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The American Journal of Accountable Care June 2017
Evolving Health Workforce Roles in Accountable Care Organizations
Shana F. Sandberg, PhD; Clese Erikson, MPAff; and Emily D. Yunker, MPA, PMP
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Peter A. Gross, MD; Morey Menacker, DO; Mitchel Easton, BS; Edward Gold, MD; Linda Naughton, RN; James A. Colbert, MD; Juliana Hart, BSN, MPH; Denise Patriaco, APN; and Mark Sparta, MPA
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Medicare Inpatient and Postdischarge Outcomes of Elective Percutaneous Coronary Interventions
Michael Pine, MD, MBA; Donald E. Fry, MD; Susan M. Nedza, MD, MBA; David G. Locke, BS; Agnes M. Reband, BS; and Gregory Pine, BA

Medicare Inpatient and Postdischarge Outcomes of Elective Percutaneous Coronary Interventions

Michael Pine, MD, MBA; Donald E. Fry, MD; Susan M. Nedza, MD, MBA; David G. Locke, BS; Agnes M. Reband, BS; and Gregory Pine, BA
An understanding of risk-adjusted outcomes for percutaneous coronary interventions for both inpatient and 90-day postdischarge events is necessary for the redesign of care outcomes.
The adverse outcomes of PCI have many similarities to those that we have reported previously in open CABG surgery.4 The overall adverse outcomes rate was 25.9% for PCI and 27.2% for CABG. There was a 1.8% inpatient and 90-day postdischarge mortality rate with PCI, and an overall 3.4% death rate for CABG. PrLOS was identified in 6.9% of PCI cases and 8.2% in CABG. A total of 20.9% of PCI patients were readmitted compared with 20.0% of CABG patients. Analysis of variance identified no difference in adverse outcomes between PCI and CABG. The comparable adverse outcome rates between the 2 populations of patients illustrates the high risk that is posed by coronary artery patients for any intervention.

In this study, 90-day postdischarge adverse outcomes exceeded the inpatient adverse outcomes. This finding may be due, in part, to progressive reductions in inpatient LOS, which result in more AEs first becoming evident after patients have been discharged. Increased awareness of the importance of postdischarge adverse outcomes has resulted in CMS imposing penalties to hospitals for excessive readmission rates for selected patient groups.13 This new focus on postdischarge AEs and the rapid evolution of accountable care organizations and bundled payment initiatives have put a premium on successful care redesign that improves important postdischarge clinical outcomes. To meet this challenge, hospitals must first institute effective methods for measuring their postdischarge adverse outcome rates. They then must devise and implement methods to link these results to specific processes of care for redesign of overall management when and where it is indicated.

Using risk-adjusted readmission rates as a measure of the quality of inpatient care is controversial because analytic methods have not been standardized and many readmissions have been judged to be clinically unavoidable or unrelated to the index hospitalization.14 The most common follow-up period for unscheduled postdischarge readmissions is 30 days, with reported rates after PCI ranging from 9% to12%.15,16 Wasfy et al reported that 30-day post-PCI readmissions are due mainly to chest pain and anxiety,17 are seldom due to complications of the PCI,18 and, in nearly half of cases, could be prevented with improved decision making.19 They also noted a modest improvement in predictions of 30-day readmissions when postprocedural risk factors, such as bleeding and prolonged LOS, were included in predictive models.20 On the other hand, Moretti et al21 extended the follow-up period for readmissions after PCI to 60 days based on their belief that 8 weeks were required to recover from the effects of myocardial damage. These investigators found overall readmission rates of 4.4% for 30 days and 8.4% for 60 days of postdischarge follow-up. They also found that readmission within 60 days of discharge was associated with increased mortality during 2 years after discharge. Similarly, Kharvaja et al found that 30-day readmissions after PCI were associated with an increased 1-year death rate.16 The only studies to examine 90-day readmissions following PCI were in clinical trials examining anticoagulation22 and hemodynamic support strategies.23 Both of these studies were performed on very restricted populations of patients.

The choice of a 90-day follow-up period for readmissions in this study is supported by the fact that of all readmissions that satisfied criteria for inclusion, 55% occurred 31 to 90 days after discharge. Cardiac-related events were the most common causes for readmission throughout the follow-up interval. Furthermore, Medicare’s bundled payment program is including 90 days of postdischarge care in its initial implementation,24 and PCI and coronary artery bypass surgery are expected to be included in the next set of scheduled episodes.25 Providers of inpatient PCI will likely have cost accountability for 90 days following discharge of the patient. The follow-up period of accountability for readmissions for 90 days will likely remain controversial.

Analysts have found risk-adjusted predictive models for readmission difficult to design.26 It has been difficult to obtain data about nonmedical factors that may have an even greater influence on readmission rates than conventional medical risk factors identified at the beginning of an index hospitalization. We have consistently found that prolonged risk-adjusted LOS during the index hospitalization is a powerful predictor of 90-day readmissions.27 In the current study, we also found that when hospitals are grouped by decile of performance, risk-adjusted prolonged LOS are highly correlated with readmission rates. Thus, it appears that hospitals with low risk-adjusted rates of severe inpatient complications have correspondingly low rates of risk-adjusted adverse outcomes following discharge.

In the current study, there was no significant difference in RAAO rates between low-volume and high-volume centers. In interpreting this finding, it is important to note that only inpatient, nonemergent PCIs were performed on Medicare patients older than 64 years who qualified for inclusion in the study, and hospitals with fewer than 50 such cases were excluded from comparative analyses. Therefore, almost all truly low-volume centers were probably excluded from this analysis.

Limitations

This study has several important limitations. Its reliance on administrative data raises concerns about the accuracy and completeness of the diagnostic information used to construct and apply risk factors. Complete abstraction of clinical records would yield better predictive models, and previous studies have shown that even modest enhancements of administrative data with numerical laboratory results that were obtained at the time of admission improve predictions of inpatient medical and surgical mortality27,28 and adverse outcomes,29 but not predictions of readmissions.30

Other studies have found that a patient’s ejection fraction and preprocedure serum creatinine are important independent variables in predictive models for mortality and complications in CABG31 and PCI.32 In its favor, administrative data has the distinct advantage of consistently capturing postdischarge AEs, such as readmissions, that often are not consistently documented in clinical registries. For example, 20% to 40% of postsurgical readmissions occur at hospitals other than the hospital at which the initial operation was performed, which probably is also the case for readmissions after PCI.33 Continuing evolution of the electronic health record (EHR) may result in the creation of new hybrid databases that combine the advantages of administrative and detailed clinical data. The use of EHRs as a source of laboratory results and other clinical data acquired at the time of discharge, rather than at admission, may further enhance the predictive power of readmission models derived from hybrid databases. EHRs have the promise of improving the accuracy of administrative data.

This study was also limited by the absence of a refined set of criteria for excluding all readmissions that were unrelated to the index procedure, by the exclusion of emergency and outpatient PCIs, and PCIs performed on patients younger than 65 years. Additional research is needed to determine whether current findings extend to these populations. The availability of all-payer claims databases with encrypted patient identifiers should facilitate expanded studies that provide accurate information about important postdischarge AEs in all patients undergoing PCIs.

CONCLUSIONS

This study of elective PCIs in Medicare beneficiaries revealed marked differences in hospital-level risk-adjusted adverse outcomes. These findings provide a realistic estimate of benefits that could be achieved by properly focused care redesign based on accurate knowledge of comparative hospital performance and successful linking of clinical outcomes to specific clinical judgments and technical proficiencies. Improved outcomes in both inpatient and postdischarge care will be very important for providers to meet the challenge of bundled payment initiatives.

Author Affiliations: MPA Healthcare Solutions (MP, DEF, SMN, DGL, AMR, GP), Chicago, IL; Department of Surgery (DEF) and Department of Emergency Medicine (SMN), Northwestern University Feinberg School of Medicine, Chicago, IL; Department of Surgery, University of New Mexico School of Medicine (DEF), Albuquerque, NM.

Source of Funding: This study was internally funded by MPA Healthcare Solutions, Chicago, IL.

Author Disclosures: Dr Fry is on the research advisory board of IrriMax Corp, and has received grants from the company for surgical site infection studies; he has also received lecture fees for speaking at CareFusion. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (MP, DEF, SMN, DGL, AMR, GP); acquisition of data (MP, DEF, SMN, DGL, AMR); analysis and interpretation of data (MP, DEF, SMN, DGL, AMR, GP); drafting of the manuscript (DEF); critical revision of the manuscript for important intellectual content (MP, DEF, SMN, DGL, AMR; GP); statistical analysis (MP, DEF, SMN, DGL, AMR, GP); provision of study materials or patients (GP); administrative, technical, or logistic support (MP, GP); and supervision (MP, DEF, GP).

Send Correspondence to: Donald E. Fry, MD, MPA Healthcare Solutions, 1 East Wacker Dr, #1210, Chicago, IL 60601. E-mail: dfry@consultmpa.com.
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