Readmission Rates and TCM Services
In this project, an extensive statewide integrated health system did not meet the target metric for Medicare VBP contract readmission rates. Previously, the contracts were successful in decreasing readmission and emergency room utilization rates by having adequate staffing, performance metrics, and care team protocols. After determining which patients were currently receiving transitional care management and who was performing these activities, multiple gaps in care were identified. All patients did not receive TCM services. Inconsistencies were identified regarding who provided the follow-up phone call, where this encounter was documented, information included in the documentation note, and a clear protocol on follow-up services. An opportunity existed to implement TCM processes allowing for TCM billing code utilization for the Medicare population in the discharges from one hospital in the integrated health system. A 2018 financial data review revealed the organization was billing TCM codes at 13% at the hospital pilot site for Medicare patients discharging home. This review revealed an opportunity to increase revenue by 80% with TCM billing for the Medicare population. The 2018 Medicare discharges at the hospital site were 9,527, and the institution only submitted 1,184 TCM billing codes for total revenue of $242,720. Increasing TCM for all hospital discharges in the health system could increase TCM reimbursement, increasing revenue (see Table 1).
Use of TCM Services
Routine TCM outreach phone calls allow nurses to identify patients requiring assistance, including the need to make office appointments (Emanuel et al., 2019; Thomas & Siaki, 2017). TCM calls also have the benefit of potentially increasing patient satisfaction (Mora et al., 2017). While phone calls are an important service in transition to home care, TCM calls by themselves do not necessarily impact readmission rates (Hart & Nutt, 2020; Mora et al., 2017). Better care for transitional care coordination post-hospital discharge and a timely follow-up visit as an intervention are needed to decrease readmission rates (Altfeld et al., 2012; Eggenberger et al., 2013; Goyal, Hall et al., 2016; Goyal, Sterling et al., 2016; Gurwitz et al., 2014; Horwitz et al., 2013; Jackson et al., 2015; Kamermayer et al., 2017; Lin et al., 2011). However, the definition of timely follow-up visits varies (Goyal, Sterling et al., 2016; Gurwitz et al., 2014; Jackson et al., 2015; Kamermayer et al., 2017). Kamermayer and colleagues (2017) defined timely as 7–21 days, depending on the circumstances; Goyal, Sterling and coauthors (2016) described timely as 7–14 days post-discharge. In the adult population, follow-up visits within 30 days of hospital discharge showed a decrease in readmission rates (Gurwitz et al., 2014; Jackson et al., 2015). In contrast, follow-up visits were associated with an increase in readmission rate (Coller et al., 2013; Doctoroff et al., 2014). Doctoroff and associates (2014) attributed increased readmission rates on patients being followed by a resident physician whose inexperience and lack of access were contributing factors.
Scheduling the follow-up appointment before and after discharge effectively reduced readmission rates (Kamermayer et al., 2017). Jackson and coauthors (2015) and Lin and colleagues (2011) scheduled appointments during the TCM outreach phone calls. Alternatively, Goyal, Hall and associates (2016) found scheduling follow-up appointments before discharge had better visit compliance rates than scheduling the appointment after discharge. Goyal, Hall and colleagues showed an increase in visit scheduling both pre-discharge and during outreach call. Still, there was a slightly larger increase in visit compliance in the pre-discharged population. The key factor is getting patient visits scheduled, whether pre-discharge or during an outreach phone call.
Most of the research involved large patient populations, which help validate the findings, but some of the studies relied on single hospital data sources (Coller et al., 2013; Doctoroff et al., 2014; Goyal, Sterling et al., 2016).
Nurs Econ. 2021;39(2):59-66. © 2021 Jannetti Publications, Inc.