Using Health Systems Engineering Approaches to Prepare for Tailoring of Implementation Interventions

Barnes, Geoffrey D.; Acosta, Jennifer; Kurlander, Jacob E.; Sales, Anne E.

doi:10.1007/s11606-020-06121-5

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…Several different types of providers were involved and communicated throughout the process, such as coordinators, hepatologists, surgeons, financial advocates, and consultants. The participants created LT evaluation process maps 28 that provided a complete understanding of the workflow. A generalized example is shown in Figure 1 .…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study

Strauss,

Sidoti,

Sung

et al. 2023

Hepatology Communications

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Background: The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variability), provides a ripe opportunity for AI-based clinical decision support (CDS). However, AI-CDS for transplant applications must consider important concerns regarding fairness (ie, health equity). The objective of this study was to use human-centered design methods to elicit providers’ perceptions of AI-CDS for liver transplant listing decisions. Methods: In this multicenter qualitative study conducted from December 2020 to July 2021, we performed semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. We used inductive coding and constant comparison analysis of interview data. Results: Analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient’s role in the AI-CDS. Conclusions: Overall, providers interviewed were cautiously optimistic about the potential for AI-CDS to improve clinical and equitable outcomes for patients. These findings can guide multidisciplinary developers in the design and implementation of AI-CDS that deliberately considers health equity.

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Section: Resultsmentioning

confidence: 99%

Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study

Strauss,

Sidoti,

Sung

et al. 2023

Hepatology Communications

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“…Focusing on the experiences and outcomes from a single implementation may stymie the ability of complex health systems to achieve system-level goals for patient engagement and measurement-based care. The pairing of implementation science theory with systems engineering methods such as SADT may offer a compliment that greatly strengthens our ability to address the increasing complexity of transforming care ( Barnes et al, 2021 ). SADT modeling offers a relatively simple approach to modeling workflow that can aid systems-level implementation without the use of sophisticated technology or technical expertise.…”

Section: Discussionmentioning

confidence: 99%

Augmenting systems-level implementation of patient-reported outcomes for depression care through the use of structured analysis and design technique

Austin

Heim

Sangameswaran

et al. 2022

Implementation Research and Practice

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Background Health systems increasingly need to implement complex practice changes such as the routine capture of patient-reported outcome (PRO) measures. Yet, health systems have met challenges when trying to bring practice change to scale across systems at large. While implementation science can guide the evaluation of implementation determinants, teams first need tools to systematically understand and compare workflow activities across practice sites. Structured analysis and design technique (SADT), a system engineering method of workflow modeling, may offer an opportunity to enhance the scalability of implementation evaluation for complex practice change like PROs. Method We utilized SADT to identify the core workflow activities needed to implement PROs across diverse settings and goals for use, establishing a generalizable PRO workflow diagram. We then used the PRO workflow diagram to guide implementation monitoring and evaluation for a 1-year pilot implementation of the electronic Patient Health Questionnaire-9 (ePHQ). The pilot occurred across multiple clinical settings and for two clinical use cases: depression screening and depression management. Results SADT identified five activities central to the use of PROs in clinical care: deploying PRO measures, collecting PRO data, tracking PRO completion, reviewing PRO results, and documenting PRO data for future use. During the 1-year pilot, 8,596 patients received the ePHQ for depression screening via the patient portal, of which 1,719 (21%) submitted the ePHQ; 367 patients received the ePHQ for depression management, of which 174 (47%) submitted the ePHQ. We present three case examples of how the SADT PRO workflow diagram augmented implementation monitoring, tailoring, and evaluation activities. Conclusions Use of a generalizable PRO workflow diagram aided the ability to systematically assess barriers and facilitators to fidelity and identify needed adaptations. The use of SADT offers an opportunity to align systems science and implementation science approaches, augmenting the capacity for health systems to advance system-level implementation. Plain Language Summary Health systems increasingly need to implement complex practice changes such as the routine capture of patient-reported outcome (PRO) measures. Yet these system-level changes can be challenging to manage given the variability in practice sites and implementation context across the system at large. We utilized a systems engineering method—structured analysis and design technique—to develop a generalizable diagram of PRO workflow that captures five common workflow activities: deploying PRO measures, collecting PRO data, tracking PRO completion, reviewing PRO results, and documenting PRO data for future use. Next, we used the PRO workflow diagram to guide our implementation of PROs for depression care in multiple clinics. Our experience showed that use of a standard workflow diagram supported our implementation evaluation activities in a systematic way. The use of structured analysis and design technique may enhance future implementation efforts in complex health settings.

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“… 15 Furthermore, other clinics that have explored this preprocedure management process have found it to be feasible. 21 As described previously, a diverse group of stakeholders was intimately involved in the development and pilot of this process. 12 While our system did require additional FTE pharmacist effort to handle the additional volume, we have previously shown that fewer cancellations resulting from this referral and review process would result in significant cost savings to the hospital system and would more than cover the additional costs.…”

Section: Discussionmentioning

confidence: 99%

“…In the United States, nearly two‐thirds of anticoagulation clinics already use pharmacists and would be ideally positioned to provide preprocedure antithrombotic medication management if the appropriate guidelines and protocols were enacted 15 . Furthermore, other clinics that have explored this preprocedure management process have found it to be feasible 21 . As described previously, a diverse group of stakeholders was intimately involved in the development and pilot of this process 12 …”

Section: Discussionmentioning

confidence: 99%

Improving preprocedure antithrombotic management: Implementation and sustainment of a best practice alert and pharmacist referral process

Han

Chung

Sippola³

et al. 2021

Research and Practice in Thrombosis and Haemostasis

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Background Electronic medical record–based interventions such as best practice alerts, or reminders, have been proposed to improve evidence‐based medication prescribing. Formal implementation evaluation including long‐term sustainment are not commonly reported. Preprocedural medication management is often a complex issue for patients taking antithrombotic medications. Methods We implemented a best practice alert (BPA) that recommended referral to an anticoagulation clinic before outpatient elective gastrointestinal (GI) endoscopies. Eligible patients were taking an oral anticoagulant (warfarin or direct oral anticoagulant [DOAC]) and/or antiplatelet medications. Patients referred to the anticoagulation clinic were compared to those managed by the ordering provider. Outcomes assessed included guideline‐adherent drug management before endoscopy, documentation of a medication management plan, guideline‐adherent rates of bridging for high‐risk patients taking warfarin, and evaluation for sustained use of BPA. Results Eighty percent of patients (553/691) were referred to the anticoagulation clinic during the initial 13‐month study period. Most referrals came from gastroenterologists (397/553; 71.8%) followed by primary care providers (127/554; 22.9%). Patients referred had improved rates of guideline‐adherent medication management compared to those who were not referred (97.4% vs 91.0%; P = .001). Documentation of medication plan was significantly higher in the referred group (99.1% vs 59.4%; P ≤ .001). There were no differences in rates of appropriate bridging for patients taking warfarin. Implementation of the BPA also resulted in sustained, consistent use over an additional 18 months following the initial study period. Conclusion Implementation of a BPA before elective outpatient GI endoscopies was associated with improved rates of guideline‐adherent medication management and documented management plan, while streamlining preprocedural medication management.

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Using Health Systems Engineering Approaches to Prepare for Tailoring of Implementation Interventions

Cited by 4 publications

References 15 publications

Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study

Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study

Augmenting systems-level implementation of patient-reported outcomes for depression care through the use of structured analysis and design technique

Improving preprocedure antithrombotic management: Implementation and sustainment of a best practice alert and pharmacist referral process

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