Workflow Models And The Systems Development Life Cycle Scena ✓ Solved

Workflow Models and the Systems Development Life Cycle Scena

Workflow Models and the Systems Development Life Cycle Scenario 3: Belle is a nurse practitioner at an obstetrical office with Dr. Berth. She has noticed trends: new mothers vary in age and experience but ask similar questions and experience anxiety due to lack of pregnancy/childbirth experience. She proposes an educational forum for these women to communicate and receive medical oversight. She intends to develop a primary workflow model and an alternative.

Assignment: Workflow Model Analysis

Briefly describe the case study.

Explain the systems development life cycle present in the case.

Describe the workflow model that was used and whether it is a good fit.

Explain how the clinical decision support system impacted workflow.

Assess the role of the nurse informaticist and benefits to internal and external customers.

Recommend an alternative workflow model and explain how it improves patient safety and outcomes.

Support your recommendation with at least two external resources and two provided resources.

Paper For Above Instructions

Case Study Summary

Belle is a nurse practitioner working in an obstetrical practice. Observing that many new mothers share similar questions and anxiety related to pregnancy and childbirth, she proposes an online or clinic-based educational forum where expectant and new mothers can communicate with peers while receiving medical oversight from Dr. Berth’s office. Belle seeks to design a primary workflow to manage enrollment, communication, clinician oversight, escalation of clinical concerns, and documentation. She also requests an alternative workflow to implement if the primary model proves impractical.

Systems Development Life Cycle (SDLC) Evident in the Case

The scenario implies an informal SDLC: (1) planning and requirements gathering—Belle has identified stakeholder needs (patients and clinicians) and a problem (maternal anxiety and repetitive educational needs); (2) analysis and design—she intends to develop a workflow model and alternative; (3) implementation—deploying the educational forum with clinician oversight; and (4) evaluation—observing outcomes and switching to an alternative if needed. This maps to iterative SDLCs common in healthcare IT where user feedback and safety considerations drive repeated refinement (Kuperman & Bates, 2003; AHRQ, 2012).

Described Workflow Model and Fit

The workflow implicitly proposed is a moderated, clinician-supervised peer-support forum integrated with the clinic’s care processes. Key steps include patient identification and enrollment (at prenatal visits), orientation to forum rules and privacy, moderated discussion threads or scheduled group sessions, triage rules for clinical questions (when to escalate to an NP or physician), documentation of interactions in the electronic health record (EHR), and scheduled follow-up or referrals as needed. This moderated peer-support workflow emphasizes patient education, social support, and clinician safety net.

This model is a good fit for the case because it addresses the expressed need (reducing anxiety and repetitive education), leverages peer learning (which can improve self-efficacy), and preserves clinician oversight to manage safety and liability (Dennis, 2003; Niela-Vilén et al., 2015). Integration with the clinic’s scheduling and documentation processes helps maintain continuity of care and ensures clinically actionable concerns are escalated.

Impact of Clinical Decision Support on Workflow

Clinical decision support (CDS) can impact this workflow in several ways. First, CDS rules can triage patient posts or messages based on keywords (e.g., bleeding, decreased fetal movement), flagging urgent issues to clinicians and prompting standardized responses or immediate contact instructions (Bates et al., 2003). Second, embedded education modules and standardized answer templates ensure consistent, evidence-based responses to common questions, reducing variability and clinician workload (AHRQ, 2012). Finally, CDS can prompt documentation entries to the EHR when a message requires clinical action, ensuring accountability and continuity (HIMSS, 2015). Properly designed CDS improves safety by ensuring urgent problems are escalated promptly and provides clinicians with rapid, reliable guidance; poorly designed CDS, however, can create alert fatigue or workflow interruptions (Ash et al., 2004).

Role of the Nurse Informaticist

The nurse informaticist is pivotal in this scenario: translating clinical needs into system requirements, designing workflows that align with clinical practice and patient behaviors, configuring CDS rules, ensuring interoperability between the forum and the EHR, training staff, and monitoring outcomes and safety metrics. For internal customers (nurses, physicians, staff), the informaticist streamlines processes, reduces duplicative work, and ensures clinical documentation and escalation pathways are clear. For external customers (patients and families), the informaticist helps craft user-centered interfaces, preserves privacy and consent, and ensures educational content is accessible and evidence-based (HIMSS, 2015; ONC, 2014). This role also mediates between IT vendors and clinicians to ensure the solution is safe, usable, and aligned with regulatory requirements (AHRQ, 2012).

Recommended Alternative Workflow Model

Alternative: A hybrid scheduled-group + asynchronous moderated message board workflow. In this model, enrollment and initial orientation occur in-clinic. Participants are assigned to small cohorts with scheduled virtual group education sessions led by a nurse practitioner or health educator every 1–2 weeks (synchronous). Between sessions, an asynchronous moderated message board allows peer interaction. A triage protocol driven by structured intake questions and simple CDS keyword triggers routes urgent messages directly to an on-call clinician, while routine questions are addressed during scheduled sessions or by curated educational modules.

Improvements to patient safety and outcomes include: (1) structured escalation ensures urgent clinical signs are rapidly identified and routed to clinicians, reducing delays in care (Bates et al., 2003); (2) scheduled sessions reduce misinformation risk by providing regular, clinician-led education while peer forums increase social support and self-efficacy, which are associated with improved maternal mental health outcomes (Dennis, 2003; Niela-Vilén et al., 2015); (3) asynchronous boards with CDS filtering reduce clinician burden by prioritizing messages and routing routine education to automated modules, improving efficiency and consistency (AHRQ, 2012).

Supporting Evidence and Integration of Resources

Peer support and structured education improve maternal confidence and breastfeeding outcomes (Niela-Vilén et al., 2015; McFadden et al., 2017). CDS and workflow integration reduce errors and support consistent care escalation (Bates et al., 2003; AHRQ, 2012). Workflow-focused implementation guidance from HIT organizations emphasizes iterative design, user engagement, and evaluation to ensure usability and safety (HIMSS, 2015; ONC, 2014). Together these resources support a hybrid model that balances peer support, clinician oversight, and automated safety checks.

Conclusion

Belle’s proposed moderated educational forum aligns with clinical needs and can reduce anxiety for new mothers while preserving safety through clinician oversight. The SDLC is iterative, requiring careful requirements gathering, design, implementation, and evaluation. CDS is integral for safe triage and consistent education. The nurse informaticist is essential to translate clinical needs into technical solutions and optimize workflows for internal and external stakeholders. A hybrid synchronous/asynchronous workflow with CDS-based triage offers improved safety, scalability, and patient outcomes by combining regular clinician-led teaching, peer support, and efficient automated prioritization of clinical concerns.

References

• Bates DW, Kuperman GJ, Wang S, et al. Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality. J Am Med Inform Assoc. 2003;10(6):523–530.
• Agency for Healthcare Research and Quality (AHRQ). Improving Clinical Decision Support: A Playbook for Hospitals. AHRQ; 2012.
• HIMSS. Workflow and Process Improvement in Health IT Implementations. HIMSS White Paper. 2015.
• Office of the National Coordinator for Health Information Technology (ONC). Patient Engagement Playbook. ONC; 2014.
• Dennis CL. Peer support within a health care context: a concept analysis. Int J Nurs Stud. 2003;40(3):321–332.
• Niela-Vilén H, Ekström A, Korja R, et al. Mobile phone applications to support breastfeeding and new mothers: A review of functionality and usability. J Adv Nurs. 2016;72(7):1757–1767.
• McFadden A, Gavine A, Renfrew MJ, et al. Support for healthy breastfeeding mothers with healthy term babies. Cochrane Database Syst Rev. 2017.
• Ash JS, Sittig DF, Dykstra RH, et al. Identifying unintended consequences of clinical decision support systems. J Am Med Inform Assoc. 2004;11(5):431–442.
• Lupton D. The quantified mother: Prenatal and infant health tracking and technologies. J Med Internet Res. 2016;18(1):e21.
• World Health Organization (WHO). Maternal Mental Health and Child Health: Guidance and Evidence. WHO; 2019.