Impacts of decision support systems on cognition and performance for intelligence-gathering path planning.

Decision Support Systems (DSS) are tools designed to help operators make effective choices in workplace environments where discernment and critical thinking are required for effective performance. Path planning in military operations and general logistics both require individuals to make complex and time-sensitive decisions. However, these decisions can be complex and involve the synthesis of numerous tradeoffs for various paths with dynamically changing conditions. Intelligence collection can vary in difficulty, specifically in terms of the disparity between locations of interest and timing restrictions for when and how information can be collected. Furthermore, plans may need to be changed adaptively mid-operation, as new collection requirements appear, increasing task difficulty. We tested participants in a path planning decision-making exercise with scenarios of varying difficulty in a series of two experiments. In the first experiment, each map displayed two paths simultaneously, relating to two possible routes for the two available trucks. Participants selected the optimal path plan, representing the best solution across multiple routes. In the second experiment, each map displayed a single path, and participants selected the best two paths sequentially. In the first experiment, utilizing the DSS was predictive of adoption of more heuristic decision strategies, and that strategic approach yielded more optimal route selection. In the second experiment, there was a direct effect of the DSS on increased decision performance and a decrease in perceived task workload.

Value of Information for Clinical Trial Design: The Importance of Considering All Relevant Comparators.

Value of Information (VOI) analyses calculate the economic value that could be generated by obtaining further information to reduce uncertainty in a health economic decision model. VOI has been suggested as a tool for research prioritisation and trial design as it can highlight economically valuable avenues for future research. Recent methodological advances have made it increasingly feasible to use VOI in practice for research; however, there are critical differences between the VOI approach and the standard methods used to design research studies such as clinical trials. We aimed to highlight key differences between the research design approach based on VOI and standard clinical trial design methods, in particular the importance of considering the full decision context. We present two hypothetical examples to demonstrate that VOI methods are only accurate when (1) all feasible comparators are included in the decision model when designing research, and (2) all comparators are retained in the decision model once the data have been collected and a final treatment recommendation is made. Omitting comparators from either the design or analysis phase of research when using VOI methods can lead to incorrect trial designs and/or treatment recommendations. Overall, we conclude that incorrectly specifying the health economic model by ignoring potential comparators can lead to misleading VOI results and potentially waste scarce research resources.

Validation of the BCIS CHIP Score in chronic total occlusion percutaneous coronary intervention.

BACKGROUND: The complex high-risk indicated percutaneous coronary intervention (CHIP) score is a tool developed using the British Cardiovascular Intervention Society (BCIS) database to define CHIP cases and predict in-hospital major adverse cardiac or cerebrovascular events (MACCE). AIM: To assess the validity of the CHIP score in chronic total occlusion (CTO) percutaneous coronary intervention (PCI). METHODS: We evaluated the performance of the CHIP score on 8341 CTO PCIs from the Prospective Global Registry for the Study of Chronic Total Occlusion Intervention (PROGRESS-CTO) performed at 44 centers between 2012 and 2023. RESULTS: In our cohort, 7.8% (n = 647) of patients had a CHIP score of 0, 50.2% (n = 4192) had a CHIP score of 1-2, 26.2% (n = 2187) had a CHIP score of 3-4, 11.7% (n = 972) had a CHIP score of 5-6, 3.3% (n = 276) had a CHIP score of 7-8, and 0.8% (n = 67) had a CHIP score of 9+. The incidence of MACCE for a CHIP score of 0 was 0.6%, reaching as high as 8.7% for a CHIP score of 9+, confirming that a higher CHIP score is associated with a higher risk of MACCE. The estimated increase in the risk of MACCE per one score unit increase was 100% (95% confidence interval [CI]: 65%-141%). The AUC of the CHIP score model for predicting MACCE in our cohort was 0.63 (95% CI: 0.58-0.67). There was a positive correlation between the CHIP score and the PROGRESS-CTO MACE score (Spearman's correlation: 0.37; 95% CI: 0.35-0.39; p < 0.001). CONCLUSIONS: The CHIP score has modest predictive capacity for MACCE in CTO PCI.

Application of Multi-Criteria Decision Analysis (MCDA) to Prioritize Real-World Evidence Studies for Health Technology Management: Outcomes and Lessons Learned by the Canadian Real-World Evidence for Value of Cancer Drugs (CanREValue) Collaboration.

Multi-criteria decision analysis (MCDA) is a value assessment tool designed to help support complex decision-making by incorporating multiple factors and perspectives in a transparent, structured approach. We developed an MCDA rating tool, consisting of seven criteria evaluating the importance and feasibility of conducting potential real-world evidence (RWE) studies aimed at addressing uncertainties stemming from initial cancer drug funding recommendations. In collaboration with the Canadian Agency for Drugs and Technologies in Health's Provincial Advisory Group, a validation exercise was conducted to further evaluate the application of the rating tool using RWE proposals varying in complexity. Through this exercise, we aimed to gain insight into consensus building and deliberation processes and to identify efficiencies in the application of the rating tool. An experienced facilitator led a multidisciplinary committee, consisting of 11 Canadian experts, through consensus building, deliberation, and prioritization. A total of nine RWE proposals were evaluated and prioritized as low (n = 4), medium (n = 3), or high (n = 2) priority. Through an iterative process, efficiencies and recommendations to improve the rating tool and associated procedures were identified. The refined MCDA rating tool can help decision-makers prioritize important and feasible RWE studies for research and can enable the use of RWE for the life-cycle evaluation of cancer drugs.

User-Centered Development of a Patient Decision Aid for Choice of Early Abortion Method: Multi-Cycle Mixed Methods Study.

BACKGROUND: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive-there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices. OBJECTIVE: We aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction. METHODS: We used a systematic, user-centered design approach guided by principles of integrated knowledge translation. We first developed a prototype using available evidence for abortion seekers' decisional needs and the risks, benefits, and consequences of each option. We then refined the prototype through think-aloud interviews with participants at risk of unintended pregnancy ("patient" participants). Interviews were audio-recorded and documented through field notes. Finally, we conducted a web-based survey of patients and health care professionals involved with abortion care, which included the System Usability Scale. We used content analysis to identify usability issues described in the field notes and open-ended survey questions, and descriptive statistics to summarize participant characteristics and close-ended survey responses. RESULTS: A total of 61 individuals participated in this study. Further, 11 patients participated in think-aloud interviews. Overall, the response to the PtDA was positive; however, the content analysis identified issues related to the design, language, and information about the process and experience of obtaining abortion care. In response, we adapted the PtDA into an interactive website and revised it to include consistent and plain language, additional information (eg, pain experience narratives), and links to additional resources on how to find an abortion health care professional. In total, 25 patients and 25 health care professionals completed the survey. The mean System Usability Scale score met the threshold for good usability among both patient and health care professional participants. Most participants felt that the PtDA was user-friendly (patients: n=25, 100%; health care professionals: n=22, 88%), was not missing information (patients: n=21, 84%; health care professionals: n=18, 72%), and that it was appropriate for patients to complete the PtDA before a consultation (patients: n=23, 92%; health care professionals: n=23, 92%). Open-ended responses focused on improving usability by reducing the length of the PtDA and making the website more mobile-friendly. CONCLUSIONS: We systematically designed the PtDA to address an unmet need to support informed, values-aligned decision-making about the method of abortion. The design process responded to a need identified by potential users and addressed unique sensitivities related to reproductive health decision-making.

Preliminary testing of "roadmap to parenthood" decision aid and planning tool for family building after cancer: Results of a single-arm pilot study.

OBJECTIVE: Many young adult female cancer survivors need to use reproductive medicine, surrogacy, or adoption to have a child. This study pilot tested Roadmap to Parenthood, a web-based, self-guided decision aid and planning tool for family building after cancer (disease agnostic). METHODS: A single-arm pilot study tested feasibility, acceptability, and obtained effect size estimates of the Roadmap tool. Participants, recruited via hospital-based and social media strategies, completed a baseline survey (T1), accessed the Roadmap tool (website), then completed surveys at one- and 3-months (T2 and T3, respectively). Feasibility and acceptability were evaluated with rates of eligibility, enrollment, and survey completion, and feedback. Pairwise t-tests and repeated measures ANOVA evaluated usage effects. Effect size estimates were calculated. RESULTS: Participants (N = 98) averaged 31 years old (SD = 5.61); 71% were nulliparous. Enrollment rate was 73%, T1-T2 completion rate was 80%, and 93% accessed the website. From T1-T2, participants reported improvements in decisional conflict (p < 0.001; Cohen's d = 0.85), unmet information needs (p < 0.001; Cohen's d = 0.70), self-efficacy (p = 0.003; Cohen's d = 0.40), and self-efficacy for managing negative emotions (p = 0.03; Cohen's d = 0.29); effects were sustained at T3. There was no change in reproductive distress (p = 0.22). By T3, 94% reported increased consideration of preparatory actions and 20%-61% completed such actions. CONCLUSIONS: The Roadmap intervention was feasible to conduct, acceptable to users, and led to improvements in key psychosocial outcomes. Future directions will test intervention efficacy in a randomized controlled trial with a larger sample and over a longer period. A web-based tool may help women make decisions about family building after cancer and prepare for potential challenges.

Study on decision-making for orthodontic treatment plans based on analytic hierarchy process.

BACKGROUND: Orthodontics is a common treatment for malocclusion and is essential for improving the oral health and aesthetics of patients. Currently, patients often rely on the clinical expertise and professional knowledge of doctors to select orthodontic programs. However, they lack their own objective and systematic evaluation methods to quantitatively compare different programs. Therefore, there is a need for a more comprehensive and quantitative approach to selecting orthodontic treatment plans, aiming to enhance their scientific validity and effectiveness. METHODS: In this study, a combination of the analytic hierarchy process (AHP) and semantic analysis was used to evaluate and compare different orthodontic treatment options. An AHP model and evaluation matrix were established through thorough research and semantic analysis of patient requirements. This model considered various treatment factors. Expert panels were invited to rate these factors using a 1-9 scale. The optimal solution was determined by ranking and comparing different orthodontic treatment plans using the geometric mean method to calculate the weights of each criterion. RESULTS: The research indicates a higher preference for invisible correction compared to other orthodontic solutions, with a weight score that is 0.3923 higher. Factors such as comfort and difficulty of cleaning have been given significant attention. CONCLUSION: The Analytic Hierarchy Process (AHP) method can be utilized to effectively develop orthodontic treatment plans, making the treatment process more objective, scientific, and personalized. The design of this study offers strong decision support for orthodontic treatment, potentially improving orthodontic treatment outcomes in clinical practice and ultimately enhancing oral health and patients' quality of life.

Decision analysis of PPP project's parties based on deep consumer participation.

Although PPP(Public-private partnership) mode has been applied for a long time in infrastructural project, the success rate is not very high. The sustainability of PPP projects is still influenced by many factors. In order to examine the evolutionary stable strategies (ESSs) of social capital, government, and paying consumers, a tripartite evolutionary game model is established in this work. In order to further promote consumer participation, it is necessary to make the assumption that customer oversight and review can have an impact on service prices. The results show: i)The strategy choice of consumer depends on the comparison between supervision cost of consumer and price coefficient for consumer to social capital. ii)Consumer supervision can promote the provision of high-quality services by social capital. iii)The difference between high-quality cost and low-quality cost, subsidy coefficient, price coefficient and supervision cost of consumer are critical factors influencing both evolutionary results and trajectories. This paper also puts forward policy implications for the three stakeholders to promote social capital's high-quality strategy so as to maintain the sustainability of PPP projects.

Design of a multiple criteria decision analysis framework for prioritizing high-impact health technologies in a regional health service.

OBJECTIVES: This study aims to develop a framework for establishing priorities in the regional health service of Murcia, Spain, to facilitate the creation of a comprehensive multiple criteria decision analysis (MCDA) framework. This framework will aid in decision-making processes related to the assessment, reimbursement, and utilization of high-impact health technologies. METHOD: Based on the results of a review of existing frameworks for MCDA of health technologies, a set of criteria was proposed to be used in the context of evaluating high-impact health technologies. Key stakeholders within regional healthcare services, including clinical leaders and management personnel, participated in a focus group (n = 11) to discuss the proposed criteria and select the final fifteen. To elicit the weights of the criteria, two surveys were administered, one to a small sample of healthcare professionals (n = 35) and another to a larger representative sample of the general population (n = 494). RESULTS: The responses obtained from health professionals in the weighting procedure exhibited greater consistency compared to those provided by the general public. The criteria more highly weighted were "Need for intervention" and "Intervention outcomes." The weights finally assigned to each item in the multicriteria framework were derived as the equal-weighted sum of the mean weights from the two samples. CONCLUSIONS: A multi-attribute function capable of generating a composite measure (multicriteria) to assess the value of high-impact health interventions has been developed. Furthermore, it is recommended to pilot this procedure in a specific decision context to evaluate the efficacy, feasibility, usefulness, and reliability of the proposed tool.

Challenges and Opportunities in Interdisciplinary Research and Real-World Data for Treatment Sequences in Health Technology Assessments.

With an ever-increasing number of treatment options, the assessment of treatment sequences has become crucial in health technology assessment (HTA). This review systematically explores the multifaceted challenges inherent in evaluating sequences, delving into their interplay and nuances that go beyond economic model structures. We synthesised a 'roadmap' of literature from key methodological studies, highlighting the evolution of recent advances and emerging research themes. These insights were compared against HTA guidelines to identify potential avenues for future research. Our findings reveal a spectrum of challenges in sequence evaluation, encompassing selecting appropriate decision-analytic modelling approaches and comparators, deriving appropriate clinical effectiveness evidence in the face of data scarcity, scrutinising effectiveness assumptions and statistical adjustments, considering treatment displacement, and optimising model computations. Integrating methodologies from diverse disciplines-statistics, epidemiology, causal inference, operational research and computer science-has demonstrated promise in addressing these challenges. An updated review of application studies is warranted to provide detailed insights into the extent and manner in which these methodologies have been implemented. Data scarcity on the effectiveness of treatment sequences emerged as a dominant concern, especially because treatment sequences are rarely compared in clinical trials. Real-world data (RWD) provide an alternative means for capturing evidence on effectiveness and future research should prioritise harnessing causal inference methods, particularly Target Trial Emulation, to evaluate treatment sequence effectiveness using RWD. This approach is also adaptable for analysing trials harbouring sequencing information and adjusting indirect comparisons when collating evidence from heterogeneous sources. Such investigative efforts could lend support to reviews of HTA recommendations and contribute to synthesising external control arms involving treatment sequences.

Wastewater management decision-making: A literature review and synthesis.

Wastewater management decision-making is complicated because of: (1) a complex regulatory structure, (2) the wide variety of conflicting expectations by stakeholders external and internal to the responsible utility, and (2) constrains including regulatory requirements, available technologies and practices, and customer willingness to pay. This review synthesizes the results from over 200 papers published since 2000 and presents a decision-making structure and process which is (1) science and fact-based, (2) reflects sustainability, (3) clear and transparent, (4) inclusive, (5) produces an objective-oriented decision, (6) scalable, (7) repeatable, and (8) efficient. Tools supporting the decision-making process are reviewed, including Multi-Criteria Decision Analysis (MCDA), Data Envelopment Analysis (DEA), Analytic Hierarchy Process (AHP), process modeling, economic assessments, Life Cycle Assessment (LCA), and Social Life Cycle Assessment (SLCA). Ultimately it was determined that engagement of decision-makers and relevant stakeholders to assess their values and preferences, coupled with supporting data and analyses, is necessary to reach a decision that, critically, has the support needed for it to be implemented. The results demonstrate that an understanding of the components of the decision process, coupled with an orderly process, enables good wastewater management decision-making. PRACTITIONER POINTS: A decision-making structure and process leading to the selection of implementable solutions is presented. The process possesses the following attributes: (1) science and fact-based, (2) reflect sustainability, (3) clear and transparent, (4) inclusive, (5) produce an objective-oriented decision, (6) scalable, (7) repeatable, and (8) efficient An extensive summary and analysis of tools supporting the decision process are provided, including Multi-Criteria Decision Analysis (MCDA), Data Envelopment Analysis (DEA), Analytic Hierarchy Process (AHP), process modeling, economic assessments, Life Cycle Assessment (LCA), and Social Life Cycle Assessment (SLCA). The critical role of internal and external stakeholders and differentiating their involvement relative to decision-makers is emphasized.

Impact of timing and format of patient decision aids for breast cancer patients on their involvement in and preparedness for decision making - the IMPACTT randomised controlled trial protocol.

BACKGROUND: After curative surgery for early-stage breast cancer, patients face a decision on whether to undergo surgery alone or to receive one or more adjuvant treatments, which may lower the risk of recurrence. Variations in survival outcomes are often marginal but there are differences in the side effects and other features of the options that patients may value differently. Hence, the patient's values and preferences are critical in determining what option to choose. It is well-researched that the use of shared decision making and patient decision aids can support this choice in a discussion between patient and clinician. However, it is still to be investigated what impact the timing and format of the patient decision aid have on shared decision making outcomes. In this trial, we aim to investigate the impact of a digital pre-consult compared to a paper-based in-consult patient decision aid on patients' involvement in shared decision making, decisional conflict and preparedness to make a decision. METHODS: The study is a randomised controlled trial with 204 patients at two Danish oncology outpatient clinics. Eligible patients are newly diagnosed with early-stage breast cancer and offered adjuvant treatments after curative surgery to lower the risk of recurrence. Participants will be randomised to receive either an in-consult paper-based patient decision aid or a pre-consult digital patient decision aid. Data collection includes patient and clinician-reported outcomes as well as observer-reported shared decision making based on audio recordings of the consultation. The primary outcome is the extent to which patients are engaged in a shared decision making process reported by the patient. Secondary aims include the length of consultation, preparation for decision making, preferred role in shared decision making and decisional conflict. DISCUSSION: This study is the first known randomised, controlled trial comparing a digital, pre-consult patient decision aid to an identical paper-based, in-consult patient decision aid. It will contribute evidence on the impact of patient decision aids in terms of investigating if pre-consult digital patient decisions aids compared to in-consult paper-based decision aids support the cancer patients in being better prepared for decision making. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05573022).

Anesthesia decision analysis using a cloud-based big data platform.

Big data technologies have proliferated since the dawn of the cloud-computing era. Traditional data storage, extraction, transformation, and analysis technologies have thus become unsuitable for the large volume, diversity, high processing speed, and low value density of big data in medical strategies, which require the development of novel big data application technologies. In this regard, we investigated the most recent big data platform breakthroughs in anesthesiology and designed an anesthesia decision model based on a cloud system for storing and analyzing massive amounts of data from anesthetic records. The presented Anesthesia Decision Analysis Platform performs distributed computing on medical records via several programming tools, and provides services such as keyword search, data filtering, and basic statistics to reduce inaccurate and subjective judgments by decision-makers. Importantly, it can potentially to improve anesthetic strategy and create individualized anesthesia decisions, lowering the likelihood of perioperative complications.

Large language models as decision aids in neuro-oncology: a review of shared decision-making applications.

Shared decision-making (SDM) is crucial in neuro-oncology, fostering collaborations between patients and healthcare professionals to navigate treatment options. However, the complexity of neuro-oncological conditions and the cognitive and emotional burdens on patients present significant barriers to achieving effective SDM. This discussion explores the potential of large language models (LLMs) such as OpenAI's ChatGPT and Google's Bard to overcome these barriers, offering a means to enhance patient understanding and engagement in their care. LLMs, by providing accessible, personalized information, could support but not supplant the critical insights of healthcare professionals. The hypothesis suggests that patients, better informed through LLMs, may participate more actively in their treatment choices. Integrating LLMs into neuro-oncology requires navigating ethical considerations, including safeguarding patient data and ensuring informed consent, alongside the judicious use of AI technologies. Future efforts should focus on establishing ethical guidelines, adapting healthcare workflows, promoting patient-oriented research, and developing training programs for clinicians on the use of LLMs. Continuous evaluation of LLM applications will be vital to maintain their effectiveness and alignment with patient needs. Ultimately, this exploration contends that the thoughtful integration of LLMs into SDM processes could significantly enhance patient involvement and strengthen the patient-physician relationship in neuro-oncology care.

A Decision Aid to Support Tubal Sterilization Decision-Making Among Pregnant Women: The MyDecision/MiDecisión Randomized Clinical Trial.

Importance: Tubal sterilization is common, especially among individuals with low income. There is substantial misunderstanding about sterilization among those who have undergone the procedure, suggesting suboptimal decision-making about a method that permanently ends reproductive capacity. Objective: To test the efficacy of a web-based decision aid for improving tubal sterilization decision quality. Design, Setting, and Participants: This randomized clinical trial conducted between March 2020 and November 2023 included English- or Spanish-speaking pregnant cisgender women aged 21 to 45 years who had Medicaid insurance and were contemplating tubal sterilization after delivery. Participants were recruited from outpatient obstetric clinics in 3 US cities. Intervention: Participants were randomized 1:1 to usual care (control arm) or to usual care plus a web-based decision aid (MyDecision/MiDecisión) (intervention arm). The aid includes written, audio, and video information about tubal sterilization procedures; an interactive table comparing contraceptive options; values-clarifying exercises; knowledge checks; and a summary report. Main Outcomes and Measures: The co-primary outcomes were tubal sterilization knowledge and decisional conflict regarding the contraceptive decision. Knowledge was measured as the percentage of correct responses to 10 true-false items. Decisional conflict was measured using the low-literacy Decision Conflict Scale, with lower scores on a range from 0 to 100 indicating less conflict. Results: Among the 350 participants, mean (SD) age was 29.7 (5.1) years. Compared with the usual care group, participants randomized to the decision aid had significantly higher tubal sterilization knowledge (mean [SD] proportion of questions answered correctly, 76.5% [16.9%] vs 55.6% [22.6%]; P < .001) and lower decisional conflict scores (mean [SD], 12.7 [16.6] vs 18.7 [20.8] points; P = .002). The greatest knowledge differences between the 2 groups were for items about permanence, with more participants in the intervention arm answering correctly that tubal sterilization is not easily reversible (90.1% vs 39.3%; odds ratio [OR], 14.2 [95% CI, 7.9-25.4]; P < .001) and that the tubes do not spontaneously "come untied" (86.6% vs 33.7%; OR, 13.0 [95% CI, 7.6-22.4]; P < .001). Conclusions and Relevance: MyDecision/MiDecisión significantly improved tubal sterilization decision-making quality compared with usual care only. This scalable decision aid can be implemented into clinical practice to supplement practitioner counseling. These results are particularly important given the recent increase in demand for permanent contraception after the US Supreme Court decision overturning federal abortion protections. Trial Registration: ClinicalTrials.gov Identifier: NCT04097717.

Decision analysis in cardiac surgery: a scoping review and methodological primer.

OBJECTIVES: Randomized controlled trials are the gold standard for evidence generation in medicine but are limited by their real-world generalizability, resource needs, shorter follow-up durations and inability to be conducted for all clinical questions. Decision analysis (DA) models may simulate trials and observational studies by using existing data and evidence- and expert-informed assumptions and extend analyses over longer time horizons, different study populations and specific scenarios, helping to translate population outcomes to patient-specific clinical and economic outcomes. Here, we present a scoping review and methodological primer on DA for cardiac surgery research. METHODS: A scoping review was performed using the PubMed/MEDLINE, EMBASE and Web of Science databases for cardiac surgery DA studies published until December 2021. Articles were summarized descriptively to quantify trends and ascertain methodological consistency. RESULTS: A total of 184 articles were identified, among which Markov models (N = 92, 50.0%) were the most commonly used models. The most common outcomes were costs (N = 107, 58.2%), quality-adjusted life-years (N = 96, 52.2%) and incremental cost-effectiveness ratios (N = 89, 48.4%). Most (N = 165, 89.7%) articles applied sensitivity analyses, most frequently in the form of deterministic sensitivity analyses (N = 128, 69.6%). Reporting of guidelines to inform the model development and/or reporting was present in 22.3% of articles. CONCLUSION: DA methods are increasing but remain limited and highly variable in cardiac surgery. A methodological primer is presented and may provide researchers with the foundation to start with or improve DA, as well as provide readers and reviewers with the fundamental concepts to review DA studies.

Promoting informed decision making about maternal pertussis vaccination: the systematic development of an online tailored decision aid and a centering-based group antenatal care intervention.

Introduction: Maintaining and enhancing vaccine confidence continues to be a challenge. Making an informed decision not only helps to avoid potential future regret but also reduces susceptibility to misinformation. There is an urgent need for interventions that facilitate informed decision-making about vaccines. This paper describes the systematic development of two interventions designed to promote informed decision making and indirectly, acceptance of maternal pertussis vaccination (MPV) in the Netherlands. Materials and methods: The 6-step Intervention Mapping (IM) protocol was used for the development of an online tailored decision aid and Centering Pregnancy-based Group Antenatal Care (CP) intervention. A needs assessment was done using empirical literature and conducting a survey and focus groups (1), intervention objectives were formulated at the behavior and determinants levels (2), theoretical methods of behavior change were selected and translated into practical applications (3), which were further developed into the two interventions using user-centered design (4). Finally, plans were developed for implementation (5), and evaluation (6) of the interventions. Results: The needs assessment showed that pregnant women often based their decision about MPV on information sourced online and conversations with their partners, obstetric care providers, and peers. Responding to these findings, we systematically developed two interactive, theory-based interventions. We created an online tailored decision aid, subjecting it to four iterations of testing among pregnant women, including those with low literacy levels. Participants evaluated prototypes of the intervention positively on relevance and usability. In addition, a CP intervention was developed with midwives. Conclusion: Using IM resulted in the creation of an online decision aid and CP intervention to promote informed decision making regarding MPV. This description of the systematic development of the interventions not only serves to illustrate design rationales, it will also aid the interpretation of the evaluation of the interventions, the development of future interventions promoting informed decision and acceptance of vaccines, and comparisons with other interventions.