The Impact of Interhospital Transfers on Surgical Quality Metrics for Academic Medical Centers
By Behrns, Kevin E | |
Proquest LLC |
The emergence of pay-for-performance systems pose a risk to an academic medical center's (AMC) mission to provide care for inter-hospital surgical transfer patients. This study examines quality metrics and resource consumption for a sample of these patients from the
THE MISSION OF academic medical centers (AMCs) is to serve the community through ongoing physi- cian training, research, technological innovations, and provision of health care to high-acuity and complex patients.1 The current healthcare reform proposed by the Affordable Care Act (ACA) poses a risk to this mission.2 Under the ACA,
Inclusive in their mission, AMCs commonly accept the risk of providing care to critically ill transfer pa- tients. Based on 2011 data from the
To determine the effect of surgical transfer patients on quality outcomes and resource consumption at AMCs, we studied two patient populations. First, the UHC's AMC data set was used to compare quality metrics, resource use, and cost between surgical trans- fers and direct admission (DA) patients for a diverse national patient population. UHC is a cooperative of 120 not-for-profit AMCs in
Methods
Data Source and Cohort Identification
Permission to conduct these studies was obtained from the
Variables Analyzed
Data for the UHC patient population included age, gender, race, admission source, admission type, ad- mission severity of illness (SOI), health insurance, mortality rate, readmission rate, length of stay (LOS), case mix index (CMI), comorbidities, and direct and total costs. Discharges were classified as transfer or DA patients. A transfer patient was defined as a patient transferred to our facility from a different hospital. A DA patient was defined as all other categories of admitted patients. Admission SOI was assigned by the 3M
Statistical Analysis
For the UHC study population, we performed a de- scriptive analysis of UHC's aggregate data. Statistical analysis was performed using SAS (SAS Version 9.3,
Results
UHC data on 1,423,893 records of surgical dis- charges from AMCs were obtained. Of these, 176,554 (12%) were classified as transfer patients and 1,247,229 (88%) were classified as DA patients. To determine if the UF DOS is an illustrative example within the larger UHC data set, demographics and quality indicators, including cost, were compared between the UHC pa- tient population and the UF DOS study population. The data comparing these two study populations are shown in Tables 1 and 2.
Table 1 displays demographic characteristics by admission source. Compared with DA patients, trans- fer patients were older and more likely to be male (60%) and white (75%). As expected, 95 per cent of transfer patients had an admit status of emergent/urgent/ trauma center compared with 53 per cent of DA pa- tients. Transfer patients had a higher admission SOI with 53 per cent classified as major or extreme, whereas 28 per cent of DA patients were classified as such. Primary payer mix for both groups of patients was comparable with over 70 per cent of cases covered by commercial/managed care and
Across all eight measured indicators, transfer pa- tients had poorer quality outcomes than DA patients (Table 2). The mortality rate for UHC transfer pa- tients was 5.70 per cent compared with 1.79 per cent for DA patients. However, transfer readmission rates were similar to DA patients. UHC transfer patients had a 37 per cent increase in CMI and a 28 per cent increase in comorbidities compared with DA patients. LOS for UHC DA patients was four days shorter, whereas transfer patients' stay in the intensive care unit (ICU) was 2.5 days longer than DA patients. The direct and total costs for UHC transfer patients were over 50 per cent higher than DA patients. The quality indicators for the UF DOS patients are higher across all eight categories for both transfer and DA patients than UHC. However, our transfer to DA differences across all quality indicators is nearly identical to UHC.
The Clinical Resource Manager (CRM) portion of UHC's database was used to compare resource use for transfer and DA patients. Five high-impact resource categories were identified and compared for all UHC members participating in the CRM (Table 3). Transfer patients had a higher percentage of patients using four of five categories (i.e., ICU, respiratory therapy, imag- ing, and medical surgical supplies). Only pharmacy use was not different between the groups. For each hospital stay, transfer patients used all resources for more days than DA patients: ICU +2.4 days, respiratory therapy +3 days, imaging +2.6 days, medical/surgical +0.9 days, and pharmacy +4.1 days). Pharmacy was the most used resource for both groups (11.4 days for transfer patients vs. 7.3 days for DA patients). Medical surgical supply was the least used resource for both groups (2.9 days for transfer patients vs. 2.0 days for DA patients).
To determine resource use in the UF DOS patient population,
Discussion
This study was conducted to test the hypothesis that transfer patients had a poorer outcome and consumed more resources than nontransfer patients. Indeed, our results demonstrated that transferred patients have higher mortality rate and a longer LOS. Resource consumption, especially in high-impact categories (respiratory therapy, ICU care, imaging, and phar- macy), is higher in transferred patients. Not surpris- ingly, the costs associated with caring for transferred patients are significantly higher than DA patients. Although the results may be intuitive, the conse- quences of these findings may have a major impact on the financial status of AMCs in a pay-for-performance reimbursement model. Thus, data demonstrating the outcomes and resource consumption for transfer patients are of paramount importance to ensure the financial stability of AMCs.
Previous investigation has established that transfer patients negatively impact the clinical outcome metrics of receiving facilities.7-10, 12, 18 Most of these reports confirm the findings of the present study. With rare exceptions,14, 15 these studies show that even with risk adjustment, outcomes are worse for transfer pa- tients.7, 8, 10, 18 For example, Santry et al.18 demon- strated that acute care transferred surgery patients were more likely to be obese, have cardiac or pulmonary comorbidities, higher mortality, and longer hospital stay (P 4 0.0001). These factors are also evident in our analysis because CMI, SOI, mortality rate, LOS, and ICU days (Tables 1 and 2) were higher for transfer patients. The use of mortality rate and LOS as the most common benchmarks for comparing performance among all healthcare centers places AMCs in a vul- nerable position for effectively competing in pay-for- performance systems.
As a result of their expertise in managing rare dis- ease entities and experience in dealing with complex patient populations, AMCs are ideal receiving facili- ties for transfer patients. Accepting and serving these patients is also consistent with the mission of an AMC. However, caring for such patient populations also re- quires that AMCs absorb the cost associated with the elevated level of care. As reflected in our UF DOS findings, the operating room costs as well as associated cost with intensive care are significantly higher in transferred patients, and this difference may be sub- stantial (Table 4). To our knowledge, this is the first study that compares UHC's RCC data (Table 2) with actual institution costs from our UF DOS financial database (Table 4). Across all UF DOS cost categories, transferred patients consistently require more resources resulting in costly care.
Currently, healthcare policy assumes that access to AMCs and the infrastructure around interhospital patient transfers functions well.19, 20 However, al- though implementation of transfer call centers has improved the process, the initiation of transfers is still at the discretion of the outside hospital and is un- regulated. The study by Bosk et al. demonstrates that only protocol care for diseases like myocardial in- farction are quickly assessed and appropriately tri- aged for transfer care in an effective manner.19 In contrast, conditions with a less standardized ap- proach are often over- or undertriaged, which leads to interorganizational tensions and suboptimal patient care. Bosk et al. further suggests that reduced cost and improved patient outcomes may be obtained with standardization of protocol efforts through collaborative partnerships between community hospitals and AMCs. In addition, AMCs should consider affiliations with healthcare organizations that provide appropriate levels of care and broader patient populations for research.21 Efforts such as these may be achievable through the use of telemedicine. For example, Angileri et al.22 found that a telemedicine network allowed for accurate de- termination and treatment of neurological cases, which avoided unnecessary costly transfers.
Current healthcare reform will result in government and private payers increasingly assessing quality mea- sures such as mortality, LOS, and cost to determine payment to providers. This places AMCs in a quandary. A mission of the AMCs is to care for the severely ill and provide a safety net to the community; however, quality metric-driven reimbursement places this mission in jeopardy because high-cost care cannot take place in perpetuity with continually lower reimbursement. The dilemma is even more pronounced for surgical spe- cialties because the surgical care rendered may have a prompt and dramatic life-saving effect but occurs with high resource consumption and costs. This predicament of delivering high-quality care to a high-risk patient population while maintaining low costs argues for a value-based system that recognizes and rewards the complexity of care.
The limitations of this study are inherent to any study that uses an administrative data set. The accuracy and reliability of the data is dependent on the efforts of each institution, their coding, and accurate physician documentation. UHC's data are based on a population of patients at the diagnosis-related group level; thus, our study did not attempt to stratify by patient condi- tion within specific service lines. In addition, this study did not review the impact of transfer patients on re- imbursements. However, a previous study has com- pared reimbursement rates across all specialties that treated transferred patients at a tertiary care center and found that reimbursement per relative value unit on transfer patients was generally worse with the excep- tion of only two specialties, emergency medicine and neurological surgery.23 To fully understand the finan- cial impacts of transfer patients, future studies should involve this type of analysis.
In conclusion, this study demonstrates that transfer patients have poorer outcomes and consume substan- tially more resources than DA patients. As recipients of large volumes of transfer patients, the new pay-for- performance models of health care pose financial risks for AMCs. To mitigate this risk, the authors forward an approach in which collaborative partnerships with community hospitals and transfer protocol devel- opment are used to enhance earlier recognition and appropriate transfer of complex surgical patients. Per- haps such an approach would improve the opportunities for patient rescue and consume fewer resources. Sur- gical care should no longer be delivered in isolated silos of community and academic surgery practices. A col- laborative approach that takes into consideration the longer-term outcome of patients and the costs to the healthcare system is warranted.
Acknowledgments
We thank
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From the
Presented at the Annual Scientific Meeting and Postgraduate Course Program,
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Copyright: | (c) 2014 Southeastern Surgical Congress |
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