APIC HAI Tools » Methodology and Limitations

Intervention Cost Calculator

Purpose

This report provides an estimate of the cost of implementing a specific intervention based on:

The cost of the current practice,
The cost of the new practice, and
The extent that the event of interest is occurring in your facility (e.g., how often a specific product is used).

This output can be combined with output from other calculators on this site to emphasize the expected benefit of the intervention.

Limitations

This tool focuses on the cost incurred each time the new product or process is used (e.g., use of a new skin prep with each surgical patient). It does not take into account other costs, such as those associated with training staff about the intervention or changes in productivity of the healthcare delivery team.
This tool is intended for interventions that involve a new product or process that is used multiple times (e.g., use of a new skin prep with each surgical patient). It is not intended for use with interventions that only involve a one-time cost (e.g., purchasing new sterilizers).
The estimates provided by this tool assume that the denominator remains relatively constant from the pre-intervention time period to the post-intervention time period (e.g., there are equal numbers of device-days during the two time periods).

Methodology

The tool guides the user through the exercise of estimating the cost of an intervention, accounts for the deferred cost of replacing an existing practice when applicable, and includes a one-time cost if applicable.
When the tool is used by itself, it assesses cost-benefit by comparing the estimated cost with the cost avoidance. The user provides the estimated cost per HAI that they want to use and can reference AHRQ estimates if they lack facility-specific data.¹
When the tool is used in conjunction with the Mortality Attribution Tool (MAT) or Deferred Admissions and Reimbursement Tool (DART) calculators it assesses cost-benefit by comparing the estimated cost with the cost avoidance calculated in those additional tools.

Explanation of Output

Access the sample results of the Intervention Cost Calculator (ICC) tool. In this hypothetical example, the proposed intervention is a switch from scrubbing the hub with alcohol pads to using alcohol disinfection caps that remain on the hub when not being accessed.

The estimated cost of implementing the intervention over 12 months ($92,578) was calculated by multiplying the per-use cost of the alcohol caps ($0.20) by the estimated number of intervention events (8.4 events per central line-day multiplied by 55,106 central line-days) and adding the one-time additional cost ($0).

The estimated cost of the current practice over 12 months ($9,257) was calculated by multiplying the per-use cost of the alcohol wipes ($0.02) by the estimated number of intervention events (8.4 events per central line-day multiplied by 55,106 central line-days).

The difference between current practice and the proposed intervention was calculated by subtracting the cost of the current practice from the cost of the proposed intervention.

The estimated savings from the 5% reduction ($132,000) was calculated by multiplying the cost per CLABSI ($48,000) by the number of prevented CLABSIs (55 CLABSIs multiplied by 0.05).

Dividing the additional cost of the intervention ($83,320) by the attributable cost of all the CLABSIs (55 CLABSIs multiplied by $48,000) reveals a required CLABSI reduction of 3% for cost neutralization. In other words, if the intervention results in a 3% (or greater) reduction in CLABSIs, the cost of the intervention is potentially offset.

When combined with DART data, the attributable cost of the HAI is not incorporated. Instead, this tool compares the total intervention cost to the payment that could potentially be received by performing additional procedures.

When combined with MAT data, the attributable cost of the HAI is not incorporated. Instead, this tool uses the total intervention cost and the estimated number of lives saved to provide an estimated cost per life saved.

References

Estimating the Additional Hospital Inpatient Cost and Mortality Associated With Selected Hospital-Acquired Conditions. Content last reviewed November 2017. Agency for Healthcare Research and Quality, Rockville, MD. https://www.ahrq.gov/hai/pfp/haccost2017-results.html

Deferred Admissions and Reimbursement Tool

Purpose

This report provides:

An estimate of how many additional patients could potentially be admitted for various procedures based on a reduction in the number of extra days that beds are filled by healthcare-associated infection (HAI) patients,
An estimate of how much reimbursement those additional patients’ procedures are potentially worth, and
The option to add information about an intervention that could help achieve an applicable HAI reduction.

Limitations

This assessment is not applicable to facilities that have sufficient bed availability. If your facility isn’t deferring admissions because of high bed occupancy issues, this isn’t the right tool to use.
The list of revenue-generating admissions that you can select from may not include procedures performed at your facility.
The beds opened up by reducing infection events may not be applicable to the revenue-generating admissions you select. For example, if CLABSIs are reduced by 20 percent but most of those are in the neonatal intensive care unit, this does not necessarily mean that the facility will have the capability to perform more pacemaker insertions.
The potential revenue from deferred admissions are calculated using average reimbursements based on the Inpatient Utilization and Payment national summary data from Centers for Medicare & Medicaid Services (CMS) and are not actual reimbursements. See the Deferred Admissions and Reimbursement Tool (DART) methodology section for more information.
This assessment assumes that the applicable denominator (e.g., patient-days, central line-days) will remain approximately constant.
These estimates are based on aggregates, and individual patient events may differ significantly.

Methodology

The estimates utilized are based on the most recent available, multi-Institutional, peer-reviewed publications in reputable journals and the most recently available CMS data.
- The attributable length of stay estimates of HAIs were derived from one of two sources. For all hospital-acquired conditions (HAC) the additional days came from a November 2018 publication of healthcare-associated infections from a network of 43 hospitals across the United States.¹ For ventilator-associated pneumonia and all surgical site infections (not just HAC procedures), the attributable days were derived from a 2013 JAMA meta-analysis of studies published between 1986 and 2013.²
- The number of potential (yet deferred) admissions, as well as the CMS and total payments for said admissions, were derived from the most recently available (FY2016) National Summary of Inpatient Charge Data by Medicare Severity Diagnosis Related Group as published by CMS.³ These estimates, specifically the payment information, are likely conservative because private insurers may reimburse for the same procedure at a higher rate.

Explanation of Output

Access the sample results of the Deferred Admissions and Reimbursement Tool. In this hypothetical example, the Solid Organ Transplant Division would like to expand their kidney transplant program, but the postoperative units had 12 Clostridioides difficile infection (CDI) cases over 1 quarter. A 50 percent reduction in CDI, which would be six fewer cases, would potentially make an estimated 38 bed-days available. Using a length of stay (LOS)* of 5.5 days per kidney transplant allows for 6 additional kidney transplants with an opportunity cost estimate of a CMS payment of $156,122.

When presenting the results of this analysis, it is important to note that payment for potential admissions is not the same as organizational revenue. Obviously, an extra total joint replacement is not cost-free, but one can reasonably argue that it is certainly better than receiving no additional reimbursement because the higher-level diagnostic-related grouping is the result of a nonreimbursable HAI event. These estimates of LOS and CMS are conservative but should be readily understood by audiences familiar with CMS, billing, and reimbursement. The estimates for attributable length of stay for the HAIs are largely contemporary and rooted in multifacility analyses but are certainly subject to interpretation and scrutiny.

* The LOS used by this tool is the geometric mean length of stay (GMLOS) provided by CMS.

References

Kast R, Grabow C, Fitch M, et al. Financial cost, length of stay, and patient experience associated with healthcare-associated infections across a 43 hospital network. Open Forum Infectious Disease. 2018;5(suppl_1):S644-5. https://doi.org/10.1093/ofid/ofy210.1839.
Zimlichman E, Hendersen D, Tamir O. Healthcare-associated infections: a meta-analysis of costs and financial impact on the US healthcare system. JAMA Intern Med 2013;173(22):2039-46. https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/1733452.
Data.CMS.gov. National Summary of Inpatient Charge Data by Medicare Severity Diagnosis Related Group (MS-DRG), FY2016. https://data.cms.gov/summary-statistics-on-use-and-payments/medicare-service-type-reports/cms-program-statistics-medicare-inpatient-hospital.

Mortality Attribution Tool

Purpose

This report provides:

An estimate of the number of healthcare-associated infection-related (HAI) deaths that occur over a given time period,
An estimate of the number of lives that could be saved through a reduced HAI rate, and
The option to add information about an intervention that could help achieve an applicable HAI reduction.

Limitations

If the HAI of interest is an infrequent event, longer time periods (e.g., 1 or more years) may need to be used to see the full impact of the associated mortality rates.
The default attributable mortality rates are not facility-specific, and although they were derived from the most recent available, peer-reviewed publications, mortality estimates vary widely.
The attribution of mortality is challenging, especially in more complicated patients, who are more likely to develop HAIs in the first place, so please consider this when viewing the results from this calculator.

Methodology

The attributable mortality of each HAI was derived from primary sources of recent peer-reviewed literature, each of which were multi-institutional with appropriate control groups:
- CLABSI¹
- CAUTI¹
- SSI¹
- CDI²
Users may opt to use estimates derived from their own facility’s data or future published estimates.
Mortality events are intentionally rounded up as one cannot experience 0.3 death events, while deaths avoided are intentionally rounded down based on similar rationale.

Explanation of Output

See the sample results of the Mortality Attribution Tool. In this hypothetical example, a facility identifies 199 cases of hospital onset Clostridioides difficile in a year. Using the default attributable mortality rate of 10.9 percent, an estimated 22 patients died as a result of this infection over the one-year period. A 25 percent reduction would prevent approximately 5 deaths.

References

Glied S, Cohen B, Liu J, et al. Trends in mortality, length of stay, and hospital charges associated with healthcare-associated infections. 2006-2012. Am J Infect Control. 2016 Sep 1;44(9):983-9. https://www.sciencedirect.com/science/article/abs/pii/S0196655316002364.
Olsen MA, Stwalley D, Demont C, et al. Clostridium difficile infection increases acute and chronic morbidity and mortality. Infect Control Hosp Epidemiol. 2019 Jan;40(1):65-71. https://www.ncbi.nlm.nih.gov/pubmed/30409240.

Hospital-Acquired Conditions Expenditures Tool

Purpose

This report is for facilities whose hospital-acquired condition (HAC) rates resulted in a financial penalty via the Centers for Medicare & Medicaid Services (CMS) HAC Reduction Program. This report incorporates the facility’s preview or final HAC Reduction Program report data to provide:

An indication of whether user-proposed reductions in the facility’s standardized infection ratios (SIRs) would have been sufficient to have avoided the financial penalty, and
The option to add information about an HAI reduction intervention.

Limitations

This tool is limited to SIR values. It does not provide the specific HAC rates or numbers of HAC events associated with avoiding the financial penalty.
The HAC reductions estimated by this tool to avoid the financial penalty refer to reductions in the infections and units applicable to the HAC Reduction Program.
The user is required to provide SIRs. It is recommended that the user understand the SIR methodology and the regression models used to calculate the predicted number of infections before estimating an SIR target. This information is covered in the National Healthcare Safety Network’s detailed analysis guide.²
This tool does not determine future standing with respect to financial penalties.
This tool does not address Value Based Purchasing, which is another CMS HAC pay-for-performance program.

Methodology

The HACET utilizes data provided to each facility by Quality Net¹ to allow the user to estimate the impact of HAI reductions on their ability to avoid incurring a financial penalty.
The HACET calculates scores and determines whether a financial penalty would be incurred using the scoring methodology detailed in the Hospital-Acquired Condition Reduction Program Fiscal Year 2020 Fact Sheet.³

Explanation of Output

Access the sample results of the Hospital-Acquired Conditions Expenditures Tool. In this hypothetical example, central line-associated bloodstream infection (CLABSI) has an SIR of 2.0, indicating the number of actual CLABSIs was double the number expected, while all other infection measures have SIRs of 1, indicating the number of actual events was equal to the number expected. These SIRs would have resulted in the organization incurring a HAC penalty. If the organization had reduced its CLABSI SIR by 50 percent to an SIR of 1 and kept all other measures constant, it would not have incurred a HAC penalty.

References

QualityNet. https://www.qualitynet.org/.
The NHSN Standardized Infection Ration (SIR): A Guide to the SIR. Accessed March 30, 2020. https://www.cdc.gov/nhsn/pdfs/ps-analysis-resources/nhsn-sir-guide.pdf.
Hospital-Acquired Condition Reduction Program Fiscal Year 2020 Fact Sheet. Accessed March 30, 2020. https://www.hhs.gov/guidance/document/hospital-acquired-condition-reduction-program-fiscal-year-2020-fact-sheet.