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SDoH to Reduce Hospital Readmissions

Updated: Aug 17, 2023

Health care spending in the U.S. has been on a constant rise and as of December 2019, accounts for approximately 17.7% of the national GDP, according to the Centers for Medicare and Medicaid Services (CMS).

Table 1. Average Cost of Readmissions in US, 2016.

Costs associated with patients’ hospital readmissions is a major area contributing to these expenditures. In 2011, hospital readmissions occurring within 30 days of discharge, cost a total of $41.4 billion with Medicare patients contributing to more than half of this cost (Hines, 2004).

A 30-day readmission is defined by CMS as an admission into an acute care hospital for any reason within 30 days of discharge from the same or another acute care hospital. While the 30-day readmission rate for Medicare patients have seen a slight improvement over the years, it still stands at an alarming rate of 17.3%, adding to expensive medical spending (Barrett, 2015). This continuous increase in health care cost has been a leading topic amongst policymakers, CMS, payers and other stakeholders. Different approaches are being utilized to reduce hospital readmissions.

Definition of a 30-day Readmission

One strategy is the inclusion of hospital readmission rate as a measure of hospital performance with the goal of incentivizing these hospitals into improving their efforts around readmissions. Another strategy is the Hospital Readmissions Reduction Plan (HRRP), where hospitals are financially penalized by CMS for having excess 30-day readmission rates (McIlvennan, 2015).

Figure 1: 30-day All Cause Readmission Rate by Payer, 2010-2016

Even though the HRRP has resulted in some improvement in select hospitals and overall readmission trends are slightly positive as shown in Figure 1, it has generally underperformed in reducing readmissions rate. Figure 2 shows the relative rates of readmissions for Medicare beneficiaries by state across the country.

Hospital readmissions occur when a patient’s medical condition worsened or did not improve as expected after discharge. While this can be purely due to uncontrollable clinical reasons, they’re more commonly associated with operational factors.

Figure 2: Medicare Readmission Rates by State Across the Country, 2018

These factors which include quality of care received and care-coordination needed upon discharge, can contribute to a patient receiving insufficient medical care the 1st time that ends in readmission. For these reasons, approaches to reduce hospital readmission have largely focused on these factors and have indeed yielded some improvements. To further improve hospital readmissions, additional elements contributing to health outcomes should be examined, such as the social factors that play a role in the health of patients. Social determinants of Health (SDoH) can play a significant role in improving or diminishing the health status of patients. As such stakeholders should undertake practices that include the impact of SDoH on hospital readmissions.

Social Determinants of Health Impacting Readmissions

Age has been proven to be a major risk factor for readmission. The elderly population has a higher rate of readmission compared to the younger population, hence the more than 50% of readmission attributed to the 65 and over, or Medicare population. After controlling for age, more awareness should be placed on other social factors that influence readmission rates. For instance, African Americans and Hispanics are associated with significantly higher readmission rates compared to Whites (Joynt et al, 2011; Durstenfeld et al, 2016). This health disparity among races and ethnic groups has been tied to African Americans and Hispanics having access to poorer performing hospitals, limited access to outpatient medical care as well as unexplained pathological differences amongst races. Outpatient medical care plays a critical role in ensuring continuity of care after a hospital discharge and when these populations have low access to this necessity, it results in poorer health outcomes that potentially leads to readmission.

The socio-economic status (SES) of a patient can also be significant in determining their chance of hospital readmission. In a study examining hospital readmission rates among different social groups, patients insured under Medicaid, a proxy for lower SES, were 25% more likely to be readmitted within 30 days of discharge compared to patients on commercial insurance (Fuller, 2013). Also, patients with lower educational level, another indication of a lower SES, were associated with higher readmission rate potentially caused by lower access to medical services, quality of care, ability to comprehend medical advice, and adherence to medication therapy (Jasti,2008). Patients facing financial hardship or from a low-income bracket had 2.5 times the odds of 30-days readmission compared to patients who were financially stable (McGregor, 2016). This has presumably been linked to poor nutrition, poor housing and poor access to ambulatory care, all of which contribute to inferior post-discharge medical care and diminished health outcome.

Language barrier is another element that introduces a gap in medical care resulting in preventable hospital readmissions. Non-English speakers have a 30% higher chance of 30-day hospital readmission than English speakers (Kartiner, 2010). Miscommunications that occur due to language barrier can lead to patients receiving improper care upon discharge. It affects the ability of their caregivers to properly care for them as well as the patient’s ability to effectively communicate their needs to medical providers. This in all declines a patient’s chances of obtaining a good medical outcome.

Economic Benefits of Reduced Readmission

The benefits of reducing hospital readmission rate goes beyond cost-savings. Economic benefits at individual and societal levels accompany it as well. Tackling factors that contribute to hospital readmissions will result in improved health outcomes for patients and a healthier population as a whole. Patients with enhanced health status, now have the opportunity to maintain and possibly increase their ability to work. With less sick days, they become more productive and less at risk of losing their source of income. They also become better positioned in seeking avenues for professional growth. Their improved health status becomes an incentive to develop their skill through continued schooling (Bloom & Canning, 2000; Weil, 2007). With the expectation of living longer and healthier lives, they hope to benefit from the educational investment that yields higher work productivity and a resulting higher income.

Another benefit is the effect a healthier population can have on economic growth. Health is considered one of the fundamental components of human capital and as such, plays a critical role in economic growth. A study by Bloom and Canning suggests that a one-year increase in life expectancy raises the GDP by approximately 4% (Bloom & Canning, 2004). As life expectancy is generally associated with improved health status and lower morbidity, efforts that ensure better health outcomes for patients become significant in ensuring long-term economic growth. In addition, longer, healthier lives are correlated to greater interest in contributing to a retirement plan. This is likely due to the fewer medical expenses they incur, income surplus available to contribute to retirement plan and the belief they will live long enough to enjoy retirement. Investments and financial activities that span from these retirement incomes can become major contributions to the economy (Bloom & Canning, 2003).


To build upon the progress health systems have made in reducing readmission rate, multi-dimensional approaches are required. Social determinants of health have been established to play critical roles in the well-being of patients and risk factors for hospital readmission. As such, health systems should incorporate these social factors when identifying and incorporating solutions to hospital readmissions into ongoing efforts. Taking these steps, will not only yield economic benefits as discussed in this paper, but a plethora of social, community, and civic benefits as well. Keeping people out of hospitals, especially the elderly population, provides the ability to engage in activities such as volunteerism, social organizations, clubs, religious services – and spending time with family – that contribute to a thriving society. Harnessing social factors to reduce hospital readmission rates will carry health, social, and economic benefits – collectively improve the welfare of individuals and society at large.



1. 2. Barrett, M. L., Wier, L. M., Jiang, H. J., & Steiner, C.A. (2015) All-Cause Readmissions by Payer and Age, 2009–2013. Healthcare Cost and Utilization Project (HCUP). Retrieved From 3. Healthcare Cost and Utilization Project (HCUP) 2010-2016 Nationwide Readmissions Database (NRD). 4. Barrett, M.L., Wier, L.M., Jiang, J. & Steiner, C.A. (2015) All-Cause Readmissions by Payer and Age, 2009–2013. Statistical Brief #199. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. 5. Bloom, D. & Canning, D (2000) The Health and Wealth of Nation. Science. 287(5456): 1207-1209 6. Bloom, D., Canning, D. & Sevilla, J. (2004) The Effect of Health on Economic Growth: A Production Function Approach. World Development. 32(1): 1-13 7. Durstenfeld, M., Ogedegbe, O., Katz, S., Park, H. & Blecker, S. (2016) Racial and Ethnic Differences in Heart Failure Readmissions and Mortality in a Large Municipal Healthcare System. JACC:Heart Failure. 4(11) DOI: DOI: 10.1016/j.jchf.2016.05.008 8. Fuller, R. L., Atkinson, G., McCullough, E. C. & Hughes, J. S. (2013). Hospital Readmission Rates: The Impacts of Age, Payer, and Mental Health Diagnoses. Journal of Ambulatory Care Management, 36(2), 147–155. doi: 10.1097/JAC.0b013e3182866c1c. 9. Hines, A. L., Barrett, M. L., Jiang, J & Steiner, C.A. (2014) Conditions With the Largest Number of Adult Hospital Readmissions by Payer, Statistical Brief #172 Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. 10. Jasti, H., Mortensen, E.M., Obrosky, D.S., Kapoor, W. N. & Fine, M.J. (2008) Causes and Risk Factors for Rehospitalization of Patients Hospitalized with Community-Acquired Pneumonia, Clinical Infectious Diseases, 46(4):550–556, 11. Joynt, K. E., Orav, E. J. & Jha, A. K. (2011) Thirty-Day Readmission Rates for Medicare Beneficiaries by Race and Site of Care. JAMA 305(7):675-81 doi: 10.1001/jama.2011.123. 12. Karliner, L.S., Kim, S.E, Meltzer, D.O., & Auerbach, A. D. (2010) Influence of language barriers on outcomes of hospital care for general medicine inpatients. Journal of Hospital Medicine. 5(5):276-282 13. McIlvennan, C. K., Eapen, Z. J., & Allen, L. A. (2015). Hospital readmissions reduction program. Circulation, 131(20), 1796–1803. 14. McGregor, M.J., Reid, R.J., Schulzer, M. et al (2016). Socioeconomic status and hospital utilization among younger adult pneumonia admissions at a Canadian hospital. BMC Health Service Research, 6(152). 15. Weil, D (2007) Accounting for the Effect of Health on Economic Growth. The Quarterly Journal of Economics, 122(3): 1265-1306 16. Bailey, Molly K., Weiss, Audrey J. Weiss, Barrett, Marguerite L., & Jiang, Joanna H. (2019), Characteristics of 30-Day All-Cause Hospital Readmissions, 2010-2016, Statistical Brief #248,

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