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Objective The objective of this study was to examine variation in hospital responses to the Centers for Medicare and Medicaid's expansion of allowable secondary diagnoses in January 2011 and its association with financial penalties under the Hospital Readmission Reduction Program (HRRP). Data sources/study setting Medicare administrative claims for discharges between July 2008 and June 2011 (N=3102 hospitals). Research design We examined hospital variation in response to the expansion of secondary diagnoses by describing changes in comorbidity coding before and after the policy change. We used random forest machine learning regression to examine hospital characteristics associated with coded severity. We then used a 2-part model to assess whether variation in coded severity was associated with readmission penalties. Results Changes in severity coding varied considerably across hospitals. Random forest models indicated that greater baseline levels of condition categories, case-mix index, and hospital size were associated with larger changes in condition categories. Hospital coding of an additional condition category was associated with a nonsignificant 3.8 percentage point increase in the probability for penalties under the HRRP (SE=2.2) and a nonsignificant 0.016 percentage point increase in penalty amount (SE=0.016). Conclusion Changes in patient coded severity did not affect readmission penalties.

BACKGROUND: The Hospital Acquired Conditions Reduction Program (HACRP) from the Centers for Medicare and Medicaid Services reduces Medicare payments to hospitals with high rates of 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. OBJECTIVE: To compare the reported savings to CMS from financial penalties levied under the HACRP with savings resulting from potential reductions in HACs. DESIGN: We evaluated the association between HACs and 90-day episode spending (adjusted to 2015 dollars). We then estimated potential annual savings to CMS if there was a relative decrease in incidence of all HACs by 1 – 20% and compared them to the actual collected HACRP penalties reported by CMS in 2015. DATA SOURCES: 20% Medicare claims data between January 1, 2009 and September 30, 2014. PARTICIPANTS: Medicare fee-for-service beneficiaries aged 65 – 115 who were discharged from an acute care hospital and who met denominator criteria for any of the eight HACs that comprise the AHRQ Patient Safety Indicator (PSI)-90 score that was targeted under the HACRP (n = 7,707,553). OUTCOME: Total price-standardized 90-day episode spending. 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 – 44 million per year, an amount much lower than the $360 million penalties levied upon 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.

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.

Objective We sought to assess the potential changes in Medicare payments and clinical outcomes of referring high-risk surgical patients to local high-quality hospitals within small geographic areas. Summary background data Previous studies have documented a benefit in referring high-risk patients to high-quality hospitals on a national basis, suggesting selective referral as a mechanism to improve the value of surgical care. Practically, referral of patients should be done within small geographic regions; however, the benefit of local selective referral has not been studied. Methods We analyzed data on elderly Medicare beneficiaries undergoing any of 4 elective inpatient surgical procedures between 2012 and 2014. Hospitals were categorized into Metropolitan Statistical Areas by zip code and stratified into quintiles of quality based on rates of postoperative complications. Patient risk was calculated by modeling the predicted risk of a postoperative complication. Medicare payments for each surgical episode were calculated. Distances between patients' home zip code and high- and low-quality hospitals were calculated. Results One quarter of high-risk patients underwent surgery at a low-quality hospital despite the availability of a high-quality hospital in their small geographic area. Shifting these patients to a local high-quality hospital would decrease spending 12% to 37% ($2,500 for total knee and hip replacement, $6,700 for colectomy, and $11,400 for lung resection). Approximately 45% of high-risk patients treated at low-quality hospitals could travel a shorter distance to reach a high-quality hospital than the low-quality hospital they received care at. Conclusions Complication rates and Medicare payments are significantly lower for high-risk patients treated at local high-quality hospitals. This suggests triaging high-risk patients to local high-quality hospitals within small geographic areas may serve as a template for improving the value of surgical care.

"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.

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.

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.To evaluate out-of-network billing across common elective operations performed with in-network primary surgeons and facilities.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.Patient, clinician, and insurance factors potentially related to out-of-network bills.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.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.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.

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.

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.

BACKGROUND: Referring patients to high-quality hospitals for complex procedures may improve outcomes. This is most feasible within small geographic areas. However, access to specialized surgical procedures may be an implementation barrier. We sought to determine the availability of high-quality hospitals performing pancreatectomy and the potential benefit and travel burden of referral within small geographic areas. METHODS: We identified elderly Medicare beneficiaries undergoing pancreatectomy between 2012 and 2014. Hospitals were stratified into quintiles of quality based on postoperative complication rates. Patient risk was assessed by modeling the predicted risk of developing a postoperative complication. The geographic unit of analysis was Metropolitan Statistical Area (MSA). Hospitals were categorized into MSA by zip-code. Travel distance was calculated using patient and hospital zip code. RESULTS: Among high-risk patients, 40.7% received care at the lowest-quality hospitals even though 80% had a high-quality hospital in the same MSA. Shifting these patients from low- to high-quality hospitals would decrease serious complications from 46.6% to 21.9% (P

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.

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.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.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.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.