Acute myocardial infarction (AMI) hospital readmission for Medicare recipients is a costly concern to the Medicare Trust Fund and to the patient in preventable suffering. "These readmissions are often a sign of inadequate discharge planning, poor care coordination between hospital and community clinicians, and the lack of effective longitudinal community-based care" (Dartmouth Institute for Health Policy & Clinical Practice, 2011, p. 4). In 2005, Medicare spending for 30-day readmissions was about $20 billion, with an average readmission cost of about $7,200, only $1,400 less than the initial hospitalization (Medicare Payment Advisory Commission, 2007, p. 108). According to the Agency for Healthcare Research and Quality (2012), the average cost for an initial hospitalization for AMI was $20,800, with a 30-day readmission for a new AMI at $17,600 for all patients aged 18 years and older (p. 2). In an effort to decrease costly unnecessary spending, the goal of Medicare reform initiatives such as the hospital readmissions reduction program is to improve the quality and efficiency of health care (Public Law 111-148, 2010), for Medicare beneficiaries.

Although federal legislation has been pushing for a reduction in preventable readmissions, there is variation across the states, with some hospitals lagging behind in making improvement. National trends show a wide variation across U.S. hospitals on all-cause readmission even after controlling for disease-specific and disease-severity differences (Medicare Payment Advisory Commission, 2007, p. 110). National trends from 2004 to 2009 on 30-day hospital readmission rates for Medicare beneficiaries show AMI 30-day readmission decreasing from 19.4% to only 18.5% (Dartmouth Institute for Health Policy & Clinical Practice, 2011, p. 15). In 2009, 30-day postdischarge emergency room visit patterns show variation among hospital referral regions for medical and surgical admissions, with the AMI median at 22.9 as compared with the heart failure median at 23.8, medical at 18.9, pneumonia at 18.7, hip fracture at 17.0, and surgical at 14.9 (Dartmouth Institute for Health Policy & Clinical Practice, 2011, p. 32). Medicare beneficiary inpatient AMI treatment varies across hospital referral regions, with more hospitals in the Midwest and Northeast regions from 2006 to 2008 rating "worse" on readmission (risk-adjusted readmission rates) than the national average. Hospitals rating "better" than the national average are in the West (Pacific and Mountain sections), East North Central, and South Atlantic sections (Centers for Medicare & Medicaid Services, 2010a, p. 23).

The purpose of this quantitative investigation was to explore the association between hospital ranking for AMI 30-day readmission for the Medicare fee-for-service (FFS) patient and predictor variables (demographic, hospital capacity, clinical process, and patient needs). The research question is as follows: What explains the variation in AMI 30-day hospital readmission performance across the states? Multivariate regression analysis of 50 state-level data is used to explore this question.

Factors Related to AMI Readmission

Studies show several factors-demographic and clinical factors, organizational capacity, and need/demand-to be related to preventable hospital readmissions. Silverstein, Qin, Mercer, Fong, and Haydar (2008) found that demographic factors such as males, individuals older than 75 years, African Americans, and those with only Medicare insurance coverage (with no secondary insurance) placed patients at a higher risk for 30-day readmission. Historically, people with lower income tend to face more barriers to accessing quality care that may, in turn, influence readmission. The Agency for Healthcare Research and Quality (2012) reported that those with a lower income, female, and 65 years of age and older have a higher rate for readmission following a new AMI than their wealthier, male, and younger cohort (p. 3). Schmeida and Savrin (2012a, 2012b) found that states with a higher percentage of White Medicare enrollees and states with a higher median household income have a greater probability for pneumonia 30-day readmission to be "worse" than the U.S. national rate and states with a higher income had a greater chance for heart failure 30-day readmission to be "worse" than the national rate. However, the Centers for Medicare & Medicaid Services (2010b) reported, "in comparison to the national average, hospitals with high proportions of low income patients do not have worse 30-day risk-standardized mortality or readmission rates for AMI, heart failure, and pneumonia" (p. 6).

Organizational capacity, such as nurse and physician staffing levels, may be related to preventable readmissions. Cheung, Aiken, Clarke, and Sloane (2008) identified inadequate nurse staffing ratios to be related to poorer clinical outcomes (p. 36). Diya, Van den Heede, Sermeus, and Lesaffre (2012) found a relationship between higher nurse staffing levels on postoperative general nursing cardiac surgery units and lower unplanned readmission into the intensive care nursing unit and/or operating theatre. Similarly, Joynt and Jha (2011) found an association between higher nurse staffing level and lower readmission rates for heart failure (p. 58). However, the literature on physician supply (or geographic density) and improved patient outcomes has been mixed and inconsistent. Chang, Stukel, Flood, and Goodman (2011) found a strong association between full-time primary care physician workforce supply and fewer ambulatory care-sensitive conditions for Medicare beneficiaries (pp. 3, 7). Laditka, Laditka, and Probst (2005) found that as primary care physician supply (nonfederal office-based) per 100,000 population increased, the chance of potentially preventable hospitalizations for age groups 40 to 64 years decreased for urban counties in 20 U.S. states (pp. 1154, 1159). In contrast, Weinberger, Oddone, and Henderson (1996) found a higher proportion of Veterans Affairs Medical Center patients who were exposed to postdischarge care with a primary care practitioner to have a higher rate of readmission and more days of rehospitalization than patients who were not exposed to primary care.

Need/demand factors, such as length of hospital stay, may have an association with 30-day AMI readmissions. Studies show that states with more total days of care per 1,000 Medicare enrollees discharged from short-stay hospitals are more likely to be "worse" on both 30-day pneumonia readmission and 30-day heart failure readmission than the national rate (Schmeida & Savrin, 2012a, 2012b). According to the Centers for Medicare & Medicaid Services (2010a), the median length of stay for Medicare FFS beneficiaries aged 65 years or older for 2006-2008 is similar for AMI, pneumonia, and heart failure across the hospital referral regions, with lower than national estimate located in the Western and North Central U.S. and higher than national estimate mostly in the Eastern and South Central sections (p. 31). Not all Americans have health insurance (Agency for Healthcare Research and Quality, 2009). Access to health care system services, such as prescription drug coverage, and community outpatient physician visits may play a role in AMI readmission. Schmeida & Savrin (2012a, 2012b) found that states with more Medicare patients having credible prescription drug coverage are more likely to rate "worse" on both 30-day pneumonia readmission and 30-day heart failure readmission than the national rate. However, individual-level studies such as Khan, Kaestner, and Lin (2008) found no statistically significant association between insurance drug coverage (employer-sponsored drug coverage, Medicare Health Maintenance Organization, and Medigap) and poorer health status among the older adults.

Postdischarge physician follow-up is critical to management of patient illness. Today, the context of patient care visits is under reform, including hospitals and other providers in the community (Medicare Payment Advisory Commission, 2007, p. 105). There is a shift from inpatient to outpatient settings, with many freestanding physician office visits giving way to hospital-owned outpatient office visits (Medicare Payment Advisory Commission, 2011). From 2004 to 2009, Medicare outpatient services increased by 23% over the 6-year period, whereas discharges decreased at about 4% for Medicare FFS Part A (hospital insurance) patients (Medicare Payment Advisory Commission, 2011, p. 44). Are community hospital outpatient physician office visits associated with AMI readmissions? Empirical studies controlling for this factor are sparse. This study will explore whether this need factor is associated with states ranking "worse" on AMI 30- day readmission of the Medicare FFS patient.

Clinical treatment with drugs, such as [beta]-blockers and aspirin, is also an important factor in exploring 30-day AMI readmission of the Medicare patient. Soumerai et al. (1997) studied elderly AMI survivors (New Jersey Medicare population) from 1987 to 1992 and found that survivors who did receive a new [beta]-blocker prescription were readmitted 22% fewer times than patients without [beta]-blocker therapy. However, Butler et al. (2002) found a decrease in [beta]-blocker use in discharged post-AMI survivors (Tennessee Medicare and Medicaid population) and that those not discharged on a [beta]-blocker prescription were not as likely to be prescribed it on an outpatient basis. Aspirin as an antiplatelet agent is believed to reduce myocardial infarction mortality when given early in treatment and to have long-term benefits even at low daily doses (Second Chinese Cardiac Study Collaborative Group, 2005). However, Portnay et al. (2005) found Medicare patients aged 65 years or older and hospitalized with AMI and who took aspirin before admission to have a higher rate of AMI readmission at 30-days but "similar rates of readmission for all causes" (p. 4) when compared with those patients not taking aspirin prior to their hospitalization.

Research Design and Methodology

"This research is a quantitative secondary data analysis of previously collected 50 state-level data made available to the public domain for study. The dependent variable AMI 30-day readmission worse than U.S. rate is available to the public from the Centers for Medicare & Medicaid Services' Hospital Compare website as part of the its Hospital Quality Initiative, in a usable format. No permission was required to use it. Data sources used by the Centers for Medicare & Medicaid Services for this variable were enrollment and claims data 2006-2009. This study required no Institutional Review Board approval. Multivariate regression analysis is used to explore the following questions: What explains the variation in AMI 30-day hospital readmission performance across the United States? Why do some states have higher 30-day readmission rates than the U.S. national rate?

The dependent variable AMI 30-day readmission (2006-2009) worse than U.S. rate* is a count of hospitals in each of 50 states that have a risk-adjusted AMI readmission rate "worse" than the U.S. national 30-day AMI readmission rate of 19.9% (Centers for Medicare & Medicaid Services, 2010b.) This variable is based on adult Medicare FFS patients hospitalized with a primary discharge diagnosis of AMI and for which a subsequent inpatient readmission occurred within 30 days of their last discharge, and it is adjusted for hospital case mix (Centers for Medicare & Medicaid Services, 2010b.)

Independent variables chosen for the study are based on previous research and are secondary data collected by government agencies or organizations funded by the government for public reporting. The two key explanatory independent variables are acetylsalicylic acid (ASA)given at discharge and [beta]-blocker given at discharge. ASA given at discharge measures patients with myocardial infarction prescribed aspirin at discharge (Centers for Medicare & Medicaid Services (2010c), and [beta]-blocker measures patients with myocardial infarction prescribed a [beta]-blocker at discharge (Centers for Medicare & Medicaid Services (2010c).

Our independent variables are demographic, hospital capacity, patient need/demand, and condition-specific clinical process. The demographic controls include female distribution rate of Medicare enrollees (Kaiser Family Foundation, 2009), the rate of White enrollees (Centers for Medicare & Medicaid Services, 2008), median household income in 2007 dollars (U.S. Census Bureau, 2010), and percentage not seen physician due to cost in the last 12 months (Kaiser Family Foundation, 2008). We control for hospital capacity (staffing levels) by using active physician rate per 1,000 resident populations in a state for 2007 (excludes doctor of osteopathy, physicians with none known address, and inactive physician status) and active nurse rate per 1,000 resident populations in a state for 2007 (U.S. Census Bureau, 2010). Need/demand variables include total days of care per 1,000 Medicare enrollees for patients discharged from short-stay hospitals (Centers for Medicare & Medicaid Services, 2008), and community hospital outpatient visits as a measure of hospital outpatient visits per 1,000 populations. These are community hospitals representing about 85% of all hospitals across the states and include all nonfederal, short-term general, and specialty hospitals whose facilities and services are available to the public (excludes long-term care, psychiatric, alcoholism, and other chemical dependency hospitals and institutions for the mentally retarded). It reflects how often patients in that region are seen in the community hospital outpatient department (U.S. Census Bureau, 2011). Other independent variables, such as patient access to prescription coverage and percentage of primary care physician shortage areas in a state, were considered in our complete model but excluded because of multicollinearity (see Table 1 for definition).

TABLE 1 Statistical Terminology for AMI Readmission Regression Analysis

Results

Since the dependent variable AMI 30-day readmission worse than U.S. rate* is a count, the model was estimated using Poisson regression. Table 2 presents the findings, which suggest that certain patient need and condition-specific clinical factors have a statistically significant impact on hospital AMI 30-day readmission status across the states (see Table 2, best model).

TABLE 2 Poisson Regression Models-Acute Myocardial Infarction 30-Day Readmission

In our best model, we find that 59.37% of the proportion of the variability in AMI 30-day readmission worse than U.S. rate* across the 50 states is explained by the regression of the seven predicting variables. That is, the independent variables explain the variation of the dependent* variable 59.37%. The variables female, White, and income were dropped in the best model, because these were not statistically significant in the complete model. Table 2 shows that the coefficients for two patient need variables, total days of patient care and community hospital outpatient visits, were each statistically significant and each positively associated with the dependent* variable.

States with more total days of care per 1,000 Medicare enrollees (for those discharged from short-stay hospitals) are more likely to be "worse" on 30-day AMI readmissions than the national rate, even after controlling for all other variables. This finding is similar to research findings for pneumonia and heart failure 30-day hospital readmission across the states (Schmeida & Savrin, 2012a, 2012b). Our finding suggests that patients with greater total days of care from a short-stay hospital may be more acutely ill and/or have more comorbidity requiring a longer term of care. However, further study is required to analyze the underlying reason(s) for this trend across AMI, pneumonia, and heart failure readmissions. We also find that states with more community hospital outpatient visits per 1,000 population are more likely to be worse on 30-day AMI readmissions than the national rate. The more often that patients (in the region) are seen in the community hospital outpatient department, the more likely that the state will rate "worse" on AMI readmission than the national rate. This is an important finding, considering many physician office visits have changed to hospital-owned outpatient office visits (Medicare Payment Advisory Commission, 2011). Additional research is required to explain this association.

Table 2 shows that the coefficient for the clinical variable ASA prescription given at discharge was statistically significant and positive, meaning that states higher on aspirin prescribed at discharge for AMI patients are more likely to also rate "worse" on AMI 30-day readmission than the national rate. More analysis is needed to better explain this finding. However, because this is a retrospective study, this variable may have been subject to selection bias. Patients who were considered to be more severely ill, more likely to suffer a recurrent AMI, or more likely to be readmitted with cardiac ischemia may have preferentially been placed on ASA at discharge. The coefficient for [beta]-blocker prescription given at discharge was statistically significant and negatively associated with AMI readmission. As [beta]-blocker given at discharge increases, the chance for AMI 30-day readmission to be "worse" than the national rate decreases. That is, giving the patient a [beta]-blocker prescription at discharge can decrease the chance that the state will be "worse" on AMI readmission than the national rate. The variables percentage not seen physician due to cost, active physician rate, and active nurse rate were not statistically significant in our best model with our level of significance set at p <= .05.

Implications for Case Management Practice Lessons Learned

The findings from our empirical research can be used in developing case management interventions for improving hospital performance on Medicare AMI 30-day readmission. Lessons can be drawn from our findings for inpatient and outpatient case management programs, hospital administrators, and researchers.

First, we find that total days of care is associated with states ranking "worse" on AMI readmission. This finding is in line with previous research (Schmeida & Savrin, 2012a, 2012b) exploring both pneumonia and heart failure 30-day readmission. These consistent findings suggest that hospitals ranking "worse" may be treating patients with more severe illness or comorbidity requiring a longer length of hospital stay. Alternatively, regions of the country with higher hospital utilization rates independent of severity of illness may be associated with higher rates of rehospitalization. Although further analysis is needed to explain these consistent findings, hospital administrators and case management leadership of short-stay hospitals treating Medicare patients with AMI, pneumonia, and/or heart failure may want to compare their hospital readmission rates for patients with an extended length of stay with the national readmission rate, in particular, for those hospitals rating "worse" on readmission than the national average, such as in the Midwest and Northeast regions (Centers for Medicare & Medicaid Services, 2010a, p. 23).

Second, we find states with more community hospital outpatient visits to be associated with rating "worse" on AMI readmission than the national rate. Since physician practices have shifted to hospital-owned outpatient office settings, this finding should be a concern to case managers. Community hospitals rating "worse" than the national rate on AMI 30-day readmission may want to consider embedding case managers in the hospital outpatient physician setting to minimize the potential for patient readmission. Managers embedded in the outpatient setting may improve the coordination of patient care and the monitoring of intermediate clinical outcomes and promote patient improvement toward positive end outcomes.

Third, our analysis shows that states that had higher rates of ASA prescribed at discharge were more likely to rate "worse" than the national average; whereas states that had higher rates of [beta]-blockers prescribed at discharge were less likely to rate "worse" than the national average on 30-day readmission rate. Even though case managers may not determine which medications are prescribed for a given patient, they can drive the coordination of the medication treatment regime during postdischarge planning and management. The continuity of care from hospital setting to the transfer setting should involve efficient medication reconciliation. Hospital administrators and case management leadership in states seeking to improve their AMI hospital readmission ranking should consider improving their continuity of care from the hospital setting to place of transfer. Efficient medication reconciliation can help minimize readmission for patients highly dependent on their medication for improved clinical outcomes.

The limitation to our study is that no individual-level inferences can be made on our analysis using state-level data. However, this research sets the groundwork for further study. Future research efforts should target the empirical findings that are consistent across AMI, pneumonia, and heart failure 30-day readmission.

Conclusion

Our research presents several findings. States with greater total days of care, states with more community hospital outpatient visits per 1,000 populations, and those with greater ASA prescription at discharge have a greater chance for AMI 30-day readmission to be "worse" than the U.S. national rate. Additional study is required to empirically explain this finding. We also find that states having greater [beta]-blocker prescription given at discharge to be associated with a lesser chance for ranking "worse" on AMI 30-day readmission. Giving a [beta]-blocker prescription at discharge can lessen the chance that the state will be "worse" on AMI readmission than the national rate.

References