Association of the New Peer Group-Stratified Method With the Reclassification of Penalty Status in the Hospital Readmission Reduction Program

IMPORTANCE

Since the introduction of the Hospital Readmission Reduction Program (HRRP), readmission penalties have been applied disproportionately to institutions that serve low-income populations. To address this concern, the US Centers for Medicare & Medicaid introduced a new, stratified payment adjustment method in fiscal year (FY; October 1 to September 30) 2019.

OBJECTIVE

To determine whether the introduction of a new, stratified payment adjustment method was associated with an alteration in the distribution of penalties among hospitals included in the HRRP.

DESIGN, SETTING, AND PARTICIPANTS

In this retrospective cross-sectional study, US hospitals included in the HRRP for FY 2018 and FY 2019 were identified. Penalty status of participating hospitals for FY 2019 was determined based on nonstratified HRRP methods and the new, stratified payment adjustment method. Hospitals caring for the highest proportion of patients enrolled in both Medicare and Medicaid based on quintile were assigned to the low-socioeconomic status (SES) group.

EXPOSURES

Nonstratified and stratified Centers for Medicare & Medicaid payment adjustment methods.

MAIN OUTCOMES AND MEASURES

Net reclassification of penalties among all hospitals and hospitals in the low-SES group, in states participating in Medicaid expansion, and for 4 targeted medical conditions (acute myocardial infarction, heart failure, chronic obstructive pulmonary disease, and pneumonia).

RESULTS

Penalty status by both payment adjustment methods (nonstratified and stratified) was available for 3173 hospitals. For FY 2019, the new, stratified payment method was associated with penalties for 75.04% of hospitals (2381 of 3173), while the old, nonstratified method was associated with penalties for 79.07% (2509 hospitals), resulting in a net down-classification in penalty status for all hospitals by 4.03 percentage points (95% CI, 2.95-5.11; P < .001). For the 634 low-SES hospitals in the sample, the new method was associated with penalties for 77.60% of hospitals (492 of 634), while the old method was associated with penalties for 91.64% (581 hospitals), resulting in a net down-classification in penalty status of 14.04 percentage points (95% CI, 11.18-16.90; P < .001). Among hospitals that were not low SES (quintiles 1-4), the new payment method was associated with a small decrease in penalty status (1928 vs 1889; net down-classification, 1.54 percentage points; 95% CI, 0.38-2.69; P = .01). Among target medical conditions, the greatest reduction in penalties was observed among cardiovascular conditions (net down-classification, 6.18 percentage points; 95% CI, 4.96-7.39; P < .001).

CONCLUSIONS AND RELEVANCE

The new, stratified payment adjustment method for the HRRP was associated with a reduction in penalties across hospitals included in the program; the greatest reductions were observed among hospitals in the low-SES group, lessening but not eliminating the previously unbalanced penalty burden carried by these hospitals. Additional public policy research efforts are needed to achieve equitable payment adjustment models for all hospitals.

Predictive risk score for unplanned 30-day rehospitalizations in the French universal health care system based on a medico-administrative database

Background

Reducing unplanned rehospitalizations is one of the priorities of health care policies in France and other Western countries. An easy-to-use algorithm for identifying patients at higher risk of rehospitalizations would help clinicians prioritize actions and care concerning discharge transitions. Our objective was to develop a predictive unplanned 30-day all-cause rehospitalization risk score based on the French hospital medico-administrative database.

Methods

This was a retrospective cohort study of all 2015 discharges from acute-care inpatient hospitalizations in a tertiary-care university center comprising four hospitals. The study endpoint was unplanned 30-day all-cause rehospitalization via emergency departments, and we collected sociodemographic, clinical, and hospital characteristics based on hospitalization database computed for reimbursement of fees. We derived a predictive rehospitalization risk score using a split-sample design and multivariate logistic regression, and we compared the discriminative properties with the LACE index risk-score.

Result

Our analysis included 118,650 hospitalizations, of which 4,127 (3.5%) led to rehospitalizations via emergency departments. Variables independently associated with rehospitalization were age, gender, state-funded medical assistance, as well as disease category and severity, Charlson comorbidity index, hospitalization via emergency departments, length of stay (LOS), and previous hospitalizations 6 months before. The predictive rehospitalization risk score yielded satisfactory discriminant properties (C statistic: 0.74) exceeding the LACE index (0.66).

Conclusion

Our findings indicate that the possibility of unplanned rehospitalization remains high for some patient characteristics, indicating that targeted interventions could be beneficial for patients at the greatest risk. We developed an easy-to-use predictive rehospitalization risk-score of unplanned 30-day all-cause rehospitalizations with satisfactory discriminant properties. Future works should, however, explore if other data from electronic medical records and other databases could improve the accuracy of our predictive rehospitalization risk score based on medico-administrative data.

Association of the Hospital Readmissions Reduction Program With Mortality Among Medicare Beneficiaries Hospitalized for Heart Failure, Acute Myocardial Infarction, and Pneumonia

IMPORTANCE

The Hospital Readmissions Reduction Program (HRRP) has been associated with a reduction in readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia. It is unclear whether the HRRP has been associated with change in patient mortality.

OBJECTIVE

To determine whether the HRRP was associated with a change in patient mortality.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cohort study of hospitalizations for HF, AMI, and pneumonia among Medicare fee-for-service beneficiaries aged at least 65 years across 4 periods from April 1, 2005, to March 31, 2015. Period 1 and period 2 occurred before the HRRP to establish baseline trends (April 2005-September 2007 and October 2007-March 2010). Period 3 and period 4 were after HRRP announcement (April 2010 to September 2012) and HRRP implementation (October 2012 to March 2015).

EXPOSURES

Announcement and implementation of the HRRP.

MAIN OUTCOMES AND MEASURES

Inverse probability-weighted mortality within 30 days of discharge following hospitalization for HF, AMI, and pneumonia, and stratified by whether there was an associated readmission. An additional end point was mortality within 45 days of initial hospital admission for target conditions.

RESULTS

The study cohort included 8.3 million hospitalizations for HF, AMI, and pneumonia, among which 7.9 million (mean age, 79.6 [8.7] years; 53.4% women) were alive at discharge. There were 3.2 million hospitalizations for HF, 1.8 million for AMI, and 3.0 million for pneumonia. There were 270 517 deaths within 30 days of discharge for HF, 128 088 for AMI, and 246 154 for pneumonia. Among patients with HF, 30-day postdischarge mortality increased before the announcement of the HRRP (0.27% increase from period 1 to period 2). Compared with this baseline trend, HRRP announcement (0.49% increase from period 2 to period 3; difference in change, 0.22%, P = .01) and implementation (0.52% increase from period 3 to period 4; difference in change, 0.25%, P = .001) were significantly associated with an increase in postdischarge mortality. Among patients with AMI, HRRP announcement was associated with a decline in postdischarge mortality (0.18% pre-HRRP increase vs 0.08% post-HRRP announcement decrease; difference in change, -0.26%; P = .01) and did not significantly change after HRRP implementation. Among patients with pneumonia, postdischarge mortality was stable before HRRP (0.04% increase from period 1 to period 2), but significantly increased after HRRP announcement (0.26% post-HRRP announcement increase; difference in change, 0.22%, P = .01) and implementation (0.44% post-HPPR implementation increase; difference in change, 0.40%, P < .001). The overall increase in mortality among patients with HF and pneumonia was mainly related to outcomes among patients who were not readmitted but died within 30 days of discharge. For all 3 conditions, HRRP implementation was not significantly associated with an increase in mortality within 45 days of admission, relative to pre-HRRP trends.

CONCLUSIONS AND RELEVANCE

Among Medicare beneficiaries, the HRRP was significantly associated with an increase in 30-day postdischarge mortality after hospitalization for HF and pneumonia, but not for AMI. Given the study design and the lack of significant association of the HRRP with mortality within 45 days of admission, further research is needed to understand whether the increase in 30-day postdischarge mortality is a result of the policy.

Non-readmission decisions in the intensive care unit under French rules: A nationwide survey of practices

PURPOSE

We investigated, using a multicentre survey of practices in France, the practices of ICU physicians concerning the decision not to readmit to the ICU, in light of current legislation.

MATERIALS AND METHODS

Multicentre survey of practices among French ICU physicians via electronic questionnaire in January 2016. Questions related to respondents' practices regarding re-admission of patients to the ICU and how these decisions were made. Criteria were evaluated by the health care professionals as regards importance for non-readmission.

RESULTS

In total, 167 physicians agreed to participate, of whom 165 (99%) actually returned a completed questionnaire from 58 ICUs. Forty-five percent were aged <35 years, 74% were full-time physicians. The findings show that decisions for non-readmission are taken at the end of the patient's stay (87%), using a collegial decision-making procedure (89% of cases); 93% reported that this decision was noted in the patient's medical file. While 73% indicated that the family/relatives were informed of non-readmission decisions, only 29% reported informing the patient, and 91% considered that non-readmission decisions are an integral part of the French legislative framework.

CONCLUSION

This study shows that decisions not to re-admit a patient to the ICU need to be formally materialized, and anticipated by involving the patient and family in the discussions, as well as the other healthcare providers that usually care for the patient. The optimal time to undertake these conversations is likely best decided on a case-by-case basis according to each patient's individual characteristics.

Compulsory community and involuntary outpatient treatment for people with severe mental disorders

BACKGROUND

It is controversial whether compulsory community treatment (CCT) for people with severe mental illness (SMI) reduces health service use, or improves clinical outcome and social functioning.

OBJECTIVES

To examine the effectiveness of compulsory community treatment (CCT) for people with severe mental illness (SMI).

SEARCH METHODS

We searched the Cochrane Schizophrenia Group's Study-Based Register of Trials (2003, 2008, 2012, 8 November 2013, 3 June 2016). We obtained all references of identified studies and contacted authors where necessary.

SELECTION CRITERIA

All relevant randomised controlled clinical trials (RCTs) of CCT compared with standard care for people with SMI (mainly schizophrenia and schizophrenia-like disorders, bipolar disorder, or depression with psychotic features). Standard care could be voluntary treatment in the community or another pre-existing form of CCT such as supervised discharge.

DATA COLLECTION AND ANALYSIS

Authors independently selected studies, assessed their quality and extracted data. We used Cochrane's tool for assessing risk of bias. For binary outcomes, we calculated a fixed-effect risk ratio (RR), its 95% confidence interval (95% CI) and, where possible, the number needed to treat for an additional beneficial outcome (NNTB). For continuous outcomes, we calculated a fixed-effect mean difference (MD) and its 95% CI. We used the GRADE approach to create 'Summary of findings' tables for key outcomes and assessed the risk of bias of these findings.

MAIN RESULTS

The review included three studies (n = 749). Two were based in the USA and one in England. The English study had the least bias, meeting three out of the seven criteria of Cochrane's tool for assessing risk of bias. The two other studies met only one criterion, the majority being rated unclear.Two trials from the USA (n = 416) compared court-ordered 'outpatient commitment' (OPC) with entirely voluntary community treatment. There were no significant differences between OPC and voluntary treatment by 11 to 12 months in any of the main health service or participant level outcome indices: service use - readmission to hospital (2 RCTs, n= 416, RR 0.98, 95% CI 0.79 to 1.21, low-quality evidence); service use - compliance with medication (2 RCTs, n = 416, RR 0.99, 95% CI 0.83 to 1.19, low-quality evidence); social functioning - arrested at least once (2 RCTs, n = 416, RR 0.97, 95% CI 0.62 to 1.52, low-quality evidence); social functioning - homelessness (2 RCTs, n = 416, RR 0.67, 95% CI 0.39 to 1.15, low-quality evidence); or satisfaction with care - perceived coercion (2 RCTs, n = 416, RR 1.36, 95% CI 0.97 to 1.89, low-quality evidence). However, one trial found the risk of victimisation decreased with OPC (1 RCT, n = 264, RR 0.50, 95% CI 0.31 to 0.80, low-quality evidence).The other RCT compared community treatment orders (CTOs) with less intensive and briefer supervised discharge (Section 17) in England. The study found no difference between the two groups for either the main health service outcomes including readmission to hospital by 12 months (1 RCT, n = 333, RR 0.99, 95% CI 0.74 to 1.32, moderate-quality evidence), or any of the participant level outcomes. The lack of any difference between the two groups persisted at 36 months' follow-up.Combining the results of all three trials did not alter these results. For instance, participants on any form of CCT were no less likely to be readmitted than participants in the control groups whether on entirely voluntary treatment or subject to intermittent supervised discharge (3 RCTs, n = 749, RR for readmission to hospital by 12 months 0.98, 95% CI 0.82 to 1.16 moderate-quality evidence). In terms of NNTB, it would take 142 orders to prevent one readmission. There was no clear difference between groups for perceived coercion by 12 months (3 RCTs, n = 645, RR 1.30, 95% CI 0.98 to 1.71, moderate-quality evidence).There were no data for adverse effects.

AUTHORS' CONCLUSIONS

These review data show CCT results in no clear difference in service use, social functioning or quality of life compared with voluntary care or brief supervised discharge. People receiving CCT were, however, less likely to be victims of violent or non-violent crime. It is unclear whether this benefit is due to the intensity of treatment or its compulsory nature. Short periods of conditional leave may be as effective (or non-effective) as formal compulsory treatment in the community. Evaluation of a wide range of outcomes should be considered when this legislation is introduced. However, conclusions are based on three relatively small trials, with high or unclear risk of blinding bias, and low- to moderate-quality evidence. In addition, clinical trials may not fully reflect the potential benefits of this complex intervention.

Burden and Timing of Hospitalizations in Heart Failure: A Community Study

OBJECTIVE

To study the temporal distribution and causes of hospitalizations after heart failure (HF) diagnosis.

PATIENTS AND METHODS

Hospitalizations were studied in 1972 Olmsted County, Minnesota, residents with incident HF from January 1, 2000, to December 31, 2011. All hospitalizations were examined for the 2 years following incident HF, and each was categorized as due to HF, other cardiovascular causes, or noncardiovascular causes. Negative binomial regression examined associations between time periods (0-30, 31-182, 183-365, and 366-730 days after diagnosis) and hospitalizations.

RESULTS

During the 2 years after diagnosis, 3495 hospitalizations were observed among 1336 of the 1972 patients with HF. The age- and sex-adjusted rates of hospitalizations were highest in the first 30 days after diagnosis (3.33 per person-year vs 1.33, 1.07, and 1.00 per person-year for 31-182 days, 183-365 days, and 366-730 days, respectively). The rates of hospitalizations were similar across sex, presentation of HF (inpatient or outpatient), and type of HF (preserved or reduced ejection fraction). Patients diagnosed as inpatients who had long hospital stays (>5 days) experienced more than a 30% increased risk of rehospitalization within 30 days of dismissal. Importantly, most hospitalizations (2222 of 3495 [63.6%]) were due to noncardiovascular causes, and a minority (440 of 3495 [12.6%]) were due to HF. The rates of noncardiovascular hospitalizations were higher than those for HF or other cardiovascular hospitalizations across all follow-up for all time periods after HF.

CONCLUSION

Patients with HF experience high rates of hospitalizations, particularly within the first 30 days, and mostly for noncardiovascular causes. To reduce hospitalizations in patients with HF, an integrated approach focusing on comorbidities is required.

Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions

IMPORTANCE

Readmission rates declined after announcement of the Hospital Readmission Reduction Program (HRRP), which penalizes hospitals for excess readmissions for acute myocardial infarction (AMI), heart failure (HF), and pneumonia.

OBJECTIVE

To compare trends in readmission rates for target and nontarget conditions, stratified by hospital penalty status.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective cohort study of Medicare fee-for-service beneficiaries older than 64 years discharged between January 1, 2008, and June 30, 2015, from 2214 penalty hospitals and 1283 nonpenalty hospitals. Difference-interrupted time-series models were used to compare trends in readmission rates by condition and penalty status.

EXPOSURE

Hospital penalty status or target condition under the HRRP.

MAIN OUTCOMES AND MEASURES

Thirty-day risk adjusted, all-cause unplanned readmission rates for target and nontarget conditions.

RESULTS

The study included 48 137 102 hospitalizations of 20 351 161 Medicare beneficiaries. In January 2008, the mean readmission rates for AMI, HF, pneumonia, and nontarget conditions were 21.9%, 27.5%, 20.1%, and 18.4%, respectively, at hospitals later subject to financial penalties and 18.7%, 24.2%, 17.4%, and 15.7% at hospitals not subject to penalties. Between January 2008 and March 2010, prior to HRRP announcement, readmission rates were stable across hospitals (except AMI at nonpenalty hospitals). Following announcement of HRRP (March 2010), readmission rates for both target and nontarget conditions declined significantly faster for patients at hospitals later subject to financial penalties compared with those at nonpenalized hospitals (for AMI, additional decrease of -1.24 [95% CI, -1.84 to -0.65] percentage points per year relative to nonpenalty discharges; for HF, -1.25 [95% CI, -1.64 to -0.86]; for pneumonia, -1.37 [95% CI, -1.80 to -0.95]; and for nontarget conditions, -0.27 [95% CI, -0.38 to -0.17]; P < .001 for all). For penalty hospitals, readmission rates for target conditions declined significantly faster compared with nontarget conditions (for AMI, additional decline of -0.49 [95% CI, -0.81 to -0.16] percentage points per year relative to nontarget conditions [P = .004]; for HF, -0.90 [95% CI, -1.18 to -0.62; P < .001]; and for pneumonia, -0.57 [95% CI, -0.92 to -0.23; P < .001]). In contrast, among nonpenalty hospitals, readmissions for target conditions declined similarly or more slowly compared with nontarget conditions (for AMI, additional increase of 0.48 [95% CI, 0.01-0.95] percentage points per year [P = .05]; for HF, 0.08 [95% CI, -0.30 to 0.46; P = .67]; for pneumonia, 0.53 [95% CI, 0.13-0.93; P = .01]). After HRRP implementation in October 2012, the rate of change for readmission rates plateaued (P < .05 for all except pneumonia at nonpenalty hospitals), with the greatest relative change observed among hospitals subject to financial penalty.

CONCLUSIONS AND RELEVANCE

Medicare fee-for-service patients at hospitals subject to penalties under the HRRP had greater reductions in readmission rates compared with those at nonpenalized hospitals. Changes were greater for target vs nontarget conditions for patients at the penalized hospitals but not at the other hospitals.

Opinions on the Hospital Readmission Reduction Program: results of a national survey of hospital leaders

OBJECTIVES

To determine the opinions of US hospital leadership on the Hospital Readmissions Reduction Program (HRRP), a national mandatory penalty-for-performance program.

STUDY DESIGN

We developed a survey about federal readmission policies. We used a stratified sampling design to oversample hospitals in the highest and lowest quintile of performance on readmissions, and hospitals serving a high proportion of minority patients.

METHODS

We surveyed leadership at 1600 US acute care hospitals that were subject to the HRRP, and achieved a 62% response rate. Results were stratified by the size of the HRRP penalty that hospitals received in 2013, and adjusted for nonresponse and sampling strategy.

RESULTS

Compared with 36.1% for public reporting of readmission rates and 23.7% for public reporting of discharge processes, 65.8% of respondents reported that the HRRP had a "great impact" on efforts to reduce readmissions. The most common critique of the HRRP penalty was that it did not adequately account for differences in socioeconomic status between hospitals (75.8% "agree" or "agree strongly"); other concerns included that the penalties were "much too large" (67.7%), and hospitals' inability to impact patient adherence (64.1%). These sentiments were each more common in leaders of hospitals with higher HRRP penalties.

CONCLUSIONS

The HRRP has had a major impact on hospital leaders' efforts to reduce readmission rates, which has implications for the design of future quality improvement programs. However, leaders are concerned about the size of the penalties, lack of adjustment for socioeconomic and clinical factors, and hospitals' inability to impact patient adherence and postacute care. These concerns may have implications as policy makers consider changes to the HRRP, as well as to other Medicare value-based payment programs that contain similar readmission metrics.

Reconviction and revocation rates in Flanders after medium security treatment

AIM

To examine the criminal outcome of Flemish forensic psychiatric patients ('internees') after medium security treatment. Also, the effect of conditional release on recidivism of two subgroups (internees under conditional release and internees who received unconditional release) was examined.

METHOD

Reconviction rates and revocation rates were collected for all participants. Kaplan-Meier survival analyses were used to investigate recidivism rates while controlling for time at risk.

RESULTS

During the 10-year period, 502 offenders were discharged from medium security treatment. Over a follow-up period averaging 3.6years, 7.4% of discharged patients were reconvicted or received a new 'not guilty by reason of insanity' (NGRI) verdict for a violent offence. One-quarter of the population had their conditional release revoked. Part of the study population was granted unconditional release. Reconviction rates were higher after unconditional release in comparison to conditional release.

CONCLUSIONS

The results of this study suggest that the court supervision of NGRI patients in Flanders is effective in protecting the community from further offending.

Vulnerable Hospitals and Cancer Surgery Readmissions: Insights into the Unintended Consequences of the Patient Protection and Affordable Care Act

BACKGROUND

Penalties from the Hospital Readmission Reduction Program can push financially strained, vulnerable patient-serving hospitals into additional hardship. In this study, we quantified the association between vulnerable hospitals and readmissions and examined the respective contributions of patient- and hospital-related factors.

METHODS

A total of 110,857 patients who underwent major cancer operations were identified from the 2004-2011 State Inpatient Database of California. Vulnerable hospitals were defined as either self-identified safety net hospitals (SNHs) or hospitals with a high percentage of Medicaid patients (high Medicaid hospitals [HMHs]). We used multivariable logistic regression to determine the association between vulnerable hospitals and readmission. Patient and hospital contributions to the elevation in odds of readmission were assessed by comparing estimates from models with different subsets of predictors.

RESULTS

Of the 355 hospitals, 13 were SNHs and 31 were HMHs. After adjusting for Hospital Readmission Reduction Program variables, SNHs had higher 30-day (odds ratio [OR] = 1.32; 95% CI, 1.18-1.47), 90-day (OR = 1.28; 95% CI, 1.18-1.38), and repeated readmissions (OR = 1.33; 95% CI, 1.18-1.49); HMHs also had higher 30-day (OR = 1.18; 95% CI, 1.05-1.32), 90-day (OR = 1.28; 95% CI, 1.16-1.42), and repeated readmissions (OR = 1.24; 95% CI, 1.01-1.54). Compared with patient characteristics, hospital factors accounted for a larger proportion of the increase in odds of readmission among SNHs (60% to 93% vs 24% to 39%), but a smaller proportion among HMHs (9% to 15% vs 60% to 115%).

CONCLUSIONS

Vulnerable status of hospitals is associated with higher readmission rates after major cancer surgery. These findings reinforce the call to account for socioeconomic variables in risk adjustments for hospitals who serve a disproportionate share of disadvantaged patients.

Readmissions, Observation, and the Hospital Readmissions Reduction Program

BACKGROUND

The Hospital Readmissions Reduction Program, which is included in the Affordable Care Act (ACA), applies financial penalties to hospitals that have higher-than-expected readmission rates for targeted conditions. Some policy analysts worry that reductions in readmissions are being achieved by keeping returning patients in observation units instead of formally readmitting them to the hospital. We examined the changes in readmission rates and stays in observation units over time for targeted and nontargeted conditions and assessed whether hospitals that had greater increases in observation-service use had greater reductions in readmissions.

METHODS

We compared monthly, hospital-level rates of readmission and observation-service use within 30 days after hospital discharge among Medicare elderly beneficiaries from October 2007 through May 2015. We used an interrupted time-series model to determine when trends changed and whether changes differed between targeted and nontargeted conditions. We assessed the correlation between changes in readmission rates and use of observation services after adoption of the ACA in March 2010.

RESULTS

We analyzed data from 3387 hospitals. From 2007 to 2015, readmission rates for targeted conditions declined from 21.5% to 17.8%, and rates for nontargeted conditions declined from 15.3% to 13.1%. Shortly after passage of the ACA, the readmission rate declined quickly, especially for targeted conditions, and then continued to fall at a slower rate after October 2012 for both targeted and nontargeted conditions. Stays in observation units for targeted conditions increased from 2.6% in 2007 to 4.7% in 2015, and rates for nontargeted conditions increased from 2.5% to 4.2%. Within hospitals, there was no significant association between changes in observation-unit stays and readmissions after implementation of the ACA.

CONCLUSIONS

Readmission trends are consistent with hospitals' responding to incentives to reduce readmissions, including the financial penalties for readmissions under the ACA. We did not find evidence that changes in observation-unit stays accounted for the decrease in readmissions.

Using decision trees to manage hospital readmission risk for acute myocardial infarction, heart failure, and pneumonia

To improve healthcare quality and reduce costs, the Affordable Care Act places hospitals at financial risk for excessive readmissions associated with acute myocardial infarction (AMI), heart failure (HF), and pneumonia (PN). Although predictive analytics is increasingly looked to as a means for measuring, comparing, and managing this risk, many modeling tools require data inputs that are not readily available and/or additional resources to yield actionable information. This article demonstrates how hospitals and clinicians can use their own structured discharge data to create decision trees that produce highly transparent, clinically relevant decision rules for better managing readmission risk associated with AMI, HF, and PN. For illustrative purposes, basic decision trees are trained and tested using publically available data from the California State Inpatient Databases and an open-source statistical package. As expected, these simple models perform less well than other more sophisticated tools, with areas under the receiver operating characteristic (ROC) curve (or AUC) of 0.612, 0.583, and 0.650, respectively, but achieve a lift of at least 1.5 or greater for higher-risk patients with any of the three conditions. More importantly, they are shown to offer substantial advantages in terms of transparency and interpretability, comprehensiveness, and adaptability. By enabling hospitals and clinicians to identify important factors associated with readmissions, target subgroups of patients at both high and low risk, and design and implement interventions that are appropriate to the risk levels observed, decision trees serve as an ideal application for addressing the challenge of reducing hospital readmissions.

Readmission penalties and health insurance expansions: a dispatch from Massachusetts

BACKGROUND

Payers are penalizing hospitals for high readmission rates. It is unknown whether major changes in population insurance coverage can affect readmission rates, despite the Affordable Care Act's coverage expansions coming into effect this year.

OBJECTIVE

To evaluate the impact of a large-scale insurance expansion on hospital readmissions, using Massachusetts' 2006 health reform as a natural experiment.

DESIGN

Difference-in-difference time-series design.

SETTING

All Massachusetts acute-care hospitals.

PATIENTS

Inpatient visits from 2004 to 2010.

MEASUREMENTS

Primary outcome was the hospital 30-day readmission rate. Readmissions to any Massachusetts hospital were tracked.

RESULTS

Decreases in uninsurance rates during and after reform were largely limited to the hospital quartile with the highest prereform uninsurance rates (from 14% uninsured at the start of the reform to 2.9% by the end of the study period). The other hospitals collectively experienced a smaller decline in their uninsured admissions (5.9% at the start of reform to 2.5% by the end of the study period). According to difference-in-difference regression analysis, the highest uninsured hospital quartile experienced a modest increase in their unadjusted readmission rate of 0.6 percentage points (95% confidence interval: 0.1%-1.1%) during the reform period as compared to the other hospital quartiles (P = 0.01). This represents a relative increase of 4.5% in the readmission rate. Risk-adjusted readmission rates showed no corresponding change.

CONCLUSIONS

The Affordable Care Act's insurance expansion may be associated with an increase in unadjusted readmission rates among hospitals that cared for disproportionate numbers of uninsured patients. Risk-adjustment appears to take this effect into account.

Understanding how to improve collaboration between hospitals and primary care in postdischarge care transitions: a qualitative study of primary care leaders' perspectives

BACKGROUND

There is limited collaboration between hospitals and primary care despite parallel efforts to improve postdischarge care transitions.

OBJECTIVE

To understand what primary care leaders perceived as barriers and facilitators to collaboration with hospitals.

METHODS

Qualitative study with in-depth, semistructured interviews of 22 primary care leaders in 2012 from California safety-net clinics.

RESULTS

Major barriers to collaboration included lack of institutional financial incentives for collaboration, competing priorities (e.g., regulatory requirements, strained clinic capacity, financial strain) and mismatched expectations about role and capacity of primary care to improve care transitions. Facilitators included relationship building through interpersonal networking and improving communication and information transfer via electronic health record (EHR) implementation.

CONCLUSIONS

Efforts to improve care transitions should focus on aligning financial incentives, standardizing regulations around EHR interoperability and data sharing, and enhancing opportunities for interpersonal networking.

The cost of preventing readmissions: why surgeons should lead the effort

In accordance with the Affordable Care Act, Medicare has instituted financial penalties for hospitals with 30-day readmission rates that exceed a predetermined value. Currently, this value only considers "excess" readmissions for myocardial infarction, heart failure, and pneumonia with a maximum fine being one per cent of total Medicare reimbursements. In 2015, this penalty will increase to three per cent and encompass more surgical diagnoses. We retrospectively reviewed a database of adult patients undergoing cardiac surgery treated at our institution in 2012 to establish whether patients with readmissions within 30 days of the index operation could have been managed more cost-effectively without readmission. A calculation of cost efficiency was performed to compare the net hospital profit for two scenarios: admitting patients versus hypothetical preventative measures. Of the 576 patients during the study period, a total of 68 (11.8%) patients with unplanned 30-day readmissions were identified. Outpatient management was determined to have been feasible for 18 (26.5%) patients. Whereas the calculated net profit for readmission was $144,000, inclusion of Medicare's penalty resulted in a loss of $11,950. A readmission reduction program with an annual cost exceeding $11,950 would lead to financial loss. The financial implications of Medicare's readmission penalty alone necessitate the development of cost-effective strategies to reduce rehospitalization.

Hospital readmissions: measuring for improvement, accountability, and patients

The Commonwealth Fund and the Institute for Healthcare Improvement convened 15 experts in May 2013 to help address the current controversy over the measurement of hospital readmissions. Experts agreed that Medicare should, through payment and other means, be encouraging greater coordination of care, improvement in care transitions, and mitigation of risks that leave patients vulnerable to readmission. While the current readmissions metric is undoubtedly an imperfect proxy for broader health system failures, it also provides a valuable foundation on which to build a better policy—one that is useful for improvement, fair for accountability, and above all, relevant to patients.

A focus on heart failure

Heart failure patients account for a hefty proportion of readmissions, so hospitals are refining their discharge processes, boosting education for patients and caregivers, and sending community health workers to their homes.

Don't let go of the rope: reducing readmissions by recognizing hospitals' fiduciary duties to their discharged patients

In the early years of the twenty-first century, it was widely speculated that massive, multi-purpose hospitals were becoming the "dinosaurs" of health care, to be largely replaced by community-based clinics providing specialty services on an outpatient basis. Hospitals, however, have roared back to life, in part by reworking their business model. There has been a wave of consolidations and acquisitions (including acquisitions of community-based clinics), with deals valued at $7.9 billion in 2011, the most in a decade, and the number of deals increasing another 18% in 2012. The costs of hospital care are enormous, with 31.5% ($851 billion) of the total health expenditures in the United States in 2011 devoted to these services. Hospitals are (1) placing growing emphasis on increasing revenue and decreasing costs; (2) engaging in pervasive marketing campaigns encouraging patients to view hospitals as an all-purpose care provider; (3) geographically targeting the expansion of their services to "capture" well-insured patients, while placing greater pressure on patients to pay for the services delivered; (4) increasing their size, wealth, and clout, with two-thirds of hospitals undertaking renovations or additional construction and smaller hospitals being squeezed out, and (5) expanding their use of hospital-employed physicians, rather than relying on community-based physicians with hospital privileges, and exercising greater control over medical staff. Hospitals have become so pivotal in the U.S. healthcare system that the Patient Protection and Affordable Care Act of 2010 (PPACA) frequently targeted them as a vehicle to enhance patient safety and control escalating health care costs. One such provision--the Hospital Readmissions Reduction Program, which goes into effect in fiscal year 2013--will reduce payments ordinarily made to hospitals if they have an "excess readmission" rate. It is estimated that adverse events following a hospital discharge impact as many as 19% of all discharged patients. When hospitals and similar health care facilities fail to adequately manage the discharge of their patients, devastating medical emergencies and sizeable healthcare costs can result. The urgency to better manage these discharges is compounded by the fact that the average length of hospital stays continues to shorten, potentially increasing the number of discharged patients who are at considerable risk of relapse. Also exacerbating the problem is a lack of clarity regarding who, if anyone, is responsible for these patients following discharge. Confusion over who bears responsibility for discharge-related preparation and community outreach, concerns about compensation, a lack of clear institutional policies, and the absence of legal mandates that patients be properly prepared for and monitored after discharge all contribute to the potential abandonment of patients at a crucial juncture. Although the PPACA establishes financial incentives for hospitals and similar facilities to combat the long-standing problem of high readmission rates, it does not provide a remedy for patients who have suffered avoidable harm after being discharged without adequate preparation or post-discharge assistance. This omission is particularly problematic as existing legal remedies, including medical malpractice suits, have provided little recourse for patients who have suffered injury that could have been prevented through the implementation of reasonable discharge-related policies. To protect the many patients who are highly vulnerable to complications following discharge and to provide them redress when needed services are not provided, hospitals' obligations to these patients should be recognized for what they are: a fiduciary duty to provide adequate discharge preparation and post-discharge services. The recognition of this duty is driven by changes in the nature of hospital care that enhance the perception that hospitals have become a "big business" that should "carry their own freight." Properly interpreted, this duty requires facilities to implement an appropriate discharge plan and provide post-discharge services for a period of time commensurate with a patient's continuing health risks. Notably, this is not the same as a generalized duty to provide all patients with continuing post-discharge treatment. It is a more limited obligation to offer necessary clarification and direction to patients upon discharge, and to institute a reasonable post-discharge monitoring program for patients with continuing health risks.

Offending prior to first psychiatric contact: a population-based register study

BACKGROUND

There is a well-established association between psychotic disorders and subsequent offending but the extent to which those who develop psychosis might have a prior history of offending is less clear. Little is known about whether the association between illness and offending exists in non-psychotic disorders. The aim of this study was to determine whether the association between mental disorder and offending is present prior to illness onset in psychotic and non-psychotic disorders.

METHOD

In a nested case-control study, cases (n=101,890) with a first psychiatric contact during the period 1995 to 2006 were identified and matched by age and gender to population-based controls (n=2,236,195). Exposure was defined as prior criminal and violent offending.

RESULTS

Males with one offence had an incidence rate ratio (IRR) of 2.32 [95% confidence interval (CI) 2.26-2.40] for psychiatric admission whereas two or more convictions yielded an IRR of 4.97 (95% CI 4.83-5.11). For violent offending the associations were stronger and IRRs of 3.97 (95% CI 3.81-4.12) and 6.18 (95% CI 5.85-6.52) were found for one and several offences respectively. Estimates for females were of a similar magnitude. The pattern was consistent across most diagnostic subgroups, although some variability in effect sizes was seen, and persisted after adjustment for substance misuse and socio-economic status (SES).

CONCLUSIONS

A prior history of offending is present in almost one in five patients presenting to mental health services, which makes it an important issue for clinicians to consider when assessing current and future risks and vulnerabilities.

Preparing for impact. Many hospitals will struggle to escape or absorb penalty for readmissions

October brings the beginning of a program hospitals around the country have been anxiously awaiting--a program that will penalize them for too-high readmission rates. Many fear the economics of the program will drive independent, community hospitals to join systems. "We are the hospitals that are least able to effect change, and we're being asked to do the most," says Stephen Estes, of Rockcastle Regional Hospital and Respiratory Care Center.

RightReturn. Partnering to reduce the high rate of hospital readmission for dialysis-dependent patients

The rate of rehospitalization is at a critical level. Twenty percent of all Medicare patients are rehospitalized within 30 days of discharge, and this rate is even higher (36%) for end-stage renal disease patients. Dialysis-dependent patients are commonly discharged from the hospital with a decline in various health measures (such as hemoglobin, albumin, and estimated dry weight) when compared to pre-hospital values, making the common response to resume previous orders" in the outpatient setting inadequate. Both quality of care and financial penalties by the Centers for Medicare & Medicaid Services have set the stage for partnerships between dialysis providers and hospitals to develop strategies to reduce readmissions for ESRD patients, and provide for the "RightReturn" to the outpatient setting with resumption of their daily lives at home in optimal health.

Improving care transitions means more than reducing hospital readmissions

Hospital readmissions are not only expensive, avoidable, and dangerous, but are also indicative of the most dysfunctional elements of US health care. The Patient Protection and Affordable Care Act places great emphasis on reducing preventable readmissions by building care systems that are patient-centered and that remove arbitrary silos of care. Hospitals that perform poorly on this measure will experience significant financial penalties beginning this fiscal year. In the short term, decreasing readmission rates will eliminate waste and enhance patient recovery from major illness. However the real vision is to ensure that vulnerable patients, particularly the chronically ill, benefit from coordinated, patient-centered systems that maintain functional independence, improve quality of life, and provide comfort without the trauma, expense, and displacement that unnecessary hospitalization often entails. The commentaries published in this issue of the NCMJ portray some of the most significant barriers to smooth transitions and reducing readmission rates and describe some of the nascent North Carolina and national solutions that demonstrate promise in real world situations.