Sepsis Among Medicare Beneficiaries: 3. The Methods, Models, and Forecasts of Sepsis, 2012-2018

Abstract

Objective: To evaluate the impact of sepsis, age, and comorbidities on death following an acute inpatient admission and to model and forecast inpatient and skilled nursing facility costs for Medicare beneficiaries during and subsequent to an acute inpatient sepsis admission.

Design: Analysis of paid Medicare claims via the Centers for Medicare & Medicaid Services DataLink Project (CMS) and leveraging the CMS-Hierarchical Condition Category risk adjustment model.

Setting: All U.S. acute care hospitals, excepting federal hospitals (Veterans Administration and Defense Health Agency).

Patients: All Part A/B (fee-for-service) Medicare beneficiaries with an acute inpatient admission in 2017 and who had no inpatient sepsis admission in the prior year.

Interventions: None.

Measurements and main results: Logistic regression models to determine covariate risk contribution to death following an acute inpatient admission; conventional regression to predict Medicare beneficiary sepsis costs. Using the Hierarchical Condition Category risk adjustment model to illuminate influence of illness on outcome of inpatient admissions, representative odds ratios (with 95% CIs) for death within 6 months of an admission (referenced to beneficiaries admitted but without the characteristic) are as follows: septic shock, 7.27 (7.19-7.35); metastatic cancer and acute leukemia (Hierarchical Condition Category 8), 6.76 (6.71-6.82); all sepsis, 2.63 (2.62-2.65); respiratory arrest (Hierarchical Condition Category 83), 2.55 (2.35-2.77); end-stage liver disease (Hierarchical Condition Category 27), 2.53 (2.49-2.56); and severe sepsis without shock, 2.48 (2.45-2.51). Models of the cost of sepsis care for Medicare beneficiaries forecast arise approximately 13% over 2 years owing the rising enrollments in Medicare offset by the cost of care per admission.

Conclusions: A sepsis inpatient admission is associated with marked increase in risk of death that is comparable to the risks associated with inpatient admissions for other common and serious chronic illnesses. The aggregate costs of sepsis care for Medicare beneficiaries will continue to increase.

Figure 1.

Models of payments, Medicare fee-for-service, inpatient only. Left column, two-parameter (linear) model regressing on sum of prior 12-mo payments. Right column, three-parameter model incorporating a phasic term (“line and a cosine”) to account for seasonal variation regressing on the monthly payment. Top row, model and actual data. Middle row, studentized residuals by month. Note the obvious nonrandom pattern of residuals by month from the two-parameter model, compare with the apparently random pattern of residuals by month from the three-parameter model. Bottom row, Q-Q plots showing the distributions of residuals versus a normal distribution. The closer the data fall on the line of identity, the closer the distribution of residuals lies to a normal (random) distribution. The three-parameter model captures the essential features of payments.

Figure 2.

Models of payments, Medicare fee-for-service and Medicare Advantage, inpatient only. Medicare advantage payments based on encounter data. Models and explanations identical to Figure 1.

Figure 3.

Models of payments, Medicare fee-for-service and Medicare Advantage, inpatient and skilled nursing facility. Medicare Advantage payments for inpatient care based on encounter data. Medicare Advantage payments for skilled nursing facility care assume similar utilization and similar payments per episode. Models and explanations identical to Figure 1.