# My attempt in drafting DIME, Logic model **Introduction:** HOPES was created to enhance patient care, addressing the issue of high caseloads that prevent case managers from providing equal attention and support to each patient. **Current Situation:** Due to high caseloads, case managers are unable to provide each patient with the necessary guidance and support. Intensive case management emphasizes that treatment must be biopsychosocial, not solely medical. This approach requires time to understand a patient’s needs and uncover predisposing, perpetuating, precipitating, and protective factors. Additionally, there is variability in service delivery among different case managers, influenced by their experience and personality. We often only become aware of crises or relapses when patients or caregivers report them, which may be too late for timely intervention. **Goals:** We aim to achieve the following with HOPES: 1. **Develop a Smart App:** The app will act as a virtual case manager to support patients through psychoeducation and knowledge sharing. 2. **Increase Self-Awareness:** The app will serve as an interventive tool to increase patients' self-awareness. By understanding their predisposing, perpetuating, precipitating, and protective factors, patients can make informed decisions to manage these factors. **Expected Improvements:** 1. **Fewer Relapses:** By enhancing patient understanding of their treatment plan and the importance of medication, we hope to reduce relapse rates. 2. **Fewer Crises:** Improved self-awareness and management should lead to fewer crises faced by patients. **Target Audience:** We recognize that insightful patients are more likely to use this app, while those lacking insight or agreement with treatment may not. However, even if only a portion of patients use the app, it can still alleviate some of the caseload, allowing case managers to focus on more challenging cases. **Standardization and Consistency:** The app will help standardize care for each patient by providing consistent content and curriculum. **Digital Phenotype:** With Digital Phenotype technology, we can continuously monitor patients remotely, enabling early detection of changes and prevention of crises or relapses. **Clinical and Patient Perspectives:** From a clinical perspective, increased support and early detection of changes should reduce relapses and improve symptom management. For patients, the app aims to activate them in their recovery journey, enhance shared decision-making, provide more control over their lives, and ultimately, support better personal recovery. **Challenges:** Psychiatry is complex, and recovery is multi-dimensional. Many confounding factors influence the recovery process, which the app will need to address. --- ## Theory of Change **Goal:** To enhance patient care and improve outcomes by leveraging the HOPES app to support case management, psychoeducation, and self-awareness among patients. **Situation:** High caseloads prevent case managers from providing adequate attention and support to each patient, leading to variability in service delivery and delayed responses to crises or relapses. **Inputs:** - Development of the HOPES app. - Training for case managers on using the app. - Integration of Digital Phenotype technology for remote monitoring. - Resources for content creation and curriculum standardization. **Activities:** - Develop and launch the HOPES app. - Train case managers to utilize the app effectively. - Implement Digital Phenotype technology to monitor patient data continuously. - Create standardized content and curriculum for patient education. **Outputs:** - Increased usage of the HOPES app by patients and case managers. - Consistent delivery of psychoeducational content. - Continuous remote monitoring of patient health indicators. - Enhanced self-awareness and self-management among patients. **Outcomes:** - **Short-Term:** - Improved patient understanding of treatment plans and medication importance. - Increased self-awareness of personal health factors. - **Medium-Term:** - Reduction in relapse rates. - Decrease in crises faced by patients. - Alleviated caseload for case managers, allowing focus on more challenging cases. - **Long-Term:** - Enhanced patient recovery journey. - Increased shared decision-making and patient control over their lives. - Standardized and consistent care across all patients. **Impact:** - Improved overall patient outcomes. - Enhanced efficiency and effectiveness of case management. - Better personal recovery and quality of life for patients. --- ### **Logic Model** | **Components** | **Description** | | --- | --- | | **Inputs** | Development of the HOPES app, training programs for case managers, Digital Phenotype technology, content creation resources | | **Activities** | Develop and launch the app, train case managers, implement remote monitoring technology, create standardized educational content | | **Outputs** | Increased app usage, consistent psychoeducational delivery, continuous monitoring of health indicators, enhanced patient self-awareness | | **Short-Term Outcomes** | Improved understanding of treatment and medication, increased self-awareness | | **Medium-Term Outcomes** | Reduction in relapses, fewer crises, decreased caseload for case managers | | **Long-Term Outcomes** | Enhanced patient recovery, increased shared decision-making, standardized patient care | | **Impact** | Improved patient outcomes, efficient case management, better quality of life for patients | --- This framework outlines the logical progression from inputs to impact, demonstrating how the HOPES app and related activities are expected to lead to improved patient care and outcomes. ----- Cross check with Perplexity ## Research on patient self-awareness and its relationship to recovery has revealed several important findings: 1. Self-awareness is a critical factor in rehabilitation outcomes for patients with brain injuries. Poor self-awareness, also known as anosognosia or impaired self-awareness (ISA), is common after moderate to severe traumatic brain injury (TBI), occurring in 30-50% of patients[5]. 2. Self-awareness tends to improve over time for many patients with TBI, though the rate and extent of improvement can vary[5]. 3. Impaired self-awareness primarily affects cognitive and behavioral domains rather than physical or sensory impairments. Patients may have difficulty recognizing deficits in areas like executive functioning, memory, or social skills[5]. 4. There are different types of self-awareness that can be impacted, including: - Anticipatory awareness (ability to predict future challenges) - Emergent awareness (recognizing problems as they occur) - Metacognitive awareness (understanding the implications of deficits)[5] 5. Poor self-awareness can negatively impact independence in daily activities. Patients with impaired awareness often exhibit poor judgment and may require supervision to ensure safety[4]. 6. Strategy training has shown promise in promoting independence after stroke, even for patients with poor self-awareness. A study found that awareness status did not significantly affect the response to strategy training, suggesting it may benefit patients regardless of their level of self-awareness[4]. 7. Assessment of self-awareness is complex and multifaceted. Common methods include: - Self-proxy discrepancy scores (comparing patient and caregiver ratings) - Structured interviews like the Self-Awareness of Deficits Interview (SADI) - Scales such as the Patient Competency Rating Scale or Awareness Questionnaire[5] 8. Different assessment methods may capture various aspects of self-awareness, as scores on different scales often correlate only moderately with each other[5]. 9. For patients with minimally conscious state (MCS), research has explored the concept of minimal self-awareness. This refers to the implicit awareness of embodied subjectivity that permeates all experiences, rather than higher-order reflective self-awareness[1]. 10. Improving self-awareness is considered important for rehabilitation outcomes. Techniques to enhance self-awareness may include feedback, coaching, and reflective practice[3]. In conclusion, self-awareness plays a crucial role in patient recovery and rehabilitation, particularly for those with brain injuries. While impaired self-awareness can hinder progress, research suggests that targeted interventions and strategy training can still be effective. Assessing and addressing self-awareness should be an integral part of rehabilitation programs to optimize patient outcomes. Citations: [1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689014/ [2] https://www.researchgate.net/publication/321512369_Self-Awareness_and_Recovery_of_Independence_With_Strategy_Training [3] https://www.linkedin.com/pulse/thoughts-self-awareness-patient-health-wellbeing-dr-nia-d-thomas [4] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5744716/ [5] https://www.sciencedirect.com/science/article/pii/S187706572030227X ---- # Research on increasing shared decision-making (SDM) and its connection to recovery in mental health has revealed several important findings: 1. Shared decision-making is increasingly recognized as a crucial component of patient-centered and recovery-oriented mental health care. It empowers patients to actively engage in their illness management and treatment decisions[1][2]. 2. SDM in mental health typically involves three key steps: choice talk, options talk, and decision talk. Throughout this process, clinicians support patient deliberation and collaboration[3]. 3. Studies have shown positive outcomes associated with SDM in mental health: - 60% of patients reported experiencing SDM during treatment[3] - SDM was associated with improved affective-cognitive patient outcomes (54%), behavioral outcomes (37%), and health outcomes (25%)[3] - Higher scores on the bond subscale of the Working Alliance Inventory, indicating increased trust and better medication adherence[3] 4. SDM is closely linked to the recovery model in mental health, which emphasizes patient autonomy, self-determination, and community integration[4]. 5. Several tools have been developed to measure SDM in mental health contexts, including: - The 9-item Shared Decision-Making Questionnaire (SDMQ-9) - Clinical Decision-Making Involvement and Satisfaction (CDIS-P Involvement subscale) - Observing Patient Involvement in Decision-Making Scale (OPTION)[2] 6. Recovery-specific outcomes related to SDM can be measured using tools like: - Recovery Assessment Scale - Developing Recovery Enhancing Environments Measure (DREEM) - Stages of Recovery Instrument (STORI)[2] 7. Challenges in implementing SDM in mental health include: - Inconsistent definitions and models - Lack of sufficient evidence for the effectiveness of SDM interventions - Unique factors such as stigma and mental capacity concerns[4] 8. Recent research suggests expanding SDM beyond the traditional patient-clinician dyad to include family members, peer support workers, and other healthcare professionals[4]. 9. In substance use disorder treatment, patient preferences for involvement in clinical decision-making have been associated with treatment retention and outcomes[5]. 10. To advance SDM in mental health, researchers recommend: - Developing and validating SDM measures specifically for people with mental illness - Focusing on person-driven measurement approaches - Incorporating participatory research methods[4] In conclusion, while SDM shows promise in improving mental health care and supporting recovery, there is a need for more tailored approaches and research specific to mental health contexts. Increasing SDM implementation and connecting it more closely to recovery outcomes remains an important area for future study and practice. Citations: [1] https://www.samhsa.gov/brss-tacs/recovery-support-tools/shared-decision-making [2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650912/ [3] https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0283994 [4] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240653/ [5] https://www.recoveryanswers.org/research-post/on-the-same-page-impact-shared-decision-patients-providers-recovery/ ---- # Research on technology-enabled care (TEC) and its connection to recovery in healthcare has revealed several important findings: 1. TEC is increasingly recognized as a crucial component in transforming how care is delivered, particularly for individuals with chronic conditions or those requiring long-term support[2][4]. 2. In the UK, approximately 1.8 million vulnerable people currently rely on telecare, and this number is expected to rise. TEC solutions aim to provide better preventative care and turn data into actionable insights, allowing care to be delivered anywhere, at any time[2]. 3. Key drivers for change in TEC include: - Increasing pressure on health and social care systems due to rising numbers of people living with long-term conditions - The need for more person-centered care - The potential to reduce hospital admissions and prolong independence[2] 4. TEC solutions encompass various technologies, including: - Telecare and telehealth systems for remote monitoring - Digital platforms for patient-professional communication - Self-monitoring tools - Tailored self-care support features - Care planning tools - Web-based community forums for peer support[4] 5. Studies have shown positive outcomes associated with TEC in chronic care management: - Improved patient-professional partnerships - Enhanced self-care education and support - Better symptom monitoring and management - Increased patient engagement in their care[4] 6. A novel digitally-enabled care pathway has been developed to support post-intensive care recovery, incorporating individualized goal setting, goal attainment scaling monitoring, and symptom monitoring[3]. 7. Recent research has highlighted the importance of expanding TEC beyond the patient-professional dyad to include family members, caregivers, and peer support networks[4]. 8. Challenges in implementing TEC include: - Ensuring data security and privacy - Addressing digital literacy and access issues - Integrating TEC solutions with existing healthcare systems - Tailoring solutions to individual needs and preferences[2][4] 9. Future directions for TEC research and development include: - Exploring how to effectively combine knowledge from online health communities, patients, caregivers, and healthcare professionals - Investigating the impact of TEC on the nature of patient-professional partnerships - Developing more sophisticated data analysis tools to provide actionable insights for care providers[4] 10. A local system dynamics model study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination, suggesting potential benefits for mental health and recovery outcomes[5]. In conclusion, technology-enabled care shows significant promise in supporting recovery and improving healthcare delivery across various conditions and settings. However, ongoing research is needed to optimize its implementation, address challenges, and fully realize its potential to enhance patient outcomes and experiences. Citations: [1] https://www.linkedin.com/pulse/remote-technology-enabled-care-service-market-research-9iuxc [2] https://www.tsa-voice.org.uk/news_and_views/tsa-member-news/empowering-care-through-technology-enabled-solutions-how-is-access-technology-enabled-care-a-driver-for-change-/ [3] https://innovations.bmj.com/content/8/1/42 [4] https://www.jmir.org/2022/8/e38980/ [5] https://www.researchgate.net/publication/352070115_The_impact_of_technology-enabled_care_coordination_in_a_complex_mental_health_system_A_local_system_dynamics_model_Preprint