Utilization Frailty and Association with 30-day Readmission and Patient Mortality Under the Hospital Readmissions Reduction Program - Part II

Note: This is Part II of a two-part Expert Analysis.
Part I | Part II

What is known
In an effort to improve health care quality and reduce costs under the Affordable Care Act, the Centers for Medicare and Medicaid Services (CMS) instituted the Hospital Readmissions Reduction Program (HRRP). This program publicly reports risk-standardized 30-day readmission rates (RSRRs) after hospitalizations for acute myocardial infarction, heart failure, and pneumonia, penalizing hospitals with excess rates and rewarding hospitals with low RSRRs, thus incentivizing hospitals to improve short-term post-discharge care and post-acute care transitions. Concerns have previously been raised about the HRRP's risk adjustment methods used to determine RSRRs, as they currently do not account for individuals who die within the 30-day period following hospital discharge, potentially benefitting hospitals with high short-term mortality rates.1

Frailty, a disorder of impaired recovery after illness2 is closely linked to mortality, and is also not accounted for by current risk adjustment metrics. The Hospital Frailty Risk Score (HFRS) is a claims-based frailty index tied to clusters of resource utilization developed in a British population3 and since externally validated in a Canadian population.4 The HFRS was created to further define patients at risk for poor outcomes by evaluating which administrative billing codes best identify individuals with prolonged hospital stay, increased rates of readmission, and increased rates of mortality. The HFRS has subsequently been associated with increased mortality after transcatheter aortic valve replacement (TAVR) within the United States.5

What is not known
It was previously unclear if lack of accounting for frailty in determination of RSRRs results in inadequate risk adjustment, potentially resulting in undue penalties for hospitals taking care of large numbers of frail individuals.

What this study adds
In this retrospective cohort analysis of 785,127 Medicare Fee-for-Service beneficiaries, Kundi et al6 used the Hospital Frailty Risk Score (HFRS) to evaluate if the identification of high risk patients improves prediction of 30-day hospital readmissions compared to clinical comorbidities alone. Inclusion of the HFRS in the risk adjustment model used to calculate risk-standardized 30-day readmission rates (RSRSs) for acute myocardial infarction, heart failure, and pneumonia hospitalizations improved prediction of 30-day readmission and short-term mortality compared to use of clinical comorbidities alone. This suggests that failure to account for frailty in risk models could potentially result in undue penalties to hospitals caring for high proportions of frail individuals.

While there is no one accepted definition for frailty, two major definitions have previously been proposed. In the Fried phenotypic frailty definition, frailty is defined as a clinical syndrome with impairment in five domains: strength, walking speed, physical activity, energy levels, and associated with unintentional weight loss.2 In the Rockwood frailty definition, frailty is considered an accumulation of deficits resulting from interactions with the healthcare system.7 Frailty as defined by the HFRS is somewhat different and only moderately correlates with the Fried and Rockwood definitions. The HFRS defines frailty according to clusters of increased health resource utilization and adverse outcomes, so-called "utilization frailty," and thus represents a distinct definition that may correlate only moderately with "syndromic frailty." Nevertheless, as this and other papers8 suggest, this definition identifies a higher risk subpopulation that is relevant to both clinical risk prediction and high healthcare utilization. This classification of frailty is increasingly important as the Medicare population continues to age and hospitals seek to tailor their post-discharge care for these high utilizing individuals.

Bullet points of most important findings

  • This study highlights the importance of risk adjustment for "utilization frailty."
  • Including the HFRS in the risk adjustment model used to calculate risk-standardized 30-day readmission rates (RSRSs) for acute myocardial infarction, heart failure, and pneumonia hospitalizations improved prediction of 30-day readmission and short-term mortality compared to use of clinical comorbidities alone.

Take Home Message for the Cardiovascular Clinician
Across all three conditions, addition of the HFRS resulted in a significant improvement in prediction of 30-day readmission and short-term mortality after multivariable adjustment for age, sex, race, and other comorbidities. "Utilization frailty" is an important confounder to be considered in risk adjustment models.

References

  1. Wadhera RK, Yeh RW, Maddox KE. The Hospital Readmissions Reduction Program - time for a reboot. N Engl J Med 2019;380:2289–91.
  2. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146-56.
  3. Gilbert T, Neuburger J, Kraindler J, et al. Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study. Lancet 2018;391:1775–82.
  4. McAlister F, van Walraven C. External validation of the Hospital Frailty Risk Score and comparison with the Hospital-patient One-year Mortality Risk Score to predict outcomes in elderly hospitalised patients: a retrospective cohort study. BMJ Qual Saf 2019;28:284-88.
  5. Kundi H, Valsdottir LR, Popma JJ, et al. Impact of a claims-based frailty indicator on the prediction of long-term mortality after transcatheter aortic valve replacement in medicare beneficiaries. Circ Cardiovasc Qual Outcomes 2018;11:e005048.
  6. Kundi H, Wadhera RK, Strom JB, et al. Association of frailty with 30-day outcomes for acute myocardial infarction, heart failure, and pneumonia among elderly adults. JAMA Cardiol 2019;4:1084-91.
  7. Rockwood K, Song X, MacKnight C, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ 2005;173:489–95.
  8. Figueroa JF, Joynt Maddox KE, Beaulieu N, Wild RC, Jha AK. Concentration of potentially preventable spending among high-cost medicare subpopulations: an observational study. Ann Intern Med 2017;167:706–13.

Keywords: Geriatrics, Patient Readmission, Fee-for-Service Plans, Length of Stay, Patient Protection and Affordable Care Act, Risk Adjustment, Transcatheter Aortic Valve Replacement, Centers for Medicare and Medicaid Services, U.S., Retrospective Studies, Health Resources, Weight Loss, Hemorrhagic Fever with Renal Syndrome, Patient Transfer, Medicare, Patient Discharge, Hospitalization, Medicaid, Heart Failure, Myocardial Infarction, Comorbidity, Pneumonia, Exercise


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