Factors Influencing Integration and Usability of Model-Informed Precision Dosing Software in the Intensive Care Unit

Abstract

Background Antimicrobial dosing in critically ill patients is challenging and model-informed precision dosing (MIPD) software may be used to optimize dosing in these patients. However, few intensive care units (ICU) currently adopt MIPD software use.

Objectives To determine the usability of MIPD software perceived by ICU clinicians and identify implementation barriers and enablers of software in the ICU.

Methods Clinicians (pharmacists and medical staff) who participated in a wider multicenter study using MIPD software were invited to participate in this mixed-method study. Participants scored the industry validated Post-study System Usability Questionnaire (PSSUQ, assessing software usability) and Technology Acceptance Model 2 (TAM2, assessing factors impacting software acceptance) survey. Semistructured interviews were used to explore survey responses. The framework approach was used to identify factors influencing software usability and integration into the ICU from the survey and interview data.

Results Seven of the eight eligible clinicians agreed to participate in the study. The PSSUQ usability scores ranked poorer than the reference norms (2.95 vs. 2.62). The TAM2 survey favorably ranked acceptance in all domains, except image. Qualitatively, key enablers to workflow integration included clear and accessible data entry, visual representation of recommendations, involvement of specialist clinicians, and local governance of software use. Barriers included rigid data entry systems and nonconformity of recommendations to local practices.

Conclusion Participants scored the MIPD software below the threshold that implies good usability. Factors such as availability of software support by specialist clinicians was important to participants while rigid data entry was found to be a deterrent.

 

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Keywords

MIPD software - usability - critical illness - antimicrobials

Background and Significance

Critically ill patients are at an increased risk of suboptimal antimicrobial exposures due to their deranged physiology and interventions commonly used in the intensive care unit (ICU).[1] Failure to achieve these target exposures are associated with poorer clinical outcomes.[2] Research in the clinical setting has identified that decision support systems in the form of model-informed precision dosing (MIPD) software can be used to increase the probability of achieving target antimicrobial exposures in these patients.[3] Such software can use patient clinical data and complex mathematical modelling to accurately predict the antimicrobial dose required to achieve target concentrations in patients.[4] [5] These personalized dosing regimens can potentially lead to improved patient clinical outcomes,[6] [7] reduced rates of antimicrobial adverse reactions,[8] [9] and reduced overall costs associated with treating severe infections.[10] [11]

Despite the wide variety of available MIPD software (over 18[4]), less than 20% of ICUs currently use software to optimize antimicrobial dosing.[12] The barriers against using dosing software are not clear, but a structured approach to implementing new technology may reduce the chances of implementation failure.[13] Frameworks guiding implementation of digital technology in the ICU exist.[14] [15] They provide strategies for a stepwise approach for addressing ICU-specific factors (such as local infrastructure and end user engagement) when introducing new technology but do not fully consider factors that are specific to MIPD software (such as availability of antimicrobial drug assays). In addition, these frameworks do not directly address the usability of MIPD software. Current literature suggests that introducing new technology into the ICU without careful consideration of usability, as determined by the end user, is associated with a lower rate of uptake.[16] [17] Identifying factors that may impact the usability of MIPD software, as assessed by the end user ICU clinicians, is of paramount importance to guide effective implementation in the ICU.

The aim of this study was to determine usability and technology acceptability of a commonly used MIPD software (ID-ODS) as perceived by ICU clinicians and identify implementation barriers and enablers of MIPD software in the ICU. This was achieved using a mixed-methods approach with a combination of validated questionnaires assessing usability of software technology and semistructured interviews. In addition, based on survey and interview responses, we sought to identify potential implementation barriers and enablers that may impact on MIPD software integration into ICU clinical workflows.

 

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Methods

Background

As part of the optimizing treatment outcomes for children and adults through rapid genome sequencing of sepsis pathogens (DIRECT) study,[18] ICU clinicians (pharmacists and physicians) from four tertiary ICUs (three adult and one pediatric) in Queensland, Australia were trained to use the MIPD software, ID-ODS (available at: https://www.optimum-dosing-strategies.org/). Most ICUs had between 26 and 27 inpatient beds with the largest having 36 beds. Clinical pharmacists were part of the clinical team within each ICU, and there were at least two to three pharmacists rostered in each ICU on a standard weekday shift. ID-ODS is the most frequently used MIPD software in Australia and provides clinicians with dosing support for many commonly used antimicrobial agents used in the ICU.[12] Prior to commencing the DIRECT study, MIPD software was not previously used across any of the four study ICUs. The detailed study protocol has been published previously.[18]

In brief, the DIRECT study was a before–after interventional study examining the impact of using MIPD software to optimize antimicrobial dosing in the ICU. During the “before” period, ICU clinicians were trained to use ID-ODS by an expert clinician who was a superuser of the software. As part of software training, all ICU clinicians received a study-specific ID-ODS instruction manual for review, a face-to-face walkthrough of the software with the expert clinician and five mock case studies to practice using ID-ODS. Following successful completion of the training session, each ICU clinician was tasked with actively using ID-ODS to optimize antimicrobial dosing for patients enrolled in the “after” period of the DIRECT study. This involved study clinicians requesting blood sample collections to quantify antimicrobial concentrations. For patients with antimicrobial exposure not at target, study clinicians would input patient clinical data into the software to generate an optimized antimicrobial dose. This process was manual as ID-ODS was not integrated into the local electronic medical records (EMR). Generated recommendations were discussed with the treating team who had the final decision on accepting or rejecting the software recommendations. Accepted recommendations were then amended manually on the local EMR systems.

The expert clinician was available throughout the entire study period to provide technical software support to all ICU clinicians. The DIRECT study ran over a period of 10 months in 2021.

 

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Target Population

Two ICU clinicians from each DIRECT study site who expressed an interest in using MIPD software were trained to use ID-ODS as part of the DIRECT study. They were all invited to participate in this usability assessment following completion of the “after” period of the DIRECT study. Written informed consent was obtained from participants who agreed to participate in the study.

 

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Study Protocol

A sequential explanatory mixed-methods assessment was used,[19] which included two validated surveys followed by semistructured interviews. A reporting structure previously described for qualitative research in informatics was used to guide the study reporting in this manuscript.[20]

On enrolment, Google Forms[21] was used to collect demographic information ([Supplementary Appendix 1], available in the online version) from participants and administer the two surveys. Each survey used a 7-point Likert scale, with a lower score denoting a favorable response.

The first survey, the Post-study System Usability Questionnaire (PSSUQ, [Supplementary Appendix 2], available in the online version), was designed to provide objective scores on software usability based on the different metrics that impact on software usability.[22] The scores were divided into three subscales, each providing information on the different metrics that impacted on the perceived usability of the software—system usefulness, information quality, and interface quality.

The second survey, the Technology Acceptance Model 2 (TAM2), was designed to objectively identify factors that impact on acceptance and intention of using the software.[23] The administered survey encompassed eight of the nine domains identified from the original TAM2 ([Supplementary Appendix 3], available in the online version). The “voluntariness” domain was omitted, as it was not relevant to this study as all clinicians were mandated to use the software as part of the DIRECT research study. Unlike the PSSUQ, TAM2 scores are used for hypothesis testing to determine if domains within the TAM2 model (such as perceived usefulness) impacts on other domains (such as intention to use). However, as this study was exploratory in nature and involved a small number of participants, hypothesis testing was not conducted and survey responses were only used to identify factors that impact on software usability and acceptance.

 

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Semistructured Interview

After completing both surveys, each participant was invited to complete a semistructured interview. The interview aimed to obtain data to further explore the constructs of software usability (from PSSUQ results) and software acceptance (from TAM2 results). The responses from both surveys were used to guide the interview with the following guidelines.

• I. Identify survey responses that were strongly positive, strongly negative, or neutral.

• II. Ask the participant to consider the responses they provided.

• III. Ask the participant to provide further explanation about their responses using prompts from the interview guide ([Supplementary Appendix 4], available in the online version).

All interviews were conducted by M.G.C. in a private meeting room or via secure online videoconference. Interviews were ended when participants had no further comments to the above core questions. Interviews were audio-recorded and transcribed verbatim using Adobe Premier Pro 2022. Transcripts were independently reviewed by M.G.C. for accuracy. N.A.R. supported qualitative research procedures.

 

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Analytic Approach

Interview findings were used to identify key barriers and enablers that influenced participant scores for each relevant subscale and domain of the PSSUQ and TAM2 surveys in relation to the MIPD software.[19]

Transcripts were coded independently using a deductive approach by two study investigators (M.G.C. and N.A.R.) according to corresponding survey domains. Using a framework approach, key factors influencing usability, acceptance, and integration into ICU workflows were synthesized from the qualitative findings as previously described.[24] Any qualitative findings that did not directly align with the framework of the survey domains were further explored inductively. Recommendations by participants for supporting future implementation of MIPD in the ICU were summarized in [Fig. 1].

Fig. 1 Key factors influencing usability, acceptance, and integration of dosing software into the intensive care unit workflows. MIPD, model-informed precision dosing; TDM, therapeutic drug monitoring.

 

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Statistical Analysis

Results from both surveys were presented as means with standard deviation for the overall score and for each subscale (PSSUQ) or domain (TAM2). Only questions that were appropriately scored were included in the calculation of the mean and standard deviation (i.e., the denominator was reduced for each not applicable score). The lower and upper limit for the PSSUQ were the 99% confidence interval.

 

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Results

Seven out of the eight eligible clinicians participated in this study. We were unable to obtain a response from the invitation from one participant. The demographic characteristics of the study participants are listed in [Table 1].

Table 1 Demographic characteristics of study participants

Demographic	Score
Age, y (median and standard deviation)	43 (±7.6)
Gender (male/female)	6/1
Experience with dosing software use prior to DIRECT study	Never: 5 Often: 1 Rarely: 1
Profession	Pharmacist: 6 Medical practitioner: 1
Number of years in clinical practice	>15 = 5 6–10 = 1 11–15 = 1
Number of years of clinical practice in the intensive care unit	>15 = 3 11–15 = 1 6–10 = 2 0–5 = 1
Interview duration, min (median and standard deviation)	31 (±4.9)

 

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Quantitative Results

Usability Construct

The overall usability score of the PSSUQ survey was 2.95 (2.60–3.31). As a lower score denoted better performance based on our 7-point Likert scale, the tested software performed poorer compared with the industry norms that denote “good” usability at 2.62. All individual subscales ranked poorer than the relevant industry norms, see [Table 2] (see [Supplementary Appendix 5], available in the online version for raw survey data).

Table 2 Post-study System Usability Questionnaire reference norms and survey results

Subscale	Questions	Reference norms[22]	Participant scores
			Lower limit	Mean scores	Upper limit
Overall	1–16	2.62	2.60	2.95	3.31
System usefulness (SysUse)	1–6	2.57	1.43	2.86	4.28
Information quality (InfoQual)	7–12	2.79	1.85	3.30	4.70
Interface quality (IntQual)	13–15	2.28	1.29	2.71	4.14

 

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Integration into the Intensive Care Unit Construct

Although there are no published reference norms for the mean scores of the TAM2 survey (making a direct comparison of the mean scores for this study not possible), the average scores were weighted toward the lower end of the Likert scale (under 3.0) for all domains except perceived ease of use, subjective norm, and image. A question in the subjective norm domain (three participants), and a question in the image domain (five participants), was reported as “not applicable” ([Supplementary Appendix 5], available in the online version).The results of each individual domain in the TAM2 survey are listed in [Table 3] (see [Supplementary Appendix 5], available in the online version for raw survey data).

Table 3 Technology Acceptance Model 2 survey results

Domain	Mean scores	95% confidence interval
Intention to use	2.89	±1.26
Perceived usefulness	2.46	±0.87
Perceived ease of use	3.36	±1.03
Subjective norm	3.21	±1.77
Job relevance	2.10	±0.70
Output quality	2.21	±0.44
Results demonstrability	1.97	±0.61
Image	4.44	±2.52

 

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Qualitative Results

Usability Constructs

System usefulness impacted user confidence and perceived competence. Participants who had more consistent use of the software found it easier to use the MIPD software. Those who had inconsistent exposure found it more challenging and attributed it to the need to relearn the rigid data entry processes.

“It definitely won't prevent us using it, but I feel like…I need to be [re]trained…I'm not very tech-minded”

Interview 5

Simple and straightforward usability was perceived as positive. Some participants reported MIPD software was not set up in line with local processes, placing additional demands on end users.

“The only thing that was a bit frustrating was in some of the processes…you sort of got halfway through and you went, oh no, I have to go back and fix that up”

Interview 3

“It didn't suit our local practices, not always no. It's just not what we do (in reference to a software recommendation)”

Interview 3

What was assessed as “intuitive” appeared to be individualized among participants, with significant variation across responses.

Information quality appeared to be influenced by the level of expertise among participants, with experienced participants reporting more regular use. In these instances, MIPD software was reported as innovative and improved dosing precision.

“Our pharmacists have quite a lot of expertise, and therefore the [MIPD] software is only a tool to make clinical care better”

Interview 7

Interface quality discussions consistently reported on the usability of graphical data reports. These were reported to enable participants to detect error from data entry and appropriateness of dosing recommendations.

“I'm a very visual learner, so I think [the graph] helped me along the way to figuring out how to use the program”

Interview 4

In some instances, the MIPD software interface was a useful communication tool to explain a patient's progress to family or for communication between clinical teams.

“I absolutely like how it is able to graph, the visual graphics are very strong and lends itself to persuade clinicians, even the naysayers”

Interview 7

 

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Acceptance Constructs

There was variation in responses regarding Intention to use. For some participants, the time taken to enter data was unacceptable.

“This takes too long, I'm not using it”

Interview 4

Many participants reported that they did their own calculations to assess the reliability of the MIPD software recommendations, which was an added step.

“…based on my own experience with vancomycin…I was an experienced pharmacist and did my own guess [of the dosing recommendation], and I did see that [the MIPD software] was as accurate”

Interview 1

The use of MIPD software in the context of a clinical trial was seen as an enabler. Implementation into routine care would require different approvals and processes.

“It's still within the research space in our unit, it hasn't become clinical practice yet. A few steps to get there”

Interview 7

“It requires organizations to approve it (MIPD software) to use as standard clinical practice”

Interview 3

Perceived usefulness discussions reflected the lack of clarity on the required antimicrobial target exposures. In addition, the limited range of antimicrobial models available was seen as a barrier to widespread use. Some participants felt their productivity would decline due to the time taken to use MIPD software while others felt it would increase as dosing outcomes would be more efficient.

“We know there's not that many models, or even this type of dosing software available for the pediatric neonates”

Interview 3

Perceived ease-of-use revisited some of the findings identified in the usability constructs above. The time-out limit was frustrating to all participants as they required data reentry. Data entry was considered problematic and participants suggested a streamlined process to improve ease of use.

“I think there was just a few too many other screens and things to have to go into to put the necessary data in and to work out exactly what was required to get it in the right place”

Interview 2

In reference to subjective norm, some participants displayed trust in the software recommendations as they had high regard for the researchers in the DIRECT study.

“So I think that (researcher name redacted)…have a high profile, so that's why I support that (in reference to MIPD software)”

Interview 6

Job relevance identified that pharmacists were perceived as the antimicrobial dosing experts. Acceptance of MIPD software was driven by the apparent high levels of trust between the pharmacist and treating teams.

“…consultants would say…what are we targeting… I don't know. Is that your job (pharmacist)?”

Interview 5

“…it's probably the experience and the trust from both the clinician side. And I'll say the pharmacist side as well.”

Interview 6

Output quality discussions built on the discussions from usability constructs. There was an identified need to ensure more customization of MIPD software settings. Some participants stated MIPD software recommendations were clinically appropriate but did not align with the dosing options typically used in their ICU.

“I think this comes back to listing all the options of dosing recommendations, but a lot of them weren't necessarily what we would consider common practice locally”

Interview 4

 

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Result Demonstrability

The timeliness of the recommendations was valued highly. Some participants felt the delays with obtaining antimicrobial concentration measurements and the time taken to use the program may reduce applicability of using the program in a clinical setting.

“that's the limitation of any software, which is you see the patient in the morning, the blood tests are done, the levels are done, and then by the next morning, it's the next level”

Interview 7

The Image of MIPD software was positively impacted by several participants who had a high-regard of clinicians within their ICU who have previously used MIPD software. However, they did feel as more clinicians learn to use the software, the effect may begin to diminish.

“And I know that (researcher name redacted) has used dosing software programs before. I trust what (researcher name redacted) does and if they trust these programs, then I trust them”

Interview 4

“…they haven't really used it up until this point, a lot of the people in the ICU aren't aware of this technology”

Interview 7

 

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Key Findings for Future Model-Informed Precision Dosing Implementation

Participants identified five different areas of focus for future MIPD implementation that they felt were important to support uptake in their local ICU. These are summarized in [Fig. 1].

 

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Discussion

This study explored end user MIPD software usability and acceptance among ICU clinicians. Our findings suggest the tested MIPD software scored below the threshold of “good” usability when assessed by our participants. However, it is unclear how it compares to other MIPD programs due to a lack of testing using validated tools reported in the literature with other software. Our participants valued MIPD software that integrates well with preexisting local workflows and produce recommendations that are visually presented. Many participants expressed frustration at rigid data entry systems. Software recommendations that did not always align with local practices inhibited confidence in MIPD. What was perceived as useful, however, was individualized and dependent on the expertise brought by the participating clinician interacting with the program. In addition, our findings suggest there are nonsoftware-specific factors (such as local organizational approval for use and availability of expert clinicians locally) that may impact on the successful rollout of an MIPD software service in an ICU. The findings of this study are unique as they provide new insights on clinician perceptions of the use of MIPD software program in the ICU setting.[12]

Given critical care patients may benefit from receiving antimicrobial doses that have been optimized with MIPD software support,[1] it is imperative the key enablers and barriers identified above to MIPD software uptake are addressed to promote a sustained uptake among ICU clinicians.

Several other studies have attempted to examine the usability of MIPD software, but none specifically among ICU clinicians. Kantasiripitak et al[25] conducted a usability assessment of various software, including ID-ODS, using criteria that were deemed important by surveyed clinicians such as user-friendliness of the software and quality of dosing outputs. However, the actual assessment of usability was performed by the study authors rather than end users. Hence, although the authors rated most software applications favorably according to their criteria, it is unclear if their findings can be generalized to other users working in the clinical setting. In contrast, our PSSUQ survey finding demonstrated reduced usability compared with other industry software and suggest there may be an opportunity for ongoing refinement.

The importance of including the end user clinician in health software development to improve rates of uptake is well reported in the literature.[26] Without sufficient input from the target end users during the build of the software interface, clinicians may find the software impractical to use. As an example, although participants in our study generally assessed software recommendations as being appropriate, several highlighted that outputs did not always align with local practices. Some participants reported recommendations were at times redundant. Similarly, other investigators have identified scenarios where end users were confused by software outputs reporting antimicrobial exposure targets that were different to those used in their local settings.[27] This discrepancy deterred clinicians from using the software, as they were unable to apply recommendations in their local settings. These findings have also been replicated in other software involving nonantimicrobial medications.[28] Compared with other software programs, our assessment of a commonly used MIPD software suggests there may be room for improving software usability as assessed by our end user clinicians.[12] [29] As some of the factors identified by end users were sufficient to deter several participants from using MIPD software in our study, software developers should strongly consider engaging with target end users before rolling out applications targeted for clinical practice.[27]

Kumar et al[30] performed a similar usability assessment of three dosing software applications but with hospital pharmacists and pharmacy students. Although ID-ODS was not an assessed software, the participants also rated the included software applications favorably. However, the recruited participants had limited software experience and based their assessment on a short introductory course for each of the MIPD software. As such, their study did not provide data from a clinical setting. In contrast, our study assessments followed software use in the ICU, potentially providing clinically relevant findings.

One limitation of the studies conducted by Kantasiripitak et al[25] and Kumar et al[30] was the lack of assessment of nonsoftware-related factors, such as clinician perceptions on the efficacy of the software and organizational approval for using the technology, which may impact on the likelihood of successful rollout of MIPD software in the ICU. The failure to consider factors beyond software usability has been shown to reduce the likelihood of clinicians accepting new technology in other settings.[17] This was concordant with our study findings, where most participants expressed a desire to continue using MIPD software and made clear recommendations to improve acceptance. The TAM2 survey used in our study identifies some aspects outside of software usability that must be considered before wider implementation. Important factors identified in our analysis, such as the need to have local experts in antimicrobial dosing to champion and guide software implementation, as well as organizational buy in, would not be identified from a study that only assessed software usability.

 

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Strength and Weaknesses

Due to our small sample size, our questionnaire data are not adequately powered to provide conclusive data on usability and acceptance of the MIPD software tested. Rather we utilized these questionnaires to explore participants perceptions using the mixed-methods approach. However, we identified consistency in our qualitative findings, indicating likely data saturation. As our study predominantly recruited pharmacists, it lacks global data for other clinicians involved with antimicrobial use in the ICU. This was due to the DIRECT study design, which ran in ICUs where pharmacists were primarily responsible for guiding antimicrobial dosing and hence using the MIPD software. As pharmacists have been identified as the main clinician group responsible for guiding antimicrobial TDM,[31] [32] our study setting likely reflects contemporary clinical practice across many ICUs.

Our findings may be limited by participants' exposure to only one MIPD software conducted in a research setting. Having said this, ID-ODS is one the most widely used in clinical practice,[12] and so our findings may be generalizable to many ICU clinical settings. Should software use become more widespread, further assessments of usability encompassing a wider range of end users may be warranted to further build on our study findings and better design software appropriate for the needs of individual centers.

 

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Conclusion

In summary, most surveyed clinicians in the ICU expressed a desire to apply MIPD software in their workflows but require several software limitations to be addressed for feasible sustained integration. In particular, there is a clear need to focus on streamlining the process of data entry and to leverage the ability of software to provide visual outputs. Importantly, our study identified that clinician expertise and acceptance by local governance may improve the successfulness of software implementation in the ICU. However, it should be noted that these findings were obtained from a small sample size involving predominantly pharmacists. Further studies involving a larger heterogenous mix of clinicians involved with antimicrobial prescribing are required to determine how broadly applicable our study findings are to other ICUs.

 

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Clinical Relevance Statement

Our study has identified barriers and enablers to MIPD software uptake within the ICU as assessed by critical care clinicians that should be considered by software developers and health services to increase the likelihood of successful implementation of software in this setting.

 

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Multiple Choice Questions

1. Which of the following factors are unlikely to impact a clinician's acceptance of MIPD software in the ICU?

   • Develop educational resources around software use for clinicians

   • Make expert clinicians available for MIPD software support

   • Restrict MIPD software use to ICU and infectious diseases medical staff

   • Provide clear and accessible data entry to the MIPD software

   Correct answer: The correct answer is c. Participants highlighted in the questions relating to job relevance that pharmacists were most likely to be the appropriate staff to be delegated the role of utilizing the MIPD software.

2. Which nonsoftware factor is important to consider to increase the success of implementing MIPD use in the ICU?

   • Approval from local governance boards to use MIPD software in the ICU

   • Make MIPD software freely available to all clinicians in the hospital

   • Inform patients that MIPD software is being used to optimize their antimicrobial therapy

   • Bill patients directly if MIPD software is used in patients to recoup costs of providing the service

   Correct answer: The correct answer is a. This study assessed clinicians who used MIPD as part of a research trial. Participants identified that integrating MIPD software into clinical practices would require different approval processes.

 

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Conflict of Interest

None declared.

Acknowledgments

The authors would like to acknowledge the clinicians in the DIRECT study who participated in this study.

Protection of Human and Animal Subjects

This study was approved by the Royal Brisbane and Women's Hospital Human Research Ethics committee (LNR/2020/QRBH/67100).

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Publication History

Received: 28 October 2023

Accepted: 17 April 2024

Article published online:
16 May 2024