The INSPIRE-ASP Trial (INtelligent Stewardship Prompts to Improve Real-Time Empiric Antibiotic Selection for Patients) for Skin and Soft Tissue (SST) Infections
Phase: NA
Conditions: Skin and Soft Tissue (SST) Infection
Sponsor: Harvard Pilgrim Health Care

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1 
  
Brief Overview 
The INSPIRE-ASP Trial (INtelligent Stewardship Prompts to Improve Real-time Empiric Antibiotic 
Selection for Patients) for Skin and Soft Tissue (SST) Infections is a cluster-randomized trial of 92 hospital 
randomized units (102 individual hospitals) to improve physicians’ choice of antibiotics for patients hospitalized 
with SST infections by reducing the unnecessary use of extended-spectrum antibiotics. This trial provides 
prescribers in half the hospitals with prescribing advice based on the probability that a patient is infected with 
antibiotic resistant bacteria. Provision of unnecessary extended-spectrum antibiotics carry risks, and the goal 
of this trial is to limit their use to situations in which the patient is likely to require them, while maintaining 
excellent patient outcomes.  
We hypothesize that providing clinicians with individual patient risk estimates for antibiotic-resistant 
infections will reduce the overuse of empiric extended-spectrum antibiotics among patients hospitalized for 
SST infections. To do this, we will use patient information in the electronic health record plus local hospital 
laboratory data on antibiotic resistance in SST cultures to develop an automated smart tool that provides the 
likelihood that a patient needs extended-spectrum antibiotics. 102 hospitals were randomized into 92 hospital 
were randomized to either routine care orto the intervention arm receiving the INSPIRE Stewardship Bundle 
units, into either routine care (46 hospital units) or to the intervention arm (46 hospital units) receiving the 
INSPIRE Stewardship Bundle which includes CPOE smart prompts, clinician feedback reports, and activities to 
support CPOE adoption (e.g., education and modifications of CPOE workflows as needed). . In half of 
hospitals, physicians will be prompted to use standard-spectrum antibiotics when the risk of an antibiotic-
resistant infection is low. This 12-month intervention will evaluate approximately 61,000 patients with SST 
infections.  
Protocol Summary 
This protocol provides detailed instructions for the conduct of the INSPIRE-ASP Trial (INtelligent 
Stewardship Prompts to Improve Real-time Empiric Antibiotic Selection for Patients) for Skin and Soft Tissue 
(SST) Infections. This trial is a 92 hospital unit (102 individual hospitals), 61,000 patient, cluster-randomized 
trial to improve physicians’ choice of antibiotics for hospitalized patients by reducing the unnecessary use of 
broad-spectrum antibiotics while maintaining excellent patient outcomes. This trial will be conducted in the 
HCA Healthcare system, which provides 5% of acute care services in the United States. 
Hospitals will be recruited through usual HCA Healthcare communication channels and randomized into 
a two-arm trial involving routine care or routine care plus a stewardship bundle that includes real-time 
personalized risk calculator for whether a patient with SST infection is infected with an antibiotic-resistant 
pathogen warranting extended-spectrum antibiotic therapy. This protocol details eligibility criteria for 
participation, factors accounted for in 1:1 hospital randomization, notification of randomization assignment, and 
provision of the two arms with arm-specific toolkit information and coaching calls. It also details the process by 
which centralized IRB approval and reliance agreements will be obtained. 
This trial evaluates a quality improvement antibiotic stewardship strategy, the INSPIRE Stewardship 
Bundle, that includes (1) computerized physician order entry (CPOE) decision support alert that provides 
physicians with patient-specific risk estimates for having a (ABD) infection due to a multidrug-resistant 
organism (MDRO) and recommends standard spectrum antibiotics for low risk patients in the first 3 days of 
hospitalization; (2) clinician feedback reports, and (3) activities to support CPOE adoption (including education 
and alignment of CPOE workflows). As such, study implementation will be performed through the local 
infrastructure provided by hospital antibiotic stewardship program leaders who serve as study champions. 
Participating hospitals in both arms will approve the arm-specific study protocol through usual hospital 
committees. The routine care arm will participate in regular coaching calls to ensure best practice for national 
standards of stewardship are taught and encouraged. This arm will also launch a trial-specific modification to 
the existing antibiotic indication screen. 
Several activities are detailed for the INSPIRE Stewardship Bundle arm. These include pre-launch 
activities such as participation in coaching calls and an on-site training visit, as well as procedures to locally 
install corporate MediTech software for the CPOE personalized risk calculator for SST antibiotic indications, 
including any modifications needed to align the CPOE workflow to support the INSPIRE prompts (e.g., order-
based exclusion of ICU patients, order set changes). In addition, the sites receiving the INSPIRE Stewardship 
Bundle will receive educational materials, participate in monthly coaching calls and every other month check in 

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calls, and receive clinician audit reports to feedback to physicians and hospital leadership about protocol 
adherence. 
As a pragmatic trial, all data will be obtained from the HCA Healthcare centralized clinical data 
warehouse. Local site champions will not need to collect any outcome data or variables for description or 
adjustment. This protocol describes how data will be obtained through a data use agreement between HCA 
Healthcare and the Harvard. Data and programmer analysts will access and analyze data on the HCA 
Healthcare server behind the HCA Healthcare firewall, thus ensuring maximum data protections.  
In summary, the INSPIRE Trial for Skin and Soft Tissue (SST) Infections is a randomized trial of 92 
hospital units (102 individual hospitals) and approximately 61,000 infected patients to improve physicians’ 
choice of antibiotics for patients hospitalized with SST infection by reducing the unnecessary use of extended-
spectrum antibiotics. This trial protocol provides the road map for the conduct of the trial to determine if a 
personalized real-time risk calculator plus audit and feedback can improve judicious use of antibiotics in 
hospitalized patients.  
B. Background Information and Scientific Rationale
B.1. Background Information
National Call for Antibiotic Stewardship in an Era of Antibiotic Resistance
Inappropriate use of extended-spectrum antibiotics is a major driver of the 2 million antibiotic-resistant 
infections in the U.S. each year.1,2 Nearly 40% of inpatient antibiotics are inappropriate or unnecessary.3,4 
Unfortunately, rising antibiotic resistance has fueled rather than curbed extended-spectrum antibiotic use, with 
prescribers using extended-spectrum agents for the possibility of resistance, thus leading to a detrimental cycle 
that urgently needs attention.5 
A main principle for judicious prescribing is to use the narrowest spectrum antibiotic necessary to treat 
infection. Antibiotics that cover the vast majority of organisms that cause a particular disease are “standard-
spectrum” agents, with “extended-spectrum” agents reserved for infections proven to be caused by antibiotic 
resistant organisms not covered by standard-spectrum agents, or for critically ill patients for whom there may 
not be time to wait for culture and susceptibility results. However, many U.S. clinicians routinely use extended-
spectrum antibiotics empirically to cover rare events. 
B.2. Rationale
In 2015, in response to a dwindling antibiotic arsenal active against resistant bacteria, a U.S. national 
action plan was forged.6 It called for every hospital to implement an antibiotic stewardship program with a set 
of core elements. Current stewardship programs employ a variety of unproven and labor-intensive approaches 
to promote judicious antibiotic prescribing. Pragmatic clinical trials to identify best practice are needed.7  
Skin and Soft Tissue (SST) Infections as Critical Disease Targets 
SST infections cause 3 million U.S. emergency department visits annually and 700,000 
hospitalizations.15-17 Here, we use the CDC National Healthcare Safety Network terminology for skin and soft 
tissue disease (SST) as interchangeable with current clinical ABSSSI (acute bacterial skin and skin structure 
infections).Causative agents are most commonly beta-hemolytic streptococci and S. aureus (including MRSA), 
but the majority of cases receive inappropriate antibiotics to broadly cover Gram-negative organisms and 
anaerobes.16,18-21 While national guidelines and recent epidemiology recommend that vancomycin should be 
used to cover MRSA,16,18-22 guidelines discourage empiric extended-spectrum therapy for resistant Gram-
negative unless the prevalence of resistance is >20%.22 This proposal will comprehensively assess absolute 
risk for antibiotic-resistant infections and recommend judicious use of extended spectrum antibiotics for SST 
infections.  
Rationale for Intervention Strategy 
Scientific Basis and Clinical Significance 
Rising antibiotic resistance and the slow development of novel antibiotics have fueled national calls to 
improve antibiotic choices by frontline physicians. There is a 2020 target to reduce “inappropriate” antibiotic 
prescribing in hospitals by 20%, as discussed in the 2014 “National Strategy for Combating Antibiotic-Resistant 

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Bacteria” released by the White House. While physicians agree that antibiotics are overprescribed, most fail to 
recognize areas for self-improvement. Therefore, hospitals have been charged with developing antimicrobial 
stewardship programs which provide ongoing education and feedback to physicians and ensure accountability 
in prescribing. Many patients who are prescribed antibiotics in U.S. hospitals receive inappropriately broad-
spectrum antibiotics. A major driver of unnecessary broad spectrum antibiotic use is clinicians’ overestimation 
of the likelihood that the patient is infected by a multidrug-resistant organism (MDROs). To improve the 
success of these efforts, it is critical to develop evidence about best practices for improving judicious antibiotic 
prescribing. Evidence, engagement, and education are required to build a culture where it is accepted that 
rationale antibiotic prescribing is every physician’s responsibility. 
The current focus of U.S. antimicrobial stewardship efforts has been to establish local hospital 
programs outfitted with a multi-disciplinary team of clinicians and pharmacists. National recommendations 
involve reviewing the antimicrobial formulary, and ensuring appropriate weight-based dosing, and IV vs oral 
selection. In recent years, national recommendations have targeted clinical care optimization by 
recommending processes to establish and update local antibiograms, evidence-based treatment guidelines 
and order sets, and active review of antimicrobial therapy to narrow antibiotic choice when pathogens grow 
from clinical cultures – e.g. “de-escalation” after when clinical cultures yield pathogens, generally three to 
seven days after cultures are sent. 
These efforts, while admirable, do not address the majority of inappropriate antibiotic use in hospital 
settings, because the majority of antibiotics are prescribed empirically while pending any possible knowledge 
of the causative pathogen from clinical cultures. Culture results and antibiotic susceptibilities typically become 
available at or after the third hospital day, which is also the median duration of hospital stays. Therefore, the 
target for de-escalation is modest, compared to the substantial use of empiric therapy, which is often initiated 
in emergency rooms.  
Analysis of the Need and Impact on Healthcare 
Skin and Soft Tissue (SST) infections are among the most common infectious reasons for 
hospitalization. SST infections are responsible for 3.4 million U.S. emergency department visits annually and 
an estimated 710,000 hospitalizations. HCA Healthcare data from 140 hospitals suggest that 50% of SST 
infections involve empiric therapy with extended-spectrum antibiotics such as antipseudomonal agents when 
Pseudomonas is rarely responsible for SST disease.  
While there is an appropriate focus on rapid initiation of extended-spectrum antibiotics for patients who 
are septic or require critical care, there is a need to focus on use of standard-spectrum empiric antibiotic 
regiments for the much larger population of patients who require hospitalization, but are not critically ill, and 
who are at low risk of MDR pathogens.  
B.2.1 Innovations in Implementation
This trial evaluates a novel strategy that interfaces with prescribers in real time to provide a) a patient- 
and hospital-specific probability that the patient is infected with an antibiotic-resistant pathogen, and b) a 
recommendation to use standard-spectrum empiric therapy if the risk is below a threshold determined in 
consultation with clinical experts and HCA Healthcare leaders. This strategy is novel for two reasons. It targets 
empiric antibiotic prescribing with the intent of influencing a physician’s initial choice of antibiotics. Second, 
it provides precision-medicine estimates of MDRO infection risk based upon the local antibiogram and an 
individual patient’s specific characteristics in the electronic health record.  
B.2.2 Innovations in Intervention
Our trial intervention offers six innovations. First, the INSPIRE-ASP Trials uniquely focus on empiric 
antibiotic selection when most stewardship programs focus on de-escalation. Targeting empiric prescribing has 
greater impact potential because it acts earlier in the prescribing sequence and because most physicians are 
reluctant to change a decision made by a prior physician.23 Second, this trial creates a computer provider 
order entry intervention that dually reaches emergency department and hospital-based physicians for patients 

 
  
4 
  
being admitted. Third, this trial re-engineers the antibiogram, providing syndrome-based risks of antibiotic 
resistance instead of pathogen-based risks. This improves the relevance for physicians as they treat cellulitis 
and reduces misinterpretation (see Section 1.2). This trial mines the electronic health record for patient and 
hospital characteristics associated with antibiotic-resistance and returns a highly curated risk estimate on 
whether an individual patient needs the extended-spectrum antibiotic that the physician is attempting to 
prescribe. This would be the first cluster-randomized trial of a precision medicine risk calculator for SST 
infection. Fourth, this trial trains physicians to focus on absolute vs relative risk. Most papers and guidelines 
provide relative risks instead of absolute risks that risk factors confer for an outcome. As an example, a large 
study found that peripheral vascular disease confers a 5-fold risk of MRSA carriage.24 Because 5-fold is a large 
ratio, this can be misinterpreted to mean that all patients with peripheral vascular disease should be treated as 
if they harbor MRSA. In actuality, the 5-fold risk reflects a carriage risk of 2.4% among those with peripheral 
vascular disease vs 0.5% in those who do not.24 Both risks are small. In this trial, we assess a host of risk 
factors relevant to whether a patient is infected with an organism resistant to the antibiotic that the physician is 
prescribing. When the risk factors collectively generate a low (e.g., <10%) risk, we prompt the physician to 
replace an in-progress order for an extended-spectrum antibiotic with a standard-spectrum agent. Fifth, this 
trial works to change the notion that the physician is “wrong” if their actions do not match what eventually 
grows from a culture. We should not expect physicians to be prescient. Instead, we should expect physicians 
to make a decision that best accounts for the available evidence. This trial documents the presence of risk 
factors and the calculated risk in the electronic medical record and establishes antibiotic stewardship protocols 
that promote certain actions at specific risk estimates. This allows “right” decisions to be based on reasonable 
probabilities, and thus reduces “just in case” prescribing. Sixth, while the main goal of the trial will be to reduce 
unnecessary extended-spectrum antibiotic prescribing when the calculated need is low, we will also explore 
the impact of prompting physicians to order extended-spectrum antibiotics when the calculated risk is high and 
physicians order standard-spectrum agents. 
 
B.3. Potential Risks and Benefits 
B.3.1. Potential Risks 
Minimal Risk 
This trial involves a minimal risk strategy of providing physicians with information from a risk calculator 
designed to assess the risk of having an antibiotic-resistant infection based upon patient and hospital 
characteristics.  
Reasons supporting a minimum risk determination include:  
1) The intervention, INSPIRE Stewardship Bundle,is a quality improvement program and does not 
involve direct testing of any FDA regulated product 
2) The participants are hospital antibiotic stewardship programs, not individual patients 
3) The protocol is concordant with current national guidelines for antibiotic prescribing,  
3)  The intervention involves computerized provider order entry (CPOE) prompts that provide risk 
estimates and recommendations, but does not supplant clinical judgment (physicians maintain final 
decision-making autonomy for antibiotic prescribing at all times),  
4)  Evidence suggests that there is time to wait for culture results in non-ICU patients instead of using 
empiric extended-spectrum antibiotics for uncommon resistant organisms.  
 
The primary risk in this study is to patient privacy and confidentiality of study data, for which we have ample 
protections (see below) 
 
B.3.2 Known Potential Benefits of the Proposed Research to Human Subjects and Others 
  
This study has potential benefits at the individual, hospital and societal level. For individual participants 
in the Intervention Arm, this study has the potential to reduce unnecessary antibiotic use, possibly preventing 
adverse events such as emergence of resistant pathogens, adverse kidney effects, and antibiotic-associated 
diarrhea. Importantly, reduction in these outcomes would have broader benefits on hospital bacteria as well as 
economic impacts to the hospital and society for both costs of unnecessary antibiotics and cost of infections 
due to engendered antibiotic resistance 

5 
C. Objectives
The objective of this protocol is to provide direction for the conduct the INSPIRE-ASP Trial for Skin and 
Soft Tissue (SST) infections Comparing Routine Care vs a Real-Time Precision Medicine Needs Assessment 
for Extended-Spectrum Empiric Antibiotics in a 92-Hospital Cluster-Randomized Trial. 
This protocol will: 
x
Describe the INSPIRE Stewardship Bundle
x
Provide details of the personalized risk calculator for determining the likelihood of resistant
organisms
x
Provide information on how to install the computerized physician order entry (CPOE) risk
calculator into your local Meditech system
x
Detail the toolkit that you will receive for intervention guidance
x
Describe the feedback and audit reports
D. Study Design and Population
Title: 
The INSPIRE-ASP Trial (INtelligent Stewardship Prompts to Improve Real-time Empiric 
Antibiotic Selection for Patients) for Skin and Soft Tissue (SST) Infections. 
Study Design: 
Cluster-randomized trial 
Participant: 
102 Hospitals affiliated with HCA Healthcare randomized into 92 units. Hospitals with 
shared antibiotic stewardship teams (physicians or pharmacists) are randomized 
together as a single hospital unit. Inclusion criteria includes affiliation with HCA 
Healthcare and use of Meditech (for standardized build of CPOE prompts for the 
INSPIRE Stewardship Bundle arm). Any qualifying facility wishing to participate will be 
permitted to enroll even if in excess of calculated study sample size to accommodate 
HCA Healthcare facility or division-level antibiotic stewardship goals. Exclusion criteria 
include care of <100 SST infection patients per year, and implementation or planned 
implementation of a new antibiotic stewardship intervention directly conflicting with the 
trial in the baseline or intervention period. 
Population: 
The analytic cohort will be patients with SST. Inclusion criteria include adults >18 years 
old admitted to a general medical or surgical floor (non-ICU) of a participating HCA 
Healthcare hospital with a diagnosis of SST infection. In addition, patients must receive 
a systemic antibiotic in the first 3 days of hospitalization (empiric period). Exclusion 
criteria will include age <18 years old and ICU admission on either hospital day 1 or 2. 
Hospitals that do not use Meditech are excluded from participation, as are those who 
use/will use Meditech Expanse or Patient Keeper for order entry. 
Number of Sites: 
92 HCA Healthcare hospital hospital units (102 individual hospitals) 
Study Duration: 
5-month phase-in period (does not contribute to analysis) and 12-month intervention
period 
Subject Duration: 
Eligible hospital admission 
Schematic of Study Design: 
Figure 1: Two Study Arms of the INSPIRE-ASP Trial 
Current HCA Healthcare 
Policy 
Clinicians determine 
empiric antibiotic therapy 
for patients admitted with 
SST infection 
Arm 1: Routine Care (N = 46 hospital units) 
x Routine prescribing practice for SST infection
x Pharmacy team prompts about bug-drug mismatch after cultures return

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E. Study Procedures
E.1. Randomization
Randomization will occur in the first quarter of the second year of the study. Hospitals will be notified of 
their randomization results via a formal email to each facility’s study champions as well as to the Chief Medical 
Officer, Chief Executive Officer, Pharmacy Director, and IT&S Director. A coaching call including each arm will 
be scheduled following randomization notification to provide the facilities with the next steps in the trial. 
Following randomization, all subsequent coaching calls, toolkit binders, FAQs and help line contact groups will 
differ by arm assignment.   
E.2. Intervention
E.2.1 Phase-In Period Activities
Post-Randomization Committee Approval and Software Implementation for Antibiotic Indication Screens
x
Arm 1: Facilities randomized to the control arm, which will not receive the antibiotic stewardship
quality improvement intervention, the INSPIRE Stewardship Bundle, still need to undergo usual
hospital approval by relevant committees to participate in the trial. The committee process will be
dependent on local hospital operations, but is anticipated to include the antibiotic stewardship
subcommittee, pharmacy and therapeutics committee, and medical executive committee.
Determination of the committees from which to seek approval is the purview of the participating
hospital. The INSPIRE study coordinators will request that each site provide the list of requisite
committees for approval and convening dates for each committee. A tracker will be maintained to
ensure all requisite committee approvals have been received.
In addition, although Arm 1 facilities will not receive the personalized risk prediction algorithm, they
will be required to install a CPOE software modification for antibiotic indication screens similar to
Arm 2. Currently, all providers ordering an antibiotic are required to input an indication for the
antibiotic. This antibiotic indication screen will be modified to allow more clarity to systemic
indications such as “sepsis.” For example, if providers select “sepsis,” a second screen will appear
asking the provider if the source of the sepsis is SST infection; similar approaches will be taken if
providers choose “empiric” or “other”. This programming can be readily adapted from a previous
trial for pneumonia and urinary tract infection that already created such a subprompt for sepsis. This
will be installed for both arms so that data on indications for prescribed antibiotics can be compared
between the two arms. Both arms will also receive a prompt asking if patients with SST infection
indications are likely to be admitted to an ICU (an exclusion criterion).
x
Arm 2: Facilities randomized to receive the intervention (antibiotic stewardship quality improvement
intervention, the INSPIRE Stewardship Bundle, to be implemented via usual care processes
Arm 2: INSPIRE Stewardship Bundle (N = 46 hospital units) 
x Hospital adopts protocol recommending empiric extended-spectrum therapy for SST
infection only if risk of a resistant pathogen is >10%
x CPOE system calculates patient-specific probability of a resistant infection
x CPOE alert recommends standard-spectrum antibiotics when the predicted
probability of a resistant infection is low (<10%)
x CPOE adoption activities (including education and alignment of CPOE workflows)
x Automated feedback reports generated for provider detailing and comparisons
x Pharmacy team prompts about bug-drug mismatch after cultures return

7 
including order sets and prompts within the electronic medical record) will need to undergo hospital 
approval by relevant committees. The committee process will be dependent on local hospital 
operations, but is anticipated to include the antibiotic stewardship subcommittee, pharmacy and 
therapeutics committee, and medical executive committee. Determination of the committees from 
which to seek approval is the purview of the participating hospital. The INSPIRE study coordinators 
will request that each site provide the list of requisite committees for approval and convening dates 
for each committee. A tracker will be maintained to ensure all requisite committee approvals have 
been received. 
In addition, Arm 2 facilities will receive a software modification for antibiotic indication screens as 
described for Arm 1. They will also receive a CPOE software modification from corporate HCA 
Healthcare information technology to install the risk prediction algorithm (see below). 
Site-Visits 
Following randomization, site visits to Arm 2 (INSPIRE Stewardship Bundle) facilities will be conducted 
by the INSPIRE study investigators and an HCA Healthcare corporate pharmacy liaison. Study investigators 
will visit all participating facilities either on-site or virtually to engage site leadership and key stakeholders, 
provide an overview of the trial and intervention activities, review roles, responsibilities, expectations of Study 
Champions and ASP leaders, and review plans for education and prescriber feedback for site clinicians. Site 
visits will be scheduled following randomization notification, both prior and during the launch of the phase-in 
period of the trial. Requested local participants will include Study Champion, stewardship pharmacy and 
clinician champions, hospital leadership, ED clinician leads, hospitalist clinician leads and any other key 
stakeholders identified by the local Antibiotic Stewardship Program. Repeat post-launch site visits for facilities 
that need additional support throughout the trial will also be available as needed or requested. 
Pre-launch Coaching Calls 
Coaching calls will be held for both routine and intervention facilities during the pre-launch and phase-in 
periods. Coaching call reminders will be sent one week and one day prior to the call. This communication will 
include the list of polling questions, so that participants have time to prepare for answering these questions as 
accurately as possible. These web-based coaching calls during the pre-launch and phase-in periods will be 
held to build engagement and review upcoming activities. These calls will be scheduled at least 3 weeks ahead 
of time to ensure Study Champions, Antibiotic Stewardship Pharmacy and Clinician Champions, and any other 
requisite local stakeholders can attend. The end of each coaching call will include a series of polling questions 
to understand facility-level implementation progress, feedback and education. 
The call-in system is very sophisticated and highly regulated. It logs participant names and allows 
posting of real-time polling questions. Hospitals that are not represented on coaching calls will receive an email 
from study staff and a phone call from HCA Healthcare trial liaisons (if needed) to address inquiries raised on 
the coaching calls and ensure future active participation.   
How the Risk Estimator Works 
Using a personalized set of risk estimates based upon patient characteristics and local antibiotic 
resistance data, we will predict the need for extended-spectrum antibiotics in patients with SST infections. 
These characteristics discriminate between high and low risk patients and generate absolute risks to guide 
clinician therapy instead of relative risks which are commonly found in medical literature.  
Coaching calls in the pre-launch and phase-in periods will review the risk calculator and the 
characteristics that best determine antibiotic risk (Figure 2). 

8 
Figure 2. Example Development of Automated Precision Medicine Smart Tool Providing MRSA Risk 
Estimates for Patients Admitted with SST Infections  
Example Variables for 
   Example of Significant Variables 
MRSA Risk Model     
  Emerging from MRSA Risk Model 
The corporate HCA Healthcare Information Technology (IT) team will develop the CPOE Personalized 
Risk Estimate Prompt template which will include creation of smart prompt algorithms, automated compliance 
reports, and centralized beta testing. Installation processes, modifications of CPOE workflow to accommodate 
the INSPIRE CPOE prompt, educational materials and training modules will be developed as described below. 
CPOE Prompt Installation 
Following the development of the CPOE Personalized Risk Estimate Prompt by the corporate HCA 
Healthcare Information Technology (IT) team, the software will be pushed out electronically to all intervention 
facilities. The local IT groups will then install and integrate the CPOE Personalized Risk Estimate Prompt into 
their local MEDITECH system. The risk prompt functionality will be installed in all Emergency Departments and 
non-ICU locations within the facilities. Following the installation process, a testing process at each facility 
involving the antibiotic stewardship team will ensure the following: 
x
The risk estimate prompt functions accurately for skin and soft tissue (SST) infections. For
example, when physicians order an antibiotic of interest, they will be required to enter the
indication for the antibiotic. For indications of SST infections, the risk estimate prompt will return
the probability that the antibiotic is needed for the MDRO target pathogen.
x
The risk estimate prompt functions accurately for both Emergency Department and hospital-
based physicians.
Age > 65 
History of 
MRSA 
Diabetes
Nursing 
Home 
Signature 1
1 
1 
0 
0
Signature 2
1 
0 
1 
0
Signature 3
1 
0 
0 
1
Signature 4
1 
1 
1 
0
Signature 5
0 
1 
1 
1
Signature 6
0 
0 
1 
1
Signature 7
0 
1 
0 
1
Signature 8
0
0
0
0
Facility Level Variables:
% MRSA for hospital-specific for SST 
infections 
Patient Level Variables: 
Age 
Male gender 
Race 
Insurance status 
Admitted from nursing home 
Hospitalization within last 3 months 
Diabetes Mellitus 
Hemodialysis  
Dementia 
Cerebrovascular Accident 
COPD 
History of antibiotic resistant organism 
Recent antibiotic use
Age 
Diabetes Mellitus 
h/o MRSA 
Admitted from 
nursing home 
Probability Table Based on 
Binary Variable Signature* 
EACH SIGNATURE IS ASSOCIATED WITH A PROBABILITY OF 
MDRO SST INFECTION THAT IS REPORTED IN THE SMART 
PROMPT BASED UPON PATIENT CHARACTERISTICS 
Derived
from full 
model 

9 
How the indications screens work 
Physicians are required by national regulation to indicate why an inpatient antibiotic is prescribed. 
When a physician in either Arm 1 or Arm 2 orders an antibiotic for a skin and soft tissue infection, this 
indication will be captured and recorded so that the frequency of antibiotics tied to skin and soft tissue 
indications can be compared across the arms. One complexity is that physicians can pick “sepsis” which is a 
non-specific indication. Because sepsis can be due to a skin and soft tissue infection, these indication screens 
will be modified for the trial to have a secondary prompt If sepsis is selected. This additional screen will ask if 
the sepsis is from a skin and soft tissue source. If ‘yes’, the skin and soft tissue risk estimate and prompt 
functionality will be triggered in intervention facilities.  
How the CPOE prompt screens work 
Based on the indication screens, if an extended-spectrum antibiotic (Table ) is ordered and the 
indication is SST infection, the CPOE system will acquire the patient and hospital characteristics that best 
discriminate whether the risk of an antibiotic resistant infection is above or below 10%. 
Table : Extended-Spectrum Antibiotics and Associated Pathogen Addressed in the 
Computerized Physician Order Entry (CPOE) Alert 
Antibiotic Ordered 
Pathogen Included in Risk Estimate 
Skin and Soft Tissue Infection 
Daptomycin 
MRSA 
 
Linezolid1 
Vancomycin (IV only) 
Ceftaroline 
Aztreonam 
Pseudomonas 
Cefepime 
Ceftazidime 
Piperacillin/Tazobactam 
Ertapenem 
ESBL, 
GNR Resistant to cephalosporins and penicillins 
Imipenem 
ESBL, 
GNR+Pseudomonas Resistant to cephalosporins and penicillins 
Meropenem 
Ceftolozane/Tazobactam 
1. Both oral and intravenous formulations of drugs in this category are included.
2. For anti-CRE medications, all models show <10% patient risk for having a highly drug resistant pathogen warranting the use of these drugs.
Therefore, patient specific risk estimate will not be calculated and a static CPOE screen will be developed that will recommend avoiding empiric
use without consultation with antibiotic stewardship team or infectious diseases.
3. Newly released ES medications require ID approval and will be considered for inclusion in the CPOE prompts on a case-by-case basis 
Abbreviations: 
MRSA - Methicillin Resistant Staphylococcus aureus 
GNR – Gram Negative Rod 
ESBL – Extended-Spectrum Beta Lactamase producers 
MDR- Multidrug-Resistant 
4. Antibiotics list subject to change as newly licensed antibiotics will be added as needed
The precision-medicine risk calculation will be provided in real-time to physicians when they order an 
antibiotic in the CPOE system. If the risk is >10%, the provider will be able to finalize the order without any 
prompt. If the risk is <10%, the provider will receive a prompt stating that the “[specific extended-spectrum 
antibiotic] is not recommended because the patient’s risk of [the relevant antibiotic resistant pathogen] is 
<10%.” The prompt will then recommend a standard-spectrum antibiotic and ask the provider if they would like 
to accept the replacement (one-click solution) or override the suggestion by entering a reason.  

10 
  
The Cancel button returns the clinician to the previous order screen and the Replace button will launch 
an order screen for the recommended standard-spectrum antibiotic. Clinicians choosing to override are asked 
to indicate the reason in a subsequent screen.   
CPOE Personalized Risk Estimate Prompt Data Capture 
When a clinician places an antibiotic order for a patient with SST infection due to an MDRO, the CPOE 
personalized risk estimate prompt screen will use the patient’s specific Electronic Medical Record (EMR) data 
to calculate the MDRO risk based on previously developed models from over 422,000 HCA Healthcare 
patients with SST infections within the HCA Healthcare Clinical Data Warehouse (CDW). As described above, 
if the risk is low (<10%), the risk estimate prompt will recommend a standard-spectrum antibiotic. If the risk is 
WKHrisk estimate prompt will allow the clinician to proceed with the ES order, without any additional 
prompts. At the time of the order, if the patient is in the ED, the first prompt will ask if the patient is ICU-bound. 
If the patient is ICU-bound, the risk estimate prompt will not fire when the clinician proceeds with ordering an 
antibiotic. 
The MDRO risk estimate models that feed in to the CPOE personalized risk estimate prompts will be 
developed using hundreds of thousands of patients within the HCA Healthcare CDW, using 3 years of data. 
Several MDRO risk factors will be evaluated including: 
y
Each HCA Healthcare hospital’s local antibiogram for SST infection patients
y
Risk factors for MDRO infection
o
Demographics
o
Comorbidities
o
MDRO or Pseudomonas history
o
Recent admission, ED visit, nursing home care
o
Recent antibiotic use
o
Labs
Statistical analysis will then be performed on the above variables to identify which variables are most often 
found in patients who develop SST infection with an MDRO. Using these risk factors (which differ for every 
MDRO), the CPOE risk estimate prompt gives the patient’s absolute risk for infection with the MDRO(s) 
targeted by the antibiotic ordered. 
Trial Toolkit 
Site study champions will receive an arm-specific trial toolkit (see Table  below) with protocols and 
educational materials, including frequently asked questions (FAQs) for providers and pharmacists. Additional 
FAQs will be added during the trial, as needed. 
Table . Contents of INSPIRE-ASP Trial Toolkit Binders 
Educational Material 
Description 
1.
Welcome and Summary of Goals
Introductory information on the trial 
2.
Study Investigators
Lists all investigators and collaborators involved in the trial 
3.
Table of Contents
Summary of documents included 
4.
Phone Matrix
Contact information for lead investigators, HCA Healthcare co-
investigators, and study staff 
5.
Roles & Responsibilities
Describes expectations of hospital study champions 
6.
Antibiotic Selection Protocol
Protocol for clinicians and prescribers providing overview of 
antibiotic select that occurs when INSPIRE-ASP CPOE alerts are 
activated  
7.
Study Champion Materials
Study Champion trial launch checklist, Frequently Asked 
Questions (FAQs) 
8.
Clinician Education Materials
FAQs, Do’s and Don’ts, education presentation providing 
overview of trial, CPOE prompt background and development, 

11 
CPOE prompt monitoring and feedback 
9.
CPOE Clinician Workflow
Visual guides for antibiotic ordering with the CPOE smart prompt 
screens 
10. Clinician Progress Report Example
Describes process for monitoring CPOE prompt usage by 
clinician prescribers; includes sample tables and graphs to be 
used by study champions to feed back to clinicians  
E.2.2 Intervention Phase Activities
During the intervention phase, monthly coaching calls and regular check-in conference calls between 
each Arm 2 facility and the study team will continue. The CPOE risk estimate will fire for the duration of the trial 
and the toolkit will continue to be updated with FAQs as needed.  
Tableau Clinician Auditing and Feedback Report 
A feedback report will be developed by HCA Healthcare corporate IT, using Tableau, an electronic 
based platform that has been used several of our previous HCA Healthcare multi-center trials. The feedback 
report will provide facility level data on acceptance of the CPOE risk estimate prompt empiric antibiotic 
recommendations and evaluate broadly, “at-a-glance”, what acceptance rates are among clinicians at the site. 
The intent of the report is for local Study champions to feed back to local clinicians on acceptance of 
the CPOE risk estimate prompt empiric antibiotic recommendations. Study Champions will be educated via 
webinars on how to use the Tableau dashboard, interpret the data, and compile reports to feed back to 
prescribing clinicians.  Summaries can be viewed at the facility and clinician level ES antibiotic selection by 
indication. Several filtering options will be available on the Tableau Report for Study Champions or other local 
users to compare and track clinician acceptance or non-acceptance of the CPOE risk estimate prompt 
recommendations. 
Several filtering options will be available on the Tableau Report for Study Champions or other local 
users to compare and track clinician acceptance or non-acceptance of the CPOE risk estimate prompt 
recommendations: 
y
Acceptance and Non-Acceptance Summary Reports - Study Champion can use this filter to look
at overall acceptance or non-acceptance of empiric antibiotic recommendations.
–
This summary level report will be available as an initial view of overall acceptance or non-
acceptance for (1) clinician-level and (2) hospital-level acceptance (compared to other Arm 2
facilities). It will allow for range filtering for viewing data across designated periods of time
that allows trending.
–
This option will be available for viewing/printing summary tables and graphs with de-
identified clinician information.
–
This report will be able to be filtered by initial antibiotic ordered.
y
Antibiotic Prescribing Per Protocol - defined as # (%) of per-protocol antibiotic prescribing
among patients with SST Infections. This gives clinicians credit for choosing standard-spectrum
antibiotics that never required a trigger in the risk estimate prompt.
y
Emergency Department (ED) ICU-Bound Prompt Report - INSPIRE CPOE workflow includes a
prompt to ED clinicians asking if the patient is ICU-bound. If response is “yes” then no further CPOE
screens will fire. This report allows study champions to see how often ED clinicians respond “yes” to
assess whether clinicians may be circumventing the prompt.
y
Prompt Report - This report provides the # or % of opportunities that results in a CPOE risk
estimate prompt activation.
–
Allows filtering by prompt action chosen (cancel, override, replace)

12 
y
Override Report – Some pharmacists may want to be able to filter by type of override for intended
follow up plan that day. They may know they are going to round in the ICU, they may want to print
out a list of all overrides due to ICU-bound and check to see if they actually went to the ICU while
they were there, or they may be doing medication reconciliation with allergies and want a printout of
all the overrides due to allergies and cross check those simultaneously.
y
Extended-Spectrum (ES) Indications Report – For use if Study champion would like to organize
by ES antibiotic orders and by indication.
F. Study Schedule
The timeline for the trial is shown in Figure 3 below, with key milestones indicated.  
Figure 3. INSPIRE-ASP Trial for Skin and Soft Tissue Infections Timeline: 6/2020 – 5/2025 
G.
Assessment of Outcome Measures
G.1. Data Sources and Collection
Trial data will not be collected by participating sites. Instead, all variables and outcomes will be 
obtained from custom extractions from the HCA Healthcare computerized data warehouse. HCA Healthcare 
has a long-established corporate data warehouse with admission data, demographics, diagnostic and 
procedure codes, CPOE data, and laboratory and pharmacy data. Trial data from the computerized data 
warehouse will include demographic, insurer, comorbidity, and laboratory (including microbiology) data for SST 
infection cohorts.  
G.2. Specifications of the Appropriate Outcome Measures
The primary, secondary and safety trial outcomes are summarized below in Table . 
G.3. Primary Outcome Measures
The primary trial outcome for SST infections reflects the national metric of days of therapy (DOT) of 
extended-spectrum antibiotic use (ES-DOT), which we will evaluate for the empiric period (hospital day 1-3). 
Trial success will be based upon the relative reduction in this metric between the INSPIRE Stewardship Bundle 
vs routine care arm when accounting for baseline values.  
G.4. Secondary Outcome Measures
There will be one secondary outcome for SST infections (antipseudomonal antibiotic days of therapy). 
G.5. Safety Outcomes
Two safety outcomes will also be assessed. W  e will evaluate if increased use of standard-spectrum 
antibiotics causes increased ICU transfers or hospital length-of-stay.  
MILESTONE
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Facility Recruitment
Randomization with Baseline 
Characteristics
Committee Approvals
Coaching Calls
Site Visits
Distribute Toolkit
Phase in (5-month)
Intervention (12-month)
Clinician Feedback Reports
Year 5
(6/24 - 5/25)
Year 1
(6/20 - 5/21)
Year 2
(6/21 - 5/22)
Year 3
(6/22 - 5/23)
Year 4
(6/23 - 5/24)

13 
Table . Trial Outcomes 
Outcome 
Metric for SST infection Cohorts 
Primary Trial Outcome: Total 
Empiric Extended-Spectrum 
Antibiotic Days of Therapy (ES-
DOT) 
The number of different extended-spectrum antibiotics each empiric day, summed 
across the first 3 days of hospitalization.1 
Secondary Trial Outcomes: Total 
Empiric Antipseudomonal Antibiotic 
Days of Therapy (ES-DOT) 
The number of different antipseudomonal antibiotics each empiric day, summed 
across the first 3 days of hospitalization.1,2 
Safety Outcomes: ICU Transfer 
and Length-of-Stay 
Intensive Care Unit (ICU) Transfer: Days to I&8WUDQVIHUIURPKRVSLWDOGD\V
DQG 
Length-of-stay: Days from hospital admission until discharge or hospital day 14, 
whichever comes first, where admission day is hospital day 1. 
1E.g., if a patient is admitted for 2 days, ES-DOT will be calculated across those 2 days; however if a patient is admitted 
for 4 days, only the first 3 days will be evaluated.  
2Does not include aminoglycosides or fluoroquinolones 
H. Statistical Considerations
H.1. Criteria for Discontinuation or Withdrawal
As a pragmatic trial of a quality improvement protocol, follow-up of the analytic cohort will be assured. It 
will involve the entire hospitalization as recorded in the electronic health record. Drop-outs will not be 
applicable at the patient level.  
Hospitals can withdraw participation at any time. New antibiotic stewardship interventions affecting 
prescriptions in the empiric period or changes in EMR system that affect antibiotic order entry (e.g., Patient 
Keeper, Meditech Expanse) will be assessed by the steering committee for possible conflict and withdrawal of 
participation (for as treated analyses) during the trial. All participating facilities (via the Study Champion) will 
report any new proposed initiatives via the study email or in response to a standing polling question on every 
coaching call. Sites will be trained to understand why competing interventions could jeopardize the findings of 
the study. Should the Steering Committee identify a conflict, we may report back to the Study Champion to 
request the facility delay implementation of the new initiative until the trial has ended. If the facility is unable 
delay implementation, we will conduct an analysis at the end of the trial to assess the impact of interventions 
on the trial outcomes, or if the impact to the trial is significant, the facility may be asked to drop from the trial 
(for as treated analysis). 
H.2. Study Outcome Measures
See Section G. above. 
H.3. Analysis Plan
Primary Statistical Analysis
The primary trial outcome is defined as the summed number of different ES antibiotics received during 
each empiric day. An empiric day is a day within the first three days of an admission. We define this outcome 
as the Total Empiric Extended-Spectrum Days of Therapy (ES-DOT). For clarity, the calculation is as follows: 
we define a DOT for a particular ES antibiotic as a day in which any number of doses of that antibiotic is given. 
Different ES antibiotics are summed within each empiric day for each patient admission to determine DOT in 
that at-risk day. Antibiotics given during an associated emergency department visit on the date of hospital 
admission are counted toward the ES-DOT of the first hospital day. 

14
  
The main trial results will be based upon as-randomized, unadjusted analyses of admission-level ES-
DOT. In contrast to the national DOT measure defined by CDC for hospitals, we define ES-DOT at the 
individual admission level so that we can perform analyses on individuals.   
The trial will be assessed among the cohort of adult admissions who: 1) have administrative claims 
codes indicating an SST infection is present on admission; 2) received any antibiotic within 3 days of 
admission; and 3) were admitted to a non-ICU location. For admissions initially on a non-ICU floor and 
transferred to the ICU, analysis will include only admission days on the non-ICU floor within 3 days of 
admission.  
The trial periods are defined as follows: (1) Baseline: January 1, 2019 – December 31, 2019 (12 
months); (2) Phase-in: August 2, 2022 – December 31, 2022 (5 months, does not contribute to analysis); (3) 
Intervention: January 1, 2023 – December 30, 2023 (12 months). The main evaluation of all outcomes will be 
difference-in-difference between the Intervention and Baseline periods and between study arm. Trial analysis 
will use a baseline period prior to the arrival of the COVID-19 pandemic since hospital operations and case mix 
were severely impacted by this pandemic between Winter 2020-Spring, 2022.25-29 Although at the time of this 
writing (June, 2022), COVID-19 surges continue to occur nationally, clinical operations and patient case mix at 
most hospitals have largely returned to near pre-pandemic activity in the setting of widespread vaccination and 
milder virus strains. Phase-In is scheduled for August, 2022 as participating hospitals are in a state of recovery 
sufficient to launch the trial intervention with pharmacy/physician engagement.    
The unit of analysis will be individual admissions. Individuals can contribute more than one admission. 
The analytic model will be a generalized linear mixed effects model for differences in differences, with random 
effects accounting for correlation within cluster, period-varying random effects to allow for differences within 
hospitals between baseline and follow-up, and admission-level random effects to account for correlation within 
person and hospital, if sufficient data exist. We plan to use a Poisson model for analysis of outcomes as 
follows: 
where 
 is the ES-DOT for patient  for admission in period  at hospital , and 
if hospital  is 
in the intervention arm and 
if not, and 
if 
is the intervention period and 
if baseline period. The 
random effects 
 and 
allow for different baseline mean admission-level ES-DOT for each hospital and 
each hospital in the intervention period, respectively.  Equivalently, they allow for correlation within hospital at 
different levels at baseline and at follow-up.  The random effect 
allows each patient to have a different mean 
ES-DOT.  Finally, 
is the number of empiric days in the admission. 
The assessment of trial success will be determined by the significance of the arm by period interaction 
term 
, which assesses whether the log relative rate of the outcome due to being in the intervention arm in the 
intervention period is different from 0. The exponentiated parameter estimate for 
 is the estimated relative 
rate of ES-DOT per at-risk day due to the intervention, relative to the baseline period. For example, if 
had a 
negative value and a p-value <0.05, we would conclude that the patient-specific CPOE smart prompts 
generated a benefit over routine care. Exponentiating the parameter value would provide an estimate of the 
relative reduction due to the intervention in the expected ES-DOT per at-risk day.  
The primary trial analysis will use an as-randomized unadjusted model with two-tailed significance set 
at alpha = 0.05. Secondary outcomes will be assessed using an as-randomized unadjusted model and will 
include adjustment for multiple comparisons with two-tailed significance set at alpha = 0.025 for the two 
secondary outcomes.  
Subsequent analyses of the primary and secondary outcomes will include both as-treated and adjusted 
models. Adjusted models will account for individual characteristics such as age, gender, comorbidities, and 
prior history of MDROs as well as hospital characteristics such as hospital antibiotic resistance. We will also 
account for seasonality.  All adjusters will be determined a priori. These analyses will be reported as point 
estimates with confidence intervals and without p-values. The reason for including these analyses is to provide 
additional information related to the trial outcomes for readers to assess the effects of potential confounders. 
The reason to not include them in a formal multiple comparisons adjustment is because these analyses are 
non-independent evaluations relative to the as-randomized unadjusted analyses.  
We will separately evaluate intervention period effects by arm alone. 

15 
  
Safety Outcomes 
Safety outcomes noted in the above table will be assessed in the most conservative manner to identify 
potential safety issues. Safety outcomes are required because a reduction in ES-DOT might be achieved only 
by incorrectly withholding ES antibiotics when they were really needed. Each safety outcome will be evaluated 
for non-inferiority using an as-randomized unadjusted analysis with a one-tailed significance set at alpha = 
0.05. Length-of-stay and days to ICU transfer are evaluated within 14 days of admission since empiric 
antibiotic selection within the first 3 hospital days is not expected to be a main driver of either outcome beyond 
this time period; evaluation of baseline data also shows that 91% of SST patients have length-of-stay equal to 
or less than 14 days. Analyses planned for these assessments are proportional hazards models with random 
effects for each hospital and admission These models are sometimes called frailty or shared frailty models. 
Because these are safety outcomes, we do not intend to make adjustments for multiple comparisons in testing 
them, further increasing conservatism.  
All analyses will be performed using current versions of SAS (Version 9.4, as of writing, SAS Institute, 
Cary NC) and/or R (Version 4.0, as of writing).
C.2.11 Power Size/Sample Size Calculations
Power assessment proceeded as follows, using a Monte Carlo approach.25 We used available data to 
define a baseline period of 1/1/2019-12/31/2019. In a bootstrap procedure, individuals were selected with 
replacement from within each hospital, once to represent baseline data and separately to represent 
“intervention period” data. Hospitals were then “randomized” to intervention or control according to multiple 
parameters, including number of admissions with SST infection and ES-DOT. We then modified the outcomes 
for the bootstrapped individuals in the “intervention” period in the “intervention” arm to reflect the effect of the 
intervention.29  
We assessed power to identify an overall 12.5% relative reduction in ES-DOT. This effect was 
implemented by reducing the relative empiric days of therapy for each admission which was exposed to the 
CPOE prompt. The amount of reduction was a uniform random variate between 0.75 and 1. For example, if the 
bootstrapped patient initially received 8 ES-DOT and was assigned to have a have a 12.5% reduction, then 
that admission intervention ES-DOT would be reduced to 7 days. The reduction of ES-DOT was selected with 
a lower bound determined by the investigators as the minimal effect achieved that would be clinically 
meaningful. Using this method, we have -99.9%) power to detect this effect.  
Since adoption of the intervention will be heavily influenced by the ability to demonstrate safety, our 
study size was based on the power to detect non-inferiority for safety outcomes. We used methods similar to 
the above to calculate the power to identify at least a one day increase in length-of-stay for 12.5% of patients 
who had hospitalizations less than 14 days and found the power was 68.9% (CI 65.9-71.8%), where non-
inferiority is defined as a hazard ratio no smaller than 0.98. For days to ICU transfer, we estimated the power 
to detect a 2% increase in transfers to the ICU on hospital day 3 through 14 to be >99.9% (CI 99.6-99.9%), 
where non-inferiority is defined as having a hazard ratio no greater than 1.1 (fewer days to ICU results in a 
hazard ratio above 1).  
For completeness, we note that there are other pre-specified outcomes intended for exploratory 
analysis in secondary papers for the INSPIRE ABD trial in Table  below.  
Table : Secondary Manuscripts - Other Pre-Specified Outcomes 
Secondary Manuscripts (other pre-specified secondary exploratory analyses for later manuscripts)
Inpatient Extended-Spectrum Days of 
Therapy after the Empiric Period  
The number of different ES antibiotics received each day, on 
KRVSLWDOGD\VDQG 

16 
  
Empiric and Total Antibiotic Costs 
Empiric and total antibiotic costs during hospitalization 
Incidence of Hospital-Onset C. difficile 
Hospital-onset C. difficile positive tests (specimen obtained) on 
KRVSLWDOGD\VDQG 
Incidence of Hospital-Onset MDRO-
positive Cultures 
Newly-detected hospital-onset MDRO-positive cultures on 
KRVSLWDOGD\VDQG. Includes total MDRO and specific 
MDRO subsets. 
I.
Access to Source Data/Documents
To protect the large volume of protected health information required for the INSPIRE-ASP SST
Infections Trial, HCA Healthcare will establish a mechanism similar to our previous trials where the study’s 
programmer analysts gain access to HCA Healthcare data behind the HCA Healthcare firewall. Programmer 
analysts will receive remote access to an HCA Healthcare web server where requested data will be placed 
after extraction by HCA Healthcare information technologists. This extraction process will involve replacement 
of names and medical record numbers with coded identifiers. Programmers will access this virtual machine to 
clean and analyze data, and to generate summary level output for review with our statistician.  
J. Quality Control and Quality Assurance
 Monthly data will be accessed by study data analysts from the HCA Healthcare CDW behind their 
corporate firewall.  We anticipate extracting data monthly to be able to validate the data streams. Data stream 
validation involves initial validation by HCA Healthcare to ensure the integrity of data capture and transfer from 
individual hospital electronic data systems to the HCA corporate centralized data warehouse. This will occur 
under general HCA Healthcare operations and has a <<1% error rate. 
 The study programmer analysts will assess each data element for variation within and across hospitals 
within individual streams. Data cleaning will involve assessing missing data and unusual month-to-month 
variation in data elements. Data discrepancies will be resolved by revised data extraction methods, particularly 
those requiring multiple data streams, and by performing quality control checks on the programming code. 
K. Subject Confidentiality
K.1. Future Use of Stored Specimens
This study will not include any stored specimens. 
K.2. Subject Confidentiality
To protect the large volume of protected health information required for the INSPIRE-ASP SST 
Infections Trial, study programmer analysts will gain access to HCA Healthcare data behind the HCA 
Healthcare firewall. Programmer analysts will receive remote access to an HCA Healthcare web server where 
requested data will be placed after extraction by HCA Healthcare information technologists. This extraction 
process will involve replacement of names and medical record numbers with coded identifiers. Programmers 
will access this virtual machine to clean and analyze data, and to generate summary level output for review 
with the study’s statistician. 
L. Ethics /Protection of Human Subjects
L.1. Centralized Institutional Review Board (IRB) Process and Prior Experience
As a pragmatic cluster-randomized trial of an antibiotic stewardship quality improvement strategy, we 
will request a minimal risk determination consistent with our prior HCA Healthcare clinical trials. Reasons 
supporting a minimum risk determination are: 1) the protocol is guideline-concordant, 2) prompts provide risk 
estimates and recommendations, but does not supplant clinical judgment, 3) evidence suggests that there is 
time to wait for culture results in non-ICU patients instead of using empiric extended-spectrum antibiotics for 
uncommon resistant organisms. 

17 
Similar to all prior HCA Healthcare clinical trials, the Harvard Pilgrim Health Care (HPHC) IRB will 
approve a centralized IRB protocol and coordinate reliance agreements with participating hospitals with 
support from HCA Healthcare’s corporate regulatory affairs liaison (David Vulcano MBA, Vice President, 
Research Compliance and Integrity). In prior trials, IRB approval can be obtained within 2-3 months and the 
reliance process can occur in a rolling fashion during recruitment, overall requiring an additional 3-4 months. 
L.2 Informed Consent Process
Similar to our prior pragmatic trials, we expect that this intervention of a quality improvement strategy for 
antibiotic stewardship will meet national regulatory standards for waiver of informed consent under the Office of 
Human Research Protections (OHRP) criteria 45 CFR 46.116(d), 117(c) since 1) trial activities meet minimal 
risk criteria, 2) the trial randomizes hospitals, not patients, to a quality improvement strategy, 3) the intervention 
is not designed to supplant physician judgment, but rather provide relevant information to prescribing 
physicians who will be educated to choose the treatment they deem most clinically appropriate for individual 
patients, and 4) all assigned activities will be performed according to usual hospital quality improvement 
procedures outlined by hospital antibiotic stewardship programs. We will also collect attestations from hospital 
antibiotic stewardship programs stating that they will continue routine antibiotic stewardship efforts.  
Literature References 
1. Centers for Disease Control and Prevention. Antibiotic Resistant Threats in the United States, 2013.
https://www.cdc.gov/drugresistance/pdf/ar-threats-2013-508.pdf. Last accessed August 24, 2019.
2. IMS Health. Avoidable Costs in U.S. Healthcare. Danbury, CT: IMS Health; 2013.
http://offers.premierinc.com/rs/381-NBB-525/images/Avoidable_Costs_in%20_US_Healthcare-
IHII_AvoidableCosts_2013%5B1%5D.pdf. Last accessed August 24, 2019.
3. Fridkin S, Baggs J, Fagan R, Magill S, Pollack LA, Malpiedi P, Slayton R, Khader K, Rubin MA, Jones
M, Samore MH, Dumyati G, Dodds-Ashley E, Meek J, Yousey-Hindes K, Jernigan J, Shehab N,
Herrera R, McDonald CL, Schneider A, Srinivasan A; Centers for Disease Control and Prevention
(CDC). Vital signs: improving antibiotic use among hospitalized patients. MMWR Morb Mortal Wkly
Rep. 2014;63(9):194-200.
4. Hecker MT, Aron DC, Patel NP, Lehmann MK, Donskey CJ. Unnecessary use of antimicrobials
in hospitalized patients: current patterns of misuse with an emphasis on the antianaerobic spectrum of
activity. Archives of Internal Medicine 2003;163(8): 972-8.
5. Baggs J, Fridkin SK, Pollack LA, Srinivasan A, Jernigan JA. Estimating National Trends in
Inpatient Antibiotic Use Among US Hospitals From 2006 to 2012. JAMA Internal Medicine 2016;
176(11):1639-48
6. National Action Plan for Combating Antibiotic-Resistant Bacteria.
https://obamawhitehouse.archives.gov/sites/default/files/docs/national_action_plan_for_combating_anti
botic-resistant_bacteria.pdf. Last accessed August 24, 2019.
7. Wagner B, Filice GA, Drekonja D, Greer N, MacDonald R, Rutks I, Butler M, Wilt TJ. Antimicrobial
stewardship programs in inpatient hospital settings: a systematic review. Infect Control Hosp
Epidemiol;35(10):1209-28.
8. Davies GM, Dasbach EJ, Teutsch S. The burden of appendicitis-related hospitalizations in the United
States in 1997. Surg Infect (Larchmt) 2004;5:160-5.
9. Wheat CL, Strate LL. Trends in Hospitalization for Diverticulitis and Diverticular Bleeding in the United
States From 2000 to 2010. Clin Gastroenterol Hepatol 2016;14:96-103 e1.
10. Peery AF, Dellon ES, Lund J, Crockett SD, McGowan CE, Bulsiewicz WJ, Gangarosa LM, Thiny MT,
Stizenberg K, Morgan DR, Ringel Y, Kim HP, DiBonaventura MD, Carroll CF, Allen JK, Cook SF,
Sandler RS, Kappelman MD, Shaheen NJ. Burden of gastrointestinal disease in the United States:
2012 update. Gastroenterology 2012;143:1179-87 e3.
11. Peery AF, Crockett SD, Murphy CC, Lund JL, Dellon ES, Williams JL, Jensen ET, Shaheen NJ, Barritt
AS, Lieber SR, Kochar B, Barnes EL, Fan YC, Pate V, Galanko J, Baron TH, Sandler RS. Burden and
Cost of Gastrointestinal, Liver, and Pancreatic Diseases in the United States: Update 2018.
Gastroenterology 2019;156:254-72 e11.

18 
12. Sartelli M, Weber DG, Ruppé E, Bassetti M, Wright GJ, Ansaloni L, et al. Antimicrobials: a global
alliance for optimizing their rational use in intra-abdominal infections (AGORA). World J Emerg Surg.
2016 Jul 15;11:33.
13. Swenson BR, Metzger R, Hedrick TL, McElearney ST, Evans HL, Smith RL, Chong TW, Popovsky
KA, Pruett TL, Sawyer RG. Choosing antibiotics for intra-abdominal infections: what do we mean by
"high risk"? Surg Infect (Larchmt). 2009;10(1):29-39.
14. Solomkin JS, Mazuski JE, Bradley JS, Rodvold KA, Goldstein EJ, Baron EJ, O'Neill PJ, Chow AW,
Dellinger EP, Eachempati SR, Gorbach S, Hilfiker M, May AK, Nathens AB, Sawyer RG, Bartlett JG.
Diagnosis and management of complicated intra-abdominal infection in adults and children: guidelines
by the Surgical Infection Society and the Infectious Diseases Society of America. Clin Infect Dis.
2010;50(2):133-64.
15. Pollack CV Jr, Amin A, Ford WT Jr, Finley R, Kaye KS, Nguyen HH, Rybak MJ, Talan D. Acute
bacterial skin and skin structure infections (ABSSSI): practice guidelines for management and care
transitions in the emergency department and hospital. J Emerg Med. 2015;48(4):508-19.
16. Hersh AL, Chambers HF, Maselli JH, Gonzales R. National trends in ambulatory visits and antibiotic
prescribing for skin and soft-tissue infections. Arch Intern Med. 2008;168(14):1585-91.
17. Pallin DJ, Egan DJ, Pelletier AJ et al. Increased US emergency department visits for skin and soft
tissue infections, and changes in antibiotic choices, during the emergence of community-associated
methicillin-resistant Staphylococcus aureus. Ann Emerg Med. 2008;51(3):291–298.
18. Jenkins TC, Sabel AL, Sarcone EE, Price CS, Mehler PS, Burman WJ. Skin and soft-tissue infections
requiring hospitalization at an academic medical center: opportunities for antimicrobial stewardship.
Clin Infect Dis. 2010;51(8):895-903.
19. Jenkins TC, Knepper BC, Sabel AL, Sarcone EE, Long JA, Haukoos JS, Morgan SJ, Biffl WL, Steele
AW, Price CS, Mehler PS, Burman WJ. Decreased antibiotic utilization after     implementation of a
guideline for inpatient cellulitis and cutaneous abscess. Arch Intern Med. 2011;171(12):1072-9.
20. Kamath RS, Sudhakar D, Gardner JG, Hemmige V, Safar H, Musher DM. Guidelines vs Actual
Management of Skin and Soft Tissue Infections in the Emergency Department. Open Forum Infect Dis.
2018;5(1):ofx188.
21. Pallin DJ, Camargo CA Jr, Schuur JD. Skin infections and antibiotic stewardship: analysis of
emergency department prescribing practices, 2007-2010. West J Emerg Med. 2014;15(3):282-9.
22. Stevens DL, Bisno AL, Chambers HF, Dellinger EP, Goldstein EJC, Gorbach SL, Hirschmann JV,
Kaplan SL, Montoya JG, Wade JC. Practice Guidelines for the Diagnosis and Management of Skin and
Soft Tissue Infections: 2014 Update by the Infectious Diseases Society of America. Clin Infect Dis,
2015:59(2):e10–e52.
23. Kiyatkin D, Bessman E, McKenzie R. Impact of antibiotic choices made in the emergency department
on appropriateness of antibiotic treatment of urinary tract infections in hospitalized patients. J Hosp
Med 2016;11:181-4.
24. Delaney JA, Schneider-Lindner V, Brassard P, Suissa S. Mortality after infection with methicillin-
resistant Staphylococcus aureus (MRSA) diagnosed in the community. BMC Med. 2008 Jan 31;6:2.
25. Kleinman K and Huang SS. Calculating Power by Bootstrap, with an Application to Cluster-
Randomized Trials. eGEMs (Generating Evidence & Methods to Improve Patient Outcomes) 2017 Feb;
4(1):1202. PMC5340517.
26. Moynihan R, et al. Impact of COVID-19 pandemic on utilisation of healthcare services: a systematic
review. BMJ Open 2021;11:e045343. doi:10.1136/ bmjopen-2020-045343.
27. Berkmeyer, JD, et al. The Impact Of The COVID-19 Pandemic On Hospital Admissions In The United
States. Health Affairs (39):11, September, 2020. https://doi.org/10.1377/hlthaff.2020.00980
28. Richmond BK, et al. The Impact of the COVID-19 Pandemic on Surgical Practice in the Southeastern
United States: Results of a Survey of the Membership of the Southeastern Surgical Congress. Am
Surg. 2020 Aug;86(8):916-925. doi: 10.1177/0003134820945203. Epub 2020 Sep 14.
29. Nguyen JL, et al. Pandemic-related declines in hospitalization for non-COVID-19-related illness in the
United States from January through July 2020. PLoS ONE 17(1): e0262347.
https://doi.org/10.1371/journal.pone.0262347.