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Cost Analysis of Computerized Clinical Decision Support and Trainee Financial Incentive for Clostridioides difficile Testing

Published online by Cambridge University Press:  23 November 2018

Gregory R. MaddenOpen the ORCID record for Gregory R. Madden[Opens in a new window],
Heather L. Cox,
Melinda D. Poulter,
Jason A. Lyman,
Kyle B. EnfieldOpen the ORCID record for Kyle B. Enfield[Opens in a new window] and
Costi D. SifriOpen the ORCID record for Costi D. Sifri[Opens in a new window]
Gregory R. Madden
Affiliation:
Division of Infectious Diseases & International Health, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
Heather L. Cox
Affiliation:
Division of Infectious Diseases & International Health, Department of Medicine, University of Virginia Health System, Charlottesville, VirginiaDepartment of Pharmacy Services, University of Virginia Health System, Charlottesville, Virginia
Melinda D. Poulter
Affiliation:
Clinical Microbiology Laboratory, Department of Pathology, University of Virginia Health System, Charlottesville, Virginia
Jason A. Lyman
Affiliation:
Department of Public Health Sciences, University of Virginia Health System, Charlottesville, Virginia
Kyle B. Enfield
Affiliation:
Division of Pulmonary & Critical Care Medicine, Department of Medicine, University of Virginia Health System, Charlottesville, Virginia
Costi D. Sifri*
Affiliation:
Division of Infectious Diseases & International Health, Department of Medicine, University of Virginia Health System, Charlottesville, VirginiaOffice of Hospital Epidemiology/Infection Prevention & Control, University of Virginia Health System, Charlottesville, Virginia
*
Author for correspondence: Costi D. Sifri, Division of Infectious Diseases & International Health, University of Virginia Health System, PO Box 800473, Charlottesville, VA 22908–0473. E-mail: csifri@virginia.edu
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Abstract

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Information

Type
Research Brief
Information
Infection Control & Hospital Epidemiology , Volume 40 , Issue 2 , February 2019, pp. 242 - 244
Copyright
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved. 

Clostridioides (formerly Clostridium) difficile infection (CDI) is the most common cause of healthcare-associated infections, leading to increased morbidity, mortality, length of hospital stay, and costs.Reference Kyne, Hamel, Polavaram and Kelly 1 , Reference Desai, Gupta, Dubberke, Prabhu, Browne and Mast 2 CDI contributes an estimated $5.4 billion to US healthcare annually.Reference Desai, Gupta, Dubberke, Prabhu, Browne and Mast 2 In an era of highly sensitive molecular testing, overdiagnosis of CDI is also suspected to be common, and up to half of inpatients with a positive C. difficile nucleic acid amplification test (NAAT) may not require treatment.Reference Polage, Gyorke and Kennedy 3

Overdiagnosis may be due to testing patients with low pretest probability for disease. Improving test utilization through diagnostic stewardship has the potential to reduce unnecessary testing and diagnostic error.Reference Madden, Weinstein and Sifri 4 Various strategies have been proposed for C. difficile testing, including computerized clinical decision support (CCDS).Reference Madden, Weinstein and Sifri 4 We previously reported implementation of a CCDS tool (as part of a multifaceted bundle of interventions to reduce National Healthcare Safety Network (NSHN)–defined hospital-onset CDI [HO-CDI]) 5 in our institution that led to significantly reduced testing and fewer HO-CDI events.Reference Madden, German Mesner and Cox 6 Here, we present a cost analysis of this intervention.

Methods

The CCDS tool was implemented after internal auditing suggested that testing for C. difficile might not have been indicated in up to 67% of HO-CDI cases in our institution.Reference Madden, German Mesner and Cox 6 A detailed description of the decision support algorithm, including a video demonstration of the CCDS tool, has previously been published.Reference Madden, German Mesner and Cox 6 House staff were involved with an educational campaign that preceded CCDS implementation and offered a 0.8% salary bonus at the end of the academic year if testing fell by≥25%.

The financial incentive, funded jointly by the UVA Office of Graduate Medical Education and UVA Health System, was part of a recurring incentivized annual quality improvement project led by trainees, for which C. difficile testing was chosen as the subject for the 2016–2017 academic year. Real-time monitoring of test utilization, with unit and service attributions, was available through an electronic portal as feedback during the intervention period.

A retrospective cost analysis was performed that included cost savings from reduced test utilization and fewer HO-CDI events (based on estimated attributable costs for hospitalized patients with CDI),Reference Kyne, Hamel, Polavaram and Kelly 1 , Reference McGlone, Bailey and Zimmer 7 , Reference Song, Bartlett, Speck, Naegeli, Carroll and Perl 8 in addition to costs of building the CCDS tool and house staff financial incentives.

Results

Hospital census remained relatively constant during the study period, with 156,154 and 159,094 patient days during the preintervention (December 2015 – November 2016) and postintervention (December 2016 – November 2017) periods, respectively. Total laboratory cost (materials and labor) was estimated at $31.36 per test (Table 1). Based on the literature, the estimated attributable cost per hospitalized CDI case was between $3,669Reference Kyne, Hamel, Polavaram and Kelly 1 and $9,197;Reference McGlone, Bailey and Zimmer 7 the median, $6,326,Reference Song, Bartlett, Speck, Naegeli, Carroll and Perl 8 was chosen for purposes of our analysis. The 0.8% house-staff financial incentive was based on house staff salaries (median, $61,669; range $54,107–$71,167). The technology-associated cost involved with creating the CCDS tool (ie, developing question algorithm, software building, testing, migration through environments, etc) was estimated to be $1,000.

Table 1

Impacts of the Clostridioides difficile Computerized Clinical Decision Support (CCDS) Tool and Incentive on Testing and Infection Events

Note. NAAT, nucleic acid amplification test; HO-CDI, hospital-onset C. difficile infection; Pre, preintervention period; Post, postintervention period.

a Identified as a test order opened by a provider, triggering the CCDS, but without a completed order.

b Within 3 days following a previous negative result.

c Within 14 days following a previous positive result.

In total, the CCDS tool was associated with a net $61,524 annual cost savings, largely attributable to estimated reductions in unnecessary inpatient CDI treatment and laboratory diagnostics (Table 2).

Table 2

Cost Analysis

Note. NAAT, nucleic acid amplification test; HO-CDI, hospital-onset C. difficile infection; Pre, preintervention period; Post, postintervention period; h, hours.

Cost differences reflect preintervention minus postintervention periods with the exception of technology-associated build time, which was factored under the postintervention period for this analysis.

Discussion

Diagnostic stewardship was successfully applied to C. difficile testing through implementation of a CCDS tool coupled with a financial incentive. The intervention not only reduced testing and HO-CDI (previously reported)Reference Madden, German Mesner and Cox 6 but resulted in a significant overall savings for the health system despite the considerable initial cost of the incentive. Cost savings could be considerably greater in subsequent years without the expense of the bonus, if the tool remains effective in guiding test utilization. Nonetheless, the study has several limitations.

First, the primary goal of our intervention was to improve patient care by reducing inappropriate tests and potential harm attributable to overtreatment, which accounted for the largest proportion of estimated savings. However, it is imperative to understand not only the benefits but also the potential harms of reduced C. difficile testing. Further studies are needed to explore the overall effectiveness and safety of the diagnostic stewardship interventions for C. difficile assessment.

Second, HO-CDI events were chosen as a convenient estimate for reduction in treatment for CDI; however, reductions in HO-CDI did not necessarily reflect prevention of CDI treatment in all patients and may have over- or underestimated savings. For example, we did not factor community-onset or recurrent CDI, which may cost up to $10,580 per case.Reference Zhang, Prabhu and Marcella 9 Other “hidden” costs, such as added provider time and administrative/quality improvement efforts, were not included. Also, savings associated with avoidance of reimbursement penalties or improved institutional reputation/rankings were not factored in the analysis.

Finally, pharmaceutical costs were not calculated separately from estimated attributable costs because nearly all patients were treated with oral vancomycin compounded by the hospital pharmacy.

The cost analysis of a CCDS diagnostic stewardship tool like ours will be impacted by institutional decisions regarding C. difficile infection testing and alternative treatment protocols. As such, this report should not be viewed as a cost-effectiveness analysis but rather as an assessment of costs and estimated cost savings of the CCDS tool at our institution. A financial incentive may not be feasible at other institutions; however, the specific contribution of the bonuses to this diagnostic stewardship intervention is unknown. Reduced testing has been sustained for at least 12 months following distribution of the 1-time financial incentive for trainees in June 2017. In addition, trainees comprised only about half of the prevented tests; other ordering providers received no incentive.

Although experimental and financial evidence support the use of diagnostic stewardship to improve C. difficile diagnostic utilization, further studies are required to establish patient safety and to generalize our findings at other institutions.

Acknowledgments

The authors thank those involved with designing and implementing the CCDS tool, particularly UVA Health System's graduate medical education house staff programs, Antimicrobial Stewardship Program, and C. difficile Prevention Coalition.

Financial support

Study supported by the National Institutes of Health Infectious Diseases (training grant no. 5T32AI007046–41).

Conflicts of interest

All authors report no conflicts of interest relevant to this article.

Footnotes

PREVIOUS PRESENTATION: Data from this study were presented in part as an abstract at the 2018 Society for Healthcare Epidemiology of America meeting on April 19, 2018, in Portland, Oregon (abstract #327).

Cite this article: Madden GR et al. (2019) Cost analysis of computerized clinical decision support and trainee financial incentive for Clostridioides difficile testing. Infection Control & Hospital Epidemiology 2019, 40, 242–244. doi: 10.1017/ice.2018.300

References

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Figure 0

Table 1Impacts of the Clostridioides difficile Computerized Clinical Decision Support (CCDS) Tool and Incentive on Testing and Infection Events

Figure 1

Table 2Cost Analysis