Hyperpolypharmacy and Readmission Risk Among Medicare Beneficiaries: The Role of Postdischarge Care

ABSTRACT

Objectives: Medication reconciliation post discharge may reduce readmission risk in populations with multimorbidity and polypharmacy. We aimed to evaluate the association between hyperpolypharmacy and 30-day readmissions; determine the impact of postdischarge care on 30-day readmissions; and identify interactions among hyperpolypharmacy, postdischarge care, and 30-day readmissions in 2 Medicare populations: individuals 65 years and older and individuals of any age with a qualifying disability.

Study Design: Retrospective observational study using the 5% national sample Medicare fee-for-service claims data from 2016 to 2019.

Methods: We used descriptive statistics and generalized estimating equation models adjusted for covariates to assess the relationships among hyperpolypharmacy, 30-day readmissions, and receipt of intervention
(medical care) via an evaluation and management visit or transitional care management (TCM) visit.

Results: Hyperpolypharmacy and readmissions were higher in the disability-eligible than age-eligible group. Receiving any postdischarge care lowered the readmission risk in both groups, with particularly lower odds for those receiving TCM. Hyperpolypharmacy at admission increased readmission risk by 25% and 6% in the age-eligible and disability-eligible groups without a postdischarge visit, respectively, and by 24% and 2% when postdischarge hyperpolypharmacy was used as the primary predictor. Results were inconsistent across study groups when comparing hyperpolypharmacy effects by postdischarge visit type. Among individuals with hyperpolypharmacy, only 14.8% in the age-eligible group and 10.5% in the disability-eligible group received TCM.

Conclusions: Receipt of postdischarge ambulatory care was associated with lower odds of readmission; however, TCM-assisted postdischarge care may be underutilized, especially in the disability-eligible group. Cost-utility analysis studies are needed to demonstrate the value of postdischarge care, especially TCM, across different groups.

Am J Manag Care. 2026;32(3):e71-e82. https://doi.org/10.37765/ajmc.2026.89899

Takeaway Points

This study addresses the knowledge gap in the literature regarding medication use and utilization of transitional care management visits and readmissions in older adults and in younger individuals with disabilities. It is relevant to providers, health services researchers, and policy makers interested in improving medication prescribing in these 2 Medicare populations.

• Our models indicate that postdischarge ambulatory care significantly reduces readmission risk and suggest that managing the effects of hyperpolypharmacy through deprescribing during the postdischarge period will significantly reduce readmission risk.
• We found that the relationship between hyperpolypharmacy and readmission risk is primarily due to chronic illness burden and prior health care use.

Approximately 15.6% of Medicare beneficiaries were readmitted within 30 days of hospital discharge in the US in 2016.¹ Hospital readmissions increase health care spending and can be a sign of poor care quality.^2,3 Age, severity of disease, number of comorbidities (including disabling conditions), polypharmacy, high-risk medication use, incomplete treatment, early discharge, treatment nonadherence, lack of or poor coordination of treatment after discharge, and unfavorable health-related social needs have all been associated with hospital readmissions.^4-8

More than one-fourth of readmissions could be prevented in the general population, and several interventions have been developed to reduce readmissions.⁴ Although some factors driving readmissions are difficult to modify, factors such as medication use and postdischarge care, including medical reconciliation, can potentially reduce readmission risk.^7,9 However, predicting which patients will have increased risk of readmission is difficult, making effective and efficient intervention a challenge.⁷

Polypharmacy, which is the simultaneous use of multiple medications,¹⁰ is associated with a higher burden of chronic conditions, presence of disabilities,¹¹ and higher use of health services, including hospitalizations.^12,13 Patients with multimorbidity and polypharmacy are at higher risk of readmissions.^5,14,15 Approximately 45% of adults 65 years and older and 25% of individuals younger than 65 years experience polypharmacy.¹⁶ Hyperpolypharmacy, the prescription of 10 or more medications, is more common in adults 65 years and older,¹⁷ but less is known about patients younger than 65 years with hyperpolypharmacy. There is also a knowledge gap in the literature regarding outcomes for patients with hyperpolypharmacy. Among adults with multimorbidity, the use of 5 or more medications may be clinically justified, but hyperpolypharmacy raises additional concerns for health risks and requires close monitoring by providers.^10,17,18 Published studies show inconsistent associations between readmission and complex medication use,^7,9,19-22 with chronic disease burden potentially playing a role in the association.

Readmissions also indicate a poor transition to outpatient care post discharge. Transitional care management (TCM) consists of services focused on supporting a patient’s transition back into the community after discharge in the hopes of avoiding hospital readmission. Most TCM interventions, particularly for older adults, provide discharge assessment and planning, patient- and caregiver-driven self-care education and planning, medication reconciliation, and patient and community-based communication and follow-up post discharge for 30 days.^23-26 Recent reports have documented significant reductions in readmissions with ambulatory TCM.²⁷ Medication reconciliation during both hospitalization and the postdischarge period may reduce inappropriate prescribing, adverse drug events, and readmissions.^28,29 Although reducing polypharmacy and conducting medication reconciliation after discharge may prevent readmissions, lower costs, and improve the patient experience, less than 12% of patients currently receive TCM services.^30,31 It is critical to identify populations at highest risk of readmission and the causes in order to tailor readmission reduction interventions.

Prior studies have examined which hospital stays are likely to result in readmissions, but these studies focused on specific populations, disease states, and hospital activities. Developing predictive modeling using hyperpolypharmacy and outpatient data would complement existing approaches reliant on inpatient data. In particular, older adults and individuals with chronic conditions or disabilities would benefit from medical reconciliation and deprescribing to ensure quality of care and safety.³²

Evaluation of the association between hyperpolypharmacy and readmissions is needed to support readmission interventions. Using Medicare population data allows for evaluation of the association in individuals both younger and older than 65 years because Medicare eligibility includes (1) those at any age receiving disability insurance benefits or having end-stage renal disease and (2) those 65 years and older. We aimed to (1) determine the association of hyperpolypharmacy and 30-day readmissions among Medicare beneficiaries, (2) determine the association of postdischarge care and 30-day readmissions, and (3) assess the interaction between hyperpolypharmacy and postdischarge care on 30-day readmission risk.

METHODS

Research Design

This was a retrospective observational study of the 5% national sample Medicare fee-for-service claims data of beneficiaries with at least 1 index hospital admission between 2016 and 2019. This study was approved by the institutional review board at UTHealth (HSC-SPH-17-0314).

To create an index admission episode, we followed the methodology of Krause et al and included all health care claims associated with the initial hospital stay.³³ If multiple claims were present for the first admission, they were merged into a single index admission episode. Duration of the index stay was calculated from admission date of the earliest claim to discharge date on the latest claim. For beneficiaries with multiple hospital stays during the study period, we included in the analysis index admissions with more than 30-day intervals between episodes, starting with the earliest admission.

After initial exploration of the data, we observed that the age-eligible and disability-eligible individuals were significantly different in age, chronic condition burden, and health care utilization. Thus, we stratified our analysis into 2 groups using original Medicare eligibility reason: (1) age-eligible beneficiaries, who qualify when they are aged 65years, and (2) disability-eligible beneficiaries, who qualify when they are younger than 65 years because they have a significant disability and receive Social Security disability benefits. Thus, we did not segregate based on the existence of a disability but rather on the reason for initial Medicare eligibility, recognizing that individuals may develop a disability later in life after receiving Medicare coverage due to age eligibility. Beneficiaries who are initially Medicare eligible due to disability have their eligibility status changed when they become age eligible; thus, Medicare group assignments were based on beneficiaries’ original enrollment eligibility status to better stratify the Medicare population into those who developed disability younger than 65 years (high-risk, high-need population) and the more traditional 65 years and older population.

Study Population

The study sample included hospital admissions of individuals 18 years and older at admission and with continuous Medicare parts A, B, and D coverage from 180 days before admission to 30 days after discharge. The eAppendix Figure (eAppendix available at ajmc.com) shows the study sample selection process. To focus on preventable readmissions, we excluded individuals with end-stage renal disease.³³ Further, we excluded admissions with primary International Classification of Diseases diagnoses for neoplasm, pregnancy, childbirth, or perinatal stay; with admission type newborn or unknown; discharged to another care facility for continued care (eg, skilled nursing facility); where the patient discharge status was expired or unknown; and for patients who died within 30 days of discharge.³³

The study sample included 579,516 inpatient admission episodes (age eligible, 368,313 admit episodes; disability eligible, 211,203 admit episodes) for 356,732 unique individuals.

Primary Outcomes

We identified 30-day all-cause readmission as an inpatient admission within 30 days of the discharge date of each index hospital admission episode.

Primary Exposures

Hyperpolypharmacy, a binary variable, was defined as simultaneous use of 10 or more medications prescribed for at least 30 days. We estimated hyperpolypharmacy at 2 points: (1) hyperpolypharmacy at admission, defined as 10 or more medications that patients were using at admission date, and (2) hyperpolypharmacy at discharge, defined as 10 or more medications being used 7 days after hospital discharge. Due to pharmacy claims data use, we included prescription claims during the 7-day period after discharge to allow time for postdischarge prescriptions to be filled.

To estimate TCM or follow-up care exposure, we examined utilization of TCM and evaluation and management (E&M) visits. Based on type of visit, we categorized postdischarge care into the following: (1) no TCM or E&M service received during the first 14 days post discharge; (2) receipt of TCM only, evidenced by Current Procedural Terminology (CPT) codes 99495 (moderate medical complexity requiring a face-to-face visit within 14 days of discharge) or 99496 (high medical complexity requiring a face-to-face visit within 7 days of discharge); (3) receipt within 14 days of any other follow-up evaluation, evidenced by episodes of care with E&M codes only (see eAppendix for CPT codes list); and (4) receipt of both types of visits.

Covariates

We included the following covariates based on their prior associations with readmission risk¹: demographic characteristics (age, sex, race/ethnicity), admission characteristics (admission type, discharge status, length of stay), chronic condition burden estimated as the Charlson Comorbidity Index score based on claims data during admission, and previous health services utilization (numbers of all-cause hospitalizations and emergency department visits [categorical variables] and professional claims within 180 days prior to admission [continuous variable]).

Statistical Analysis

Stata 18 (StataCorp LLC) was used for statistical analysis. Descriptive statistics were calculated using mean (SD) for continuous variables and frequencies for categorical variables. Due to clustered data, we used univariate generalized estimating equations (GEEs) to assess statistically significant differences between groups with and without readmissions for each Medicare category.

The association between exposures and hospital readmission was evaluated using GEE models presented as ORs with 95% CIs. GEE models were fitted using the binomial family and a logit link function to model the binary outcome of readmission. To account for the correlation between repeated index admission events for the same patient over study years, an exchangeable correlation structure was specified because it assumes constant correlation between repeated observations and provided the best fit based on the quasi-likelihood under the independence model criterion (QIC).

We evaluated multiple GEE models using stepwise selection of variables. We selected and tested covariates based on the strong theoretical link to the outcome identified in the literature, evaluated correlation structure of the data using contingency tables, and used QIC to determine the best-fitting model. We tested the following models: (1) simple GEE models with 1 exposure variable, (1a) hyperpolypharmacy or (1b) postdischarge care, and (1c) both exposures; (2) models adjusted for demographic and admission characteristics; (3) models further adjusted for chronic condition status using the Charlson Comorbidity Index score; (4) models further adjusted for utilization of health care services within 180 days prior to admission; and (5) models further incorporating an interaction term between hyperpolypharmacy and postdischarge follow-up care. We tested a time-varying covariate (ie, year; model 6), but it did not improve model fit; thus, it was not included in the final model. Models 1 to 5 are shown in the Results section and eAppendix tables. We conducted analyses in the 2 Medicare study groups separately, evaluating hyperpolypharmacy at admission and hyperpolypharmacy at discharge as separate key exposures for 30-day readmission.

We also conducted a sensitivity analysis to evaluate how different definitions of 30-day readmissions related to assessing the effect of TCM intervention. We tested 2 exclusions: (1) excluding readmissions occurring within the first 7 days after discharge because the readmission may have occurred before the TCM postdischarge visit could be completed, and (2) excluding readmissions occurring within the first 14 days after discharge because TCM visits may not occur until day 14 (for moderate-risk beneficiaries).

RESULTS

The study sample included 356,732 individuals (579,516 hospital admissions) with a mean (SD) age of 70.5 (13.8) years who were admitted to care facilities between 2016 and 2019. Age-eligible Medicare beneficiaries (58% female) had 368,313 admissions, and disability-eligible beneficiaries (53% female) had 211,203 admissions (Table 1).

Hyperpolypharmacy and Readmission Risk

Both hyperpolypharmacy at admission and 30-day readmissions were more prevalent among disability-eligible beneficiaries (19.5% and 16.9% of admissions, respectively) than among age-eligible beneficiaries (11.3% and 11.7% of admissions, respectively) (Table 2 [part A and part B]). Among age-eligible beneficiaries, those with hyperpolypharmacy had 46% higher odds of 30-day readmission in the unadjusted model (Table 3 [part A and part B], model 1a) and 9% in the adjusted model (Table 3, model 4). Among disability-eligible beneficiaries, those with hyperpolypharmacy had 14% and 2% higher unadjusted and adjusted odds of a readmission, respectively, although these were not statistically significant in the adjusted model. After adjusting for covariates, the largest drops in ORs were attributable to chronic illness burden and prior health care use (Table 3, models 2 through 4). Similar associations were identified when postdischarge hyperpolypharmacy was used as the primary predictor of readmission risk (Table 3).

Receipt of Ambulatory Postdischarge Care

The association between postdischarge care and readmissions remained stable across study groups and models. Compared with beneficiaries who did not receive follow-up care, all groups receiving follow-up care showed a reduction in the likelihood of a 30-day readmission. Among the age-eligible group, there was a 47% reduction in the odds of a 30-day readmission for TCM only, 24% reduction for E&M only, and 45% reduction for those who had both TCM and E&M visits (Table 3, model 4). Similar associations were identified among the disability-eligible group and when postdischarge hyperpolypharmacy was used as the primary predictor of readmission risk.

Interaction Between Hyperpolypharmacy and Postdischarge Care

Disability-eligible beneficiaries overall had higher chronic condition burden and higher prevalence of hyperpolypharmacy than age-eligible beneficiaries, but they received follow-up visits and TCM visits less often (14.8% of age-eligible beneficiaries with hyperpolypharmacy and 12.4% without hyperpolypharmacy received TCM visits post discharge, whereas only 10.5% of disability-eligible beneficiaries with hyperpolypharmacy and 7.3% without hyperpolypharmacy received TCM visits).

In the model (model 5) with an interaction term (Table 4 [part A and part B]), we identified that receiving any postdischarge care lowered the risk of readmissions in individuals without hyperpolypharmacy, with lower odds for TCM (Table 4 and Figure). The effect of hyperpolypharmacy on readmission risk varied by postdischarge care received. Hyperpolypharmacy increased readmission risk in both Medicare groups without postdischarge visits, but the association was not statistically significant among the disability-eligible group when hyperpolypharmacy was assessed at discharge. When comparing hyperpolypharmacy effects by postdischarge visit type, receiving TCM and/or E&M lowered the odds of readmission, but the effect was not always statistically significant across study groups (Table 4 and eAppendix Tables 1-4). Beneficiaries with hyperpolypharmacy receiving TCM had higher odds of readmission in the disability-eligible group; however, the expected readmission risk was still lower compared with those with no visits or E&M only (Figure [D]). The sensitivity analysis yielded similar associations between exposures and readmission risk.

DISCUSSION

Hyperpolypharmacy and readmission were more prevalent among disability-eligible beneficiaries. Previous research has shown that high-need patients are at risk of high health care utilization^34,35 and has reported a high risk of readmission associated with prescribing more than 6 medications.^5,8,15 We found that hyperpolypharmacy was associated with only a slightly increased risk of readmission in our sample of age-eligible beneficiaries, after other factors were accounted for, and there was minimal to no association in disability-eligible beneficiaries. Notably, the factors in our model related to 30-day readmission risk were also related to an increased risk of hyperpolypharmacy for both age-eligible and disability-eligible beneficiaries. Our results suggest the strong relationship between hyperpolypharmacy and 30-day readmission risk is primarily due to the influence of chronic illness burden and prior health care use on both, and, to a lesser extent, on the influence of demographic differences among beneficiaries. Similarly, Robinson et al found that the number of medications at discharge was not a significant predictor of readmission, whereas chronic condition burden and certain medical conditions increased the risk of readmission.⁹ In our study, despite the higher number of medications and increased prevalence of hyperpolypharmacy at discharge, we found that the association of hyperpolypharmacy and readmissions remained similar regardless of whether we used admission or discharge hyperpolypharmacy. When we compared the prevalence of individual medications prescribed in readmission vs no-readmission groups, the difference was likely due to the severity of chronic conditions in the no-readmission and readmission groups (eg, heart failure in older adults and associated diuretic use, rather than the effect of diuretic use on increased risk of readmission on its own).

Polypharmacy is a risk factor for adverse drug events and prescribing potentially inappropriate medications (PIM), which increase the risk of readmission.¹⁰ The quality of prescribing (ie, appropriate vs inappropriate polypharmacy) may affect readmission risk rather than the quantity of medications used. Although criteria for PIM in older populations are well established and implemented in clinical practice, there are no universally accepted criteria for populations younger than 65 years with disabilities. More research is needed to identify tools for assessing the quality of prescribing patterns among younger populations with disabilities.

Hyperpolypharmacy was associated with higher readmission odds in the group with no TCM or E&M visits. Our models indicate that postdischarge ambulatory care significantly reduces the risk of readmission. Our findings suggest an opportunity to reduce readmission risk by managing the negative effects of hyperpolypharmacy through deprescribing during the postdischarge period as a part of medication reconciliation for those groups with hyperpolypharmacy and chronic conditions. Medication reconciliation is recommended as part of TCM interventions; however, recent research has identified challenges in the ability to effectively complete medication reconciliation, especially during cross-institutional transitions from the hospital to ambulatory care setting.³⁶ We identified a reduction in readmission risk for those who had TCM visits, or any E&M visit, compared with those with no visit, with a stronger association between postdischarge care and reduced readmission risk in groups receiving TCM. However, only a small percentage of discharged patients with hyperpolypharmacy received postdischarge care, especially among disability-eligible beneficiaries, indicating a gap in intervention delivery in health care settings. Previous study findings have suggested that TCM care reduces readmission risk, but those data also indicated that the prevalence of TCM was low and comparable to the results of our study.^23,37

Future Research

Our findings are useful for developing evidence-based interventions post discharge to reduce the risk of hospital readmission. Economic models are needed to identify the most useful target populations for TCM and/or E&M follow-up, given limited health system and staffing resources to implement TCM. This would establish a decision-analytic framework for guiding the identification of patients likely to benefit from different modes of follow-up care post hospitalization. A longitudinal analysis of health care patterns within individuals would identify early interventions for reducing longer-term health needs and reducing pharmacy needs prior to care transitions. Lastly, further research is needed to evaluate the role of hyperpolypharmacy as a readmission risk predictor focusing on interactions with specific comorbidities and medications.^9,38

Limitations and Strengths

This study utilized a representative sample from the 5% Medicare national sample. Claims data eliminate recall bias. However, we were not able to accurately identify elective vs nonelective readmissions using only claims data, thus preventable readmissions may be overestimated. By using pharmacy claims, we could assess which medications were prescribed and collected by the patient, but we were not able to directly assess medication usage or medication regimen adherence. Also, claims data lack timely information on whether the medication was discontinued. Thus, our data on hyperpolypharmacy after discharge should be interpreted with caution. We evaluated all-cause readmissions; future studies may focus on adverse drug event–related readmissions to determine which medications or combinations of medications in polypharmacy regimens increase the risk of readmission.

CONCLUSIONS

Hyperpolypharmacy by itself only slightly increases risk of readmission in Medicare age-eligible beneficiaries, with a stronger association in groups without TCM or E&M visits. Chronic conditions, previous health services utilization, and receipt of transitional care post discharge can predict readmission risk. In addition, postdischarge care may be underutilized, especially in the disability-eligible group. 

Author Affiliations: UTHealth Houston School of Public Health (MU, TMK, GMF, ROM), Houston, TX; Baylor Scott & White Health System (LDH), Temple, TX.

Source of Funding: Cullen Trust for Healthcare Grant 0014517.

Author Disclosures: The 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 (MU, LDH, TMK, GMF, ROM); acquisition of data (TMK, GMF); analysis and interpretation of data (MU, LDH, TMK, GMF, ROM); drafting of the manuscript (MU, LDH, GMF); critical revision of the manuscript for important intellectual content (LDH, GMF, ROM); statistical analysis (MU, LDH); obtaining funding (LDH); administrative, technical, or logistic support (TMK); and supervision (LDH).

Address Correspondence to: Gayla M. Ferguson, DrPH, UTHealth School of Public Health, 1200 Pressler St, Houston, TX 77030. Email: gayla.m.ferguson@uth.tmc.edu.

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