Payer-Negotiated Price Variation and Relationship to Surgical Outcomes for the Most Common Cancers at NCI-Designated Cancer Centers

BACKGROUND

Federal rules mandate that hospitals publish payer-specific negotiated prices for all services. Little is known about variation in payer-negotiated prices for surgical oncology services or their relationship to clinical outcomes. We assessed variation in payer-negotiated prices associated with surgical care for common cancers at National Cancer Institute (NCI)-designated cancer centers and determined the effect of increasing payer-negotiated prices on the odds of morbidity and mortality.

MATERIALS AND METHODS

A cross-sectional analysis of 63 NCI-designated cancer center websites was employed to assess variation in payer-negotiated prices. A retrospective cohort study of 15,013 Medicare beneficiaries undergoing surgery for colon, pancreas, or lung cancers at an NCI-designated cancer center between 2014 and 2018 was conducted to determine the relationship between payer-negotiated prices and clinical outcomes. The primary outcome was the effect of median payer-negotiated price on odds of a composite outcome of 30 days mortality and serious postoperative complications for each cancer cohort.

RESULTS

Within-center prices differed by up to 48.8-fold, and between-center prices differed by up to 675-fold after accounting for geographic variation in costs of providing care. Among the 15,013 patients discharged from 20 different NCI-designated cancer centers, the effect of normalized median payer-negotiated price on the composite outcome was clinically negligible, but statistically significantly positive for colon [aOR 1.0094 (95% CI 1.0051-1.0138)], lung [aOR 1.0145 (1.0083-1.0206)], and pancreas [aOR 1.0080 (1.0040-1.0120)] cancer cohorts.

CONCLUSIONS

Payer-negotiated prices are statistically significantly but not clinically meaningfully related to morbidity and mortality for the surgical treatment of common cancers. Higher payer-negotiated prices are likely due to factors other than clinical quality.

Characterizing geographic variation in postoperative venous thromboembolism

OBJECTIVE

Venous thromboembolism (VTE) after major surgery remains an important contributor to morbidity and mortality. Despite significant quality improvement efforts in prevention and prophylaxis strategies, the degree of hospital and regional variation in the United States remains unknown.

METHODS

Medicare beneficiaries undergoing 13 different major surgeries at U.S. hospitals between 2016 and 2018 were included in this retrospective cohort study. We calculated the rates of 90-day VTE. We adjusted for a variety of patient and hospital covariates and used a multilevel logistic regression model to calculate the rates of VTE and coefficients of variation across hospitals and hospital referral regions (HRRs).

RESULTS

A total of 4,115,837 patients from 4116 hospitals were included, of whom 116,450 (2.8%) experienced VTE within 90 days. The 90-day VTE rates varied substantially by procedure, from 2.5% for abdominal aortic aneurysm repair to 8.4% for pancreatectomy. Across the hospitals, there was a 6.6-fold variation in index hospitalization VTE and a 5.3-fold variation in the rate of postdischarge VTE. Across the HRRs, there was a 2.6-fold variation in 90-day VTE, with a 12.1-fold variation in the coefficient of variation. A subset of HRRs was identified with both higher VTE rates and higher variance across hospitals.

CONCLUSIONS

Substantial variation exists in the rate of postoperative VTE across U.S. hospitals. Characterizing HRRs with high overall rates of VTE and those with significant variation across the hospitals will allow for targeted quality improvement efforts.

Changes in Hospital-acquired Conditions and Mortality Associated With the Hospital-acquired Condition Reduction Program

IMPORTANCE

To improve patient safety, the Centers for Medicare and Medicaid Services announced the Hospital-Acquired Condition Reduction Program (HACRP) in August 2013. The program reduces Medicare payments by 1% for hospitals in the lowest performance quartile related to hospital-acquired conditions. Performance measures are focused on perioperative care.

OBJECTIVE

To evaluate changes in HACs and 30-day mortality after the announcement of the HACRP.

DESIGN

Interrupted time-series design using Medicare Provider and Analysis Review (MEDPAR) claims data. We estimated models with linear splines to test for changes in HACs and 30-day mortality before the Affordable Care Act (ACA), after the ACA, and after the HACRP.

SETTING

Fee-for-service Medicare 2009-2015.

PARTICIPANTS

Medicare beneficiaries undergoing surgery and discharged from an acute care hospital between January 2009 and August 2015 (N = 8,857,877).

MAIN OUTCOME AND MEASURE

Changes in HACs and 30-day mortality after the announcement of the HACRP.

RESULTS

Patients experienced HACs at a rate of 13.39 per 1000 discharges [95% confidence interval (CI), 13.10 to 13.68] in the pre-ACA period. This declined after the ACA was passed and declined further after the HACRP announcement [adjusted difference in annual slope, -1.34 (95% CI, -1.64 to -1.04)]. Adjusted 30-day mortality was 3.69 (95% CI, 3.64 to 3.74) in the pre-ACA period among patients receiving surgery. Thirty-day mortality continued to decline after the ACA [adjusted annual slope -0.04 (95% CI, -0.05 to -0.02)] but was flat after the HACRP [adjusted annual slope -0.01 (95% CI, -0.04 to 0.02)].

CONCLUSIONS AND RELEVANCE

Although hospital-acquired conditions targeted under the HACRP declined at a greater rate after the program was announced, 30-day mortality was unchanged.

Evaluation of US Hospital Episode Spending for Acute Inpatient Conditions After the Patient Protection and Affordable Care Act

IMPORTANCE

Under the Patient Protection and Affordable Care Act (ACA), US hospitals were exposed to a number of reforms intended to reduce spending, many of which, beginning in 2012, targeted acute care hospitals and often focused on specific diagnoses (eg, acute myocardial infarction, heart failure, and pneumonia) for Medicare patients. Other provisions enacted in the ACA and under budget sequestration (beginning in 2013) mandated Medicare fee cuts.

OBJECTIVE

To evaluate the association between the enactment of ACA reforms and 30-day price-standardized hospital episode spending.

DESIGN, SETTING, AND PARTICIPANTS

This policy evaluation included index discharges between January 1, 2008, and August 31, 2015, from a national random 20% sample of Medicare beneficiaries. Data analysis was performed from February 1, 2019 to July 8, 2020.

EXPOSURE

Payment reforms after passage of the ACA.

MAIN OUTCOMES AND MEASURES

30-day price-standardized episode payments. Three alternative estimation approaches were used to evaluate the association between reforms following the ACA and episode spending: (1) a difference-in-difference (DID) analysis among acute care hospitals, comparing spending for diagnoses commonly targeted by ACA programs with nontargeted diagnoses; (2) a DID analysis comparing acute care hospitals and critical access hospitals (not exposed to reforms); and (3) a generalized synthetic control analysis, comparing acute care and critical access hospitals. Supplemental analysis examined the degree to which Medicare fee cuts contributed to spending reductions.

RESULTS

A total of 7 634 242 index discharges (4 525 630 [59.2%] female patients; mean [SD] age, 79.31 [8.02] years) were included. All 3 approaches found that reforms following the ACA were associated with a significant reduction in episode spending. The DID estimate comparing targeted and untargeted diagnoses suggested that reforms following the ACA were associated with a -$431 (95% CI, -$492 to -$369; -2.87%) change in total spending, while the generalized synthetic control analysis suggested that reforms were associated with a -$1232 (95% CI, -$1488 to -$965; -10.12%) change in total episode spending, amounting in a total annual savings of $5.68 billion. Cuts to Medicare fees accounted for most of these savings.

CONCLUSIONS AND RELEVANCE

In this policy evaluation, the ACA was associated with large reductions in US hospital episode spending.

A Comparison of Estimated Cost Savings from Potential Reductions in Hospital-Acquired Conditions to Levied Penalties Under the CMS Hospital-Acquired Condition Reduction Program

BACKGROUND

The Hospital-Acquired Condition Reduction Program (HACRP) from the Centers for Medicare & Medicaid Services (CMS) reduces Medicare payments to hospitals with high rates of hospital-acquired conditions (HACs) by 1% each year. It is not known how the savings accruing to CMS from such penalties compare to savings resulting from a reduction in HACs driven by this program. This study compares the reported savings to CMS from financial penalties levied under the HACRP with savings resulting from potential reductions in HACs.

METHODS

Using a random sample of 20% of Medicare claims data (January 1, 2009-September 30, 2014), the research team evaluated the association between HACs and 90-day episode spending (adjusted to 2015 dollars), then estimated potential annual savings to CMS if there was a relative decrease in incidence of all HACs by 1%-20%. These savings were then compared to the actual collected HACRP penalties reported by CMS in 2015.

RESULTS

All HACs were associated with significant increases in total 90-day episode spending, ranging from $3,183 for iatrogenic pneumothorax to $21,654 for postoperative hip fracture. The total estimated savings to Medicare from potential reduction in all HACs ranged from $2.2 million to $44 million per year, an amount much lower than the $361 million in penalties levied on hospitals per year for HACs.

CONCLUSION

The penalties levied under the HACRP far exceed the potential cost savings accruing from a 1%-20% reduction in HACs that might result from hospitals' efforts in response to the program.

Most Patients Undergoing Ground And Air Ambulance Transportation Receive Sizable Out-Of-Network Bills

"Surprise" out-of-network bills have come under close scrutiny, and while ambulance transportation is known to be a large component of the problem, its impact is poorly understood. We measured the prevalence and financial impact of out-of-network billing in ground and air ambulance transportation. For members of a large national insurance plan in 2013-17, 71 percent of all ambulance rides involved potential surprise bills. For both ground and air ambulances, out-of-network charges were substantially greater than in-network prices, resulting in median potential surprise bills of $450 for ground transportation and $21,698 for air transportation. Though out-of-network air ambulance bills were larger, out-of-network ground ambulance bills were more common, with an aggregate impact of $129 million per year. Out-of-network air ambulance bills averaged $91 million per year, rising from $41 million in 2013 to $143 million in 2017. Federal proposals to limit surprise out-of-network billing should incorporate protections for patients undergoing ground or air ambulance transportation.

Is social capital protective against hospital readmissions?

BACKGROUND

To evaluate the association between social capital and 30-day readmission to the hospital among Medicare beneficiaries overall, beneficiaries with dementia and related memory disorders, and beneficiaries with dual eligibility for Medicaid.

METHODS

Using Health and Retirement Study (HRS) data linked with 2008-2015 Medicare claims from traditional Medicare beneficiaries hospitalized during the study period (1246 unique respondents, 2212 total responses), we examined whether dementia and related memory disorders and dual eligibility were associated with social capital. We then estimated a multiple regression model to test whether social capital was associated with a reduced likelihood of readmission.

RESULTS

Dementia was associated with an - 0.241 standard deviation (sd) change in social capital (95% CI: - 0.378, - 0.103), dual eligibility with a - 0.461 sd change (95% CI: - 0.611, - 0.310), and the occurrence of both was associated with an additional - 0.236 sd change (95% CI: - 0.525, - 0.053). 30-day readmission rates were 14.47% over the study period. In both adjusted and unadjusted models, social capital was associated with small and nonsignificant differences in 30-day readmissions. These effects did not vary across dementia status and socioeconomic status.

CONCLUSIONS

Dementia and dual eligibility were associated with lower social capital, but social capital was not associated with the risk of readmission for any population.

Out-of-Network Bills for Privately Insured Patients Undergoing Elective Surgery With In-Network Primary Surgeons and Facilities

IMPORTANCE

Privately insured patients who receive care from in-network physicians may receive unexpected out-of-network bills ("surprise bills") from out-of-network clinicians they did not choose. In elective surgery, this can occur if patients choose in-network surgeons and hospitals but receive out-of-network bills from other involved clinicians.

OBJECTIVE

To evaluate out-of-network billing across common elective operations performed with in-network primary surgeons and facilities.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective analysis of claims data from a large US commercial insurer, representing 347 356 patients who had undergone 1 of 7 common elective operations (arthroscopic meniscal repair [116 749]; laparoscopic cholecystectomy [82 372]; hysterectomy [67 452]; total knee replacement [42 313]; breast lumpectomy [18 018]; colectomy [14 074]; coronary artery bypass graft surgery [6378]) by an in-network primary surgeon at an in-network facility between January 1, 2012, and September 30, 2017. Follow-up ended November 8, 2017.

EXPOSURE

Patient, clinician, and insurance factors potentially related to out-of-network bills.

MAIN OUTCOMES AND MEASURES

The primary outcome was the proportion of episodes with out-of-network bills. The secondary outcome was the estimated potential balance bill associated with out-of-network bills from each surgical procedure, calculated as total out-of-network charges less the typical in-network price for the same service.

RESULTS

Among 347 356 patients (mean age, 48 [SD, 11] years; 66% women) who underwent surgery with in-network primary surgeons and facilities, 20.5% of episodes (95% CI, 19.4%-21.7%) had an out-of-network bill. In these episodes, the mean potential balance bill per episode was $2011 (95% CI, $1866-$2157) when present. Out-of-network bills were associated with surgical assistants in 37% of these episodes; when present, the mean potential balance bill was $3633 (95% CI, $3384-$3883). Out-of-network bills were associated with anesthesiologists in 37% of episodes; when present, the mean potential balance bill was $1219 (95% CI, $1049-$1388). Membership in health insurance exchange plans, compared with nonexchange plans, was associated with a significantly higher risk of out-of-network bills (27% vs 20%, respectively; risk difference, 6% [95% CI, 3.9%-8.9%]; P < .001). Surgical complications were associated with a significantly higher risk of out-of-network bills, compared with episodes with no complications (28% vs 20%, respectively; risk difference, 7% [95% CI, 5.8%-8.8%]; P < .001). Among 83 021 procedures performed at ambulatory surgery centers with in-network primary surgeons, 6.7% (95% CI, 5.8%-7.7%) included an out-of-network facility bill and 17.2% (95% CI, 15.7%-18.8%) included an out-of-network professional bill.

CONCLUSIONS AND RELEVANCE

In this retrospective analysis of commercially insured patients who had undergone elective surgery at in-network facilities with in-network primary surgeons, a substantial proportion of operations were associated with out-of-network bills.

Who Will be the Costliest Patients? Using Recent Claims to Predict Expensive Surgical Episodes

INTRODUCTION

Surgery accounts for almost half of inpatient spending, much of which is concentrated in a subset of high-cost patients. To study the effects of surgeon and hospital characteristics on surgical expenditures, a way to adjust for patient characteristics is essential.

DESIGN

Using 100% Medicare claims data, we identified patients aged 66-99 undergoing elective inpatient surgery (coronary artery bypass grafting, colectomy, and total hip/knee replacement) in 2014. We calculated price-standardized Medicare payments for the surgical episode from admission through 30 days after discharge (episode payments). On the basis of predictor variables from 2013, that is, Elixhauser comorbidities, hierarchical condition categories, Medicare's Chronic Conditions Warehouse (CCW), and total spending, we constructed models to predict the costs of surgical episodes in 2014.

RESULTS

All sources of comorbidity data performed well in predicting the costliest cases (Spearman correlation 0.86-0.98). Models on the basis of hierarchical condition categories had slightly superior performance. The costliest quintile of patients as predicted by the model captured 35%-45% of the patients in each procedure's actual costliest quintile. For example, in hip replacement, 44% of the costliest quintile was predicted by the model's costliest quintile.

CONCLUSIONS

A significant proportion of surgical spending can be predicted using patient factors on the basis of readily available claims data. By adjusting for patient factors, this will facilitate future research on unwarranted variation in episode payments driven by surgeons, hospitals, or other market forces.

Changes in coding of pneumonia and impact on the Hospital Readmission Reduction Program

OBJECTIVE

To evaluate whether changes in diagnosis assignment explain reductions in 30-day readmission for patients with pneumonia following the Hospital Readmission Reduction Program (HRRP).

DATA SOURCES

100 percent MedPAR, 2008-2015.

STUDY DESIGN

Retrospective cohort study of Medicare discharges in HRRP-eligible hospitals. Outcomes were 30-day readmission rates for pneumonia under a "narrow" definition (used for the HRRP until October 2015; n = 2 288 644) and a "broad" definition that included certain diagnoses of sepsis and aspiration pneumonia (used since October 2015; n = 3 618 215). We estimated changes in 30-day readmissions in the pre-HRRP period (January 2008-March 2010), the HRRP implementation period (April 2010-September 2012), and the HRRP penalty period (October 2012-June 2015).

PRINCIPAL FINDINGS

Under the narrow definition, adjusted annual readmission rates changed by +0.07 percentage points (pp) during the pre-HRRP period (95% CI: -0.03 pp, +0.18 pp), -1.07 pp during HRRP implementation (95% CI: -1.15 pp, -0.99 pp), and -0.09 pp during the penalty period (95% CI: -0.18 pp, -0.00 pp). Under the broad definition, 30-day readmissions changed by +0.21 pp during the pre-HRRP period (95% CI: +0.12 pp, +0.30 pp), -1.28 pp during HRRP implementation (95% CI: -1.35 pp, -1.21 pp), and -0.09 pp during the penalty period (95% CI: -0.16 pp, -0.02 pp).

CONCLUSIONS

Changes in the coding of inpatient pneumonia admissions do not explain readmission reduction following the HRRP.

Changes in hospital safety following penalties in the US Hospital Acquired Condition Reduction Program: retrospective cohort study

OBJECTIVE

To evaluate the association between hospital penalization in the US Hospital Acquired Condition Reduction Program (HACRP) and subsequent changes in clinical outcomes.

DESIGN

Regression discontinuity design applied to a retrospective cohort from inpatient Medicare claims.

SETTING

3238 acute care hospitals in the United States.

PARTICIPANTS

Medicare fee-for-service beneficiaries discharged from acute care hospitals between 23 July 2014 and 30 November 2016 and eligible for at least one targeted hospital acquired condition (n=15 470 334).

INTERVENTION

Hospital receipt of a penalty in the first year of the HACRP.

MAIN OUTCOME MEASURES

Episode level count of targeted hospital acquired conditions per 1000 episodes, 30 day readmissions, and 30 day mortality.

RESULTS

Of 724 hospitals penalized under the HACRP in fiscal year 2015, 708 were represented in the study. Mean counts of hospital acquired conditions were 2.72 per 1000 episodes for penalized hospitals and 2.06 per 1000 episodes for non-penalized hospitals; 30 day readmissions were 14.4% and 14.0%, respectively, and 30 day mortality was 9.0% for both hospital groups. Penalized hospitals were more likely to be large, teaching institutions, and have a greater share of patients with low socioeconomic status than non-penalized hospitals. HACRP penalties were associated with a non-significant change of -0.16 hospital acquired conditions per 1000 episodes (95% confidence interval -0.53 to 0.20), -0.36 percentage points in 30 day readmission (-1.06 to 0.33), and -0.04 percentage points in 30 day mortality (-0.59 to 0.52). No clear patterns of clinical improvement were observed across hospital characteristics.

CONCLUSIONS

Penalization was not associated with significant changes in rates of hospital acquired conditions, 30 day readmission, or 30 day mortality, and does not appear to drive meaningful clinical improvements. By disproportionately penalizing hospitals caring for more disadvantaged patients, the HACRP could exacerbate inequities in care.

Association Between Medicare Policy Reforms and Changes in Hospitalized Medicare Beneficiaries' Severity of Illness

IMPORTANCE

The measured severity of illness of hospitalized Medicare beneficiaries has increased. Whether this change is associated with payment reforms, concentrated among hospitalizations with principal diagnoses targeted by payment reform, and reflective of true increases in severity of illness is unknown.

OBJECTIVES

To assess whether the expansion of secondary diagnosis codes in January 2011 and the incentive payments for health information technology under the US Health Information Technology for Economic and Clinical Health Act were associated with changes in measured severity of illness and whether those changes are reflective of true increases in underlying patient severity.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study of Medicare fee-for-service beneficiary discharges (N = 47 951 443) between January 1, 2008, and August 31, 2015, used a regression-discontinuity design to evaluate changes in measured severity of illness after the expansion of secondary diagnoses. Discharge-level linear regression model with hospital fixed effects was used to evaluate changes in measured severity of illness after hospitals' receipt of incentives for health information technology. The change in predictive accuracy of measured severity of illness on 30-day readmissions after the implementation of both policies was evaluated. Data analysis was performed from November 1, 2018, to March 5, 2019.

MAIN OUTCOMES AND MEASURES

The primary outcome was patients' measured severity of illness determined by the number of condition categories from secondary discharge diagnosis codes. Measured severity of illness for diagnoses commonly targeted by Medicare policies and untargeted diagnoses was assessed.

RESULTS

In total, 47 951 443 discharges at 2850 hospitals were included. In 2008, these beneficiaries included 3 882 672 women (58.5%) with a mean (SD) age of 78.5 (8.4) years. In 2014, the discharges included 3 377 137 women (57.8%) with the mean (SD) age of 78.4 (8.7) years. The Centers for Medicare & Medicaid Services expansion of secondary diagnoses was associated with a 0.348 (95% CI, 0.328-0.367; P < .001) change in condition categories for all diagnoses, 0.445 (95% CI, 0.419-0.470; P < .001) for targeted diagnoses, and 0.321 (95% CI, 0.302-0.341; P < .001) for untargeted diagnoses. Health information technology incentives were associated with a 0.013 (95% CI, 0.004-0.022; P = .005) change in condition categories for all diagnoses, 0.195 (95% CI, 0.184-0.207; P < .001) for targeted diagnoses, and -0.016 (95% CI, -0.025 to -0.007; P < .001) for untargeted diagnoses. Minimal improvements in predictive accuracy were observed.

CONCLUSIONS AND RELEVANCE

Changes in Centers for Medicare & Medicaid Services policies appear to be associated with increases in measured severity of illness; these increases do not appear to reflect substantive changes in true patient severity.

Association of Coded Severity With Readmission Reduction After the Hospital Readmissions Reduction Program

This study uses the Medicare Provider Analysis and Review file to examine whether coded severity of illness is associated with reduced rates of readmission after implementation of the Hospital Readmissions Reduction Program.

A randomized clinical trial of an identity intervention programme for women with eating disorders

OBJECTIVE

Findings of a randomized trial of an identity intervention programme (IIP) designed to build new positive self-schemas that are separate from other conceptions of the self in memory as the means to promote improved health in women diagnosed with eating disorders are reported.

METHOD

After baseline data collection, women with anorexia nervosa or bulimia nervosa were randomly assigned to IIP (n = 34) or supportive psychotherapy (SPI) (n = 35) and followed at 1, 6, and 12 months post-intervention.

RESULTS

The IIP and supportive psychotherapy were equally effective in reducing eating disorder symptoms at 1 month post-intervention, and changes were stable through the 12-month follow-up period. The IIP tended to be more effective in fostering development of positive self-schemas, and the increase was stable over time. Regardless of baseline level, an increase in the number of positive self-schemas between pre-intervention and 1-month post-intervention predicted a decrease in desire for thinness and an increase in psychological well-being and functional health over the same period.

DISCUSSION

A cognitive behavioural intervention that focuses on increasing the number of positive self-schemas may be central to improving emotional health in women with anorexia nervosa and bulimia nervosa.