0.98 [95% CI, 0.79-1.23; P = .89]; IRR for change in slope, 1.00 [95% CI, 0.97-1.03; P = .80]). Before program implementation, infection rates were statistically significantly higher for safety-net than for non-safety-net hospitals for CLABSI (IRR, 1.23; 95% CI, 1.07-1.42; P = .004), CAUTI (IRR, 1.38; 95% CI, 1.16-1.64; P < .001), and SSI after colon surgical procedure (odds ratio [OR], 1.26; 95% CI, 1.06-1.50; P = .009). The disparity persisted over time when comparing the last year of the study with the first year (CLABSI: ratio of ratios [ROR], 0.93 [95% CI, 0.77-1.13; P = .48]; CAUTI: ROR, 0.90 [95% CI, 0.73-1.10; P = .31]; SSI after colon surgical procedures: ROR, 0.96 [95% CI, 0.78-1.20; P = .75]). Rates of SSI after abdominal hysterectomy procedure were similar in safety-net and non-safety-net hospitals before implementation (OR, 1.13; 95% CI, 0.91-1.40; P = .27) but higher after implementation (OR, 1.43; 95% CI, 1.11-1.83; P = .006), although this change was not significant (ROR, 1.20; 95% CI, 0.91-1.59; P = .20).Conclusions and relevanceThis study found that HACRP and HVBP implementation was not associated with any improvements in targeted health care-associated infections among safety-net or non-safety-net hospitals or with changes in disparities in infection rates. Given the persistent health care-associated infection rate disparities, these programs appear to function as a disproportionate penalty system for safety-net hospitals that offer no measurable benefits for patients.

Project description:Performance measures, particularly pay for performance, may have unintended consequences for safety-net institutions caring for disproportionate shares of Medicaid or uninsured patients.To describe emergency department (ED) compliance with proposed length-of-stay measures for admissions (8 hours or 480 minutes) and discharges, transfers, and observations (4 hours or 240 minutes) by safety-net status.The 2008 National Hospital Ambulatory Medical Care Survey (NHAMCS) ED data were stratified by safety-net status (Centers for Disease Control and Prevention definition) and disposition (admission, discharge, observation, transfer). The 2008 NHAMCS is a national probability sample of 396 hospitals (90.2% unweighted response rate) and 34 134 patient records. Visits were excluded for patients younger than 18 years, missing length-of-stay data or dispositions of missing, other, left against medical advice, or dead on arrival. Median and 90th percentile ED lengths of stay were calculated for each disposition and admission/discharge subcategories (critical care, psychiatric, routine) stratified by safety-net status. Multivariable analyses determined associations with length-of-stay measure compliance.Emergency Department length-of-stay measure compliance by disposition and safety-net status.Of the 72.1% ED visits (N = 24 719) included in the analysis, 42.3% were to safety-net EDs and 57.7% were to non-safety-net EDs. The median length of stay for safety-net was 269 minutes (interquartile range [IQR], 178-397 minutes) for admission vs 281 minutes (IQR, 178-401 minutes) for non-safety-net EDs; 156 minutes (IQR, 95-239 minutes) for discharge vs 148 minutes (IQR, 88-238 minutes); 355 minutes (IQR, 221-675 minutes) for observations vs 298 minutes (IQR, 195-440 minutes); and 235 minutes (IQR, 155-378 minutes) for transfers vs 239 minutes (IQR, 142-368 minutes). Safety-net status was not independently associated with compliance with ED length-of-stay measures; the odds ratio was 0.83 for admissions (95% CI, 0.52-1.34); 1.03 for discharges (95% CI, 0.83-1.27); 1.05 for observations (95% CI, 0.57-1.95), 1.30 for transfers (95% CI, 0.70-2.45]); or subcategories except for psychiatric discharges (1.67, [95% CI, 1.02-2.74]).Compliance with proposed ED length-of-stay measures for admissions, discharges, transfers, and observations did not differ significantly between safety-net and non-safety-net hospitals.

Dataset Information

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics.

Importance

Objective

Design, setting, and participants

Exposures

Main outcomes and measures

Results

Publications

Comparison of 3 Safety-Net Hospital Definitions and Association With Hospital Characteristics.

Similar Datasets

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